
==== Front
Genome Biol Evol
Genome Biol Evol
gbe
Genome Biology and Evolution
1759-6653
Oxford University Press UK

39228319
10.1093/gbe/evae193
evae193
Article
AcademicSubjects/SCI01130
AcademicSubjects/SCI01140
Natural Transposable Element Insertions Contribute to Host Fitness in Model Yeasts
https://orcid.org/0009-0002-5375-6082
Wang Yan College of Life Sciences, Nanjing Normal University, Nanjing, Jiangsu 210023, China

https://orcid.org/0009-0009-6641-2749
Xu Hao College of Life Sciences, Nanjing Normal University, Nanjing, Jiangsu 210023, China

https://orcid.org/0009-0008-4132-434X
He Qinliu College of Life Sciences, Nanjing Normal University, Nanjing, Jiangsu 210023, China

https://orcid.org/0009-0008-5172-3088
Wu Zhiwei College of Life Sciences, Nanjing Normal University, Nanjing, Jiangsu 210023, China

https://orcid.org/0000-0002-8352-7726
Han Guan-Zhu College of Life Sciences, Nanjing Normal University, Nanjing, Jiangsu 210023, China

Giraud Tatiana Associate Editor
Corresponding author: E-mail: guanzhu@njnu.edu.cn.
9 2024
04 9 2024
04 9 2024
16 9 evae19331 8 2024
16 9 2024
© The Author(s) 2024. Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution.
2024
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Abstract

Transposable elements (TEs) are ubiquitous in the eukaryote genomes, but their evolutionary and functional significance remains largely obscure and contentious. Here, we explore the evolution and functional impact of TEs in two model unicellular eukaryotes, the fission yeast Schizosaccharomyces pombe and the budding yeast Saccharomyces cerevisiae, which diverged around 330 to 420 million years ago. We analyze the distribution of LTR retrotransposons (LTR-RTs, the only TE order identified in both species) and their solo-LTR derivatives in 35 strains of S. pombe and 128 strains of S. cerevisiae. We find that natural LTR-RT and solo-LTR insertions exhibit high presence-absence polymorphism among individuals in both species. Population genetics analyses show that solo-LTR insertions experienced functional constraints similar to synonymous sites of host genes in both species, indicating a majority of solo-LTR insertions might have evolved in a neutral manner. When knocking out nine representative solo-LTR insertions separately in the S. pombe strain 972h- and 12 representative solo-LTR insertions separately in the S. cerevisiae strain S288C, we find that one solo-LTR insertion in S. pombe has a significant effect on the fitness and transcriptome of its host. Together, our findings indicate that a fraction of natural TE insertions likely shape their host transcriptomes and thereby contribute to their host fitness, with implications for understanding the functional significance of TEs in eukaryotes.

transposable elements
LTR retrotransposons
co-option
fitness
yeast
National Natural Science Foundation of China 10.13039/501100001809 32270684
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pmcSignificance

Many hypotheses have been proposed to account for the function, maintenance, and evolution of transposable elements (TEs). However, to what extent TEs have affected the evolution of host gene regulation and hence biology remains largely obscure and contentious. Our study suggests that a fraction of natural TE insertions might impact the fitness of model yeasts, with implications for understanding the functional significance of TEs in eukaryotes.

Introduction

Transposable elements (TEs) are ubiquitous in eukaryote genomes, but much remains unclear about the role of TEs in shaping the evolution and functional complexity of eukaryotes (Finnegan 1992; Wicker et al. 2007; Wells and Feschotte 2020). Based on their transposition mechanisms, TEs can be classified into two classes, namely class I (retrotransposons) and class II (DNA transposons) (Wicker et al. 2007; Wells and Feschotte 2020). Retrotransposons proliferate via a “copy-and-paste” mechanism with RNA as intermediates, whereas DNA transposons move via a “cut-and-paste” mechanism (Wicker et al. 2007). TE proteins can be recruited to become part of host proteins, a process known as co-option or exaptation. Co-option of TE proteins has been identified across eukaryotes, and the co-opted TE proteins are engaged in diverse biological processes, such as placental development, myelination, synaptic plasticity, and immunity (Best et al. 1996; Mi et al. 2000; Ashley et al. 2018; Pastuzyn et al. 2018; Wang and Han 2020, 2021a; Ghosh et al. 2024). Moreover, TEs also encompass various regulatory sequences, and have long been proposed to play a crucial role in the evolution of host gene regulation and drive the evolution of host gene regulatory networks in eukaryotes (McClintock 1956, 1984; Britten and Davidson 1969; Feschotte 2008; Chuong et al. 2017). Genome-wide assays indicate that many TE-derived sequences exhibit biochemical hallmarks of active regulatory elements (Rebollo et al. 2012; Chuong et al. 2016, 2017; Wu et al. 2016). On the other hand, the biochemical activity of these TE sequences does not necessarily imply their biological functionality or significance for their hosts (de Souza et al. 2013; Graur et al. 2013; Chuong et al. 2017), and it might simply represent relics of preexisting regulatory potentials of TEs (de Souza et al. 2013; Chuong et al. 2017). From the perspective of evolutionary biology, sequences that exert biological function are subject to certain level of natural selection (Graur et al. 2013). However, due to the complex TE composition in most of the eukaryotes, it is technically unfeasible to perform genome-wide selection analysis of TEs. Therefore, to what extent TEs have affected the evolution of host gene regulation and hence biology remains largely obscure and contentious (Feschotte 2008; Rebollo et al. 2012; de Souza et al. 2013; Sorrells and Johnson 2015; Chuong et al. 2016; Horvath et al. 2017; Simonti et al. 2017; Sundaram and Wysocka 2020; Baduel et al. 2021; Zhang et al. 2021; Coronado-Zamora and González 2023).

Long terminal repeat retrotransposons (LTR-RTs) are a major order of retrotransposons characterized by LTRs flanking at their termini (Wicker et al. 2007; Wells and Feschotte 2020). LTR-RTs are traditionally classified into four superfamilies, namely Ty1, Ty3, Bel-Pao, and endogenous retroviruses (ERVs) (Wicker et al. 2007). LTR regions encode cis-regulatory sequences that functionally mimic host cis-regulatory elements and are required for the expression of LTR-RT genes using host cell machinery (Medstrand et al. 2005; Mager and Stoye 2015). After its insertion, the two LTRs of an LTR-RT often undergo ectopic recombination, forming the so-called solo-LTR (the coding sequences and one solo-LTR are then deleted), and most of LTR-RTs exist as solo-LTRs (Chuong et al. 2016). Recombination between LTR-RTs might also lead to chromosomal rearrangements, shaping the evolution of genome structure complexity (Balachandran et al. 2022). Intuitively, if an LTR-RT inserts in the vicinity of a host gene, it potentially alters (either increases or decreases) the expression of the nearby host genes. Like new mutations, most new LTR-RT insertions are likely to be deleterious or neutral (Arkhipova 2018). Co-option of solo-LTR sequences has been sporadically reported to be implicated in diverse biological processes, such as embryonic development and innate immunity (reviewed by Rebollo et al. 2012; Chuong et al. 2017; Horvath et al. 2017). As a striking example, LTRs of MER41 retrotransposons (an ERV family) were co-opted as interferon-inducible enhancers of proinflammatory gene absent in melanoma 2 (AIM2) in primates (Chuong et al. 2016).

The fission yeast Schizosaccharomyces pombe and the budding yeast Saccharomyces cerevisiae are two model organisms for studying the biology of eukaryotes, which diverged around 330 to 420 million years ago. LTR-RTs are the only TE order identified in the two yeast species: LTR-RTs are classified into two families (Tf2 and Tf1) in S. pombe, whereas LTR-RTs are classified into five families (Ty1 to Ty5) in S. cerevisiae (Goffeau et al. 1996; Kim et al. 1998; Bowen et al. 2003; Lesage and Todeschini 2005; Carr et al. 2012; Esnault and Levin 2015; Bleykasten-Grosshans et al. 2021). The relatively small repertoire of LTR-RTs in terms of copy number and family number makes the two yeast species excellent systems to explore the effect of TEs on the evolution and biology of their hosts. In this study, we analyzed the evolution of LTR-RTs in natural populations and interrogated the potential functional significance of LTR-RT insertions in the two highly diverging yeast species, potentially offering insight into the evolutionary significance of TEs in fungi and more generally in eukaryotes.

Results

LTR-RT Insertions Exhibit High Presence-absence Polymorphism in S. pombe and S. cerevisiae Populations

We first re-analyzed the distribution and diversity of TEs in the reference genomes of S. pombe (strain 972h−) and S. cerevisiae (strain S288C). In the S. pombe reference genome, we identified 13 complete or nearly complete LTR-RT (cLTR-RT) copies, all of which pertain to the Tf2 family, and 245 solo-LTRs, among which 97 and 148 belong to Tf2 and Tf1 families, respectively (Fig. 1a and b; supplementary table S3, Supplementary Material online; Wang et al. 2021b). In the S. cerevisiae reference genome, we identified a total of 50 cLTR-RTs, and these cLTR-RTs can be assigned into families Ty1 (31 copies), Ty2 (13 copies), Ty3 (2 copies), Ty4 (3 copies), and Ty5 (1 copies) (Fig. 1a;  Kim et al. 1998; Jordan and McDonald 1999). We also identified 380 solo-LTRs, among which 283, 42, 42, and 13 belong to Ty1/Ty2, Ty3, Ty4, and Ty5, respectively (Fig. 1b; supplementary table S4, Supplementary Material online). Because of the extremely high identity shared between Ty1 and Ty2 LTR sequences, it is technically unfeasible to distinguish them based on sequences (Kim et al. 1998). Nevertheless, these results confirm that the two model yeasts, S. pombe and S. cerevisiae, possess a relatively small number of TE copies.

Fig. 1. LTR-RTs in natural populations of S. pombe and S. cerevisiae. a) The number of cLTR-RTs in the reference genomes of S. pombe (strain 972h−) and S. cerevisiae (strain S288C). b) The number of solo-LTRs in the reference genomes of S. pombe (strain 972h−) and S. cerevisiae (strain S288C). c) The number of cLTR-RTs in the genomes of 35 S. pombe strains and the genomes of 128 S. cerevisiae strains. d) The number of solo-LTRs in the genomes of 35 S. pombe strains and the genomes of 128 S. cerevisiae strains. Different LTR-RT families were labeled using different colors. e) The number of cLTR-RTs and solo-LTRs in each of the 35 S. pombe strains. f) The number of cLTR-RTs and solo-LTRs in each of the 35 S. pombe strains. g) The frequency distribution of LTR-RT insertions in 35 S. pombe strains. h) The frequency distribution of solo-LTR insertions in 35 S. pombe strains. i) The distribution of genetic distance between 5′- and 3′-LTRs of cLTR-RT insertions in 35 S. pombe strains. j) The frequency distribution of LTR-RT insertions in 128 S. cerevisiae strains. k) The frequency distribution of solo-LTR insertions in 128 S. cerevisiae strains. l) The distribution of genetic distance between 5′- and 3′-LTRs of cLTR-RT insertions in 128 S. cerevisiae strains.

We then analyzed the natural variation of TEs in the genomes of S. pombe (35 strains sampled globally) that were sequenced using long-read sequencing approaches and the telomere-to-telomere genome assemblies of S. cerevisiae [128 strains sampled globally (Tusso et al. 2022; O’Donnell et al. 2023; supplementary tables S1 and S2, Supplementary Material online)]. These strains were isolated in diverse niches (wild, laboratory, domesticated, or human-associated) (Tusso et al. 2022; O’Donnell et al. 2023). In the 35 strains of S. pombe, we identified 895 cLTR-RTs and 6,588 solo-LTRs (Fig. 1c and d). Variation in cLTR-RT and solo-LTR copy numbers was also observed among different S. pombe strains (Fig. 1e). In the 128 strains of S. cerevisiae, we identified a total of 3,340 cLTR-RTs and 48,988 solo-LTRs (Fig. 1c and d). The number of cLTR-RTs varies greatly among different S. cerevisiae strains, from 0 in strains BMB and ADE to 117 in strain AMM_1a (Fig. 1f). Moreover, the number of solo-LTRs exhibits extensive variation among different S. cerevisiae strains (Fig. 1f). Taken together, our results show that the insertions of LTR-RTs and their solo-LTR derivatives are highly polymorphic in the populations of both S. pombe and S. cerevisiae.

cLTR-RTs Have Been Proliferating Recently in S. pombe and S. cerevisiae

To explore the evolutionary dynamics of LTR-RTs, we identified orthologous cLTR-RT insertions and solo-LTR insertions in 35 strains of S. pombe and 128 strains of S. cerevisiae. In both yeast species, the frequency of cLTR-RT insertions is low and heavy-tailed, suggesting that either the majority of cLTR-RT insertions were rapidly purged by purifying selection from the host population after their insertions or a recent burst of LTR-RT insertions occurred (Fig. 1g and j). Similarly, most solo-LTR insertions are present in relatively low frequency (Fig. 1h and k). Interestingly, some solo-LTR insertions are present in higher frequency in S. pombe, and we observed 25 solo-LTR insertions were fixed in the population of S. pombe (Fig. 1h). However, no fixed solo-LTR insertion was identified in the population of S. cerevisiae.

The divergence between the two LTRs flanking a cLTR-RT can be used to estimate the time of its insertion. To explore the temporal dynamics of cLTR-RT insertions in 35 strains of S. pombe and 128 strains of S. cerevisiae, we estimated the genetic distance between the 5′- and 3′-LTRs of cLTR-RT insertions. We observed a peak in genetic distance between 5′ and 3′ LTRs at 0 (maximum distance: 0.026 for S. pombe and 0.104 for S. cerevisiae), revealing the extreme recency of LTR-RT activity in both species (Fig. 1i and l). Moreover, no orthologous solo-LTR insertion was identified between S. pombe and Schizosaccharomyces octosporus (a species closely related to S. pombe), suggesting that LTR-RT insertions may have occurred after divergence between S. pombe and S. octosporus. Similarly, no orthologous cLTR-RT insertion was identified between S. cerevisiae and its closely related species Saccharomyces paradoxus. It follows that cLTR-RT insertions likely occurred along the evolutionary course of the species S. cerevisiae and after the divergence between S. cerevisiae and S. paradoxus. Taken together, our results reveal a similar pattern of cLTR-RT activity in S. pombe and S. cerevisiae: cLTR-RTs have been proliferating recently, resulting in extensive presence-and-absence variation among strains, and most of the cLTR-RTs become solo-LTRs rapidly following their insertions.

solo-LTRs Evolved in a Largely Neutral Manner in S. pombe and S. cerevisiae

To perform population genetics analysis, we focused on the solo-LTR insertions in the reference genomes with orthologous insertions present in more than five strains (Figs. 2a and 3a). The frequency of solo-LTR insertions varies along the genomes (Figs. 2a and 3a). We compared the nucleotide diversity of solo-LTR insertions with that of the coding regions, the synonymous sites, and the nonsynonymous sites of 215 nearby genes in S. pombe and 363 nearby genes in S. cerevisiae, which are physically closest to the corresponding solo-LTR insertions. In S. pombe, we found that the nucleotide diversity of solo-LTR insertions was significantly higher than that of the coding regions (P = 6.5 × 10−12, Wilcoxon–Mann–Whitney test) and the nonsynonymous sites (P < 2.22 × 10−16, Wilcoxon–Mann–Whitney test) of their nearby genes. However, no significant difference was observed among solo-LTR insertions and the synonymous sites of their nearby genes (P = 0.38, Wilcoxon–Mann–Whitney test; Fig. 2b). In S. cerevisiae, we found that the nucleotide diversity of solo-LTR insertions was significantly higher than that of the coding regions (P < 2.22 × 10−16, Wilcoxon–Mann–Whitney test) and the nonsynonymous sites of their nearby genes (P < 2.22 × 10−16, Wilcoxon–Mann–Whitney test), whereas no significant difference was found in nucleotide diversity between solo-LTR insertions and the synonymous sites of their nearby genes (P = 0.97, Wilcoxon–Mann–Whitney test; Fig. 3b). Furthermore, we performed neutrality test through calculating Tajima's D values (D values for short). In S. pombe, the D values of solo-LTR insertions are not significantly different from those of both the synonymous sites (P = 0.31, t-test) and the coding regions of their nearby genes (P = 0.29, Wilcoxon–Mann–Whitney test; Fig. 2c). However, the D values of solo-LTR insertions are significantly higher than those of both the coding and the nonsynonymous sites of their nearby genes (P = 0.00052, Wilcoxon–Mann–Whitney test; Fig. 2c). In S. cerevisiae, the D values of solo-LTR insertions are significantly higher than both the coding regions (P = 3.2 × 10−10, Wilcoxon–Mann–Whitney test) and nonsynonymous sites (P = 2 × 10−13, Wilcoxon–Mann–Whitney test) of their nearby genes. However, no significant difference in D values was observed between solo-LTR insertions and the synonymous sites of their nearby genes (P = 0.044, Wilcoxon–Mann–Whitney test; Fig. 3c). If the assumption that the synonymous sites evolved neutrally holds, the results of genetic diversity and neutrality test suggest that a majority of solo-LTR insertions might have evolved in a neutral manner in S. pombe and S. cerevisiae. It should be noted that this does not necessarily repudiate the functional significance of certain solo-LTR insertions.

Fig. 2. Population genetics analysis of solo-LTR insertions in S. pombe strains. a) The distribution of cLTR-RT insertions and solo-LTR insertions in S. pombe laboratory strain 972h−. The frequency of solo-LTR insertions for orthologous solo-LTR insertions present in more than five strains is shown above each chromosome. The comparison of nucleotide diversity b) and Tajima's D c) among the solo-LTR insertions, the coding regions of their nearby genes, and the synonymous sites and the nonsynonymous sites of their nearby genes. The values are represented by a filled circle. Statistical significance was assessed using Wilcoxon–Mann–Whitney test or Student's t-test (*P < 0.05, **P < 0.01, and ***P < 0.001). “Coding” indicates coding regions, “Syn” indicates synonymous sites, and “NonSyn” indicates nonsynonymous sites.

Fig. 3. Population genetics analysis of solo-LTR insertions in S. cerevisiae strains. a) The distribution of cLTR-RT and solo-LTR insertions in S. cerevisiae laboratory strain S288C. The frequency of solo-LTR insertions for orthologous solo-LTR insertions present in more than five strains is shown above each chromosome. The comparison of nucleotide diversity b) and Tajima's D c) among the solo-LTR insertions, the coding regions of their nearby genes, and the synonymous sites and the nonsynonymous sites of their nearby genes. The values are represented by filled circle. Statistical significance was assessed using Wilcoxon–Mann–Whitney test or Student's t-test (*P < 0.05, **P < 0.01, and ***P < 0.001). “Coding” indicates coding regions, “Syn” indicates synonymous sites, and “NonSyn” indicates nonsynonymous sites.

Certain solo-LTR Insertions Have Effect on the Host Fitness

To explore whether solo-LTR insertions affect the host fitness, we leveraged CRISPR-Cas9 to knock out nine randomly chosen solo-LTR insertions with various D values in S. pombe strain 972h- and 12 randomly chosen solo-LTR insertions with various D values in S. cerevisiae strain S288C (Figs. 4a, b and 5a, b; supplementary table S5, Supplementary Material online). We then used spot assay, a semi-quantitative method, to study the effect of LTR knockout (ΔLTR) on the host growth (Wang et al. 2021b). For the 9 ΔLTR strains of S. pombe, spot assay shows that the growth of wide-type (WT) and ΔLTR strains is overall similar under the normal culture condition of 30 °C (Fig. 4c). We challenged WT and ΔLTR strains by diverse stresses, including nutritional stress (cultured by adding 3% glycerol), osmotic stress (cultured by adding 0.25 M NaCl), oxidative stress [cultured by adding 3% hydrogen peroxide or 2.5 mM cobalt chloride (CoCl2)], and hyperthermal stress (cultured in 37 °C). No obvious difference in growth was found between WT and ΔLTR strains except for the ΔSpL2 strain of S. pombe (Fig. 4c). Interestingly, knocking out SpL2 attenuated yeast growth under both heat and CoCl2 challenges. The growth curves also confirmed the difference in growth between WT and ΔSpL2 strains cultured at 37 °C, and the ΔSpL2 strain has a significantly lower maximum growth rate than WT [P = 0.0013, t-test (Fig. 4d; supplementary table S6, Supplementary Material online]. For the 12 ΔLTR strains of S. cerevisiae, spot assay results show that the growth of WT and ΔLTR strains is overall similar under the normal culture condition of 30 °C and various stress conditions (Fig. 5c). Taken together, these results indicate that, although a majority of solo-LTR insertions might have no impact on in vitro growth, certain solo-LTR insertions do have effect on the fitness of their hosts.

Fig. 4. The effects of solo-LTR insertions on the growth of S. pombe strain 972h−. a) The distribution of Tajima's D values of solo-LTR insertions. The D values of nine solo-LTR insertions that were knocked out are highlighted with their names. The density distribution of D values of solo-LTR insertions and the synonymous sites of their nearby genes is shown with solid lines as the means and dotted lines as the 95% confidence intervals. b) The model of knocking out solo-LTR insertions. The CRISPER-Cas9 plasmid and donor DNA were introduced into yeast cells to achieve a knockout. c) Spot assay of solo-LTR element knockout strains under diverse stress challenges. WT and solo-LTR knockout strains were cultured in liquid medium until the logarithmic growth phase, and the stock suspensions obtained by 10-fold serial dilution were spotted onto the rich medium, rich media containing 3% glycerin, rich media containing 2.5 mM CoCl2, rich media containing 3% H2O2, rich media containing 0.25 M NaCl. For heat stress, it was cultured at 37 °C. d) The growth curves and maximum growth rates of WT and ΔSpL2 cultured at 37 °C. The WT and ΔSpL2 were assayed with three biological replicates for growth curves. The solid lines represent the mean OD600, with standard deviation among biological replicates depicted using error bars. The maximum growth rate is represented by a bar chart showing the average of the three biological replicates with difference between the two strains assessed using Student's t-test (*P < 0.05, **P < 0.01, and ***P < 0.001).

Fig. 5. The effects of solo-LTR insertions on the growth of S. cerevisiae strain S288C growth. a) The distribution of Tajima's D values of solo-LTR insertions. The D values of 12 solo-LTR insertions that were knocked out are highlighted with their names. The density distribution of D values of solo-LTR insertions and the synonymous sites of their nearby genes is shown with solid lines as the means and dotted lines as the 95% confidence intervals. b) The model of knocking out solo-LTR insertions. The CRISPER-Cas9 plasmid and donor DNA were introduced into yeast cells to achieve knockout. c) Spot assay of solo-LTR element knockout strains under diverse stress challenges. WT and ΔLTRs were cultured in liquid medium until logarithmic growth phase, and the stock suspensions obtained by 10-fold serial dilution were spotted onto the rich medium, rich media containing 0.8 NaCl, rich media containing 4.5% H2O2, rich media containing 3% glycerin, rich media containing 50 mM acetic acid, rich media containing 3 mM CoCl2. For heat stress, it was cultured at 37 °C.

SpL2 has Impact on the Host Gene Regulation

Due to its effect on the fitness of their hosts, we studied the evolution of the SpL2 and its impact on the host fitness and transcriptomes. SpL2 was present in 21 out of 35 (60%) strains, and all the orthologous SpL2 insertions shared identical sequences, indicating that a selective sweep might have occurred. We examined the impact of SpL2 knockout on the expression of its neighboring genes (pro1 and sod1; SpL2 is upstream for both genes) under normal conditions and heat stress. We observed a significant difference in the expression of pro1 and sod1 genes between WT and ΔSpL2 strains under both normal conditions (for pro1, P = 0.022, t-test; for sod1, P = 0.044, t-test; Fig. 6a) and heat stress (for pro1, P = 0.0014, t-test; for sod1, P = 0.031, t-test; Fig. 6b) using real-time quantitative PCR. However, when comparing the transcriptome profiles between WT and ΔSpL2 cultured under the heat stress (at 37 °C), we identified 127 significantly differentially expressed genes (DEGs), among which 28 and 99 are down-regulated and up-regulated, respectively (Fig. 6c). pro1 and sod1 genes were not identified as DEGs, consistent with low fold change revealed by real-time quantitative PCR. These results suggest that SpL2 might mediate the expression of distant gene(s), shaping their host transcriptome and thus affecting their host fitness. Therefore, our analyses show that certain solo-LTR insertions do have a profound impact on the transcriptomes and fitness of their hosts.

Fig. 6. The effects of solo-LTR SpL2 on the gene regulation in S. pombe strain 972h−. a) The comparison of the expression levels of their nearby genes (sod1 and pro1) between WT and ΔSpL2 at 30 °C. b) The comparison of the expression levels of their nearby genes (sod1 and pro1) between WT and ΔSpL2 at 37 °C. The synteny for SpL2 is shown. Green and purple triangles indicate the nearby genes sod1 and pro1. Gray triangle indicates the SpL2. All experiments were performed for three biological replicates which are represented by filled circles, and the error bar represents SD. Statistical significance was determined by Student's t-test (*P < 0.05, **P < 0.01, ***P < 0.001). c) Transcriptome profiling analysis of WT and ΔSpL2 cultured at 37 °C. The x-axis represents the differential expression level of genes, while the y-axis indicates statistical significance. The statistical significance thresholds were represented by dotted lines. The significantly down-regulated genes and up-regulated genes are highlighted in colors.

Discussion

In this study, we explored the evolution and functional significance of TEs in two model yeasts, which diverged around 330 to 420 million years ago. Eukaryotes such as vertebrates and land plants have extremely complex TE landscapes, making analysis of TE evolution at the population level challenging. However, the two model yeasts, S. pombe and S. cerevisiae, possess a relatively small number of TEs but a highly dynamic TE landscape that only comprises a limited number of cLTR-RTs or their solo-LTR derivatives. Therefore, the two yeasts represent excellent models for systematically studying the impact of TEs on the evolution and biology of their hosts.

Through analyzing TEs in two highly divergent yeast species, several general patterns on the evolution of TEs arise: (i) Both species possess a small number of TE copies and TE families, as only LTR-RTs were identified. (ii) solo-LTRs greatly outnumber cLTR-RTs in both species, suggesting ectopic recombination frequently occurred between two flanking LTRs of cLTR-RTs. cLTR-RTs likely become solo-LTRs rapidly following their insertions. (iii) Both species have been experiencing recent bursts of LTR-RT activity, resulting in extremely high presence-absence polymorphism in natural populations. (iv) Most LTR-RT insertions and solo-LTR insertions are present in relatively low frequency. The majority of LTR-RT insertions or solo-LTR insertions are rapidly purged from the host population after their insertions. Only a few LTR-RT or solo-LTR insertions reach high frequency or are fixed.

In the two yeast species, both the nucleotide diversity level and Tajima's D values of LTRs are not significantly different from those of synonymous sites of host genes. It has been generally thought that synonymous mutations are likely to be neutral, or almost so, whereas most nonsynonymous mutations are subject to purifying selection (Kimura 1977; Escalante et al. 1998; Fragata et al. 2018). We empirically tested the effect of LTRs on the fitness of yeasts. We knocked out 9 and 12 representative solo-LTR insertions separately in S. pombe and S. cerevisiae, respectively. In most cases, knocking out solo-LTR insertions has no obvious impact on the growth of their hosts, consistent with the population genetics analysis. In a previous study, we knocked out each of the 13 cLTR-RT insertions in S. pombe strain 972h−, and found that knocking out cLTR-RT insertions does not affect the host fitness either in normal condition or under diverse stress challenges (Wang et al. 2021b). Therefore, a majority of solo-LTR and cLTR-RT insertions might have little impact on in vitro growth at the assayed growth conditions. However, this does not necessarily mean all the solo-LTR insertions evolved neutrally.

Interestingly, knocking out one solo-LTR insertion has profound impact on the transcriptomes and fitness of their hosts. It follows that a fraction of solo-LTR insertions likely contribute to the fitness of their hosts in S. pombe at least in conditions tested in this study. The solo-LTR SpL2 appears to have impact on the expression of their neighboring genes, and transcriptome profiling shows that solo-LTR SpL2 knocking out changes the expression of a large number of distant genes, indicating that the LTR might not merely act as proximal regulatory elements affecting the expression of neighboring genes. The solo-LTR SpL2 is probably involved in complex regulatory networks, and thereby have an effect on the fitness of their hosts. Indeed, a recent study shows that Tf2 elements provide a positive fitness contribution to its host, S. pombe, by deleting the coding regions of all the complete Tf2 insertions, which results in changes to the regulation of a mitochondrial gene (Cranz-Mileva et al. 2024). Nevertheless, our results indicate that a fraction of TE insertions contribute to the fitness of their hosts through mediating host regulatory networks.

TEs are highly abundant in the genomes of multicellular organisms (Wicker et al. 2007; Wells and Feschotte 2020). TEs have been reported to shape the transcriptome diversity in many multicellular eukaryotes, from fruit fly, to mouse, and to humans (Feschotte 2008; Rebollo et al. 2012; Sorrells and Johnson 2015; Chuong et al. 2016; Sundaram and Wysocka. 2020; Baduel et al. 2021; Zhang et al. 2021; Coronado-Zamora and González 2023). Based on our results in two model yeasts, we suspect that a majority of TEs might similarly have evolved in a largely neutral manner in multicellular eukaryotes, and regulatory co-option could sporadically occur.

Materials and Methods

TE Identification

We identified cLTR-RTs in the genomes of 35 S. pombe strains sequenced using long-read sequencing approaches and the telomere-to-telomere genome assemblies of 128 S. cerevisiae strains [supplementary tables S1 and S2, Supplementary Material online (Tusso et al. 2022; O’Donnell et al. 2023)]. For all the yeast strains, we only analyzed the haploid genomes, and collapsed assemblies were excluded. We first searched reverse transcriptase (RT) protein homologs using the tBLASTn algorithm with representative RT proteins of Ty3, Ty1, and Bel-Pao retrotransposons as queries and an e cutoff of 10⁻5 (Carr et al. 2012). The significant hits of RT proteins were then bidirectionally extended to identify other proteins and LTRs. LTRs were identified using LTRharvest (Ellinghaus et al. 2008). solo-LTRs were identified using the BLASTn algorithm with LTRs of cLTR-RTs as queries and an e cutoff of 10⁻5. In S. cerevisiae, cLTR-RTs (complete LTR-RTs) were clustered based on phylogenetic analyses of the full-length nucleotide sequences with classified sequences. In S. pombe, cLTR-RTs were clustered based on phylogenetics analyses of their group-specific antigen (Gag) proteins with classified Gag proteins. All the sequences were aligned using MAFFT 7.402 with the G-INS-I strategy (Katoh and Standley 2013). Phylogenetic analyses were performed using an approximate maximum likelihood method implemented in FastTree 2.1.10 (Price et al. 2010). The solo-LTRs with a length of >100 bp were retrieved for subsequent analyses, because the length of typical LTRs ranges from 250 to 350 bp (supplementary fig. S1, Supplementary Material online). The orthologous relationship of cLTR-RT insertions or solo-LTR insertions across different strains and different species was established based on their 1000-bp flanking regions retrieved using SeqKit 2.1.0 (Shen et al. 2016). Sequences with 90% or higher sequence identity were clustered into the same group as an orthologous group using cd-hit-est 4.7 (Li and Godzik 2006; Fu et al. 2012).

Population Genetics Analysis

To perform population genetics analysis, we focused on the solo-LTR insertions in the reference genomes with orthologous insertions present in more than five strains. The nucleotide sequences of orthologous solo-LTR insertions and orthologs of their nearby genes were retrieved from the annotated genomes (Tusso et al. 2022; O’Donnell et al. 2023). The nearby genes are the ones that are physically closest to the solo-LTR insertions. The coding sequences for these genes were retrieved from the Saccharomyces Genome Database (https://www.yeastgenome.org/) and PomBase (https://www.pombase.org/). The sequences were aligned using MAFFT 7.402 with the strategy of G-INS-I (Katoh and Standley 2013). The nucleotide diversity and Tajima's D of solo-LTR insertions and the coding sequences, the synonymous sites, and the nonsynonymous sites of their nearby genes were estimated using DNASP 6 (Rozas et al. 2017). We compared the differences between pairs of groups with a t-test or Wilcoxon–Mann–Whitney test using R 4.3.2.

Evolutionary Dynamics Analysis

The divergence between the two LTRs flanking a cLTR-RT can be used to estimate the time of its insertion. To explore the evolutionary dynamics of cLTR-RT insertions, we retrieved 5′- and 3′-LTRs of cLTR-RT insertions. Since ectopic recombination can occur between cLTR-RTs, we performed phylogenetic analysis of 5′- and 3′-LTRs, and only these cLTR-RTs whose 5′- and 3′-LTRs cluster together were retrieved for further study; 5′- and 3′-LTRs were aligned using the L-INS-I method of MAFFT 7.402 (Katoh and Standley 2013). The Kimura two-parameter substitution model was employed to estimate the genetic distance between 5′- and 3′-LTRs (Kimura 1980; Kumar et al. 2016).

solo-LTR Knockout

All the strains used in this study were derived from S. pombe laboratory strain 972h- and S. cerevisiae laboratory strain S288C. 9 solo-LTR insertions in S. pombe 972h- and 12 solo-LTR insertions in S. cerevisiae strain S288C were chosen to cover the range of D values for knocking out. We used CRISPR-Cas9 to knock out representative solo-LTR insertions. To knock out solo-LTR insertions, we used the CRISPR-Cas9 plasmid, which contains a KanMX marker and can simultaneously encode both the Cas9 protein and sgRNA. CRISPR guidance sequences were designed using the CRISPR design tool [http://crispr.dbcls.jp/ (Naito et al. 2015)]. The guidance sequences were introduced into the gene editing plasmid carrying Cas9 by whole-plasmid PCR. Knockout cassettes carrying the flanking solo-LTRs were constructed by PCR. The gene editing plasmid and knockout cassette were co-transformed into yeast cells by the lithium acetate/single-stranded carrier DNA/polyethylene glycol (LiAc/SS carrier DNA/PEG) method (Gietz and Schiestl 2007). The yeast was cultured on mediums containing G418 (for S. cerevisiae, yeast extract peptone dextrose (YPD) + 0.05% G418; for S. pombe, yeast extract (YE) + 0.01% G418). The LTR knockout strains were verified by PCR. The PCR was performed in a 20-µL reaction volume with an annealing temperature of 58 °C. PCR products were analyzed by electrophoresis on a 1% agarose gel. The primers used for solo-LTR insertions knockout in S. pombe and S. cerevisiae are provided in supplementary table S7, Supplementary Material online.

Growth Curve Analysis

The ΔLTR and WT strains were cultured in a liquid medium at 37 °C with an initial OD600 value of 0.2. We quantified cell number by measuring OD600 and determined the maximum growth rate. Samples were collected at 0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, and 24 h, and OD600 values were measured in 96-well plates to generate growth curves. Each sample was performed in three replicates. The maximum growth rate for each knockout strain was determined from the growth rate during the logarithmic phase of the growth curve. This rate was calculated by dividing the change in OD600 between the start and end of the logarithmic phase by the corresponding time interval.

Spot Assay

The ΔLTR and the WT strains were cultured in a liquid medium at 30 °C with shaking at 200 rpm overnight. The cells were collected by centrifugation, and OD600 was adjusted to 3. Then, each of these strains was continuously diluted by a gradient of ten times to 10−5, generating five stock suspensions. We plated 2 μL of each stock suspension on the surface of solid medium under normal or stress conditions. The solid media include YE, YE + 0.25 M NaCl, YE + 3% glycerol, YE + 3% H2O2, and YE + 2.5 mM cobalt chloride in S. pombe strains and YPD, YPD + 0.8 M NaCl, YPD + 3% glycerol, YPD + 50 mM acetic acid, YPD + 3 mM cobalt chloride, and YPD + 4.5% H2O2 for S. cerevisiae strains. The plates were cultured at 30 °C before observing the growth of colonies. We also cultured the YPD and YE plates at 37 °C to observe the growth of colonies.

Transcriptome Analysis

We conducted transcriptome sequencing for three biological replicates of WT and solo-LTR knockout strains. The WT and SpL2 knockout strains were cultured under conditions of 37 °C. Total RNA was isolated using the Trizol Reagent (Invitrogen Life Technologies). The mRNA was purified from total RNA using poly-T oligo-attached magnetic beads. mRNA was fragmented into approximately 300-bp lengths and reverse transcribed into cDNA used for constructing high-throughput sequencing libraries. High-throughput paired-end sequencing was performed using the Illumina platform. Hisat2 2.1.0 (Kim et al. 2015) was utilized to align the high-throughput sequencing data to the reference genome. FeatureCounts 2.0.1 (Liao et al. 2014) was employed for sequence counting. DESeq2 package (Love et al. 2014) was used for differential gene expression analysis, and significant DEGs were identified with fold change ≥2 and adjusted P value ≤0.05.

RNA Extraction and qRT-PCR

Yeast samples were grown overnight in 10 mL YE medium. The cultures were diluted to an OD600 value of 0.2 and then were grown to an OD600 value of 0.8. RNA was extracted by FastPure Universal Plant Total RNA Isolation Kit (Vazyme). RNA was reverse transcribed into cDNA using HiScript III RT SuperMix for qPCR (+gDNA wiper; Vazyme). qRT-PCR was carried out using intercalating dye ChamQTM SYBR qPCR Master Mix (Low ROX Premixed) (Vazyme) with each primer set (supplementary table S8, Supplementary Material online). The qRT-PCR reactions were performed in 10 µL volume. We extracted RNA triplicates. qRT-PCR was performed using a StepOne Real-Time PCR System (Applied Biosystems, USA). The CT values were normalized against Actin mRNA levels from the same preparation to give the ΔCT values, and the relative changes in gene expression were estimated using the 2−ΔΔCt method.

Supplementary Material

evae193_Supplementary_Data

Supplementary Material

Supplementary material is available at Genome Biology and Evolution online.

Funding

This work was supported by National Natural Science Foundation of China (32270684).

Data Availability

The data underlying this article are available in the article and in its online Supplementary material. The RNA-seq data generated in this study was deposited to the National Center for Biotechnology Information (NCBI; https://www.ncbi.nlm.nih.gov/) under BioProject ID PRJNA1122139.
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