
==== Front
Sci Rep
Sci Rep
Scientific Reports
2045-2322
Nature Publishing Group UK London

67270
10.1038/s41598-024-67270-9
Article
Chromosomal-level reference genome assembly of muskox (Ovibos moschatus) from Banks Island in the Canadian Arctic, a resource for conservation genomics
Lok Si si.lok@sickkids.ca

12
Lau Timothy N. H. 12
Trost Brett 123
Tong Amy H. Y. 4
Paton Tara 12
Wintle Richard F. 12
Engstrom Mark D. 5
Gunn Anne 6
http://orcid.org/0000-0002-8326-1999
Scherer Stephen W. Stephen.scherer@sickkids.ca

1278
1 https://ror.org/057q4rt57 grid.42327.30 0000 0004 0473 9646 The Centre for Applied Genomics, Peter Gilgan Centre for Research and Learning, The Hospital for Sick Children, 686 Bay Street, Rm 13.9713, Suite 03-6577, Toronto, ON M5G 0A4 Canada
2 https://ror.org/057q4rt57 grid.42327.30 0000 0004 0473 9646 Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON M5G 0A4 Canada
3 https://ror.org/057q4rt57 grid.42327.30 0000 0004 0473 9646 Program in Molecular Medicine, The Hospital for Sick Children, Toronto, ON M5G 0A4 Canada
4 https://ror.org/03dbr7087 grid.17063.33 0000 0001 2157 2938 Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON M5S 3E1 Canada
5 https://ror.org/00vcj2z66 grid.421647.2 0000 0001 2197 9375 Department of Natural History, Royal Ontario Museum, Toronto, ON M5S 2C6 Canada
6 Salt Spring Island, Canada
7 https://ror.org/03dbr7087 grid.17063.33 0000 0001 2157 2938 McLaughlin Centre, University of Toronto, Toronto, ON M5G 0A4 Canada
8 https://ror.org/03dbr7087 grid.17063.33 0000 0001 2157 2938 Department of Molecular Genetics, Faculty of Medicine, University of Toronto, Toronto, ON M5S 1A8 Canada
16 9 2024
16 9 2024
2024
14 2102327 2 2024
9 7 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by/4.0/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
The muskox (Ovibos moschatus), an integral component and iconic symbol of arctic biocultural diversity, is under threat by rapid environmental disruptions from climate change. We report a chromosomal-level haploid genome assembly of a muskox from Banks Island in the Canadian Arctic Archipelago. The assembly has a contig N50 of 44.7 Mbp, a scaffold N50 of 112.3 Mbp, a complete representation (100%) of the BUSCO v5.2.2 set of 9225 mammalian marker genes and is anchored to the 24 chromosomes of the muskox. Tabulation of heterozygous single nucleotide variants in our specimen revealed a very low level of genetic diversity, which is consistent with recent reports of the muskox having the lowest genome-wide heterozygosity among the ungulates. While muskox populations are currently showing no overt signs of inbreeding depression, environmental disruptions are expected to strain the genomic resilience of the species. One notable impact of rapid climate change in the Arctic is the spread of emerging infectious and parasitic diseases in the muskox, as exemplified by the range expansion of muskox lungworms, and the recent fatal outbreaks of Erysipelothrix rhusiopathiae, a pathogen normally associated with domestic swine and poultry. As a genomics resource for conservation management of the muskox against existing and emerging disease modalities, we annotated the genes of the major histocompatibility complex on chromosome 2 and performed an initial assessment of the genetic diversity of this complex. This resource is further supported by the annotation of the principal genes of the innate immunity system, genes that are rapidly evolving and under positive selection in the muskox, genes associated with environmental adaptations, and the genes associated with socioeconomic benefits for Arctic communities such as wool (qiviut) attributes. These annotations will benefit muskox management and conservation.

Keywords

Ovibos moschatus
Muskox
Umingmak
Continuous long read
Chromosomal-level assembly
Climate adaption
Climate change
Conservation genomics
Subject terms

Biodiversity
Biodiversity
issue-copyright-statement© Springer Nature Limited 2024
==== Body
pmcIntroduction

The muskox (Ovibos moschatus), a large iconic and charismatic animal closely related to sheep and goats within the Caprinae subfamily, is one of the few surviving relics of the Pleistocene megafauna1,2. The muskox has an intriguing recent history. It was largely unknown by the early Europeans until the first published account in 1720. For the next several decades, classification attempts were debated and confounded naturalists by the muskox’s apparent sheep, cow, and buffalo-like features3,4. The muskox was formally introduced into systematic zoology by Zimmermann in 1780 under the name Bos moschatus5. After further debate, it was removed from the Linnean genus Bos and was reassigned to a new genus, Ovibos, by Blainville in 1816, where the name stands today with the muskox being the only living member of that genus6. However, the classification debate continues to this day over subspecies designation, their number and distribution7–9. In the present study, we follow the last formal taxonomic revision of the species, which regarded O. moschtus as a monotypic species7.

Muskoxen are physiologically and behaviourally adapted to live year-around in the cold conditions of the Arctic tundra. Once widely distributed across the Holarctic, the present endemic population is restricted to Northern Canada and Greenland. In the last century, muskoxen have been reintroduced to Northern Quebec, Norway, Russia, Southwest Greenland, and Alaska (see Fig. 1). The reintroduction effort in Alaska was to replace populations extirpated by overhunting. Muskox populations today inhabit a large and relatively diverse range that extends from the sub-arctic northern edge of the boreal forest (56° N) to the high-arctic tundra (83° N).Figure 1 Muskox distributions. (A) Population distributions and regional conservation status of the muskox in 2023 (Tomaselli M, Cuyler C, Kutz S, Adamczewski J, Brodeur V, Campbell M, Cluff D, Gorn T, Hughes LJ, Leclerc L-M, Nelson M, Parr B, Sipko T, Suiter M, Taillon J and Gunn A. Muskox health, status and trends—crossing the boundaries. Unpubl. Poster, Arctic Ungulate Conference, Anchorage, Alaska, May 2023). Endemic populations in Canada and Greenland are separated from the translocated (introduced or re-introduced) populations by the enclosed dotted boundary line. The Sachs Harbour area of Banks Island, Northwest Territories, Canada, where our specimen (Royal Ontario Museum archive: ROMMRAN27; NCBI BioSample: SAMN26661894) originated is denoted by an asterisk (*). (B) Muskoxen in a defensive posture. Despite their well-known group defence, muskoxen are prey for wolves (Canis lupus) and grizzly bears (Ursus arctos). The muskoxen in the photograph are descendants of individuals translocated in 1935 from eastern Greenland to the Arctic Wildlife Refuge, Alaska, USA. (Photograph: ©Peter Mather, 2010).

Known by the Inuit as Umingmak (the Bearded One), the muskox is an integral and evolving part of Inuit cultural and social-economic heritage10,11. In addition to being a meat source, and providing direct economic benefits such as tourism and the commercialisation of hide and luxury qivut wool12–15, the muskox is a key species in the Arctic tundra ecosystem. Muskox grazing critically impacts plant communities and nutrient flow16,17 as well as carbon dioxide and methane fluxes in the Arctic biosphere18, which are expected to be disrupted by climate change.

The world-wide population of muskox in 2020 is estimated to be 170,00019. As such, the muskox holds the International Union for Conservation of Nature (IUCN) Conservation status of Least Concern20. However, of the 55 muskox populations reported in 202019, six are in decline, including the population on Banks Island, which is well-known for its historic fluctuations in number21. The population on Banks Island was the largest in Canada in the 1990s but has suffered a 70% decline since 2000. Among the factors contributing to this decline include infection by a new bacterial pathogen Erysipelothrix rhusiopathiae, which normally infects farm animals and poultry22,23. Together with the expanding range of muskox lungworms24–26, and other diseases including brucellosis27, these could be early harbingers of emerging disease modalities from climate disruption.

Climate records supported by mitochondrial and microsatellite markers and by whole genome genotyping have provided evidence that the muskox underwent multiple population bottlenecks, which have resulted in contemporary populations having very low genetic diversity9,28–30. Although the muskox has been shown to have the lowest genome-wide heterozygosity reported in an ungulate, there are no overt signs of inbreeding depression in native muskox populations31. Additionally, Prewer and colleagues commented that the extremely low variability is a variance with many increases in muskox numbers and expanding distribution raising the possibility that the adaptive capacity has been under-estimated32. A likely mechanism is that over time, deleterious genes can be purged as have been suggested for the endangered kākāpō33 and the Svalbard reindeer34. Bayesian modelling suggests the muskox might have reached a genetic diversity minimum32, and it is not clear whether their remaining genetic capacity is sufficient for them to adapt to a rapidly changing Arctic.

The past decade has experienced an unprecedented increase in temperature in the Arctic. The Intergovernmental Panel on Climate Change 2023 climate models predict a mean global increase between 1.4 and 4.4 °C by 210035 with a disproportionate effect in the Arctic. Large herbivores are particularly at risk36. Thus, whether the muskox could physiologically and behaviourally adapt to a warmer Arctic would be of fundamental consequence for their conservation and management. An initial step to understand the muskox’s adaptive capacity has been to move toward the use of whole-genome re-sequencing31 based on the alignments to the draft short-read assemblies of the muskox2,37. While these assemblies provided an important first glimpse of the muskox genome, they are relatively incomplete and fragmented, typical of assemblies derived from short reads. As a resource for a conservation genomics-based approach for the management of the muskox, we report a chromosomal-level assembly derived from long-reads of a male muskox from Banks Island in the Canadian Arctic Archipelago. The ability of long reads to span repetitive sequences and other difficult regions of the genome38 has enabled the present assembly to have a more complete representation of the coding genes, isoforms of these genes, and the elucidation of their genomic organization. Moreover, the anchoring of our assembly to the 24 muskox chromosomes allows a direct cytogenetic comparison to other members of Bovidae, notably to the useful quantitative trait loci (QTLs) identified from economically important livestock. These QTLs could potentially be mapped to the muskox. From this assembly, we also provide exon-level annotation of genes that could be useful in muskox management, including genes of the immune system, those associated with environmental adaptations, particularity to heat stress, and genes associated with relevant socioeconomic benefits as direct drivers for species conservation.

Materials and methods

Specimen selection for genome assembly

Kidney tissue (NCBI: BioSample SAMN26661894) from a male muskox (Ovibos moschatus) was obtained from the Royal Ontario Museum Tissue Archive (catalog number: ROMMRAN27). The tissue was collected on 25 October 1991 near Sachs Harbor, Banks Island, NWT, Canada.

Species identity of the specimen was verified by matching a segment of the cytochrome oxidase 1 (COX1) gene from the specimen’s assembled mitochondrial genome against the Barcode of Life Database (http://www.boldsystems.org). The top nine hits in the database were Ovibos moschatus at a 100% match. Male specimens are typically selected for genome assembly to have representation of the X and Y chromosomes. The male sex of our muskox specimen was denoted by the presence in our assembly of the X and Y chromosome-specific genes, ZFX (Acc KAL1286804) and ZFY (Acc KAL1286379)39, and the Y chromosome-specific gene, SRY (Acc KAL1286397).

DNA extraction for sequencing and genome assembly

Genomic DNA was extracted from frozen kidney tissue using a Puregene Reagent Kit (Qiagen, Hilden, Germany), with the resulting purified kidney DNA having 260 nm/280 nm and 260 nm/230 nm absorbance ratios of 1.90. DNA had a peak length of 22.6 kb on an Agilent TapeStation (Agilent, Santa Clara, CA). Although DNA from flash-frozen fresh whole blood is often preferred for long-read sequencing, when blood samples are not available due to logistical or regulatory issues, DNA purified from well-maintained archival tissue banks (particularly kidney tissues) is acceptable for PacBio sequencing and genome assembly. DNA for library construction was quantified by fluorometry using the Qubit DNA HS Assay (ThermoFisher, Waltham, MA).

Genome sequencing and pre-assembly filtering

Long-read libraries for genome sequencing were prepared from five μg of un-sheared genomic DNA using an Express template prep kit (version 2.0) (Pacific Biosciences, Menlo Park, CA) followed by a post-library-construction sizing step of > 15 kb on the BluePippin system (Sage Science, Beverly, MA). Size-selected library was sequenced on a Sequel II sequencer (Pacific Biosciences; PacBio) in the Continuous Long-Read (CLR) mode with a 15-h movie acquisition time. Raw reads were processed on PacBio’s P filter to remove low-quality reads and adapter sequences. The longest sub-read was selected from each productive zero-mode waveguide on the flow-cell. Sub-reads of less than 2 kb length were discarded. 16,756,911 reads remained with a read length N50 value of 15,868 bp, similar to the peak length of the starting DNA (22.6 kb). Using an estimated genome size of 3 Gb inferred by tabulating k-mer frequencies40, the resulting CLRs used for the assembly comprised 207.6 Gb of sequences, representing 71.6× genome coverage. Read statistics, including genomic coverage at different ranges of read-length N50 values are provided in Supplementary Figure S1.

Short reads used to polish the assembled genome were produced from 700 ng of the same genomic DNA used for long-read sequencing. DNA was randomly fragmented to 500–600 bp using a Covaris LE220 Focused Ultrasonicator (Covaris, Woburn, MA), followed by library construction carried out in accordance with the Illumina TruSeq DNA PCR-Free protocol (Document 1000000039279v00) (Illumina, San Diego, CA). Sequencing was performed on the HiSeq X sequencer (Illumina), producing 2 × 150 nt paired-end reads. Only sequences with quality scores Q35 or better were used. To achieve this level of accuracy, the first 10 bases were discarded in read 1 and read 2, the last 20 bases were discarded in read 1, and the last 30 bases were discarded in read 2. After trimming the least accurate portions of the reads and removal of adapter sequences, 777 million paired-end reads remained, comprising 178.6 Gb of sequences (61.6× coverage).

De novo genome assembly and chromosome assignment

A two-step assembly workflow was used to assemble the muskox genome. In the first step, de novo genome assembly was carried out directly from uncorrected PacBio CLRs (71.6× coverage) using Flye 2.8.2, which was designed to assemble error-prone reads41. To resolve mis-assemblies and other errors, the primary assembly was polished three times with Flye-polish41 using the same CLRs that were used to construct the assembly. To correct residual PacBio sequencing errors remaining in the primary assembly, typically single base or small insertions and deletions (indels) inherent to CLRs, the assembly was subjected to eight rounds of additional polishing with high-quality trimmed Illumina short-reads (61.6× coverage) using Freebayes 1.3.1 (https://github.com/freebayes/freebayes).

In the second step, multiple cross-species scaffolding against reference genomes of related Cervidae was used to generate super-scaffolds to produce a chromosomal-level assembly for the muskox. To mitigate potential bias during this process, all input de novo assembled contigs and scaffolds of the muskox were to be left intact and unaltered. This cross-species super-scaffolding step drew heavily on the previous comparative studies of karyotypes in the Cervidae family42 and on the comparative chromosome painting-based map of the muskox, dromedary (Camelus dromedaries) and human43, and similar information from 43 other bovid genomes44. The chromosome number of the muskox was established at 2n = 4843,45,46. Making use of the finding that autosomal arms are highly syntenic in typical Bovidae family members42,47, we used the chromosomal-level reference genomes of the closely related takin (Budorcas taxicolor) (GCF_023091745.1), goat (Capra hircus) (GCF_001704415.2), and sheep (Ovis aries)(GCA_016772045.2) to scaffold our muskox contigs into provisional chromosome arms. Muskox contigs were aligned against the aforementioned reference genomes using minimap2 (v2.24)48 with parameter − x asm20, allowing alignments with up to 20% divergence in the nonrepetitive sequences49. As a quality control step, the resulting alignments were then reviewed and filtered to ensure there were no contradictions with the Repeat Graph generated by the Flye assembler. The Repeat Graph represented all assembled contigs and their junctions, thus providing a guide as to whether viable paths between contigs in question were plausible during scaffolding. The resulting scaffolded chromosome arms were then localised and assigned to 24 provisional chromosomes using the cattle genome (GCF_002263795.3) as an anchor in accordance with the cross-species relationships previously established43. Chromosomal scaffolding, orientation and assignments were further refined and adjusted with a final alignment against the comparative chromosome map established by chromosome painting for the muskox, human (GCF_000001405.40) and the dromedary genomes (GCF000803125.2)43. In another quality control step, Minimap2 was used once again to return the best pairwise unique matching segments against the human and dromedary genomes, enabling our assembled scaffolds to be anchored to the 24 chromosomes of the muskox with high confidence. In a final quality control step, long reads were tiled along the length of the assembly to identify regions of discordance for curation. The resulting assembly, O.moschatus_RAN27-v1.0, has a contig N50 of 44.7 Mbp, a scaffold N50 of 112.3 Mbp, and a completeness of 93.49% as determined by the tabulation of k-mers derived from highly accurate Illumina short-reads using Merqury50.

Sequence contamination in muskox assembly

As PacBio CLRs could have up to 15–20% pseudorandom errors in the forms of base substitutions and small insertions and deletions51, a search for DNA contamination from environmental or laboratory sources might not be sensitive at the read level. Likewise, Illumina short reads might be too short to make reliable and unambiguous calls of potential contaminating DNA. As a consequence, contamination assessment was carried out in the final assembly after the ensuring correction steps for sequencing errors.

Potential microbial and other environmental DNA contaminants in the DNA sample that made it into the final assembly were assessed using the workflow depicted in Supplementary Fig. 2. BLAST analysis of non-overlapping 5 kb windows in the assembly revealed five windows showing a match (95–99%) to Delftia acidovoran (Acc CP058970.1), a common aerobic environmental organism found in soil. The five positive windows were adjacent to each other and were all confined to a single contig of 26 kb length, which was removed from the assembly. No microbial or fungal sequences were found amongst the top 50 ranked hits in the remaining windows, indicating there were no other overt environmental contaminants in the final muskox assembly.

Human DNA contamination has been reported in many non-primate genome databases, presumably from laboratory sources52. Using a primate-specific SINE, AluY, we found no discernible primate sequences in the muskox assembly.

BUSCO and genome annotation

The completeness our muskox assembly was qualitatively assessed using BUSCO v5.2.2 (Benchmarking Universal Single Copy Orthologs; mammalia_odb10)53. BUSCO designates the status of a set of 9226 mammalian lineage marker genes as complete, fragmented, or missing in an assembly. Muskox genes that were failed by BUSCO were subjected to a verification step at exon-level resolution to determine their true status in our assembly. In this verification procedure, we first identified a seed exon for that the gene query in the assembly using a set of orthologous human, sheep, and cow exon probes (NCBI RefSeq). Typically, the seed exon has the highest BLAST score amongst the exon queries for the gene under investigation. From the seed exon, we then scanned up-stream and down-stream along the assembly or scaffold using BLAST in incremental 10 kb size windows in the search for the adjacent exon. Specific search criteria include nucleotide and amino acid sequence identity to the query exon, and the conservation of the reading frame relative to the consensus splice signals at the exon boundaries. Once an adjacent exon was identified, the process was repeated until all exons were identified. For a gene to be designated as complete in the muskox assembly, the full-length polypeptide encoded by the predicted exons must begin with an initiation codon and end with a termination codon, and to be at least 70% identical to the full-length human, sheep, takin, or cow protein encoded by the query as reported in RefSeq.

Correction of sequencing errors

Sequencing errors in the PacBio platform are typically between 10 and 15%, comprising single base substitutions or small indels. These errors were corrected in the primary assembly using Flye-polish41 followed by eight rounds of “polishing” with high-quality trimmed Illumina short-reads of Q35 or better using Freebayes 1.3.1 (https://github.com/freebayes/freebayes). From monitoring the kinetics of base changes in the primary assembly at different rounds of polishing, we found base changes from polishing with Freebayes do not approach a plateau value until after the fifth or sixth rounds, after which further base changes are confined to a small number of positions where they alternate between what appear to be allelic bases in successive rounds (data not shown).

Assessment of residual sequencing errors in the assembly

In the absence of a reference DNA of a known sequence to make a direct comparison, it was not possible to tabulate the base accuracy of our assembly following the polishing steps. However, we can tabulate base substitute errors indirectly when errors generate premature termination codons disrupting the Open Reading Frames (ORFs) we have annotated.

The following formula depicts the probability of creating a spurious termination codon at different levels of sequencing accuracies:T=1-A3×3/63

where A is the probability of a correct base call (i.e. the sequencing accuracy for that nucleotide position); A3 is the joint probability of three consecutive correct calls forming a correct codon; 1 − A3 is the probability of a codon being incorrect with at least one incorrect base call; 3/63 is the probability of an incorrect codon being a termination codon*; T is the probability of an in-frame termination codon created from an in-frame non-termination codon due to sequencing error; * Of the 64 possible codons, only one is correct and 63 are incorrect at a given position. Since there are three possible termination codons, therefore, the probability of an incorrect codon being a termination codon is 3/63.

The muskox gene with the longest coding capacity, Titin (TTN, Acc KAL1287845), in conjunction with the annotated genes in Supplementary Tables S2, S3, S8, and S9, yield ORFs comprising 782,521 codons. Since all of these genes were found to encode uninterrupted ORFs where none of the 782,521 codons are termination codons, a value for T can be set at < 1/782,521 or < 0.00013%. Substituting this value for T and solving for A in the aforementioned formula yields an inferred sequence accuracy in the assembly of not less than 99.99910%, corresponding to a Phred score54 of no less than 50.4839 in these coding regions.

Identification of repetitive DNA in the genome

Repetitive elements described in RepBase were identified and tabulated in the muskox genome using RepeatMasker49. Supplementary Table S1 summarizes the distributions of repetitive sequences in the muskox.

Assessment of genetic diversity in muskox

Genetic diversity was assessed for the Banks Island muskox specimen assembled in this study, and was compared to the genetic diversity of selected muskox specimens collected by Van Coeverden de Groot and colleagues55 and Pečnerová and colleagues31. Ilumina short reads from selected specimens with the highest sequence read depth were downloaded from NCBI SRA (see Supplementary Table S11 for accession numbers) from each geographic region depicted in Fig. 1 of Pečnerová’s paper31. Reads from the selected specimens comprised an average 14× coverage of the muskox genome (median coverage of 12×).

Sequence reads were aligned to the muskox reference genome in the present study using BWA 0.7.17r119856. Duplicate reads were marked using the “MarkDuplicate” function of GATK 4.1.9.057. The average depth of coverage of each sample was calculated using the “depth” function of SAMtools 1.956. To ensure that heterozygosity estimates were not confounded by differences in read depths, reads from samples with high read depths were subsampled to 10–15× average depth. Single nucleotide variants (SNVs) and small insertions and deletions (indels) were detected using Genome Analysis Toolkit (GATK) best practices58.

Using the alignment file from BWA as input, SNVs and indels were identified using the “HaplotypeCaller” function of GATK with parameter—minimum-mapping quality 20 followed by the GATK function “GenotypeGVCFs”. The FILTER column of the VCFs was populated using the hard-filtering criteria suggested by the authors of GATK (https://gatk.broadinstitute.org/hc/en-us/articles/360035890471-Hard-filtering-germline-short-variants). For SNVs the criteria were: QD < 2.0, MQ < 40.0, SQR > 3.0, SOR > 3.0, FS > 60.0, MQRankSum < − 12.5, and ReadPosRankSum < − 8.0. For indels the criteria were: QD < 2.0, SQR > 10.0, FS > 200.0, and ReadPosRankSum < − 20.0. Only variants passing these filters were used for assessing heterozygosity or to make variant calls against the reference muskox genome. The degree of heterozygosity for each genome was tabulated based on the number of heterozygous variants per megabase of reference sequence. To assess genetic diversity in the muskox immune genes including genes in the MHC, we determined the exon coordinates for the genes of interest and tabulated the calls within those coordinates from the alignment files for each muskox specimen, as well as the variant counts and profiles aggregated across all of the specimens.

Mitochondrial genome assembly

The muskox mitochondrial genome was assembled with Abyss V2.1.5 (parameters k = 103, kc = 6)59 from 40 million Illumina paired-end reads. The NCBI muskox mitochondrion sequence NC_020631.1 was used as a BLAST query to select the contig containing the presumptive mitochondrion sequence. Circularization of the selected contig yielded a complete mitochondrial genome of 16,431 bp. The accuracy of the mitochondrial assembly was supported by the uninterrupted tiling of mapped Illumina short reads across the length of the assembly in 50 bp moving windows of single base increments. Tiling depths of greater than 7500 reads were tabulated across 100% of the assembled circular mitochondrion genome. The mitochondrial assembly was further supported by the alignment of PacBio long reads, yielding a read depth of 90×. We also performed a de novo assembly of the aligned long reads and produced a circular contig of 16,341 bp in length that is identical to the one assembled from short reads.

Results and discussion

Assembly strategy and assessment of assembly quality

Pacific Biosciences (PacBio) Continuous Long-Reads (CLRs) were assembled directly using the Flye assembler41 into a high-quality haploid assembly for the muskox. The resulting assembly, O.moschatus_RAN27-v1.0, has a contig N50 of 44.7 Mbp, a scaffold N50 of 112.3 Mbp, and a completeness of 93.49% as determined by the tabulation of k-mers derived from highly accurate Illumina short-reads using Merqury50. The incomplete portion of the assembly can be attributed to the incomplete Chromosome Y, centromeres, telomeres, and other unresolved repeats that are missing in the assembly.

As shown here and in our previous study of the North American wolverine genome60, the 15–20% pseudorandom sequencing errors typically associated with CLRs51 can be effectively mitigated by the Flye assembler and the ensuing polishing regimens to yield a high-quality assembly that is essentially free of residual sequencing errors. Using the assessment method for the estimation of residual sequencing errors described in Materials and Methods, we estimate the sequence accuracy in our muskox assembly after the polishing steps to be not less than 99.99910% corresponding to a Phred score of not less than 50.4839 (corresponding to < 1 substitution error in 111,787 bases in the coding regions). This level of accuracy exceeds the recommend value for “finished genomes”61.

We favour the error mitigation strategy used in this study over the computationally intensive approach of correcting individual PacBio reads prior to assembly62 or the use of PacBio’s recent Circular Consensus Sequencing also known as HiFi Sequencing (HiFi/CCS)63,64 where reads are partially corrected during sequencing. HiFi/CCS holds promise as the technology continues to improve in accuracy and achieves a more favourable cost profile; however, at the time of this study, HiFi/CCS technology could achieve a uniform Q30 or better correction for only a small portion of the flow cell, with the majority of the other reads having very heterogeneous and lower degrees of correction. This heterogeneity in read accuracy complicates the models used by many assemblers to build contigs. Moreover, the HiFi/CCS process itself often has a detrimental effect on the overall lengths of the reads compared to CLR, with concomitant impact on the efficiency of scaffolding and assembly. By contrast, assemblers such as Flye could easily model the uniform, but albeit higher overall error rate across all CLRs, to build accurate contigs. At least at the time of this study, CLRs arguably offer a better functional trade-off for cost effective de novo assembly of large, complex genomes.

Table 1 compares the assembly metrics of our muskox assembly, O.moschatus_RAN27-v1.0, against the two current short-read assemblies for the muskox (ASM2148233v1)2 and (ASM2253363v2)37. All three muskox assemblies have similar ungapped lengths of between 2.5 and 2.6 Gb. The improved continuity of our long-read assembly is evident by having a much higher contig and scaffold N50 values and lower contig and scaffold counts over the previously reported short-read assemblies for the muskox and other ruminant genomes assembled from short reads65. Of the two short-read assemblies for the muskox, the assembly reported by Prewer and colleagues37 is more fragmented, which could be due to the lower quality of the source DNA extracted from hide as opposed to the DNA extracted from fresh blood used by Li and colleagues2. The low contig and scaffold L50 values (i.e., the number of contigs or scaffolds that represent half the genome) further reflect the improved contiguity offered by long-read technologies. In terms of the usual continuity metrics, our muskox assembly is at par with, or is better than, the other chromosomal-level reference assemblies currently available for Bovidae, the takin, goat, sheep, and cow. Table 1 Assembly metrics.

	Ovibos moschatus (Muskox)
male
2024/04/26
O.moschatus
_RAN27_v1.0	O. moschatus* (Muskox)
male
2021/01/13
ASM2146233v1	O. moschatus (Muskox)
male
2022/05/16
ASM2253363v2	Budorcas taxicolor* (Takin)
male
2022/04/22
Takin1.1 ARS-UI_Ramb_v3.0	Ovis aries* (Sheep Breed: Rambouillet)
female
2023/07/20
ARS1.2	Capra hircus* (Goat)
male
2016/08/24
ARS-UCD2.0	Bos taurus* (Cattle Breed: Hereford)
female
2023/07/01	
Total sequence length (bp)	2,602,202,933	2,615,835,778	2,621,888,837	2,851,954,952	2,654,063,983	2,922,617,086	277,0686,120	
Total ungapped length (bp)	2,602,159,733	2,601,841,192	2,473,402,365	2,851,579,369	2,654,021,983	2,922,578,899	2,770,657,958	
Number of contigs	654	14,255	114,188	1515	227	30,378	2344	
Contig N50 (bp)	44,730,146	843,055	38,369	68,053,581	43,178,051	26,244,591	26,402,946	
Contig L50	20	832	18,652	15	24	32	32	
Number of scaffolds	222	6709	8658	1363	143	29,886	1958	
Scaffold N50 (bp)	112,334,376	46,819,416	13,200,690	109,747,698	101,274,418	87,277,232	103,308,737	
Scaffold L50	9	20	61	10	8	13	12	
	72×

PacBio Sequell II

CLR

Flye 2.8.2

Freebayes 1.3.1

	60×

Ilumina Hi-Seq SOAPdenovo 1.12 (Li et al.2)

	85×

Ilumina Hi-Seq SOAPdenovo 240 (Prewer et al.37)

	24×

PacBio Sequel I

CLR

Illumina NovaSeq

Bionano

Hifiasm v0.13

	55×

PacBio RSII Nanopore Illumina HiSeq Canu 1.8 Nanopolish 0.12.5

Salsa 2.2

PB Jelly 15.8.24

Freebayes 1.3.1

	50×

PacBio Bionano

Hi-C Celera 8.2 Bionano Irys April 2015

Lachesis HiC June 2015

	Various Falcon v FEB-2016	
Comparison of the muskox assembly of this study with other muskox and Bovidae assemblies. Asterisk (*) denotes current NCBI reference genomes.

Assembly completeness and residual sequence errors

The BUSCO (Benchmarking Universal Single-Copy Orthologs) program has long been used to assess the completeness of genome assemblies53. When BUSCO v5.2.2 with its set of 9226 mammalian linage marker genes was applied to our muskox assembly, 8852 genes (95.9%) were scored as complete, and 374 genes (4.1%) were scored as fragmented or missing in the assembly. At face value, these BUSCO scores placed our muskox assembly in the top echelon for reported genome assemblies derived from long reads. Figure 2 compares the BUSCO scores of our muskox assembly with current NCBI designated reference genome assemblies for sheep (ARS-UI_Ramb_v3.0; GCF_016772045.2) and human (GRCh39.14; GCF_000001405.40).Figure 2 Venn diagram of BUSCO results. Analysis by Benchmarking Universal Single Copy (BUSCO) v5.2.2 of the muskox O.moschatus_RAN27_v1.0, human GRCh38.p14 (GCF_000001405.40) and sheep ARS-UI_RAMb_v3.0 (GCF_016772045.2) assemblies. The mammalian linage (mammalia_odb10) comprised of 9226 ortholog groups was used. “Complete genes” refers to those scored as “Complete” or “Duplicated” by BUSCO, while incomplete genes refer to those scored as “Fragmented” or “Missing” by BUSCO. The official human reference GRCh38.p14 only had 96.0% BUSCO complete even though it is the most thoroughly annotated genome to date. All muskox incomplete genes were found and annotated in the muskox assembly (Supplementary Table S2).

An important and useful feature of BUSCO is its ability to assess the completeness of genome assemblies across a broad range of species. This was accomplished by balancing sensitivity and specificity to create a single universal set of consensus gene profiles that can be used generically across all mammalian species. To enable this feature, gene profiles are not optimized for any particular species. Due to this compromise, it is possible that subsets of BUSCO profiles could have difficulties detecting their cognate genes in species whose orthologs deviate significantly from the consensus. Accordingly, BUSCO could under-count those genes, resulting in an under-estimation of the quality of an assembly being evaluated. Undercounting of genes by BUSCO was exemplified by our recent genome assembly for the wolverine60 and by the current build of the gold standard human reference genome, GRCh38.p14, where 369 BUSCO genes were called as fragmented or missing (Fig. 2), despite those genes being annotated by the NCBI Genome Data Viewer as complete and experimentally verified.

To address the possibility of an undercounting in our muskox assembly, the 374 genes that BUSCO scored as fragmented or missing (Fig. 2) were annotated at exon-level resolution. The results revealed that all 374 genes are present and complete (Supplementary Table S2), revising the BUSCO score to 100%. Interestingly, amongst the genes BUSCO deemed to be missing in the muskox, LRP1B (LDL receptor related protein 1B), might have evaded BUSCO solely due to its size. In many species, LRP1B is among a small number of genes that span more than a million base pairs (2.20 Mbp in sheep and 1.90 Mbp in human). In the muskox, LRP1B (Acc KAL1287620) comprises 91 highly conserved exons spanning 2.17 Mbp, encoding 4596 amino acids, and is present in its entirety on contig MUS01_AAA20220901_F8-ctg00025 (Acc JBFTXH010000025).

Assessment of genome-wide genetic diversity

Genetic heterozygosity was tabulated for our specimen and compared to the muskox previously sampled across Greenland and Canada31,55. Figure 3 depicts plots of the number of heterozygous variants per megabase for the muskox, two threatened mammalian species, and a ~ 21,000-year-old ancient muskox sample from Siberia. Consistent with previous findings measured by the tabulation of heterozygous positions, contemporary muskoxen have very low overall genetic diversity across the genome, although mainland muskoxen have higher diversity than those from the Arctic Islands, possibly because the muskox survived the 1900s over-harvesting in six geographically separated refugia. The ancient sample from Siberia showed that genetic diversity was higher in the past. Muskox genetic diversity is lower than two mammalian species under threat that have undergo recent genetic bottlenecks, the Tasmanian devil (Sarcophilus harrisii)66 and the cheetah (Acinonyx jubatus)67. Interestingly, despite the muskox having the lowest genome-wide heterozygosity reported in an ungulate, there are no overt signs of inbreeding depression in native muskox populations31. The other large Arctic ruminant, the reindeer, is relatively diverse in comparison.Figure 3 Number of heterozygous variants per megabase of reference sequence for variants of various sizes. Negative values on the x-axis indicate deletions, positive values indicate insertions, and a value of zero indicates single nucleotide variants. Heterozygous variant frequencies of different muskox populations are plotted against two diverse outbred species (human of African and European descent and wolverine), and two species that had undergone recent genetic bottleneck, the cheetah and the Tasmanian devil. The heterozygosity of the Canadian mainland muskox is on par with the cheetah, while that of the High Arctic/Greenland muskox is lower than that of the Tasmanian devil. The other large Arctic ruminant, the reindeer, is relatively diverse in comparison.

Muskox subspecies

Although muskoxen have not been viewed to be sufficiently variable to warrant sub-species recognition7, recent genome analysis showed a distinct clustering of barren-ground muskoxen separate from the Greenland and Arctic Island muskoxen9,31. However, the interpretation of the taxonomic significance of this clustering pattern is not clear in a species with such low genetic diversity. Moreover, phenotypic differences due to diet and nutrition, age, or other environmental factors have not been rigorously investigated. As such, the designation of muskox subspecies is still an open question awaiting more studies.

Muskox mitochondrial genome assembly and nuclear mitochondrial DNA

Identical, full-length mitochondrial genome sequences of 16,431 bp were assembled from long and short reads (Acc CM083088.1). Sequence comparisons with the other muskox mitochondrial genomes reported showed only minor differences, notably in the control-region, consistent with the muskox being monotypic, and do not allow definition of muskox subspecies30.

Blast analysis of the muskox mitochondrial genome against the O.moschatus_RAN27_V1.0 assembly at a threshold of 1E4 revealed 597 potential mitochondrial pseudogene loci of varying lengths and degeneracies (data not shown). These “Nuclear Mitochondrial DNAs” (NUMTs), are believed to originate from invasion of the nuclear genome by mitochondrial DNA via nonhomologous recombination68. It is generally viewed that the accumulation of NUMTs is a continuous evolutionary process69. Using the same threshold, the mouse genome (Mus musculus) has 190 copies, the rat genome (Rattus norvegicus) has 61 copies, and the human genome has 1356 copies68.

Chromosome assignment and chromosome evolution

As described in the Materials and Methods, we drew heavily on the previous comparative studies of karyotypes in the Cervidae family42,43 to anchor our assembly to the 24 chromosomes of the muskox. The muskox karyotype differed from the ancestral pecoran karyotype by six major fusions, one fission, and three inversions. The muskox karyotype includes six submetacentric and 17 acrocentric autosomes, and the sex chromosomes. Our assembly provides near complete representation of all the autosomes. The assembly of the X chromosome is essentially complete. However, the assembly of the Y chromosome is fragmented due to the extremely high composition of repetitive DNA, despite the use of the current generation of long reads. Further resolution of the Y chromosome would require yet longer and more accurate reads, perhaps combined with optical mapping. The comparative assemblies of the X and Y chromosomes in the muskox, takin, sheep and human are shown in Fig. 4. Table 2 presents the correspondence between conserved chromosome segments in the muskox, takin, sheep, goat, cow, pecoran ancestral karyotype70, and human.Figure 4 Synteny of the sex chromosomes between muskox, cattle, sheep and takin. Grey-shaded ribbons indicate regions of broad synteny, orange ribbons represent inversions, green ribbons represent translocations, and blue ribbons indicates duplications. Plotsr71 was used in the construction of the figure. (A) Comparison of chr X between the four animals. The cattle differs from the rest by three inversions and one translocation with inversion. The sheep mainly differs from muskox and takin by one inversion. The beginning of sheep and takin chromosome X represents a centromeric region not assembled in muskox. Selected genes associated with X-linked disorders or discussed in the paper are marked along with their orientation. (B) Comparison of chromosome Y between the four animals. Chromosome Y proved challenging to assemble and remained highly fragmented and incomplete for muskox, sheep and takin. Selected Y-specific genes were annotated and marked denoting their orientation.

Table 2 Correspondence of conserved chromosomal segments between muskox, sheep, goat, takin, pecoran ancestral karyotype (PAK), cattle and human.

MUSKOX	Sheep (GCA_016772045.2)	Goat (GCF_001704415.2)	Takin (GCF_023091745.1)	Pecoran Ancestral karyotype (PAK)	Cattle (GCF_002263795.3)	Human (GCF_000001405.40)	
1p	17	17	17	N1	17	22q′/12q″/4pq	
1q	1q	1	1q	A2	1	21/3/21	
2p	20	23	11p	R	23	6p	
2q	2q	2	2q	B2	2	2q″/1	
3p	24	25	2p	T	25	16p/7	
3q	3q	5	5q	C2	5	12pq′/22q″/12pq′/22q″	
4p	26	27	24	V	27	4/8p″	
4q	3p	11	11q	C1	11	2pq/9	
5p	21	29	25	W	29	11	
5q	23	24	22	s	24	18	
6p	25	28	5p	u	28	10q	
6q	19	22	1p	Q	22	3	
7	6	6	6	F	6	4pq	
8	5	7	7	E	7	19p/5	
9	1p	3	3	A1	3	1	
10	2p	8	8	B1	8	8p7 9/8p′/9	
11	12	16	16	K	16	1	
12	4	4	4	D	4	7	
13	7	10	10	G	10	15/14/15/14	
14	8	9	9	H1	9	6q	
15	14	18	18	M	18	16q/19q	
16	18	21	21	P	21	15/14	
17	10	12	12	I	12	13	
18	13	13	13	J	13	20/10p/20	
19	15	15	15	L	15	11	
20	11	19	19	N2	19	17	
21	9	14	14	H2	14	8q	
22	16	20	20	0	20	5	
23	22	26	23	U	26	10q	
X	X	X	X	X	X	X	
Y	Y		Y		Y	Y	
The relationships between muskox, PAK, cattle, and human were established by Proskuryakova and colleagues through chromosome painting43 and validated in this study by sequence alignment. The correspondence between muskox and sheep, goat and takin were established in this study by sequence alignment. Corresponding segments were ordered beginning from the centromere (most relevant for the human column). Chromosome 7–23 and X in muskox are acrocentric. The karyotype of muskox represents a departure from the PAK by six fusions (N1 + A2, R + B2, T + C2, V + C1, W + S, U + Q) and one fission (U), maintaining an autosomal fundamental number (i.e. autosomal arm count) of 58, a stable number for most karyotyped Bovidae species with varying diploid chromosome number (2n).47.

Conservation genomics

Global ecosystems are under threat from rapid climate change35,72. In addition to direct threats to food supplies, and alterations to prey-to-predator or host-to-pathogen dynamics, there are climate induced anthropogenic disruptions affecting the Arctic ecology73. The latter include increased human intrusions and industrial activities. Large herbivores, such as the muskox, are particularly at risk from such ecological disruptions19,36.

Arctic animals are adapted to live year-round in extreme seasonal variations2,34,74–76, characterized by a short season of plant growth and a period of less digestible forage19. Temperature (and duration) and photoperiod changes are major cues regulating host–pathogen interactions77. The disruption of these seasonal cues by climate change could have profound consequences in host–pathogen dynamics in the Arctic78–81.

Conservation genomics is application of advanced genomics analyses for the preservation of the viability of populations and the biodiversity of living organisms. This important arsenal of tools helps to mitigate the effects of climate change82–87. High-quality reference genome assemblies are increasingly recognized as an important foundation of conservation genomics84–91. This is particularly so as the new chromosomal-level assemblies derived from long reads are superseding the earlier, more fragmented assemblies with fewer gene representations.

One immediate use for the new assemblies is for the identification of comprehensive sets of relevant genes at exon level resolution. These gene sets are the starting points to identify specific genes or variants to elucidate adaptive pathways, and to develop genomic and epigenomic biomarkers to monitor gene flow, hybridization and introgression, disease susceptibility, and other responses to a changing environment. To provide this important resource for the muskox, we have annotated selected families or classes of genes that could participate in the conservation and management of Arctic wildlife. These include genes encoding components of the innate immune system, and are provided in Table 3 and in Supplementary Tables S3 through S9. Table 3 Selected genes of the innate immunity pathways.

Gene symbol	Alternative name/symbol	Accession	Muskox chromosome	
Toll-like receptors	
 TLR1	CD281	KAL1288282	Chr 7	
 TLR2	CD282	KAL1286936	Chr 1	
 TLR3	CD283	KAL1287412	Chr 4	
 TLR4	CD294	KAL1288035	Chr 10	
 TLR5	CD295	KAL1288066	Chr 11	
 TLR6	CD296	KAL1288284	Chr 7	
 TLR7	CD287	KAL1286564	Chr X	
 TLR8	CD288	KAL1286565	Chr X	
 TLR9	CD289	KAL1287817	Chr 6	
 TLR10	CD290	KAL1288283	Chr 7	
Nod-like receptors	NLR family pyrin domain containing			
 NLRP1	NALP1; CARD7	KAL1287737	Chr 20	
 NLRP2	NALP2	KAL1286518	Chr 15	
 NLRP3	NALP3	KAL1288227	Chr 8	
 NLRP5	NALP5	KAL1286519	Chr 15	
 NLRP6	NALP6	KAL1286925	Chr 5	
 NLRP8	NOD16	KAL1286520	Chr 15	
 NLRP12	NALP12	KAL1286516	Chr 20	
 NLRP13	NOD14; NALP13	KAL1286517	Chr 15	
 NLRP14	NALP14	KAL1287893	Chr 19	
 NLRX1	NOD5	KAL1287894	Chr 19	
 NOD1	NLRC1; CARD4	KAL1288359	Chr 12	
 NOD2	NLRC2; CARD15	KAL1287942	Chr 15	
 NLRC3	NOD3	KAL1287486	Chr 3	
 NLRC5	NOD4	KAL1287941	Chr 15	
C-type receptors	C-type lectin domain family			
 CD209	CLEC4L; DC-SIGN	KAL1286854	Chr 8	
 OLR1	CLEC8A	KAL1288126	Chr 3	
 CLEC1A	CLEC1	KAL1288098	Chr 3	
 CLEC1B	CLEC2; CLEC2B	KAL1288099	Chr 3	
 CLEC4D	CD368; CLEC6; CLECSF8; DECTIN-3	KAL1288101	Chr 3	
 CLEC4E	CLECSF9; MINCLE	KAL1288102	Chr 3	
 CLEC4G	DTTR431	KAL1286857	Chr 8	
 CLEC5A	CLECSF5	KAL1287060	Chr 12	
 CLEC7A	CLECSF12; DECTIN-1	KAL1288104	Chr 3	
 CLEC9A	CD370; DNGR-1	KAL1288105	Chr 3	
 CLEC12A	CD371	KAL1288097	Chr 3	
Rig-like receptors	Retinoic acid-inducible gene-l-like receptors			
 RIGI	DDX58; DExD/H-box helicase 58; RLR1	KAL1287283	Chr 10	
 DHX58	RLR-3; LPG2; RLR3	KAL1286474	Chr 20	
 MAVS	CARDIF; IPS-1; IPS1; VISA	KAL1287541	Chr 18	
I FIH1	MDA5; IDDM19; RLR; 2IDDM19	KAL1287835	Chr 2	
 ZBP1	Z-DNA binding protein 1	KAL1287555	Chr 18	
Adaptors	
 MYD88	IMD68; MYD88D	KAL1287811	Chr 6	
 STING1	ERIS	KAL1288231	Chr 8	
 TICAM1	TRIF; MyD88-3	KAL1287077	Chr 8	
 TIRAP	MYD88-2	KAL1287636	Chr 5	
 UNC93B1	UNC93; TLR signaling regulator	KAL1286931	Chr 5	
 TRAF1	TNF receptor associated factor 1	KAL1288038	Chr 10	
 TRAF2	TNF receptor associated factor 2	KAL1288514	Chr 4	
 TRAF3	TNF receptor associated factor 3	KAL1286829	Chr 16	
 TRAF4	TNF receptor associated factor 4	KAL1287767	Chr 20	
 TRAF5	TNF receptor associated factor 5	KAL1287044	Chr 11	
 TRAF6	TNF receptor associated factor 6	KAL1287434	Chr 19	
 TRAF7	TNF receptor associated factor 7	KAL1286545	Chr 3	
Janus and other kinases	
 JAK1	Janus kinase 1	KAL1286939	Chr 9	
 JAK2	Janus kinase 2	KAL1287446	Chr 10	
 JAK3	Janus kinase 3	KAL1286737	Chr 8	
 TYK2	Janus kinase JTK1	KAL1286878	Chr 8	
 IRAK1BP1	AIP70; SIMPL	KAL1286883	Chr 14	
 IRAK1	IRAK-1	KAL1286446	Chr X	
 IRAK2	IRAK-2	KAL1287806	Chr 6	
 IRAK3	IRAKM	KAL1288117	Chr 3	
 IRAK4	IRAK-4	KAL1286989	Chr 3	
 RIPK1	RIP-1	KAL1287230	Chr 2	
 RIPK2	RIP-2; CARD3	KAL1288301	Chr 21	
STATs	Signal transducer/activation of transcription			
 STAT1	CANDF7; IMD31A; IMD31B; IMD31C; ISGF-3; STAT91	KAL1287623	Chr 2	
 STAT2	IMD44; ISGF-3; P113; PTORCH3; STAT113	KAL1288135	Chr 3	
 STAT3	ADMIO; ADMIO1; APRF; HIES	KAL1286482	Chr 20	
 STAT4	DPMC; SLEB11	KAL1287624	Chr 2	
 STAT5A	MGF	KAL1286483	Chr 20	
 STAT5B	GHISID2	KAL1286484	Chr 20	
 STAT6	D12S1644; HIES6; IL-4-STAT; STAT6B; STAT6C	KAL1288136	Chr 3	
Interferon pathway	
 IFNA1	IFN-alpha 1	KAL1286370	Chr 10	
 IFNA2	IFN-alpha 2	KAL1286361	Chr 10	
 IFNA3	IFN-alpha 3	KAL1286362	Chr 10	
 IFNA4	IFN-alpha 4	KAL1286377	Chr 10	
 IFNB1	IFN-beta 1	KAL1287444	Chr 10	
 IFNE	IFN-epsilon	KAL1287280	Chr 10	
 IFNG	IFN-gamma	KAL1288112	Chr 3	
 IFNK	IFN-kappa	KAL1287281	Chr 10	
 IFNT1	IFN-tau 1	KAL1286371	Chr 10	
 IFNT2	IFN-tau 2	KAL1286372	Chr 10	
 IFNT3	IFN-tau 3	KAL1286373	Chr 10	
 IFNT4	IFN-tau 4	KAL1286374	Chr 10	
 IFNT5	IFN-tau 5	KAL1286375	Chr 10	
 IFNT6	IFN-tau 6	KAL1286358	Chr 10	
 IFNT7	IFN-tau 7	KAL1286359	Chr 10	
 IFNT8	IFN-tau 8	KAL1286355	Chr 10	
 IFNT9	IFN-tau 9	KAL1286356	Chr 10	
 IFNT10	IFN-tau 10	KAL1286363	Chr 10	
 IFNT11	IFN-tau 11	KAL1286364	Chr 10	
 IFNT12	IFN-tau 12	KAL1286365	Chr 10	
 IFNT13	IFN-tau 13	KAL1286378	Chr 10	
 LTA	Interferon B	KAL1286623	Chr 2	
 IFNAR1	Interferon-alpha R1	KAL1286550	Chr 1	
 IFNAR2	Interferon-alpha R2	KAL1286551	Chr 1	
 IFNGR1	CD119; IFN-gamma R1	KAL1288382	Chr 14	
 IFNGR2	IFN-gamma R2	KAL1286552	Chr 1	
 IFNLR1	IFN-lambda R1; IL-28 R1; IL-28 RA	KAL1287147	Chr 2	
 IL10RB	CD210B; CRFB4; IL-10R2; IL-10 RB; IL-28R	KAL1286553	Chr 1	
 IRF1	Interferon regulatory factor 1	KAL1287074	Chr 8	
 IRF2BP1	Interferon regulatory factor 2 BP1	KAL1286769	Chr 15	
 IRF2BP2	Interferon regulatory factor 2 BP2	KAL1287784	Chr 6	
 IRF2BPL	Interferon regulatory factor 2 BPL	KAL1287051	Chr 13	
 IRF2	Interferon regulatory factor 2	KAL1287409	Chr 4	
 IRF3	Interferon regulatory factor 3	KAL1286770	Chr 15	
 IRF4	Interferon regulatory factor 4	KAL1286770	Chr 2	
 IRF5	Interferon regulatory factor 5	KAL1288356	Chr 12	
 IRF6	Interferon regulatory factor 6	KAL1287038	Chr 11	
 IRF7	Interferon regulatory factor 7	KAL1286920	Chr 5	
 IRF8	Interferon regulatory factor 8	KAL1287935	Chr 15	
 IRF9	Interferon regulatory factor 9	KAL1287250	Chr 13	
 MAVS	IPS1; VISA; CARDIF	KAL1287541	Chr 18	
 IFRD1	Interferon dev regulator 1	KAL1288353	Chr 12	
Muskox orthologs of the pattern recognition receptors, interferons and intermediaries. See Supplementary Table S6 for the mitogen-activated protein kinases (MAPs), beta-defensins, interleukins, tumor necrosis factors (TNFs), and the chemokines.

Muskox genes associated with Arctic adaptation

Supplementary Table S3 provides exon-level annotation, chromosome location, and citations of genes that are associated with Arctic adaptation74. These genes are involved in metabolic processes, including various aspects of brown adipose tissue (BAT)92 and circadian rhythm93,94. Supplementary Table S3 also includes candidate genes in the muskox previously identified2 as having convergent amino acid substitutions, are rapidly evolving, or that are under positive selection.

Genes of the innate immunity pathways

There has been a marked increase in outbreaks of infectious disease among wildlife attributable to environmental disruptions from anthropogenic climate changes79,80. Arctic species are particularly vulnerable as pathogens invade new northern niches. The innate immune system is the first to respond to pathogens95,96. As a resource to support infection genomics and wildlife management, we provide gene annotations and accession numbers for the principal members of the innate immunity pathways in the muskox (Table 3 and Supplementary Tables S6 and S7).

Table 3 highlights the major classes of cell surface and intracellular innate receptors of the innate immunity system, and their principal signalling intermediaries in the muskox. These receptors include the Toll-like97, Nod-like98, C-type lectin99, and the RIG-I100 families of receptors that recognize pathogen-associated patterns or damage-associated molecular patterns. RIGI (DHX58) and IFIH1 (MDA5) are the principal sensors for nucleic acids from viral pathogens101. Once receptors are activated, signals are potentiated into the cell nucleus by specific adaptor molecules such as MYD88, TICAM1(TRIF), MAVS, and STING102, and a series of signalling intermediaries, notably the TRAFs, STATs and members of the IRAK, JAK103 and the mitogen-activated protein (MAPKs)104 families of kinases. Signals potentiated through MAPKs could also provide cross-talk with the adaptive immunity pathways, and the support of apoptosis or autophagy leading to the removal of damaged or infected cells. The 55 MAPK genes in muskox are provided in Supplementary Table S6.

Host responses upon receptor activation include the expression of interferons105–107 (Table 3), specific inflammatory cytokines108, chemokines109,110, and anti-microbial peptides such as the defensins111. Chemokines, notably CXCL7, CXCL9-11, CCL20, and CCL28 (Supplementary Table S6), appear to have direct antimicrobial activities similar to the defensins109. We identified 16 beta defensin genes in muskox (Supplementary Table S6). All paralogs of the large extended human interleukin-17 (IL17A to IL17F) and interleukin-17 receptor (IL17RA to IL17RE; IL17REL) families are present in muskox, pointing to a broad evolutionary conservation of all individual family members in the rapid response to infectious agents112. The chemokines, interleukins, and tumor necrosis factors and receptors involved in muskox innate immunity are presented in Supplementary Table S6.

Genes of the major histocompatibility complex

The major histocompatibility complex (MHC) is the most important region in the genome with respect to adaptive and innate immunity95,96,113–116. In human, the MHC is located on the short arm of chromosome 6 (6p21.3). The MHC is particularly gene rich, occupying more than 7.5 Mbp of the genome, comprising several hundred genes encoding ligands, receptors, and other mediators and regulators of the inflammatory and immune responses. As such, the MHC plays a vital role in fighting infection by pathogenic agents. Apart from regulating immunity, the MHC may also have roles in reproduction and social behaviors, such as mate selection and kin recognition117,118.

The MHC is divided into three main regions loosely based on related structure or functions. Recently, the MHC has been extended to include the flanking genes113. The Class I region is located nearest to the telomere and includes the Class I leukocyte antigen presenting genes. These genes encode highly polymorphic cell surface receptor subunits, which when paired with a beta-2-microglobin subunit (B2M), the functional receptor present endogenous antigens processed from intercellular pathogens to T-lymphocytes (CD8 + T-cells). The MHC Class II region includes the Class II leukocyte antigen presentation genes, which also encode highly polymorphic cell surface receptor subunits. However, they differ from the Class I receptors in that they form functional receptors through heterodimers comprised of alpha and beta Class II receptor subunits. By contrast to the widespread expression of the Class I leukocyte receptors, Class II receptor expression is restricted to the professional antigen-presenting cells such as macrophages, dendritic and B cells, and present exogenous antigens to CD4 + helper T-cells. The Class III region contains genes encoding immune regulatory molecules, such as tumor necrosis factor (TNF), TNF family members, heat shock proteins, and complement factors.

Figure 5A compares the chromosomal organizations of the MHC in human, muskox, sheep, goat and cow. The chromosome arms in the five species share extensive synteny along their lengths, with the cow less so as indicated by the shorter lengths of the synteny blocks. Overall, muskox MHC contains a similar number of principal genes and are organized similarly as in the other species. Figure 5B is a schematic of the functional MHC genes we annotated in the muskox. However, when compared to human MHC, a striking finding is that in muskox, sheep, and cow, the MHC Class II region is interrupted, where a large segment comprising the distal portion of the MHC Class II region through to the Extended MHC Class II region is inverted in orientation, resulting in the distal portion of the MHC Class II region being translocated 17.4 Mb away from the rest of the complex in the direction of the centromere. Otherwise, we observed a high degree of synteny in the overall organization of muskox chromosome 2 with human chromosome 6 in GRCh38.p14.Figure 5 Major histocompatibility complex (MHC) on muskox chromosome 2. (A) Upper panel: Organization of the human MHC. Landmark genes serving as region boundaries are highlighted. Region lengths are drawn to scale. Lower panel: Comparison of the chromosome arm containing the MHC between human, muskox, sheep, goat and cattle was visualized using plotsr.70 Grey-shaded ribbons indicate regions of broad synteny, orange ribbons represent inversions, and green ribbons indicate translocations. When compared to human, the MHC Class II region in muskox, sheep, and cow is interrupted, where a segment is inverted in orientation from the rest of the cluster as well as being translocated 17.4 Mb toward the direction of the centromere. There is broad synteny across the chromosome arm among the Bovidae species, with cattle being the outgroup of the four. (B) Gene map of the 245 genes in the extended MHC in muskox. Class I and Class II leukocyte antigen presenting genes are in red type. Asterisk (*) denotes a pseudogene.

In the muskox MHC Class I region we identified five Class I leukocyte antigen presenting genes, HLA-L1, HLA-L2, HLA-L5, HLA-L6 and HLA-L7. Two other genes, HLA-L3* and HLA-L4*, were predicted to be pseudogenes based on the presence of in-frame termination codons, which were verified using Illumina short reads. MICA and MICB in human are adjacent stress-inducible genes related to the MHC Class I leukocyte antigen presenting genes119, but MICA and MICB use KLRK1 (NKG2D) as the co-receptor subunit instead of B2M120. KLRK1 (CD314, NKG2-D) and B2M co-receptor genes are located on muskox chromosomes 3 and 13, respectively. Interesting, we observed a tandem duplication of B2M on muskox chromosome 13. The duplicated gene appears to be functional and was assigned the symbol B2ML. In the muskox, we only find MICB. Since the two genes might have overlapping functions, the absence of MICA in the muskox might be mitigated by redundancy; however, its absence could impair the muskox’s response to certain stressors.

In the muskox MHC Class II region, we identified thirteen Class II leukocyte antigen presenting genes: HLA-DRA-L1, HLA-DRB-L1, HLA-DRB-L2, HLA-DPA-L1, HLA-DQB-L1, HLA-DQA-L1, HLA-DQB-L2, HLA-DOA-L1, HLA-DMA-L1, HLA-DMB-L1, HLA-DOB-L1, HLA-DQA-L2, and HLA-DRB-L3. As denoted by the A and B designations in their assigned gene symbols, six genes encode potential alpha-receptor subunits and seven genes encode potential beta-receptor subunits.

The MHC Class III genes are generally heterogeneous in structure. None present antigens to T-cells, but most are involved in some other aspects of immune regulation or inflammation121,122. We identified and annotated 61 genes in the muskox MHC Class III region, including members of the TNF family123,124, the Lymphocyte Antigen-6 family members125, and the members of the complement cascade.126 Compared to human, we observed a tandem duplication of the C4 gene in the muskox. The second gene was assigned the symbol C4L. Including the 121 genes in the extended Class I and Class II regions, the final number of annotated genes in the muskox extended MHC is 245. Exon-level annotations for these genes are provided in Supplementary Table S4.

Two CD antigens are encoded by the MHC, CD167 (DDR1) and CD337 (NCR3). CD (Cluster of Differentiation) molecules or antigens are cell surface markers, many of which are receptors or ligands involved in activation or inhibitory pathways.127 As such, many CD antigens are biomarkers of, or are participants in, infectious disease. A list of the several hundred annotated CD antigens in the muskox can be found in Supplementary Table S7.

Genetic diversity of muskox MHC

We have shown the muskox MHC region is similar in structure and overall genomic organization to the other Bovidae, indicating no potential deficiencies in muskox due to gross deletions or arrangements in the MHC region. The number of MHC Class I and Class II genes in the muskox is also similar to many other mammals, suggest that at face value, the muskox is immune-competent in interactions with T-cells. Genetic diversity within a population is viewed to be important in evolutionary ecology and conservation biology128–131. We thus examined the genetic (polymorphic) diversity of the MHC genes in muskox.

In an early study of the muskox, no genetic diversity was found using an exon 2 probe that spanned the MHC DRB locus (corresponding to HLA-DRB-L1 in the present study)132. This early result points to a lack of MHC diversity in muskox. However, the study was constrained by the small size of the study cohort, and by the limited sensitivity of amplicon sequencing that targeted only a single exon. With the complete characterization of muskox MHC combined with the use of whole genome re-sequencing and mapping-based variant calling methods133–135 we could now overcome the sensitivity and throughput issues associated with previous amplicon sequencing attempts. To test the feasibility of this approach, we took advantage of whole-genome short-reads from a recent population survey of the muskox31 to provide an initial assessment of the genetic diversity of all the genes in the MHC of the muskox. These reads are available through NCBI SRA and are comprised of sets of Illumina reads with an average 14× genome coverage of individuals from 18 distinct populations of muskoxen across their native range. For our study, we downloaded reads from one representative specimen from each population. We included reads from a 21,100-year-old individual from Siberia from which inferences could be made of the muskox’s demographic history.

Reads from individual muskox samples were mapped onto our newly constructed reference assembly, O.moschatus_RAN27-v1.0, and variant calls were made from the mapped reads against this reference genome. Figure 6A presents the variant calls made for each muskox specimen across the coding regions of genes in the MHC regions (see Fig. 5B for a schematic of the gene organization in the muskox). All variant calls were found to be single base substitutions. We did not observe any insertions or deletions among the calls. The specimen from Banks Island, ROMMRAN27, from which DNA was used to assemble the reference genome is denoted by an asterisk (*). Variant calls made for ROMMRAN27 were heterozygous Single Nucleotide Polymorphisms (SNPs) present in our sample. The two-letter prefix for each sample is a geographic identifier denoting the origin of the 18 muskox specimen shown in Fig. 6B. The prehistoric sample from Siberia is designated SIB.Figure 6 Gene diversity in the MHC region of muskoxen across various geographic locations. (A) Illumina reads of 20 muskoxen, including a 21,000-year-old individual from Siberia, were used to tabulate variants in the coding region of the 245 genes in the MHC (see Material and Methods). ROMMRAN27, from which we have assembled the genome is denoted by an asterisk (*). The two-letter prefix is a geographic abbreviation. The prehistoric sample from Siberia is designated SIB. (B) Geographic origins of the 19 muskox samples in northern Canada and Greenland. The Siberian sample is not depicted.

Variant calls spanning the coding regions of the 245 genes in the MHC across all 20 muskox samples are tabulated in Supplementary Table S5. It is likely the calls presented in Supplementary Table S5 are an under-representation, since we adopt stringent mapping criteria in an effort to minimize false positive variant calls. The sensitivity of a short-read mapping approach to call variants is highest for the regions of the genome that are free of major mapping impediments, such as the presence of highly repetitive sequences and other features associated with genomic regions of low complexity. Historically, the MHC region was renowned for the presence of such impediments, which could not be fully resolved until the recent advent of using long reads with better mapping specificity for variant calling136,137. However, until the implementation of using long reads to make variant calls for the muskox, the present use of shortreads might result in significant false-negative calls, but it would still provide a useful first look at the genetic diversity in this region of the genome.

From the initial set of variants depicted in Fig. 6A, there appears to be no clear and consistent regional pattern, despite that some populations have been through human-caused bottlenecks, while others have been through climate-caused ones. Quite possibly, low population sampling has hampered a more complete assessment of the species. For example, there are no representations from Victoria Island, and Banks Island is represented only by our reference specimen, which seemed to be neither particularly invariant nor have a high number of variants compared to those from other Arctic islands. Interestingly, the prehistoric sample from Siberia, SIB, does not consistently have the highest number of variants across all six groups of genes.

The MHC Class I and Class II genes function to present processed antigens to CD8+ T-cells and CD4+ helper T-cells, respectively, and are critical for mounting an immune response. Table 4 summarizes variant calls for the seven MHC Class I genes, and the thirteen MHC Class II genes across the twenty muskox samples. Column 3 depicts the number of sets of unique combinations of single base variants (variant profile) for each gene across the 19 modern muskox specimens. However, in the absence of phasing information, such as long reads, RNA-seq reads, or other genetic information, to establish the two haplotypes, we cannot reconstruct the two alleles from each variant profile with certainty. Nevertheless, these profiles provide a direct indication, albeit a lower limit, of the coding diversity of the muskox MHC. Table 4 Number of variants in the MHC Class I and Class II genes across 20 muskox samples of different geographic locations.

Category	Gene	Unique combinations of variants in 19 modern specimens	Siberia	Canada mainland	Canada Arctic Islands	Greenland	
SIB	BL-24	CH-7	KU-23	TH-27	*ROM	AI-1	AH-1	BI-35	CI-8	CM-2	DI-16	EI-23	EU-7	FR-2	GF-19	SF-1	HD-3	JA-1	RY-3	
MHC Class I	HLA-L1	9			5	21	8	3		17	3	12	3				12	11					
MHC Class I	HLA-L2	4	3				13			1		1					9						
MHC Class I	HLA-L3*	8					5	6			7		6				12	1			7		
MHC Class I	HLA-L4*	5	2				1	2			2		2		5								
MHC Class I	HLA-L5	1																					
MHC Class I	HLA-L6	1	1																				
MHC Class I	HLA-L7	2						1	1													1	
MHC Class II	HLA-DRA-L1	3		2	2			1		2												2	
MHC Class II	HLA-DRB-L1	7		7	6		5	7		5						5						6	
MHC Class II	HLA-DRB-L2	2	3		1			1															
MHC Class II	HLA-DPA-L1	2	1	2	2			2			2												
MHC Class II	HLA-DQB-L1	3	3	26	2			26			26												
MHC Class II	HLA-DQA-L1	1	3																				
MHC Class II	HLA-DQB-L2	3	1	9	9			9			7												
MHC Class II	HLA-DOA-L1	2																				1	
MHC Class II	HLA-DMA-L1	2		1	1		1																
MHC Class II	HLA-DMB-L1	1																					
MHC Class II	HLA-DOB-L1	1																					
MHC Class II	HLA-DQA-L2	2		1		1																	
MHC Class II	HLA-DRB-L3	1	1																				
Variant calls for the seven MHC Class I genes and thirteen MHC Class II genes were performed in as described in the Materials and Methods. The assembled sample ROMMRAN27 (*ROM) is in bold. Pseudogenes are designated by an asterisk after the gene name. Column 3 depicts the number of sets of unique combinations of single base variants (variant profile) for each gene across the 19 modern muskox specimens.

Even though the small sample size precludes an in-depth analysis for the muskox, some general observations can be made. For instance, HLA-L1 and HLA-L2 appear to be particularly polymorphic across many samples. Mainland muskoxen, with the exception of the Helena Island sample (sample BI), and our Banks Island sample (ROMMRAN27), are generally more diverse than samples from the other Arctic islands, especially those from Eastern Greenland (samples JA and HD). Interestingly, Class I pseudogenes, HLAL3* and HLA-L4*, accumulated many variants principally across the Arctic Island samples, none of which however restore the coding sequence to create a functional gene. Finally, we observed that HLA-L5, HLA-L6, HLA-DQA-L1, HLA-DQ-L1, HLA-DMB-L1, HLA-DQB-L1, and HLA-DRB-L3 are markedly free of variants across all samples, when compared to our reference specimen, ROMMRAN27.

Genetic diversity in the MHC is believed to impact wildlife health and conservation128–131. In contrast to early work pointing to low or no genetic diversity in the muskox MHC132, our tabulation of variants across multiple specimens showed a significant diversity across the MHC. Although an extensive direct gene-to-gene comparison could not be made, at least qualitatively in selective regions that could be compared, the diversity of the muskox MHC appears to be similar to the level reported for the reindeer, another Arctic ruminant under threat138. While the muskox has been shown to have the lowest genome-wide heterozygosity reported in an ungulate31 (Fig. 3), this lack of genetic diversity is not necessarily extended to the MHC region. This finding, along with the muskox having no overt signs of inbreeding depression in native populations31, is consistent with the view of Teixeira and Huber139 that argues against the perceived importance of neutral genetic diversity over functional genetic diversity for the conservation of wild populations and species.

Conservation management

The present study provides genomics tools that will advance muskox conservation and management in at least three ways. First, the creation of a high-quality reference genome provides a resource to develop genetic markers that could be used estimate gene flow, effective population size, the timing of extirpation, and to monitor progress of future recolonization efforts. As shown by our initial survey of diversity of the MHC in the muskox, whole genome reference-assisted re-sequencing is a sensitive and powerful tool to identify markers. In the immediate future, the use of re-sequencing is likely to be used in a discovery phase, where selective cohorts are re-sequenced to generate a comprehensive set of informative sequence markers, after which these markers would be interrogated on lower cost and higher throughput genotyping panels that are constructed for specific applications.

Second, the genomic tools especially the annotated genes will contribute to management and conservation. Muskox population structure and connectivity can now be assessed from both a neutral and adaptive basis, as currently muskox populations are delimited based on hunting areas. The annotated genes can contribute to measure connectivity between populations and for understanding the dynamics of expanding muskox distribution on the mainland or options for translocations to rescue depleted populations. Regional populations can be sampled to assess for local adaptive loci identification from the annotated genes, and regional planning undertaken to conserve local adaptations. However, there are still considerable uncertainties in the present muskox population numbers and trends, thereby limiting the usefulness of the new genomics tools. In their recent review19, Cuyler and colleagues have acknowledged these shortcomings and have proposed increased frequency of muskox surveys, standardizing monitoring protocols, and the inclusion other informative metrics.

Finally, the remarkable super-fine under-wool of the muskox has garnered much attention for its economic potential, and has driven some early attempts to domesticate the muskox to improve yield and ease of qiviut harvest12–15. While the role of domestication as a driver for conservation and management of endangered species is controversial140–142, it could be one facet of an integrated adaptive solution that is locally implemented. However, domestication is a long and difficult process, but the genetics of domestication are relatively well understood for livestock143–148. Although muskox domestication has been attempted, it has not yet succeeded149–151. Efforts were too small-scale and brief to allow the selection for particular traits, although the muskox became tame. As a first step to support a possible future marker assisted selection scheme152–154 for the muskox, we provide exon-level annotation of genes that have contributed to livestock domestication (Supplementary Table S8) and desirable commercial traits such as meat and dairy production, wool quality, prolificity, and heat tolerance155–159 (Supplementary Table S9).

Given the high market price of qiviut, the genetic signatures for qiviut may become useful in the future, especially if the genetics of its production differ regionally with different muskox populations. To this end, Fig. 7 and Supplementary Table S10 show the organization and annotation of the principal keratin and keratin-associated protein gene clusters in muskox. Keratins and the keratin-associated proteins are conserved across multiple species with family members encoding the principal structural components of hair and wool160–163. Importantly, variants of these genes have been shown to associate with wool quality, and are potential selection markers for livestock improvements164–167.Figure 7 Schematic of Muskox keratin and keratin-associated protein gene clusters. Gene clusters are depicted in the same orientation as in the assembly. Genes flanking the clusters are depicted by black boxes. Keratin genes are depicted by green boxes. Keratin-associated protein genes are depicted by blue boxes. The direction of transcription is indicated by the box outdent. Gene annotations can be found in Supplementary Table S10.

Arctic conservation management can be complex with intersecting and at times conflicting environmental, cultural and socioeconomic issues90,168,169. However, co-management (i.e., joint management between Indigenous people and government) and adaptive management169,170, where multiple integrated solutions are differentially implemented locally, can help navigate many of those complexities. In particular, a co-management regime gives a clear voice to local communities in the balancing of cultural traditions, and costs incurred by environmental protection can be offset against the potential returns from developing economic values of muskoxen, including meat and leather production, sport hunting, tourism, and production of qiviut.

In conclusion, we report a chromosomal-level assembly of a muskox from Banks Island in the Canadian Arctic Archipelago with a view toward genomics-based approaches for the management and conservation of the muskox, with relevant benefits to Inuit communities and muskox conservation.

Supplementary Information

Supplementary Information.

Supplementary Tables.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-024-67270-9.

Acknowledgements

We are grateful to the staff of the Informatics and Biostatistics, and Sequencing Facilities of The Centre for Applied Genomics (TCAG) at The Hospital for Sick Children in Toronto. TCAG is part of CGEn, a Major Science Initiative of the Canada Foundation for Innovation. We acknowledge the contributions of Karen Ho and Sachin Desai for expert library construction and DNA sequencing, Joe Whitney and Omar Hamdan for informatics support, and Peter J. Van Coeverden de Groot for sample collection. The sample of muskox analyzed in this study was originally obtained from the tissue collection of the University of Alberta under the direction of Dr. Curtis Strobeck in 1991. We thank the Inuvialuit harvesters at the time from Sachs Harbour, NWT and Dr. Strobeck for this critical contribution. We acknowledge the Inuvialuit’s long-standing role and sovereign responsibilities in muskox management.

Author contributions

SL and SWS conceived the project. SL directed the project, analysed results, performed gene annotation, and wrote the manuscript. TNHL analysed results and performed genome assembly, informatics and gene annotation. BT performed genetic diversity analysis. AHYT contributed to gene annotation. TA contributed to the analysis of mitochondrial DNA. AG contributed to aspects of biology, phylogenetic analysis, ecology and conservation management. All authors contributed to writing and editing the manuscript.

Funding

This study was funded by the Lau Family Endowment for Genome Science Development and by Genome Canada’s Disruptive Innovation in Genomics Program (Grant number 9425). The work was conducted at The Centre for Applied Genomics (TCAG) using infrastructure funded by the Canada Foundation for Innovation, and was operationally supported by the Canada Foundation for Innovation (CGEn Major Science Initiative), the Government of Ontario, Genome Canada through Ontario Genomics, and The Hospital for Sick Children (SickKids) Foundation. SWS holds the Northbridge Chair in Paediatric Research, a joint Hospital-University Chair between the University of Toronto, The Hospital for Sick Children, and the SickKids Foundation.

Data availability

Sequences described for the muskox have been submitted to GenBank and other public archives and repositories. This study has been assigned BioProject number PRJNA1071053 to facilitate data dissemination. Accessions for muskox genes depicted in the manuscript are listed in the relevant Supplementary Tables.

Competing interests

The authors declare no competing interests.

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
==== Refs
References

1. Lent PC Ovibos moschatus Mamm. Species 1988 302 1 9 10.2307/3504280
Lent, P. C. Ovibos moschatus. Mamm. Species 302, 1–9 (1988).10.2307/3504280
2. Li M Convergent molecular evolution of thermogenesis and circadian rhythm in arctic ruminants Proc. R. Soc. B 2023 290 20230538 10.1098/rspb.2023.0538 37253422
Li, M. et al. Convergent molecular evolution of thermogenesis and circadian rhythm in arctic ruminants. Proc. R. Soc. B 290, 20230538 (2023).37253422 10.1098/rspb.2023.0538
3. Allen JA Ontogenetic and other variations in muskoxen, with a systematic review of the muskox group, recent and extinct Mem. Am. Mus. Nat. Hist. 1913 1 6 105 226
Allen, J. A. Ontogenetic and other variations in muskoxen, with a systematic review of the muskox group, recent and extinct. Mem. Am. Mus. Nat. Hist. 1(6), 105–226 (1913).
4. Glover R The muskox (Ovibos moschatus) Oryx 1953 2 2 76 86 10.1017/S0030605300036371
Glover, R. The muskox (Ovibos moschatus). Oryx 2(2), 76–86 (1953).10.1017/S0030605300036371
5. Zimmermann FAW Geographische Geschichte des Menschen und der Vierfusigen Thiere 1780 Weygand 86 88
Zimmermann, F. A. W. Geographische Geschichte des Menschen und der Vierfusigen Thiere Vol. 2, 86–88 (Weygand, 1780).
6. de Blainville HHD Sur plusier espéces d’animaux mammiféres de l’ordre de ruminans Bull. Sci. Soc. Philomath. Paris 1816 1816 5 73 82
de Blainville, H. H. D. Sur plusier espéces d’animaux mammiféres de l’ordre de ruminans. Bull. Sci. Soc. Philomath. Paris 1816(5), 73–82 (1816).
7. Tener JS Muskoxen in Canada, a Biological and Taxonomic Review. Canadian Wildlife Service Monograph No. 2 1965 Queen’s Printer 166
Tener, J. S. Muskoxen in Canada, a Biological and Taxonomic Review. Canadian Wildlife Service Monograph No. 2 166 (Queen’s Printer, 1965).
8. Wilson DE Reeder DM Mammal Species of the World. A Taxonomic and Geographic Reference 2005 3 Johns Hopkins Press
Wilson, D. E. & Reeder, D. M. (eds) Mammal Species of the World. A Taxonomic and Geographic Reference 3rd edn. (Johns Hopkins Press, 2005).
9. Hansen CCR The muskox lost a substantial part of its genetic diversity on its long road to Greenland Curr. Biol. 2018 28 4022 2028 10.1016/j.cub.2018.10.054 30528581
Hansen, C. C. R. et al. The muskox lost a substantial part of its genetic diversity on its long road to Greenland. Curr. Biol. 28, 4022–2028 (2018).30528581 10.1016/j.cub.2018.10.054
10. Kutz S Muskox health ecology symposium 2016: gathering to share knowledge on Umingmak in a time of rapid change Arctic 2017 70 2 225 236 10.14430/arctic4656
Kutz, S. et al. Muskox health ecology symposium 2016: gathering to share knowledge on Umingmak in a time of rapid change. Arctic 70(2), 225–236 (2017).10.14430/arctic4656
11. Tomaselli M Iqaluktutiaq voices: Local perspectives about the importance of muskoxen, contemporary and traditional use and practices Arctic 2018 71 1 1 4 10.14430/arctic4697
Tomaselli, M. et al. Iqaluktutiaq voices: Local perspectives about the importance of muskoxen, contemporary and traditional use and practices. Arctic 71(1), 1–4 (2018).10.14430/arctic4697
12. Barr W The commercial trade in muskox hides in the Northwest Territories in 1860–1916 Rangifer 1991 11 2 81 81 10.7557/2.11.2.982
Barr, W. The commercial trade in muskox hides in the Northwest Territories in 1860–1916. Rangifer 11(2), 81–81 (1991).10.7557/2.11.2.982
13. Von Bergen W Muskox wool and its possibilities as a new textile fiber Melliand Text. Mon. 1932 3 10 844 846
Von Bergen, W. Muskox wool and its possibilities as a new textile fiber. Melliand Text. Mon. 3(10), 844–846 (1932).
14. Rowell JE Fiber characteristics of qiviut and guard hair from wild muskoxen (Ovibos muschatus) J. Anim. Sci. 2001 79 1670 1674 10.2527/2001.7971670x 11465352
Rowell, J. E. et al. Fiber characteristics of qiviut and guard hair from wild muskoxen (Ovibos muschatus). J. Anim. Sci. 79, 1670–1674 (2001).11465352 10.2527/2001.7971670x
15. Helfferich D The muskox: Wooly and warm in a northern fiber industry Agroborealis 2007 39 1 29 37
Helfferich, D. The muskox: Wooly and warm in a northern fiber industry. Agroborealis 39(1), 29–37 (2007).
16. Mosbacher JB Quantifying muskox plant biomass removal and spatial relocation of nitrogen in a high arctic tundra ecosystem Arct. Antarct. Alp. Res. 2016 48 2 229 240 10.1657/AAAR0015-034
Mosbacher, J. B. et al. Quantifying muskox plant biomass removal and spatial relocation of nitrogen in a high arctic tundra ecosystem. Arct. Antarct. Alp. Res. 48(2), 229–240 (2016).10.1657/AAAR0015-034
17. Mosbacher JB Mushoxen modify plant abundance, phenology, and nitrogen dynamics in a high arctic fen Ecosystems 2019 22 5 1095 1107 10.1007/s10021-018-0323-4
Mosbacher, J. B. et al. Mushoxen modify plant abundance, phenology, and nitrogen dynamics in a high arctic fen. Ecosystems 22(5), 1095–1107 (2019).10.1007/s10021-018-0323-4
18. Falk JM Large herbivore grazing affects the vegetation structure and greenhouse gas balance in a high arctic mire Envir. Res. Let. 2015 10 4 45001 10.1088/1748-9326/10/4/045001
Falk, J. M. et al. Large herbivore grazing affects the vegetation structure and greenhouse gas balance in a high arctic mire. Envir. Res. Let. 10(4), 45001 (2015).10.1088/1748-9326/10/4/045001
19. Cuyler C Muskox status, recent variation, and uncertain future Ambio 2020 49 805 819 10.1007/s13280-019-01205-x 31187429
Cuyler, C. et al. Muskox status, recent variation, and uncertain future. Ambio 49, 805–819 (2020).31187429 10.1007/s13280-019-01205-x
20. Gunn, A. & Forchammer, M. Ovibos moschatus. The IUCN Red List of Threaten Species (2022).
21. Gunn A The history, status and management of the muskoxen on Banks Island Arctic 1991 44 3 188 195 10.14430/arctic1538
Gunn, A. et al. The history, status and management of the muskoxen on Banks Island. Arctic 44(3), 188–195 (1991).10.14430/arctic1538
22. Kutz S Cross-Canada disease report—Erysipelothrix rhusiopathiae associated with recent widespread muskox mortalities in the Canadian Arctic Can. Vet. J. 2015 56 560 563 26028673
Kutz, S. et al. Cross-Canada disease report—Erysipelothrix rhusiopathiae associated with recent widespread muskox mortalities in the Canadian Arctic. Can. Vet. J. 56, 560–563 (2015).26028673
23. Forde TL Bacterial genomics reveal the complex epidemiology of an emerging pathogen in Arctic and Boreal Ungulates Front. Micol. 2016 7 11 1759
Forde, T. L. et al. Bacterial genomics reveal the complex epidemiology of an emerging pathogen in Arctic and Boreal Ungulates. Front. Micol. 7(11), 1759 (2016).
24. Kutz SJ Invasion, establishment, and range expansion of two parasitic nematodes in the Canadian Arctic Glob. Change Biol. 2013 19 3254 3262 10.1111/gcb.12315
Kutz, S. J. et al. Invasion, establishment, and range expansion of two parasitic nematodes in the Canadian Arctic. Glob. Change Biol. 19, 3254–3262 (2013).10.1111/gcb.12315
25. Okulewicz A The impact of global climatic change on the spread of nematodes Ann. Parasitol. 2017 63 1 15 20 28432859
Okulewicz, A. The impact of global climatic change on the spread of nematodes. Ann. Parasitol. 63(1), 15–20 (2017).28432859
26. Kafle P Range expansion of muskox lungworms track rapid arctic warming: Implications of geographic colonization under climate forcing Sci. Rep. 2020 10 17323 10.1038/s41598-020-74358-5 33057173
Kafle, P. et al. Range expansion of muskox lungworms track rapid arctic warming: Implications of geographic colonization under climate forcing. Sci. Rep. 10, 17323 (2020).33057173 10.1038/s41598-020-74358-5
27. Tomaselli M A transdisciplinary approach to Brucella in muskoxen of the Western Canadian Arctic 1989–2016 EcoHealth 2019 16 488 501 10.1007/s10393-019-01433-3 31414318
Tomaselli, M. et al. A transdisciplinary approach to Brucella in muskoxen of the Western Canadian Arctic 1989–2016. EcoHealth 16, 488–501 (2019).31414318 10.1007/s10393-019-01433-3
28. Holm L-E Low genetic variation in muskoxen (Ovibos moschatus) from western greenland using microsatellites Mol. Ecol. 1999 8 675 679 10.1046/j.1365-294x.1999.00615.x 10327661
Holm, L.-E. et al. Low genetic variation in muskoxen (Ovibos moschatus) from western greenland using microsatellites. Mol. Ecol. 8, 675–679 (1999).10327661 10.1046/j.1365-294x.1999.00615.x
29. MacPhee RDE Late quaternary loss of genetic diversity in muskox (Ovibos) BMC Evol. Biol. 2005 5 49 10.1186/1471-2148-5-49 16209705
MacPhee, R. D. E. et al. Late quaternary loss of genetic diversity in muskox (Ovibos). BMC Evol. Biol. 5, 49 (2005).16209705 10.1186/1471-2148-5-49
30. Groves CP Interspecific variation in mitochondrial DNA of muskoxen, based on control-region sequences Can. J. Zool. 2011 75 4 568 575 10.1139/z97-070
Groves, C. P. Interspecific variation in mitochondrial DNA of muskoxen, based on control-region sequences. Can. J. Zool. 75(4), 568–575 (2011).10.1139/z97-070
31. Pečnerová P Population genomics of the muskox’s resilience in the near absence of genetic variation Mol. Ecol. 2024 33 2 e17205 10.1111/mec.17205 37971141
Pečnerová, P. et al. Population genomics of the muskox’s resilience in the near absence of genetic variation. Mol. Ecol. 33(2), e17205 (2024).37971141 10.1111/mec.17205
32. Prewer E Already at the bottom? Demographic declines are unlikely further to undermine genetic diversity of a large Arctic ungulate: Muskox, Ovibos moschatus (Artiodactyla: Bovidae) Biol. J. Linn. Soc. 2020 129 459 469 10.1093/biolinnean/blz175
Prewer, E. et al. Already at the bottom? Demographic declines are unlikely further to undermine genetic diversity of a large Arctic ungulate: Muskox, Ovibos moschatus (Artiodactyla: Bovidae). Biol. J. Linn. Soc. 129, 459–469 (2020).10.1093/biolinnean/blz175
33. Dussex N Population genomics of the critically endangered kākāpō Cell Genom. 2021 1 1 100002 10.1016/j.xgen.2021.100002 36777713
Dussex, N. et al. Population genomics of the critically endangered kākāpō. Cell Genom. 1(1), 100002 (2021).36777713 10.1016/j.xgen.2021.100002
34. Dussex N Adaptation to the high-Arctic island environment despite long-term reduced genetic variation in Svalbard reindeer iScience 2023 26 107811 10.1016/j.isci.2023.107811 37744038
Dussex, N. et al. Adaptation to the high-Arctic island environment despite long-term reduced genetic variation in Svalbard reindeer. iScience 26, 107811 (2023).37744038 10.1016/j.isci.2023.107811
35. IPCC Summary for Policymakers. In: Climate Change 2023: Synthesis Report. Contribution of Working Groups I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (eds Core Writing Team, H. Lee & J. Romero) 1–34 (IPCC). 10.59327/IPCC/AR6-9789291691647.001.
36. Atwood TB Herbivores at the highest risk of extinction among, bird, and reptiles Sci. Adv. 2020 6 eabb9458 10.1126/sciadv.abb8458
Atwood, T. B. Herbivores at the highest risk of extinction among, bird, and reptiles. Sci. Adv. 6, eabb9458 (2020).10.1126/sciadv.abb8458
37. Prewer E Draft genome assembly of an iconic species: Muskox (Ovibos moschatus) Genes 2022 13 809 10.3390/genes13050809 35627194
Prewer, E. et al. Draft genome assembly of an iconic species: Muskox (Ovibos moschatus). Genes 13, 809 (2022).35627194 10.3390/genes13050809
38. Warburton PE Sebra RP Long-read DNA sequencing: Recent advances and remaining challenges Annu. Rev. Genom. Hum. Genet. 2023 24 109 132 10.1146/annurev-genom-101722-103045
Warburton, P. E. & Sebra, R. P. Long-read DNA sequencing: Recent advances and remaining challenges. Annu. Rev. Genom. Hum. Genet. 24, 109–132 (2023).10.1146/annurev-genom-101722-103045
39. Aasen E Medrano JF Amplification of the ZFY and ZFX genes for sex identification in humans, cattle, sheep and goats Bio/Technology 1990 8 1279 1281 1369448
Aasen, E. & Medrano, J. F. Amplification of the ZFY and ZFX genes for sex identification in humans, cattle, sheep and goats. Bio/Technology 8, 1279–1281 (1990).1369448
40. Simpson JT Exploring genome characteristics and sequence quality without a reference Bioinformatics 2014 30 9 1228 1235 10.1093/bioinformatics/btu023 24443382
Simpson, J. T. Exploring genome characteristics and sequence quality without a reference. Bioinformatics 30(9), 1228–1235 (2014).24443382 10.1093/bioinformatics/btu023
41. Kolmogorov M Assembly of long, error-prone reads using repeat graphs Nat. Biotechnol. 2019 37 5 540 546 10.1038/s41587-019-0072-8 30936562
Kolmogorov, M. et al. Assembly of long, error-prone reads using repeat graphs. Nat. Biotechnol. 37(5), 540–546 (2019).30936562 10.1038/s41587-019-0072-8
42. Proskuryakova AA Comparative studies of karyotypes in Cervidae family Cytogenet. Genome Res. 2022 162 312 322 10.1159/000527349 36463851
Proskuryakova, A. A. et al. Comparative studies of karyotypes in Cervidae family. Cytogenet. Genome Res. 162, 312–322 (2022).36463851 10.1159/000527349
43. Proskuryakova AA Comparative chromosome mapping of Musk ox and X chromosome among some Bovidae species Genes 2019 10 857 10.3390/genes10110857 31671864
Proskuryakova, A. A. et al. Comparative chromosome mapping of Musk ox and X chromosome among some Bovidae species. Genes 10, 857 (2019).31671864 10.3390/genes10110857
44. Rubes I Comparative molecular cytogenetics in Cetartiodactyla Cytogenet. Genome Res. 2012 137 2–4 194 207 10.1159/000338932 22627059
Rubes, I. et al. Comparative molecular cytogenetics in Cetartiodactyla. Cytogenet. Genome Res. 137(2–4), 194–207 (2012).22627059 10.1159/000338932
45. Tietz WJ Teal JJ Chromosome number of the muskox Can. J. Zool. 1967 45 235 237 10.1139/z67-032
Tietz, W. J. & Teal, J. J. Chromosome number of the muskox. Can. J. Zool. 45, 235–237 (1967).10.1139/z67-032
46. Heck HD Chromosome study of members of the subfamily Caprinae and Bovinae, family Bovidea, the muskox, ibex, aoudad, Congo buffalo, and gaur Säugetiek. Mitt. 1968 33 172 179
Heck, H. D. et al. Chromosome study of members of the subfamily Caprinae and Bovinae, family Bovidea, the muskox, ibex, aoudad, Congo buffalo, and gaur. Säugetiek. Mitt. 33, 172–179 (1968).
47. Gallagher DS Jr Womack JE Chromosome conservation in the Bovidae J. Hered. 1991 83 287 298 10.1093/oxfordjournals.jhered.a111215
Gallagher, D. S. Jr. & Womack, J. E. Chromosome conservation in the Bovidae. J. Hered. 83, 287–298 (1991).10.1093/oxfordjournals.jhered.a111215
48. Li H Minimap2: Pairwise alignment for nucleotide sequences Bioinformatics 2018 34 3094 3100 10.1093/bioinformatics/bty191 29750242
Li, H. Minimap2: Pairwise alignment for nucleotide sequences. Bioinformatics 34, 3094–3100 (2018).29750242 10.1093/bioinformatics/bty191
49. Tarailo M Chen N Using RepeatMasker to identify repetitive elements in genomic sequences Curr. Protoc. Bioinform. 2009 4 10
Tarailo, M. & Chen, N. Using RepeatMasker to identify repetitive elements in genomic sequences. Curr. Protoc. Bioinform. 4, 10 (2009).
50. Rhie A Merqury: Reference-free quality, completeness, and phasing assessment for genome assemblies Genome Biol. 2020 21 245 10.1186/s13059-020-02134-9 32928274
Rhie, A. et al. Merqury: Reference-free quality, completeness, and phasing assessment for genome assemblies. Genome Biol. 21, 245 (2020).32928274 10.1186/s13059-020-02134-9
51. Zhang H A comprehensive evaluation of long read error correction methods BMC Genom. 2020 21 Suppl 6 889 10.1186/s12864-020-07227-0
Zhang, H. et al. A comprehensive evaluation of long read error correction methods. BMC Genom. 21(Suppl 6), 889 (2020).10.1186/s12864-020-07227-0
52. Longo MS Abundant human DNA contamination identified in non-primate genome databases PLoS ONE 2011 6 e16410 10.1371/journal.pone.0016410 21358816
Longo, M. S. et al. Abundant human DNA contamination identified in non-primate genome databases. PLoS ONE 6, e16410 (2011).21358816 10.1371/journal.pone.0016410
53. Simão FA BUSCO: Assessing genome assembly and annotation completeness with single-copy orthologs Bioinformatics 2015 31 19 3210 3212 10.1093/bioinformatics/btv351 26059717
Simão, F. A. et al. BUSCO: Assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics 31(19), 3210–3212 (2015).26059717 10.1093/bioinformatics/btv351
54. Ewing B Green P Base-calling of automated sequencer traces using Phred. II. Error probabilities Genome Res. 1998 8 186 194 10.1101/gr.8.3.186 9521922
Ewing, B. & Green, P. Base-calling of automated sequencer traces using Phred. II. Error probabilities. Genome Res. 8, 186–194 (1998).9521922 10.1101/gr.8.3.186
55. Van Coeverden de Groot, P. J.V. C. Conservation Genetic Implications of Microsatellite in the Muskox Ovibos moschatus: The Effect of Refugial Isolation and the Arctic Ocean on Genetic Structure. PhD thesis, Queen’s University, Canada (2001).
56. Li H Durbin R Fast and accurate short read alignment with Burrows–Wheeler transform Bioinformatics 2009 15 1754 1760 10.1093/bioinformatics/btp324
Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 15, 1754–1760 (2009).10.1093/bioinformatics/btp324
57. McKenna A The genome analysis toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data Genome Res. 2010 20 9 1297 1303 10.1101/gr.107524.110 20644199
McKenna, A. et al. The genome analysis toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20(9), 1297–1303 (2010).20644199 10.1101/gr.107524.110
58. Van der Auwera GA From FastQ data to high confidence variant calls: The genome analysis toolkit best practices pipeline Curr. Protoc. Bioinform. 2013 43 1110 1
Van der Auwera, G. A. et al. From FastQ data to high confidence variant calls: The genome analysis toolkit best practices pipeline. Curr. Protoc. Bioinform. 43(1110), 1 (2013).
59. Jackman D ABySS 2.0: Resource-efficient assembly of large genomes using a Bloom filter Genome Res. 2017 27 5 768 777 10.1101/gr.214346.116 28232478
Jackman, D. et al. ABySS 2.0: Resource-efficient assembly of large genomes using a Bloom filter. Genome Res. 27(5), 768–777 (2017).28232478 10.1101/gr.214346.116
60. Lok S Chromosomal-level reference genome assembly of the North American wolverine (Gulo gulo luscus): A resource for conservation genomics Genes Genomes Genet. 2022 12 8 jkac138 10.1093/g3journal/jkac138
Lok, S. et al. Chromosomal-level reference genome assembly of the North American wolverine (Gulo gulo luscus): A resource for conservation genomics. Genes Genomes Genet. 12(8), jkac138 (2022).10.1093/g3journal/jkac138
61. Chain PSG Genome project standards in a new era of sequencing Science 2009 326 236 237 10.1126/science.1180614 19815760
Chain, P. S. G. et al. Genome project standards in a new era of sequencing. Science 326, 236–237 (2009).19815760 10.1126/science.1180614
62. Koren S Hybrid error correction and de novo assembly of single-molecule sequencing reads Nat. Biotechnol. 2012 30 7 693 700 10.1038/nbt.2280 22750884
Koren, S. et al. Hybrid error correction and de novo assembly of single-molecule sequencing reads. Nat. Biotechnol. 30(7), 693–700 (2012).22750884 10.1038/nbt.2280
63. Lou DI High-throughput DNA sequencing errors are reduced by orders of magnitude using circle sequencing Proc. Natl. Acad. Sci. (U.S.A.) 2013 110 49 19872 19877 10.1073/pnas.1319590110 24243955
Lou, D. I. et al. High-throughput DNA sequencing errors are reduced by orders of magnitude using circle sequencing. Proc. Natl. Acad. Sci. (U.S.A.) 110(49), 19872–19877 (2013).24243955 10.1073/pnas.1319590110
64. Wenger AM Accurate circular consensus long-read sequencing improves variant detection and assembly of a human genome Nat. Biotechnol. 2019 37 10 1155 1162 10.1038/s41587-019-0217-9 31406327
Wenger, A. M. et al. Accurate circular consensus long-read sequencing improves variant detection and assembly of a human genome. Nat. Biotechnol. 37(10), 1155–1162 (2019).31406327 10.1038/s41587-019-0217-9
65. Chen L Large-scale ruminant genome sequencing provides insights into their evolution and distinct traits Science 2019 364 1152 10.1126/science.aav6202
Chen, L. et al. Large-scale ruminant genome sequencing provides insights into their evolution and distinct traits. Science 364, 1152 (2019).10.1126/science.aav6202
66. Morris K Low major histocompatibility complex diversity in the Tasmanian devil predates European settlement and may explain susceptibility to disease epidemics Bio. Lett. 2012 9 20120900 10.1098/rsbl.2012.0900 23221872
Morris, K. et al. Low major histocompatibility complex diversity in the Tasmanian devil predates European settlement and may explain susceptibility to disease epidemics. Bio. Lett. 9, 20120900 (2012).23221872 10.1098/rsbl.2012.0900
67. Dobrynin PS Genomic legacy of the African cheetah, Acinonyx jubatus Genome Biol. 2015 16 1 277 10.1186/s13059-015-0837-4 26653294
Dobrynin, P. S. et al. Genomic legacy of the African cheetah, Acinonyx jubatus. Genome Biol. 16(1), 277 (2015).26653294 10.1186/s13059-015-0837-4
68. Richly E Leister D NUMTs in sequenced eukaryotic genomes Mol. Biol. Evol. 2004 21 6 1081 1084 10.1093/molbev/msh110 15014143
Richly, E. & Leister, D. NUMTs in sequenced eukaryotic genomes. Mol. Biol. Evol. 21(6), 1081–1084 (2004).15014143 10.1093/molbev/msh110
69. Triant DA DeWoody JA Extensive mitochondrial DNA transfer in a rapidly evolving rodent has been mediated by independent insertion events and by duplications Gene 2007 401 1–2 61 70 10.1016/j.gene.2007.07.003 17714890
Triant, D. A. & DeWoody, J. A. Extensive mitochondrial DNA transfer in a rapidly evolving rodent has been mediated by independent insertion events and by duplications. Gene 401(1–2), 61–70 (2007).17714890 10.1016/j.gene.2007.07.003
70. Kulemzina AI Comparative chromosome painting of pronghorn (Antilocapra americana) and saola (Pseudoryx nghetinhensis) karyotypes with human and dromedary probes BMC Genet. 2014 15 68 10.1186/1471-2156-15-68 24923361
Kulemzina, A. I. et al. Comparative chromosome painting of pronghorn (Antilocapra americana) and saola (Pseudoryx nghetinhensis) karyotypes with human and dromedary probes. BMC Genet. 15, 68 (2014).24923361 10.1186/1471-2156-15-68
71. Goel M Schneeberger K Plotsr: Visualizing structural similarities and rearrangements between multiple genomes Bioinformatics 2022 38 2922 2926 10.1093/bioinformatics/btac196 35561173
Goel, M. & Schneeberger, K. Plotsr: Visualizing structural similarities and rearrangements between multiple genomes. Bioinformatics 38, 2922–2926 (2022).35561173 10.1093/bioinformatics/btac196
72. WMO Report. The global climate 2011–2020—A decade of accelerating climate change. WMO-No. 1338 (2023).
73. Crépin A-M Arctic climate change, economy and society (ACCESS): Integrated perspectives Ambio 2017 46 Suppl. 3 S341 S354 10.1007/s13280-017-0953-3
Crépin, A.-M. et al. Arctic climate change, economy and society (ACCESS): Integrated perspectives. Ambio 46(Suppl. 3), S341–S354 (2017).10.1007/s13280-017-0953-3
74. Blix AS Adaptation to polar life in mammals and birds J. Exp. Biol. 2016 219 1093 1105 10.1242/jeb.120477 27103673
Blix, A. S. Adaptation to polar life in mammals and birds. J. Exp. Biol. 219, 1093–1105 (2016).27103673 10.1242/jeb.120477
75. Castruita JAS Analysis of key genes involved in Arctic adaptation in polar bears suggest selection on both standing variation and de novo mutations played an importation role BMC Genom. 2020 21 543 10.1186/s12864-020-06940-0
Castruita, J. A. S. et al. Analysis of key genes involved in Arctic adaptation in polar bears suggest selection on both standing variation and de novo mutations played an importation role. BMC Genom. 21, 543 (2020).10.1186/s12864-020-06940-0
76. Tong C Convergent genomics and Arctic adaption of ruminants Proc. R. Soc. B 2024 291 20232448 10.1098/rspb.2023.2448 38166424
Tong, C. Convergent genomics and Arctic adaption of ruminants. Proc. R. Soc. B 291, 20232448 (2024).38166424 10.1098/rspb.2023.2448
77. Hueffer K Adaption of mammalian host–pathogen interactions in a changing arctic environment Acta Vet. Scand. 2011 53 17 10.1186/1751-0147-53-17 21392401
Hueffer, K. et al. Adaption of mammalian host–pathogen interactions in a changing arctic environment. Acta Vet. Scand. 53, 17 (2011).21392401 10.1186/1751-0147-53-17
78. Parkinson AJ Climate change and infectious diseases in the Arctic: Establishment of a circumpolar working group Int. J. Circumpolar Health 2014 73 25163 10.3402/ijch.v73.25163 25317383
Parkinson, A. J. et al. Climate change and infectious diseases in the Arctic: Establishment of a circumpolar working group. Int. J. Circumpolar Health 73, 25163 (2014).25317383 10.3402/ijch.v73.25163
79. Omazic A Identifying climate-sensitive infectious diseases in animals and human in Northern regions Acta Vet. Scand. 2019 61 53 10.1186/s13028-019-0490-0 31727129
Omazic, A. et al. Identifying climate-sensitive infectious diseases in animals and human in Northern regions. Acta Vet. Scand. 61, 53 (2019).31727129 10.1186/s13028-019-0490-0
80. Cohen JM Divergent impacts of warming weather on wildlife disease risk across climates Science 2020 370 933 10.1126/science.abb1702
Cohen, J. M. et al. Divergent impacts of warming weather on wildlife disease risk across climates. Science 370, 933 (2020).10.1126/science.abb1702
81. Rohr JR Cohen JM Understanding how temperature shifts could impact infectious disease PLoS Biol. 2020 18 11 e3000938 10.1371/journal.pbio.3000938 33232316
Rohr, J. R. & Cohen, J. M. Understanding how temperature shifts could impact infectious disease. PLoS Biol. 18(11), e3000938 (2020).33232316 10.1371/journal.pbio.3000938
82. Allendorf FW Genomics and the future of conservation genetics Nat. Rev. Genet. 2010 11 10 697 709 10.1038/nrg2844 20847747
Allendorf, F. W. et al. Genomics and the future of conservation genetics. Nat. Rev. Genet. 11(10), 697–709 (2010).20847747 10.1038/nrg2844
83. Wullschleger SD Genomics in a changing arctic: Critical questions awaiting the molecular ecologist Mol. Ecol. 2015 24 2301 2309 10.1111/mec.13166 25809088
Wullschleger, S. D. et al. Genomics in a changing arctic: Critical questions awaiting the molecular ecologist. Mol. Ecol. 24, 2301–2309 (2015).25809088 10.1111/mec.13166
84. Khan S Overview on the role of advance genomics in the conservation biology of endangered species Int. J. Genom. 2016 2016 3460416
Khan, S. et al. Overview on the role of advance genomics in the conservation biology of endangered species. Int. J. Genom. 2016, 3460416 (2016).
85. Colella JP Conservation genomics in a changing Arctic Trends Ecol. Evol. 2020 35 2 149 162 10.1016/j.tree.2019.09.008 31699414
Colella, J. P. et al. Conservation genomics in a changing Arctic. Trends Ecol. Evol. 35(2), 149–162 (2020).31699414 10.1016/j.tree.2019.09.008
86. Wright BR A demonstration of conservation genomics for threatened species management Mol. Ecol. Resour. 2020 20 6 1526 1541 10.1111/1755-0998.13211 32562371
Wright, B. R. et al. A demonstration of conservation genomics for threatened species management. Mol. Ecol. Resour. 20(6), 1526–1541 (2020).32562371 10.1111/1755-0998.13211
87. Theissinger K How genomics can help biodiversity conservation Trends Genet. 2023 39 7 545 559 10.1016/j.tig.2023.01.005 36801111
Theissinger, K. et al. How genomics can help biodiversity conservation. Trends Genet. 39(7), 545–559 (2023).36801111 10.1016/j.tig.2023.01.005
88. Brandies PE The value of reference genomes in the conservation of threatened species Genes 2019 10 11 846 10.3390/genes10110846 31717707
Brandies, P. E. et al. The value of reference genomes in the conservation of threatened species. Genes 10(11), 846 (2019).31717707 10.3390/genes10110846
89. Formenti G The era of reference genomes in conservation genomics Trends Ecol. Evol. 2022 37 3 197 202 10.1016/j.tree.2021.11.008 35086739
Formenti, G. et al. The era of reference genomes in conservation genomics. Trends Ecol. Evol. 37(3), 197–202 (2022).35086739 10.1016/j.tree.2021.11.008
90. Hohenlohe PA Population genomics for wildlife conservation and management Mol. Ecol. 2021 30 1 62 82 10.1111/mec.15720 33145846
Hohenlohe, P. A. et al. Population genomics for wildlife conservation and management. Mol. Ecol. 30(1), 62–82 (2021).33145846 10.1111/mec.15720
91. Paez S Reference genomes for conservation Science 2022 37 6604 364 366 10.1126/science.abm8127
Paez, S. et al. Reference genomes for conservation. Science 37(6604), 364–366 (2022).10.1126/science.abm8127
92. Nam M Cooper MP Role of energy metabolism in the brown fat gene program Front. Endocrinol. 2015 6 104 10.3389/fendo.2015.00104
Nam, M. & Cooper, M. P. Role of energy metabolism in the brown fat gene program. Front. Endocrinol. 6, 104 (2015).10.3389/fendo.2015.00104
93. Van Oort BEH Circadian organization on reindeer Nature 2005 438 1095 1096 10.1038/4381095a 16371996
Van Oort, B. E. H. et al. Circadian organization on reindeer. Nature 438, 1095–1096 (2005).16371996 10.1038/4381095a
94. Van Beest FM Environmental conditions alter behavioral organization and rhythmicity of a large Arctic ruminant across the annual cycle R. Soc. Open Sci. 2020 7 201614 10.1098/rsos.201614 33204486
Van Beest, F. M. et al. Environmental conditions alter behavioral organization and rhythmicity of a large Arctic ruminant across the annual cycle. R. Soc. Open Sci. 7, 201614 (2020).33204486 10.1098/rsos.201614
95. Aristizábal B González A Anaya J-M Chapter 2 Innate immune system Autoimmunity from Bench to Bedside 2013 El Rosario University Press
Aristizábal, B. & González, A. Chapter 2 Innate immune system. In Autoimmunity from Bench to Bedside (eds Anaya, J.-M. et al.) (El Rosario University Press, 2013).
96. Paludan SR Constitutive immune mechanisms: Mediators of host defence and immune regulation Nat. Rev. Immunol. 2021 21 3 137 150 10.1038/s41577-020-0391-5 32782357
Paludan, S. R. et al. Constitutive immune mechanisms: Mediators of host defence and immune regulation. Nat. Rev. Immunol. 21(3), 137–150 (2021).32782357 10.1038/s41577-020-0391-5
97. Kawai T Akira S Toll-like receptors and their crosstalk with other innate receptors in infection and immunity Immunity 2011 24 5 637 650 10.1016/j.immuni.2011.05.006
Kawai, T. & Akira, S. Toll-like receptors and their crosstalk with other innate receptors in infection and immunity. Immunity 24(5), 637–650 (2011).10.1016/j.immuni.2011.05.006
98. Franchi L Function of nod-like receptors in microbial recognition and host defence Immul. Rev. 2009 227 1 106 128 10.1111/j.1600-065X.2008.00734.x
Franchi, L. et al. Function of nod-like receptors in microbial recognition and host defence. Immul. Rev. 227(1), 106–128 (2009).10.1111/j.1600-065X.2008.00734.x
99. Bermejo-Jambrina M C-type lectin receptors in antiviral immunity and viral escape Front. Immunol. 2018 9 590 10.3389/fimmu.2018.00590 29632536
Bermejo-Jambrina, M. et al. C-type lectin receptors in antiviral immunity and viral escape. Front. Immunol. 9, 590 (2018).29632536 10.3389/fimmu.2018.00590
100. Rehwinkel J Gack MU RIG-I-like receptors: Their regulation and roles in RNA sensing Nat. Rev. Immunol. 2020 20 9 537 551 10.1038/s41577-020-0288-3 32203325
Rehwinkel, J. & Gack, M. U. RIG-I-like receptors: Their regulation and roles in RNA sensing. Nat. Rev. Immunol. 20(9), 537–551 (2020).32203325 10.1038/s41577-020-0288-3
101. Kawai T Akira S Innate immune recognition of viral infection Nat. Rev. Immunol. 2006 7 2 131137
Kawai, T. & Akira, S. Innate immune recognition of viral infection. Nat. Rev. Immunol. 7(2), 131137 (2006).
102. Chen H Jiang Z The essential adaptors of innate immune signalling Protein Cell 2013 4 1 27 39 10.1007/s13238-012-2063-0 22996173
Chen, H. & Jiang, Z. The essential adaptors of innate immune signalling. Protein Cell 4(1), 27–39 (2013).22996173 10.1007/s13238-012-2063-0
103. Bousoik E Alibadi HM Do we know jack about JAK? A closer look at JAK/STAT signalling Front. Oncol. 2018 8 287 10.3389/fonc.2018.00287 30109213
Bousoik, E. & Alibadi, H. M. Do we know jack about JAK? A closer look at JAK/STAT signalling. Front. Oncol. 8, 287 (2018).30109213 10.3389/fonc.2018.00287
104. Arthur JSC Ley SC Mitogen-activated protein kinases in innate immunity Nat. Rev. Immunol. 2013 13 9 679 692 10.1038/nri3495 23954936
Arthur, J. S. C. & Ley, S. C. Mitogen-activated protein kinases in innate immunity. Nat. Rev. Immunol. 13(9), 679–692 (2013).23954936 10.1038/nri3495
105. McNab F Type I interferons in infectious disease Nat. Rev. Immunol. 2015 15 2 87 103 10.1038/nri3787 25614319
McNab, F. et al. Type I interferons in infectious disease. Nat. Rev. Immunol. 15(2), 87–103 (2015).25614319 10.1038/nri3787
106. Kak G Interferon-gamma (IFN-gamma): Exploring its implications in infectious disease Biomol. Concepts 2018 9 64 79 10.1515/bmc-2018-0007 29856726
Kak, G. et al. Interferon-gamma (IFN-gamma): Exploring its implications in infectious disease. Biomol. Concepts 9, 64–79 (2018).29856726 10.1515/bmc-2018-0007
107. Mesev EV Decoding type I and III interferon signalling during viral infection Nat. Microbiol. 2019 4 6 914 924 10.1038/s41564-019-0421-x 30936491
Mesev, E. V. et al. Decoding type I and III interferon signalling during viral infection. Nat. Microbiol. 4(6), 914–924 (2019).30936491 10.1038/s41564-019-0421-x
108. Abraha R Review on the role and biology of cytokines in adaptive and innate immune system Arch. Vet. Anim. Sci. 2020 2 2 2
Abraha, R. Review on the role and biology of cytokines in adaptive and innate immune system. Arch. Vet. Anim. Sci. 2(2), 2 (2020).
109. Esche C Chemokines: Key players in innate and adaptive immunity J. Investig. Dermatol. 2005 125 615 628 10.1111/j.0022-202X.2005.23841.x 16185259
Esche, C. et al. Chemokines: Key players in innate and adaptive immunity. J. Investig. Dermatol. 125, 615–628 (2005).16185259 10.1111/j.0022-202X.2005.23841.x
110. Sokol CL Luster AD The chemokine systems in innate immunity Cold Spring Harb. Perspect. Biol. 2015 7 a016303 10.1101/cshperspect.a016303 25635046
Sokol, C. L. & Luster, A. D. The chemokine systems in innate immunity. Cold Spring Harb. Perspect. Biol. 7, a016303 (2015).25635046 10.1101/cshperspect.a016303
111. Xu D Lu W Defensins: A double-edged sword in host immunity Front. Immunol. 2020 11 764 10.3389/fimmu.2020.00764 32457744
Xu, D. & Lu, W. Defensins: A double-edged sword in host immunity. Front. Immunol. 11, 764 (2020).32457744 10.3389/fimmu.2020.00764
112. Valeri M Raffatellu M Cytokines IL-17 and IL-22 in host response to infection Pathog. Dis. 2016 74 ftw111 10.1093/femspd/ftw111 27915228
Valeri, M. & Raffatellu, M. Cytokines IL-17 and IL-22 in host response to infection. Pathog. Dis. 74, ftw111 (2016).27915228 10.1093/femspd/ftw111
113. Horton R Gene map of the extended human MHC Nat. Rev. Genet. 2004 5 889 899 10.1038/nrg1489 15573121
Horton, R. et al. Gene map of the extended human MHC. Nat. Rev. Genet. 5, 889–899 (2004).15573121 10.1038/nrg1489
114. Shiina T The HLA genomic loci map: expression, interaction, diversity and disease J. Hum. Genet. 2009 54 15 39 10.1038/jhg.2008.5 19158813
Shiina, T. et al. The HLA genomic loci map: expression, interaction, diversity and disease. J. Hum. Genet. 54, 15–39 (2009).19158813 10.1038/jhg.2008.5
115. Cruz-Tapias P Anaya J-M Chapter 10 Major histocompatibility complex: antigen processing and presentation Autoimmunity from Bench to Bedside 2013 El Rosario University Press
Cruz-Tapias, P. et al. Chapter 10 Major histocompatibility complex: antigen processing and presentation. In Autoimmunity from Bench to Bedside (eds Anaya, J.-M. et al.) (El Rosario University Press, 2013).
116. Kulski JK Genomic diversity of the major histocompatibility complex in health and disease Cells 2019 8 1270 10.3390/cells8101270 31627481
Kulski, J. K. et al. Genomic diversity of the major histocompatibility complex in health and disease. Cells 8, 1270 (2019).31627481 10.3390/cells8101270
117. Ziegler A Female choice and the MHC Trends Immunol. 2005 26 9 496 502 10.1016/j.it.2005.07.003 16027037
Ziegler, A. et al. Female choice and the MHC. Trends Immunol. 26(9), 496–502 (2005).16027037 10.1016/j.it.2005.07.003
118. Knapp LA The ABC of the MHC Envol. Anthropol. 2005 14 28 37
Knapp, L. A. The ABC of the MHC. Envol. Anthropol. 14, 28–37 (2005).
119. Groth V Cell stress-regulated human major histocompatibility complex class I gene expressed in gastrointestinal epithelium Proc. Natl. Acad. Sci. (U.S.A.) 1996 93 12445 12450 10.1073/pnas.93.22.12445 8901601
Groth, V. et al. Cell stress-regulated human major histocompatibility complex class I gene expressed in gastrointestinal epithelium. Proc. Natl. Acad. Sci. (U.S.A.) 93, 12445–12450 (1996).8901601 10.1073/pnas.93.22.12445
120. Bauer S Activation of NK cells and T cells by NKG2D, a receptor for stress-inducible MICA Science 1999 285 727 729 10.1126/science.285.5428.727 10426993
Bauer, S. et al. Activation of NK cells and T cells by NKG2D, a receptor for stress-inducible MICA. Science 285, 727–729 (1999).10426993 10.1126/science.285.5428.727
121. Deakin JE Evolution and comparative analysis of the MHC class III inflammatory region BMC Genom. 2006 7 281 10.1186/1471-2164-7-281
Deakin, J. E. et al. Evolution and comparative analysis of the MHC class III inflammatory region. BMC Genom. 7, 281 (2006).10.1186/1471-2164-7-281
122. Gruen JR Weissman SM Human MHC class III and class IV genes and disease associations Front. BioSci. 2001 6 d960 972 10.2741/Gruen 11487469
Gruen, J. R. & Weissman, S. M. Human MHC class III and class IV genes and disease associations. Front. BioSci. 6, d960-972 (2001).11487469 10.2741/Gruen
123. Sedy J Tumor necrosis factor superfamily in innate immunity and inflammation Cold Spring Harb. Perspect. Biol. 2015 7 a016279 10.1101/cshperspect.a016279
Sedy, J. et al. Tumor necrosis factor superfamily in innate immunity and inflammation. Cold Spring Harb. Perspect. Biol. 7, a016279 (2015).10.1101/cshperspect.a016279
124. Wallach D The tumor necrosis factor family: Family conversions and private idiosyncrasies Cold Spring Harb. Perspect. Biol. 2018 10 a028431 10.1101/cshperspect.a028431 28847899
Wallach, D. The tumor necrosis factor family: Family conversions and private idiosyncrasies. Cold Spring Harb. Perspect. Biol. 10, a028431 (2018).28847899 10.1101/cshperspect.a028431
125. Upadhyay G Emerging role of lymphocyte antigen-6 family of genes in cancer and immune cells Front. Immol. 2019 10 819 10.3389/fimmu.2019.00819
Upadhyay, G. Emerging role of lymphocyte antigen-6 family of genes in cancer and immune cells. Front. Immol. 10, 819 (2019).10.3389/fimmu.2019.00819
126. Dunkelberger JR Song W-C Complement and its role in innate and adaptive immune responses Cell Res. 2010 20 34 50 10.1038/cr.2009.139 20010915
Dunkelberger, J. R. & Song, W.-C. Complement and its role in innate and adaptive immune responses. Cell Res. 20, 34–50 (2010).20010915 10.1038/cr.2009.139
127. Cruse JM Cluster of Differentiation (CD) Antigens 2007 Immunology Guidbook
Cruse, J. M. et al. (eds) Cluster of Differentiation (CD) Antigens (Immunology Guidbook, 2007). 10.1016/B978-012198382-6/50027-3.
128. Sommer S The importance of immune gene variability (MHC) in evolutionary ecology and conservation Front. Zool. 2005 2 16 10.1186/1742-9994-2-16 16242022
Sommer, S. The importance of immune gene variability (MHC) in evolutionary ecology and conservation. Front. Zool. 2, 16 (2005).16242022 10.1186/1742-9994-2-16
129. Radwan J Does reduced MHC diversity decrease viability of vertebrate population? Biol. Conserv. 2010 143 537 544 10.1016/j.biocon.2009.07.026 32226082
Radwan, J. et al. Does reduced MHC diversity decrease viability of vertebrate population?. Biol. Conserv. 143, 537–544 (2010).32226082 10.1016/j.biocon.2009.07.026
130. Ujvari B Belov K Major histocompatibility complex (MHC) markers in conservation biology Int. J. Mol. Sci. 2011 12 5168 5186 10.3390/ijms12085168 21954351
Ujvari, B. & Belov, K. Major histocompatibility complex (MHC) markers in conservation biology. Int. J. Mol. Sci. 12, 5168–5186 (2011).21954351 10.3390/ijms12085168
131. Coker OM Major histocompatibility complex (MHC) diversity and its implications for human and wildlife health and conservation Genet. Biodivers. J. 2023 7 2 1 11
Coker, O. M. et al. Major histocompatibility complex (MHC) diversity and its implications for human and wildlife health and conservation. Genet. Biodivers. J. 7(2), 1–11 (2023).
132. Mikko S Monomorphism and polymorphism at the Mhc DRB loci in domestic and wild ruminants Immunol. Rev. 1999 167 169 178 10.1111/j.1600-065X.1999.tb01390.x 10319259
Mikko, S. et al. Monomorphism and polymorphism at the Mhc DRB loci in domestic and wild ruminants. Immunol. Rev. 167, 169–178 (1999).10319259 10.1111/j.1600-065X.1999.tb01390.x
133. Zverinova S Guryev V Variant calling: Considerations, practices, and developments Hum. Muation 2022 43 976 985 10.1002/humu.24311
Zverinova, S. & Guryev, V. Variant calling: Considerations, practices, and developments. Hum. Muation 43, 976–985 (2022).10.1002/humu.24311
134. Pan B Assessing reproducibility of inherited variants detected with short-read whole genome sequencing Genome Biol. 2022 23 2 10.1186/s13059-021-02569-8 34980216
Pan, B. et al. Assessing reproducibility of inherited variants detected with short-read whole genome sequencing. Genome Biol. 23, 2 (2022).34980216 10.1186/s13059-021-02569-8
135. Brlek P Implementing whole genome sequencing (WGS) in clinical practice: Advantages, challenged, and future perspectives Cells 2024 13 504 10.3390/cells13060504 38534348
Brlek, P. et al. Implementing whole genome sequencing (WGS) in clinical practice: Advantages, challenged, and future perspectives. Cells 13, 504 (2024).38534348 10.3390/cells13060504
136. Mahmoud M Structural variant calling: the long and the short of it Genome Biol. 2019 20 246 10.1186/s13059-019-1828-7 31747936
Mahmoud, M. et al. Structural variant calling: the long and the short of it. Genome Biol. 20, 246 (2019).31747936 10.1186/s13059-019-1828-7
137. Edge P Bansal V Longshot enables accurate variant calling in diploid genomes from single-molecule long read sequencing Nat. Commun. 2019 10 4660 10.1038/s41467-019-12493-y 31604920
Edge, P. & Bansal, V. Longshot enables accurate variant calling in diploid genomes from single-molecule long read sequencing. Nat. Commun. 10, 4660 (2019).31604920 10.1038/s41467-019-12493-y
138. Lukacs M Functional immune diversity in reindeer reveals a high arctic population at risk Front. Ecol. Evol. 2023 10 1058674 10.3389/fevo.2022.1058674
Lukacs, M. et al. Functional immune diversity in reindeer reveals a high arctic population at risk. Front. Ecol. Evol. 10, 1058674 (2023).10.3389/fevo.2022.1058674
139. Teixeira JC Huber C D. The inflated significance of neutral genetic diversity in conservation genetics Proc. Natl. Acad. Sci. (U.S.A.) 2021 118 10 e2015096118 10.1073/pnas.2015096118 33608481
Teixeira, J. C., Huber, C. & D.,. The inflated significance of neutral genetic diversity in conservation genetics. Proc. Natl. Acad. Sci. (U.S.A.) 118(10), e2015096118 (2021).33608481 10.1073/pnas.2015096118
140. Abbott B Van Kooten GC Can domestication of wildlife lead to conservation? The economics of tiger farming in China Ecol. Econ. 2011 70 4 721 728 10.1016/j.ecolecon.2010.11.006
Abbott, B. & Van Kooten, G. C. Can domestication of wildlife lead to conservation? The economics of tiger farming in China. Ecol. Econ. 70(4), 721–728 (2011).10.1016/j.ecolecon.2010.11.006
141. Teletchea F Lameed GA Wildlife conservation: Is domestication a solution? Global Exposition of Wildlife Management, Chapter 1 2017 IntechOpen Ltd
Teletchea, F. Wildlife conservation: Is domestication a solution? In Global Exposition of Wildlife Management, Chapter 1 (ed. Lameed, G. A.) (IntechOpen Ltd, 2017). 10.5772/65660.
142. Moyers BT Genetic costs of domestication and improvement J. Hered. 2018 109 2 103 116 10.1093/jhered/esx069 28992310
Moyers, B. T. et al. Genetic costs of domestication and improvement. J. Hered. 109(2), 103–116 (2018).28992310 10.1093/jhered/esx069
143. Larson G Genetics and domestication Curr. Anthropol. 2011 52 S485 S495 10.1086/658401
Larson, G. Genetics and domestication. Curr. Anthropol. 52, S485–S495 (2011).10.1086/658401
144. Hunter P The genetics of domestication EMBO Rep. 2018 19 2 201 205 10.15252/embr.201745664 29335247
Hunter, P. The genetics of domestication. EMBO Rep. 19(2), 201–205 (2018).29335247 10.15252/embr.201745664
145. Alberto FJ Convergent genomic signatures of domestication in sheep and goats Nat. Commun. 2018 9 813 10.1038/s41467-018-03206-y 29511174
Alberto, F. J. et al. Convergent genomic signatures of domestication in sheep and goats. Nat. Commun. 9, 813 (2018).29511174 10.1038/s41467-018-03206-y
146. Ahmad HI The domestication makeup: Evolution, survival, and challenges Front. Ecol. Evol. 2020 8 103 10.3389/fevo.2020.00103
Ahmad, H. I. et al. The domestication makeup: Evolution, survival, and challenges. Front. Ecol. Evol. 8, 103 (2020).10.3389/fevo.2020.00103
147. Zheng Z The origin of domestication genes in goats Sci. Adv. 2020 6 eaaz5216 10.1126/sciadv.aaz5216 32671210
Zheng, Z. et al. The origin of domestication genes in goats. Sci. Adv. 6, eaaz5216 (2020).32671210 10.1126/sciadv.aaz5216
148. Dou M A missense mutation in RRM1 contribute to animal tameness Sci. Adv. 2023 9 eadf4068 10.1126/sciadv.adf4068 37352351
Dou, M. et al. A missense mutation in RRM1 contribute to animal tameness. Sci. Adv. 9, eadf4068 (2023).37352351 10.1126/sciadv.adf4068
149. Wilkinson PF The history of musk-ox domestication Polar Rec. 1974 17 106 13 22 10.1017/S0032247400031302
Wilkinson, P. F. The history of musk-ox domestication. Polar Rec. 17(106), 13–22 (1974).10.1017/S0032247400031302
150. Helfferich D The muskox: A new northern farm animal Agroborealis 2006 38 2 18 21
Helfferich, D. The muskox: A new northern farm animal. Agroborealis 38(2), 18–21 (2006).
151. Helfferich D The muskox: Muskox husbandry Agroborealis 2007 39 2 10 19
Helfferich, D. The muskox: Muskox husbandry. Agroborealis 39(2), 10–19 (2007).
152. Georges M Mapping, fine mapping and molecular dissection of quantitative trait loci in domestic animals Annu. Rev. Genom. Hum. Genet. 2007 8 131 162 10.1146/annurev.genom.8.080706.092408
Georges, M. Mapping, fine mapping and molecular dissection of quantitative trait loci in domestic animals. Annu. Rev. Genom. Hum. Genet. 8, 131–162 (2007).10.1146/annurev.genom.8.080706.092408
153. Wakchaure R Marker assisted selection (MAS) in animal breeding: A review J. Drug Metab. Toxicol. 2015 6 5 1000e127 10.4172/2157-7609.1000e127
Wakchaure, R. et al. Marker assisted selection (MAS) in animal breeding: A review. J. Drug Metab. Toxicol. 6(5), 1000e127 (2015).10.4172/2157-7609.1000e127
154. Sharma P Overview of marker-assisted selection in animal breeding J. Adv. Biol. Biotechnol. 2024 27 5 303 318 10.9734/jabb/2024/v27i5790
Sharma, P. et al. Overview of marker-assisted selection in animal breeding. J. Adv. Biol. Biotechnol. 27(5), 303–318 (2024).10.9734/jabb/2024/v27i5790
155. Georges M Harnessing genomics information for livestock improvement Nat. Rev. Genet. 2019 20 3 135 156 10.1038/s41576-018-0082-2 30514919
Georges, M. et al. Harnessing genomics information for livestock improvement. Nat. Rev. Genet. 20(3), 135–156 (2019).30514919 10.1038/s41576-018-0082-2
156. Gavran M Candidate genes associated with economically important traits of sheep—A review Agric. Conspec. Sci. 2021 86 3 195 201
Gavran, M. et al. Candidate genes associated with economically important traits of sheep—A review. Agric. Conspec. Sci. 86(3), 195–201 (2021).
157. Zeng L Genes related to heat tolerance in cattle—A review Anim. Biotechnol. 2023 34 5 1840 1848 10.1080/10495398.2022.2047995 35290167
Zeng, L. et al. Genes related to heat tolerance in cattle—A review. Anim. Biotechnol. 34(5), 1840–1848 (2023).35290167 10.1080/10495398.2022.2047995
158. Worku D Candidate genes associated with heat stress and breeding strategies to relieve its effects in dairy cattle: A deeper insight into the genetic architecture and immune response to heat stress Front. Vet. Sci. 2023 10 1151241 10.3389/fvets.2023.1151241 37771947
Worku, D. et al. Candidate genes associated with heat stress and breeding strategies to relieve its effects in dairy cattle: A deeper insight into the genetic architecture and immune response to heat stress. Front. Vet. Sci. 10, 1151241 (2023).37771947 10.3389/fvets.2023.1151241
159. Arzik Y Genome-wide scan of wool production traits in Akkaraman sheep Genes (Basel) 2023 14 3 713 10.3390/genes14030713 36980985
Arzik, Y. et al. Genome-wide scan of wool production traits in Akkaraman sheep. Genes (Basel) 14(3), 713 (2023).36980985 10.3390/genes14030713
160. Moll R The human keratins: Biology and pathology Histocom. Cell Biol. 2008 129 705 733 10.1007/s00418-008-0435-6
Moll, R. et al. The human keratins: Biology and pathology. Histocom. Cell Biol. 129, 705–733 (2008).10.1007/s00418-008-0435-6
161. Wu D-D Molecular evolution of the keratin associated protein gene family in mammals, role in the evolution of mammalian hair BMC Evol. Biol. 2008 8 241 10.1186/1471-2148-8-241 18721477
Wu, D.-D. et al. Molecular evolution of the keratin associated protein gene family in mammals, role in the evolution of mammalian hair. BMC Evol. Biol. 8, 241 (2008).18721477 10.1186/1471-2148-8-241
162. Gong H Wool keratin-associated protein genes in sheep—A review Genes 2016 7 24 10.3390/genes7060024 27240405
Gong, H. et al. Wool keratin-associated protein genes in sheep—A review. Genes 7, 24 (2016).27240405 10.3390/genes7060024
163. Zhou H The complexity of the ovine and caprine keratin-associated protein genes Int. J. Mol. Sci. 2021 22 12838 10.3390/ijms222312838 34884644
Zhou, H. et al. The complexity of the ovine and caprine keratin-associated protein genes. Int. J. Mol. Sci. 22, 12838 (2021).34884644 10.3390/ijms222312838
164. Li S Variation in the ovine KAP6-3 gene (KRTAP6-3) is associated with variation in mean fibre diameter-associated wool traits Genes 2017 8 204 10.3390/genes8080204 28820492
Li, S. et al. Variation in the ovine KAP6-3 gene (KRTAP6-3) is associated with variation in mean fibre diameter-associated wool traits. Genes 8, 204 (2017).28820492 10.3390/genes8080204
165. Sulayman A Association analysis of polymorphisms in six keratin genes with wool traits in sheep Asian Australas. J. Anim. Sci. 2018 31 6 775 783 10.5713/ajas.17.0349 29103286
Sulayman, A. et al. Association analysis of polymorphisms in six keratin genes with wool traits in sheep. Asian Australas. J. Anim. Sci. 31(6), 775–783 (2018).29103286 10.5713/ajas.17.0349
166. Kalds P Genetics of the phenotypic evolution in sheep: A molecular look at diversity-driving genes Genet. Sel. Evol. 2022 54 61 10.1186/s12711-022-00753-3 36085023
Kalds, P. et al. Genetics of the phenotypic evolution in sheep: A molecular look at diversity-driving genes. Genet. Sel. Evol. 54, 61 (2022).36085023 10.1186/s12711-022-00753-3
167. Zhang W Whole-genome resequencing reveal selection signal related to sheep wool fitness Animals 2023 13 2944 10.3390/ani13182944 37760343
Zhang, W. et al. Whole-genome resequencing reveal selection signal related to sheep wool fitness. Animals 13, 2944 (2023).37760343 10.3390/ani13182944
168. Willi Y Conservation genetics as a management tool: The five best-supported paradigms to assist the management of threatened species Proc. Natl. Acad. Sci. (U.S.A.) 2022 119 e2105076119 10.1073/pnas.2105076119 34930821
Willi, Y. et al. Conservation genetics as a management tool: The five best-supported paradigms to assist the management of threatened species. Proc. Natl. Acad. Sci. (U.S.A.) 119, e2105076119 (2022).34930821 10.1073/pnas.2105076119
169. Buschman VQ Sudlovenick E Indigenous-led conservation in the Arctic supports global conservation practices Arctic Sci. 2023 9 714 719
Buschman, V. Q. & Sudlovenick, E. Indigenous-led conservation in the Arctic supports global conservation practices. Arctic Sci. 9, 714–719 (2023).
170. Madsen J Implementation of the first adaptive management plan for a European migratory waterbird population: The case of the Svalbard pink-footed goose Anser bracyrhynchus Ambio 2017 46 suppl. 2 S275 S289 10.1007/s13280-016-0888-0
Madsen, J. et al. Implementation of the first adaptive management plan for a European migratory waterbird population: The case of the Svalbard pink-footed goose Anser bracyrhynchus. Ambio 46(suppl. 2), S275–S289 (2017).10.1007/s13280-016-0888-0
