
==== Front
Poult Sci
Poult Sci
Poultry Science
0032-5791
1525-3171
Elsevier

S0032-5791(24)00715-6
10.1016/j.psj.2024.104136
104136
GENETICS AND MOLECULAR BIOLOGY
Inter and intra population genetic variability in ducks under conservation programs
Wolc Anna *†
Lisowski Mirosław ‡1
Grajewski Bartosz ‡
Lewko Lidia §
Szwaczkowski Tomasz tomasz.szwaczkowski@up.poznan.pl
║2
⁎ Department of Animal Science, Iowa State University, Ames, IA 50010, USA
† Hy-Line International, Dallas Center, IA 50063, USA
‡ Department of Reproductive Biotechnology and Cryoconservation, National Research Institute of Animal Production, 32-083 Balice, Poland
§ Department of Poultry Breeding, National Research Institute of Animal Production, 32-083 Balice, Poland
║ Department of Genetics and Animal Breeding, Poznan University of Life Sciences, 60-637 Poznan, Poland
2 Corresponding author: tomasz.szwaczkowski@up.poznan.pl
1 Deceased.

07 8 2024
11 2024
07 8 2024
103 11 10413611 3 2024
24 7 2024
© 2024 The Authors
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
This study focuses on estimation of the inter and intra population genetic variability of 6 duck populations. Microsatellite loci were used to assess the genetic variation and population structure of 6 duck populations under a conservation program in Poland. DNA polymorphism was assessed using 24 microsatellite markers and 50 individuals from each population. Polymorphism information content (PIC), heterozygosity with 2 estimators of genetic differentiation (FST and GST), and Nei's standard genetic distance were calculated. The results showed that these 6 endangered duck populations showed high genetic polymorphism. Observed heterozygosity within populations ranged from 0.14 to 0.83, with the average value of 0.58. PIC within populations ranged from 0.038 (P-8 and P-9 lines) to 0.89 (LsA line). Average number of alleles in the studied populations ranged from 4.5 (KhO-1 line) to 7.3 (LsA line). Based on the results, the pairs of lines LsA: P-33 and P-8: P-9 were found to be the most related; and the most genetically distant group was KhO-1 line, which originated as a cross between Khaki Campbell with Orpington duck.

Key words

genetic resource
genetic distance
genetic diversity
microsatellite marker
==== Body
pmcINTRODUCTION

There are currently about 200 breeds of ducks in the world. However, despite their important socio-economic role and the relatively large number of breeds that exist, information on genetic diversity of ducks is limited. Only a few highly productive populations are used to produce commercial hybrids. These are mainly Pekin ducks, produced by global breeding companies. Such an approach, not only in case of ducks, leads inevitably to extinction of breeds that don't have any currently perceived important economic impact (Oldenbroek, 1999) but can contain valuable genetic variation for future use.

Animal genetic resources include all species, breeds and varieties of livestock and poultry which, according to recommendations of the Commission on Genetic Resources for Food and Agriculture – FAO, and should be protected for economic, scientific, and cultural reasons (Alderson, 1990; NRC, 1993; Polak et al., 2021). Long term selection towards improved production, however, leads to a reduction of genetic diversity in livestock as specific highly prolific and productive breeds are exclusively utilized. To eliminate unfavourable loss of genetic diversity due to intensive selection, genetic reserves are needed. In Poland, genetic reserve flocks of ducks have been maintained in situ since the 1970s (Polak et al., 2021). Molecular markers can be used to evaluate these populations to guide prioritization of conservation efforts (Zhang et al., 2019).

So far, research (Kokoszynski et al. 2019) on Polish duck populations covered by genetic resources flocks has focused on carcass composition and some meat quality traits. There have been limited studies about genetic diversity in these populations, except for 1 comparative study with Italian duck populations by Carco et al. (2018). Today, most genetic diversity studies utilize single nucleotide polymorphism (SNP) markers. These are biallelic and are useful when large numbers of markers are available. However, genetic characterization of diversity within and between populations can be done using microsatellite markers. Microsatellites are characterized by a core sequence that consists of several tandemly repeated units with a length of 1-6 base pairs. The repetitive nature of these markers results in multiple alleles per locus (Wu et al., 2008). Compared to biallelic SNPs, microsatellites are 2 to 3 times more informative (Fernández et al. 2013). Hence, this type of genetic markers is still successfully and routinely applied to analyse the molecular variability of many species (Choi et al., 2018), including duck (Lai et al., 2020; Debnath et al., 2023).

Animal genetic resources, regardless of their geographical location, are perceived as elements of the world's cultural heritage. To our knowledge, local duck populations included in in situ genetic resources conservation programs have not been the subject of comprehensive research on genetic diversity to date.

The objective of this study was to estimate the inter and intra population genetic variability of 6 duck populations to evaluate the effectiveness of the existing conservation program in protecting duck genetic resources.

MATERIAL

Genetic Resources

Duck breeds utilized in this study are all maintained at the Genetic Resources Station for Waterfowl in Dworzyska near Kórnik, owned by National Institute of Animal Science Experimental Station in Kołuda Wielka. The material originated from local and foreign origin birds and synthetic lines which have been kept in the genetic resources program in situ since the 1970s. There are 6 unique duck lines within the genetic conservation program: Mini duck (K-2), crossbreed duck (KhO-1), English Pekin (LsA), Danish Pekin (P-8), French Pekin (P-9) and Local Pekin (P-33). The K-2 population was created in the mid-1970s by crossing mallard ducks with Pekin drakes. In turn, the KhO-1 population was created in the late 1970s by crossing Khaki Campbell and Orpington ducks. The origin of the LsA population was 3 English Pekin flocks imported to Poland also in the late 1970s which were subsequently crossed with other lines. The populations P-8 and P-9 came from 600 hatching eggs brought to Poland from Denmark in 1983 and from France in 1978, respectively. The P-33 population is the result of crossbreeding local Polish ducks with birds imported from the Netherlands. After including these lines in the genetic resources conservation program, the sizes of all populations are approximately equal: from 204 to 227 total individuals (170–190 females and 34–40 males). Additional phenotype descriptions of these populations are given in the Table 1.Table 1 Description of the duck populations utilized in this study, including their physical characteristics production type and economic significance.

Table 1Population	Characteristics	Productive Purpose	Economic importance	
Mini duck	Small body weight. Stocky and compact build. Broad chest, short neck and legs.	Amateur and backyard breeding.	High quality meat.	
Crossbreed duck	Light-brown plumage. Darker, black-brown neck in males. Small and quite vertical torso.	Due to the original shape and colour of the plumage, they are suitable for keeping in water reservoirs in parks, gardens, and zoos.	High egg production, high slaughter yield, birds' resistance to adverse environmental and nutritional conditions.	
English Pekin	White plumage. Harmonious body shape.
The breast is well developed, wide and convex.
Strong legs spread wide.	They are a rich source of genetic variation that can be used to create new breeds.	High performance value.
Very good health.	
Danish Pekin	White plumage.
Harmonious body shape with a slightly raised torso. The breast is full and wide. Strong legs spread wide.	This population may be useful in work to obtain commercial hybrids.	Excellent performance values, well-muscled and a high level of reproductive characteristics.	
French Pekin	White plumage. Relatively large head and long neck. The back is rounded and long. The torso is cylindrical and quite vertical.	Multipurpose population. They have better reproductive characteristics than meat ones.	A valuable population for research and breeding work.	
Polish Pekin	White plumage. A delicate figure with a more vertical posture.	Multipurpose population. Backyard breeding.	These ducks are characterized by high dietary value of meat, low fat content in the carcass and good quality feathers.
Birds' resistance to adverse environmental and nutritional conditions.	

METHODS

Samples Collection and DNA Isolation

DNA was isolated from whole blood collected from the clavicle vein. All experiments were approved by the 2nd Local Ethical Commission for Animal Experiments in Krakow (resolution no. 503/2007). DNeasy Tissue from Qiagen was used for DNA extraction. DNA concentration was assessed by spectrometry and electrophoresis on 0.8% agarose gel.

Microsatellite Analysis

The primers for amplification of microsatellite sequences were chosen based on the literature, mostly from waterfowl (Buchholz et al., 1998; Huang et al., 2005, 2006; Maak et al., 2003).

Using PCR with fluorescent tagged primers, 24 loci were amplified. Reactions were carried out in 4 loci multiplex with Type-it Microsatellite PCR Kit (Qiagen). Reactions were in a 10μl volume which contained 5μl of 2x concentrated reaction mix Type-it, 1μl of DNA matrix (approx. 50ng), and with each of the primers at 0.25μM concentration. Amplification was done in a 2720 Thermal Cycler (Applied Biosystems) with an initial denaturation step at 95°C for 5 min followed by 30 cycles of 95°C for 30s, primer-specific hybridization temperature (see Table 2) at 50 to 60°C for 90 s, 72°C for 30 s, with a final extension step at 60°C for 30 min. Each amplification product was diluted with water (10–100 times), 1μl was added to 9μl of formamid containing 0.5μl size standard DNA GeneScan-600 LIZ Size Standard (Applied Biosystems) and denatured for 5 min. at 95°C. Capillary electrophoresis was performed in ABI Prism 3130XL (Applied Biosystems), with 36 cm long capillaries, polymer POP7 (https://www.thermofisher.com/order/catalog/product/4393708) and G5 filter. The allele sizes were read in Peak Scanner v 1.0 (2006, Applied Biosystems, www.appliedbiosystems.com).Table 2 Description of the microsatellite markers: including their chromosomal locations, GenBank accession numbers, Tm, Dye and primer sequence.

Table 2Locus	Chromosomal location*	GenBank accession	Tm (°C)	Dye	Primer sequences (5`–3`)	
CAUD038	9:14555012-14555071	AY493283	55	NED	GATAATGGCTGGCTCCTTGA GACCACAACATCGTGCAGAG	
CAUD024	1:184977427-184977486	AY493269	55	VIC	TCGCATTAAGCTCTGATCT ATCAACAGAATCCAAAATATG	
CAUD050	4:3786088-3786147	AY493295	55	6-Fam	GGACAAGTGGCATGTGTCAT GGCTTCTGTGCTCCTCAGAT	
CAUD117	1:134970773-134970832	AY587036	55	PET	GCCTTCATTCCTCTGCTAC GCTCATCCCTGCTGCTCA	
CAUD069	CAU1	AY493314	50	NED	CAGCATTATTATTTCAGAAGG CTCATTCCAATTCCTCTGTA	
CAUD070	CAU2	AY493315	50	6-Fam	GTAACAACTCAGTGCTTTCAA GTAAGTATTGACAGAGACATC	
CAUD120	20:10548501-10548560	AY587039	50	PET	AATATCCTGTCGCCGTGGT AATTCTTGCTGAGATTATAGAG	
CAUD126	CAU1	AY587045	50	VIC	TTGCCACATAAACCCACTAC CAGAGAATTTTAGTAAGAGT	
CAUD111	CAU5	AY587030	50	NED	TGACATTACACACCCAAAC CAAGGGCAGGGGTAAGGAT	
CAUD013	14:14024200-14024259	AY493258	50	6-Fam	ACAATAGATTCCAGATGCTGAA ATGTCTGAGTCCTCGGAGC	
CAUD022	CAU7	AY493267	50	PET	CATGCTGAGTGTCCTATCCT CCAGGTCAGGCGTGTGCT	
CAUD124	12:13261098-13261157	AY587043	50	VIC	CCAGCCAAGAACCTCCAGT CTTTGAATGTCCATGTAGCAG	
CAUD093	1:53563719-53563778	AY493338	50	PET	AGAGCGGTGTGAGAGCAGAG GATATCGCTCGCAATTTTGG	
CAUD112	1:47985196-47985255	AY587031	50	6-Fam	CAACTGACAGAGAGGCACG GACTGTGTTTCCAATGCTCC	
CAUD060	CAU2	AY493305	50	NED	AGAAAGCTCCTGTATGTGAT ATGCTGGTGTGAGATTTGAA	
CAUD040	28:4819663-4819722	AY493285	50	VIC	TGTGTAACCCTGATAGACTGA TCCCACCCCAAACCCTGC	
CAUD019	20:2571875-2571934	AY493264	55	VIC	CTTAGCCCAGTGAAGCATG GCAGACTTTTACTTATGACTC	
CAUD086	1:53563719-53563778	AY493331	55	6-Fam	AACACAGCTTCACCCCACAG GCAGAGCGGTGTGAGAGCA	
CAUD136	2:144222943-144223002	AY587055	55	PET	GTTGCATGAAAAAGGAAAGG GGAAGATAGAAGATGGAATG	
CAUD036	UNK	AY493281	55	6-Fam	AAGTTGGGAGAGGAGTCAG CTAAGGCTTTTCCAGAATGC	
CAUD091	CAU3	AY493336	60	NED	GAAAAAGGCAGCACAGCAC GCAAAGTTGAGGCATGTAATC	
CAUD039	1:54663830-54663889	AY493284	55	VIC	GGGACATCTCTTGGAGCAAA AGTGAAAGCTGCTGCTGGAT	
CAUD026	6:35089244-35089303	AY493271	55	VIC	ACGTCACATCACCCCACAG CTTTGCCTCTGGTGAGGTTC	
CAUD082	UNK	AY493327	55	VIC	ATGTAAAGCAAGGAAGAGCC AAGAGTCTGAGCCAAGCAC	
⁎ Locations based on: Ensembl search, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1461431/, https://hal.science/hal-01702555/document, UNK – no chromosomal assignment found.

Genetic Diversity Analyses

Genetic diversity was assessed using 24 microsatellite markers for 50 individuals (40 females and 10 males) from each population. Each population was characterized by the following characteristics: number of alleles per locus, observed and expected heterozygosity, polymorphic information content (PIC) and deviation from Hardy-Weinberg equilibrium. These parameters were estimated using the CERVUS program (Marshall et al., 1998). FIS was estimated for each locus following Weir and Cockerham (1984) and coefficient of gene differentiation Gst between populations (Nei, 1973). Significance of Fis was tested in FSTAT 2.9.3 (updated in 2001 from Goudet (1995). P-value for Fis within samples, based on 2880 randomizations.

Phylogenic tree with 100 bootstrap samples was constructed using Nei's standard genetic distance (Nei, 1972), in Populations 1.2.31 (Langella, 1999) and edited in TREEVIEW (Page, 1996). Admixture between populations was evaluated using STRUCTURE (Evanno et al. 2005) assuming independent loci and 4 to 10 populations, admixture level inferred from the data and prior population assignment according to population assignment at sampling.

The STRUCTURE analysis was implemented using an admixture model and a Markov Chain Monte Carlo (MCMC) chain of 20,000 rounds where the initial 1,000 were discarded as burn-in period and K (number of clusters) ranging from 2 to 10. For each value of K, 20 independent runs were performed. DeltaK method (Evanno et al., 2005) was used to evaluate optimal number of clusters.

Principal Components Analysis was performed in Genetix (Belkhir et al., 1996).

Data analysis was performed using CERVUS (Marshall et al. 1998), FSTAT 2.9.3 (updated in 2001 from Goudet (1995), Microsat (Minch et al. 1997) and GENEPOP (Rousset, 2008).

RESULTS AND DISCUSSION

Genetic Variation

The 24 microsatellite loci were dispersed across 13 chromosomes, including both macro and microchromosomes, with 2 loci (CAUD36 and CAUD82) for which no chromosomal assignment has been made. The parameters describing heterozygosity, polymorphism, as well as genetic equilibrium are listed in Table 3, Table 4.Table 3 Summary statistics of the microsatellite markers in the populations LsA, P33 and P8.

Table 3	LsA	P33	P8	
Locus	k	HO	He	PIC	HW	k	H0	He	PIC	HW	K	H0	He	PIC	HW	
CAUD050	7	0.653	0.804	0.769	NS	7	0.860	0.828	0.795	NS	5	0.319	0.513	0.438	NS	
CAUD024	12	0.776	0.886	0.865	ND	14	0.840	0.891	0.871	ND	8	0.429	0.769	0.734	NS	
CAUD038	13	0.776	0.773	0.736	NS	10	0.680	0.716	0.686	NS	4	0.265	0.277	0.262	ND	
CAUD117	10	0.878	0.839	0.812	NS	9	0.800	0.820	0.786	NS	9	0.796	0.835	0.804	NS	
CAUD070	14	0.857	0.873	0.849	NS	14	0.826	0.874	0.851	NS	7	0.740	0.731	0.682	NS	
CAUD120	3	0.480	0.485	0.397	NS	4	0.638	0.585	0.537	NS	4	0.780	0.741	0.684	NS	
CAUD126	9	0.796	0.866	0.842	NS	11	0.809	0.816	0.785	NS	9	0.820	0.738	0.700	NS	
CAUD069	11	0.820	0.798	0.769	NS	11	0.872	0.869	0.845	NS	10	0.900	0.853	0.825	NS	
CAUD111	6	0.760	0.771	0.727	NS	4	0.580	0.538	0.484	NS	5	0.571	0.604	0.537	NS	
CAUD013	4	0.460	0.567	0.491	NS	5	0.820	0.746	0.694	NS	6	0.560	0.645	0.572	NS	
CAUD022	3	0.480	0.597	0.508	NS	3	0.460	0.594	0.517	NS	3	0.440	0.424	0.368	NS	
CAUD124	4	0.600	0.661	0.606	NS	4	0.720	0.719	0.655	NS	5	0.520	0.556	0.468	NS	
CAUD060	16	0.449	0.908	0.890	ND	17	0.633	0.893	0.874	ND	9	0.755	0.839	0.807	NS	
CAUD112	3	0.460	0.472	0.413	NS	3	0.694	0.663	0.582	NS	3	0.490	0.409	0.331	NS	
CAUD093	5	0.673	0.686	0.628	NS	4	0.878	0.687	0.627	*	4	0.620	0.707	0.647	NS	
CAUD040	14	0.720	0.867	0.843	NS	9	0.776	0.823	0.790	NS	9	0.694	0.786	0.757	NS	
CAUD019	10	0.600	0.800	0.764	NS	9	0.673	0.813	0.779	NS	5	0.260	0.775	0.730	***	
CAUD086	4	0.280	0.556	0.499	*	5	0.367	0.457	0.414	NS	3	0.440	0.653	0.573	NS	
CAUD136	2	0.100	0.132	0.122	ND	3	0.292	0.384	0.348	NS	2	0.040	0.040	0.038	ND	
CAUD091	4	0.878	0.745	0.689	NS	4	0.500	0.634	0.552	NS	4	0.660	0.623	0.549	NS	
CAUD039	5	0.653	0.658	0.602	NS	4	0.688	0.669	0.603	NS	4	0.511	0.460	0.390	NS	
CAUD036	5	0.286	0.684	0.613	***	5	0.167	0.639	0.569	***	3	0.000	0.230	0.209	ND	
CAUD026	5	0.320	0.568	0.520	NS	4	0.286	0.617	0.535	***	3	0.500	0.594	0.517	NS	
CAUD082	7	0.680	0.717	0.674	NS	6	0.776	0.819	0.784	NS	6	0.720	0.708	0.651	NS	
Average	7.3	0.601	0.696	0.651	-	7.4	0.561	0.712	0.665	-	5.4	0.534	0.605	0.553	-	
K: number of alleles per locus; HO: observed heterozygosity; He: expected heterozygosity; PIC: polymorphic information content; HW: Hardy-Weinberg equilibrium; ND: not defined.

NS, *, *** - statistically significant deviation from HW for P > 0.05, P ≤ 0.05 and P ≤ 0.001, respectively

50 birds per population.

Table 4 Summary statistics of the microsatellite markers in the populations P9, KhO-1 and K2 (50 birds per population).

Table 4	P9	KhO-1	K2	
Locus	k	HO	He	PIC	HW	k	H0	He	PIC	HW	K	H0	He	PIC	HW	
CAUD050	7	0.653	0.710	0.657	NS	4	0.638	0.605	0.556	NS	6	0.250	0.737	0.687	*	
CAUD024	10	0.735	0.841	0.811	NS	8	0.787	0.845	0.817	NS	10	0.490	0.868	0.843	NS	
CAUD038	9	0.633	0.752	0.717	NS	8	0.745	0.785	0.742	NS	13	0.755	0.831	0.802	NS	
CAUD117	9	0.837	0.789	0.754	NS	6	0.383	0.460	0.403	NS	5	0.583	0.758	0.710	NS	
CAUD070	11	0.714	0.692	0.666	NS	7	0.604	0.665	0.609	NS	8	0.727	0.807	0.770	NS	
CAUD120	4	0.813	0.716	0.658	NS	2	0.604	0.505	0.375	NS	4	0.545	0.563	0.463	NS	
CAUD126	10	0.796	0.855	0.828	NS	6	0.604	0.615	0.580	NS	9	0.659	0.824	0.790	NS	
CAUD069	11	0.878	0.811	0.775	NS	7	0.625	0.650	0.603	NS	8	0.886	0.854	0.824	ND	
CAUD111	4	0.780	0.708	0.644	NS	5	0.520	0.591	0.544	NS	7	0.720	0.741	0.690	NS	
CAUD013	4	0.520	0.492	0.395	NS	3	0.200	0.187	0.177	ND	6	0.800	0.780	0.735	NS	
CAUD022	3	0.540	0.533	0.416	NS	3	0.400	0.371	0.337	NS	3	0.400	0.620	0.533	NS	
CAUD124	4	0.800	0.724	0.665	NS	5	0.520	0.549	0.443	NS	5	0.760	0.777	0.731	NS	
CAUD060	14	0.780	0.883	0.863	NS	5	0.440	0.751	0.697	**	9	0.574	0.787	0.745	NS	
CAUD112	3	0.560	0.600	0.526	NS	3	0.540	0.622	0.534	NS	3	0.511	0.553	0.464	NS	
CAUD093	4	0.640	0.624	0.554	NS	4	0.540	0.538	0.454	NS	5	0.574	0.668	0.613	NS	
CAUD040	11	0.540	0.857	0.832	NS	4	0.860	0.542	0.438	***	12	0.796	0.771	0.741	NS	
CAUD019	8	0.440	0.710	0.667	**	6	0.420	0.698	0.651	**	8	0.809	0.781	0.740	NS	
CAUD086	3	0.540	0.552	0.466	NS	4	0.280	0.647	0.593	***	4	0.174	0.432	0.367	***	
CAUD136	2	0.040	0.040	0.038	ND	2	0.122	0.276	0.236	ND	3	0.261	0.543	0.473	**	
CAUD091	4	0.630	0.658	0.596	NS	3	0.620	0.588	0.518	NS	5	0.512	0.727	0.677	NS	
CAUD039	5	0.413	0.482	0.439	NS	3	0.420	0.512	0.455	NS	7	0.651	0.780	0.741	NS	
CAUD036	4	0.065	0.324	0.301	ND	4	0.600	0.680	0.612	NS	5	0.302	0.613	0.531	**	
CAUD026	3	0.220	0.296	0.267	ND	3	0.220	0.392	0.333	NS	4	0.260	0.427	0.389	NS	
CAUD082	7	0.820	0.719	0.663	NS	3	0.660	0.652	0.572	NS	5	0.460	0.422	0.395	NS	
Average	6.4	0.599	0.640	0.591		4.5	0.515	0.572	0.512		6.4	0.561	0.694	0.644		
K: number of alleles per locus; HO: observed heterozygosity; He: expected heterozygosity; PIC: polymorphic information content; HW: Hardy-Weinberg equilibrium; ND: not defined.

NS, **, *** - statistically significant deviation of HW for P > 0.05, P ≤ 0.01 and P ≤ 0.001, respectively.

The total number of observed alleles across the 24 microsatellites was 244, with an average of 6.2 alleles per locus. Average number of alleles per locus ranged from 2.3 for CAUD136 to 11.7 for CAUD060 with the total number of alleles being between 3 (CAUD120 and CAUD022) and 24 (CAUD060) (Table 3, Table 4). The number of detected alleles is comparable to that reported by Carco et al. (2018) with a similar panel who identified 261 alleles with an average of 11.36 alleles across 2 Italian and 2 Polish duck breeds, while Hariyono et al. (2019) identified 153 alleles across 22 loci in Indonesian ducks with average of 6.96 alleles. Chepiha et al. (2021) identified 99 alleles for 20 loci and 89 alleles for 17 loci in Ukrainian Black White Breasted and Ukrainian Clay, respectively. As expected, the number of alleles in local duck breeds is larger compared to experimental and commercial populations under long term selection. For example, Zhang et al. (2021) in experimental duck population found the average number of alleles per locus was 4.133 with a range from 2 to 7.

Observed average heterozygosity within populations ranged from 0.14 to 0.83, with the average value being 0.58. PIC measures the quantity of information of each microsatellite and depends on the number of alleles identified and the allele frequencies (Purwantini and Purwantini, 2010). The scale of PIC index reflects the proportion of heterozygotes in populations. The average number of alleles in the studied populations ranged from 4.5 (KhO-1) to 7.3 (LsA). The highest average heterozygosity was estimated in the P-33 line (0.65), and the lowest in the KhO-1 line (0.51). Khan Ahmadi et al. (2007) estimated a similar level of heterozygosity for Pekin (0.53) and Muscovy (0.44) ducks. Even higher variability in heterozygosity was reported for Asian ducks: Seo et al. (2016) reported 0.49 heterozygosity of south-east Asian ducks, while Li et al. (2010) obtained a very high estimate of 0.86.

Heterozygosity and PIC are perceived as the most important indicators utilized to determine the genetic variation of population (Huang et al., 2005). The diversity of a locus is generally considered low when PIC < 0.25 and high when PIC > 0.5 (Botstein et al., 1980). In this study, the average PIC of all sites and all populations was 0.73, with 24 microsatellites showing high diversity (Table 3, Table 4). It is important to note that significant variation between loci and populations did exist, ranging from 0.038 (CAUD136 in the P-8 and P-9 lines) to 0.89 (CAUD060 in the LsA line). Joint PICs across the 6 populations studied were high, and only for 2 loci (CAUD022 and CAUD136) were these parameters smaller than 0.5. This is similar to reports in literature (Su and Chen, 2009; Pham et al., 2022). In contrast, relatively low PICs were found for 2 Italian local duck populations (Carco et al., 2018). The average frequency of private alleles was 0.085, which provides an estimate of on average 0.6 migrants per generation. The estimates of PIC between 0.51 in KhO-1 and 0.67 in P-33 indicates smaller genetic diversity in the analysed populations compared to results of Wu et al. (2008) who found that the PIC for all populations was around 0.75.

Inbreeding coefficients (FIS) for 24 loci of 6 duck populations are listed in Table 5. The average inbreeding coefficients for the analysed populations were close to zero. Considering averages of all analysed loci jointly, the lowest inbreeding coefficient was estimated in the P-9 line (0.078) and the highest in the K-2 line (0.205). However, it is worth noting the large differences between individual markers with FIS values ranging from -0.597 for CAUD040 in the KhO-1 line to 1 for CAUD0036 marker in P-8 line. Negative FIS estimates were obtained in each population, however, their distribution among loci was quite diverse. The numbers of negative FIS values varied from 4 (LsA) to 11 (P-9). Generally, the Pekin duck lines were characterized by larger numbers of negative inbreeding coefficients compared to other populations. At the same time, high FIS values were obtained for some loci, indicating a high level of undesirable homozygosity. The applied permutation test indicates the significance of Fis for 5 populations, except P-9 (adjusted nominal level of 5% is 0.00035).Table 5 Inbreeding coefficient (Fis) analysis for 24 loci in 6 duck populations.

Table 5	LsA	P-33	P-8	P-9	KhO-1	K-2	
CAUD050	0.190	−0.039	0.381	0.081	−0.055	0.664	
CAUD024	0.126	0.058	0.446	0.127	0.069	0.438	
CAUD038	−0.003	0.050	0.042	0.160	0.052	0.092	
CAUD117	−0.046	0.025	0.048	−0.061	0.169	0.232	
CAUD070	0.018	0.055	−0.012	−0.032	0.093	0.100	
CAUD120	0.010	−0.093	−0.054	−0.136	−0.199	0.032	
CAUD126	0.082	0.010	−0.113	0.070	0.018	0.202	
CAUD069	−0.028	−0.004	−0.056	−0.083	0.038	−0.039	
CAUD111	0.014	−0.079	0.055	−0.103	0.121	0.029	
CAUD013	0.190	−0.101	0.133	−0.058	−0.071	−0.026	
CAUD022	0.198	0.227	−0.039	−0.014	−0.079	0.357	
CAUD124	0.094	−0.002	0.065	−0.106	0.054	0.022	
CAUD060	0.508	0.294	0.101	0.118	0.417	0.272	
CAUD112	0.026	−0.047	−0.201	0.067	0.133	0.077	
CAUD093	0.019	−0.282	0.124	−0.026	−0.004	0.142	
CAUD040	0.171	0.059	0.118	0.373	−0.597	−0.033	
CAUD019	0.252	0.173	0.667	0.383	0.401	−0.035	
CAUD086	0.499	0.198	0.328	0.022	0.570	0.600	
CAUD136	0.241	0.241	−0.010	−0.010	0.559	0.522	
CAUD091	−0.179	0.213	−0.059	0.043	−0.054	0.298	
CAUD039	0.007	−0.028	−0.112	0.145	0.181	0.167	
CAUD036	0.585	0.741	1.000	0.801	0.118	0.509	
CAUD026	0.439	0.540	0.159	0.258	0.441	0.393	
CAUD082	0.053	0.054	−0.016	−0.141	−0.013	−0.092	
Mean	0.144	0.096	0.125	0.078	0.098	0.205	

Estimated levels of heterozygosity of the studied populations was not as expected based on their method of origination. Three of the populations (KhO-1, K-2 and P-33) resulted from crossbreeding and this were expected to have high rates of heterozygosity. From this perspective, the highest inbreeding level in the K-2 population is surprising. Generally, obtained averages of variability parameters within populations are relatively similar. Khan Ahmadi et al. (2007) reported that low average heterozygosity may be attributed to the small number of alleles in given population. Some deficits of heterozygotes in the studied lines were observed. From the perspective of conservation programs, this is an undesirable result.

Hardy-Weinberg equilibrium was demonstrated for nearly all the loci analysed. This is undoubtedly good from the perspective of maintaining genetic variability within each of the 6 populations. Significant or highly significant deviations from genetic balance have been demonstrated only for a few loci: CAUD086 (for LsA, KhO-1, K-2), CAUD036 (for LsA, P-33, K-2), CAUD093 (for P-33), CAUD026 (for P-33), CAUD019 (for P8, P-9, KhO-1), CAUD060 (for KhO-1), CAUD040 (for KhO-1) and CAUD136 (for K-2). Similar trends (some loci with deviations from the Hardy-Weinberg equilibrium) can also be seen in research conducted by other authors (Lai et al., 2020; Pham et al., 2022) on indigenous duck populations under the conservation programs. Other research, such as by Hsiao et al. (2008), showed no loci with significant deviation from Hardy-Weinberg equilibrium in Tsaya duck.

Genetic Diversity Among the Studied Populations

Estimated genetic distances are given in (Table 6). The 2 pairs of lines, LsA with P-33 and P-8 with P-9, were found to be the most related, while the most genetically distant group was the KhO-1 line. The estimates of FST suggest large (>0.15) or moderate (0.05–0.15) genetic differentiation between the analysed populations (Wright, 1978). The lowest FST (0.069) was found between lines P-33 and LsA which can be explained by participation of P-33 in creation of synthetic line LsA. Similar range of FST values were reported by Su et al. (2007) between local Chinese duck populations. Similar conclusions can be drawn based on GST, indicating the highest genetic differentiation was between KhO-1 and other populations, with the majority of genetic variation originating between populations while maintaining some level of within population heterozygosity.Table 6 Genetic distances between the population with pairwise Fst (above diagonal) and coefficients of gene differentation (Gst; below diagonal).

Table 6Lines	K-2	KhO-1	LsA	P-33	P-8	P-9	
K-2		0.221	0.156	0.159	0.233	0.227	
KhO-1	0.527	-	0.227	0.219	0.327	0.292	
LsA	0.469	0.559	-	0.069	0.112	0.112	
P-33	0.507	0.531	0.173	-	0.124	0.134	
P-8	0.644	0.795	0.232	0.27	-	0.109	
P-9	0.693	0.728	0.259	0.334	0.203	-	

The tree of genealogical distances is shown in Figure 1. The results from microsatellite data agree with the known history of the analysed lines: small distances were found between the P-8 line (Danish Pekin) and the P-9 line (French Pekin). Larger distance was observed between those 2 groups and birds from the P-33 line (Polish Pekin) and LsA (English Pekin). The most genetically distant breed from the Pekin type ducks were animals from the KhO-1 line, which were created as a cross between Khaki Campbell and Orpington breeds, showing clear distinction between these populations with different breed origins.Figure 1 The tree of genealogical distances.

Figure 1

The first 4 principal components explained 5.93%, 4.53%, 2.99%, and 2.44% of genetic variations, respectively, which indicates that there was not a very strongly dominating component (see Figure 2, Figure 3). PCA1 vs PCA2 clearly separated K-2 population (pink) and KhO-1 (green) from the remaining populations (Figure 2, Figure 3). PCA1 vs PCA3 separated populations LsA (yellow) and P-33 (blue) from P-8 (white) and P-9 (grey) which confirms the results of the phylogenetic tree.Figure 2 Principal components analysis PCA1 vs PCA2. Populations: K-2 (pink), KhO-1 (green), LsA (yellow), P-33 (blue), P-8 (white), P-9 (grey).

Figure 2

Figure 3 Principal components analysis PCA1 vs PCA3. Populations: K-2 (pink), KhO-1 (green), LsA (yellow), P-33 (blue), P-8 (white), P-9 (grey).

Figure 3

STRUCTURE confirmed 6 distinctive populations with low level (less than 10%) of misclassified or admixed individuals (Figure 4). Additional genotyping of current breeding stock may be recommended to ensure no genetic introgression between the populations. K values in the range of 2 to 10 were tested. Large increase in likelihood was observed going from 2 to 6 populations suggesting that there are 6 populations involved; smaller additional improvement was observed between 6 and 8 populations which likely represents known history of KhO-1 and K2 being crossbreds back in 1970s (Figure 5A). However, deltaK method confirmed K=6 as the optimal number of clusters (Figure 5B)Figure 4 Population admixture identified by STRUCTURE with samples ordered according to original population assignment and coloured according to clustering algorithm. (1 - K-2; 2 - KhO-1; 3 – LsA; 4 – P-33; 5 – P-8; 6 – P-9). The clustering diagrams obtained for K values ranging from 2 to 10. (K=10 was very similar to K=9).

Figure 4

Figure 5 Log-likelihood (A) and delta K (B) for the K-values ranging from 2 to 10 estimated by the STRUCTURE.

Figure 5

CONCLUSIONS

The analysis of microsatellite variation showed the presence of acceptable levels of genetic variation in the duck populations maintained as genetic reserves, indicating that the conservation program was successful. Some markers had a large number of segregating alleles and indicated differentiation of the populations. Molecular tools can be used to better maintain genetic diversity in the conservation program and preserve the unique alleles of different populations. Generally, the parameters of genetic variability for these populations are similar to the genetic variability information obtained by other authors with other duck populations. This confirms the validity of the implemented concept of continued protection of these genetic groups.

DISCLOSURES

The authors declare that they have no conflict of interest.

Appendix Supplementary materials

Photo1. Mini duck (K-2)

Image, image 1

Photo2-Crossbreed duck (KhO-1)

Image, image 2

Photo3-English Pekin (LsA)

Image, image 3

Photo4-Polish Pekin (P-33)

Image, image 4

Photo5-Danish Pekin (P-8)

Image, image 5

Photo6-French Pekin (P-9)

Image, image 6

ACKNOWLEDGMENTS

The research was financed by the National Science Centre Poland - grant no. NN311295635 . The authors would like to thank the anonymous reviewers for their valuable comments improving our manuscript. We are grateful to Dr. Janet Fulton and Dr. Luke Kramer for language correction of the manuscript and, above all, useful comments.

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.psj.2024.104136.
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