Breeds: BB, Blackbelly; CH, Charollais; DB, Dorper white; DP, Dorper; DS, Dorset;
HM, Hampshire; KT, Katahdin; PL, Pelibuey; SU, Suffolk; TX, Texel
| Livestock Research for Rural Development 33 (3) 2021 | LRRD Search | LRRD Misssion | Guide for preparation of papers | LRRD Newsletter | Citation of this paper |
Genetic diversity information is the basis for conservation and genetic improvement programs. The objective was to analyze the genetic diversity and population structure, based on 84 genetic markers of SNP type, in ten breeds of sheep: Blackbelly (BB; 459), Charollais (CH; 209), White Dorper (DB; 122), Dorper (DP; 2,106), Dorset (DS; 534), Hampshire (HM; 1,298), Katahdin (KT; 3,864), Pelibuey (PL; 821), Suffolk (SU; 596) and Texel (TX; 88). For genetic variability, within breed, the expected (He) and observed (Ho) heterozygosis, the polymorphic information content (PIC), effective size (Ne), Hardy Weinberg disequilibrium (HW), the Shannon Index (SI), as well as the Wright's FIS and FIT statistics were analyzed. To analyze genetic relationships across breeds, Nei's standard genetic distance (DGN) and Wright's FST statistic were calculated, with the Neighbor-Joining procedure the clusters were made to build the phylogenetic tree. The mean values for Ho, He, PIC and IS were 0.413, 0.422, 0.33 and 0.609, respectively. The DGN (mean, 0.10) and the FST (mean, 11.0) show that the genetic differentiation between breeds was low to moderate. Within populations, on average, 16 genetic markers presented HW (p <0.05). The phylogenetic tree topology exposed three clades: wool breeds (SU, HM, TX and CH); the separation of the DB and DP given its origin from DS; and, KT, BB and PL (hair breeds) independently on a branch.
Keywords: heterozygosis, genetic distances, genetic variability, phylogenetic tree, polymorphic information
In Mexico, specialized and registered sheep breeders are grouped in the National Ovinoculture Unit (NOU), where genealogical records and production data are coordinated, as well as genetic improvement schemes based on national genetic evaluations (CONARGEN, 2010; Domínguez-Viveros and Rodríguez-Almeida, 2007). Recently, with the aim of strengthening genetic improvement, the NOU implemented paternity tests based on SNP-type genetic markers (Domínguez-Viveros et al, 2020a).
Genetic variability in populations of zootechnical interest is the basis for decision-making in the improvement of productive traits, to satisfy production needs in various environments (Notter, 1999; Groeneveld et al 2010). In this context, Domínguez-Viveros et al (2020b), in ten breeds administered by the NOU, evaluated genetic variability and population structure based on population genetic parameters derived from the analysis of pedigree and genealogical information.
On the other hand, genetic markers express DNA polymorphism, their evolution and applications have strengthened animal genetic improvement programs. Heterozygosity estimates, Wright's F statistics, effective size as well as genetic distances, derived from the genetic markers analysis, allow evaluating the genetic structure and variability of populations (Farid et al 2000; Curkovic et al 2016; Abdelkader et al 2018).
In sheep, various studies have been carried out on genetic diversity and structure based on microsatellite-type genetic markers (Lawson et al 2007; Bozzi et al 2009; de la Barra et al 2010; Ciani et al 2013; Yilmaz et al., 2015; Curkovic et al 2016; Souheil et al 2016, Vajed et al 2017; Abdelkader et al. 2018). With the description of the ovine genome through sequencing and the development of new analysis tools (ISGC et al 2010; Kijas et al 2009), genetic markers of the SNP type (Single Nucleotide Polymorphism) have been developed, given their advantages and advances, they are the most stable for genetics studies (Vignal et al 2002; Negrini et al., 2008; Deniskova et al 2015). Based on the above, the objective of this study was to analyze the genetic variability and structure of populations based on a panel of SNPs.
The genotypes of 10,097 individuals of ten breeds were analyzed: Blackbelly (BB; 459), Charollais (CH; 209), White Dorper (DB; 122), Dorper (DP; 2,106), Dorset (DS; 534), Hampshire (HM; 1,298), Katahdin (KT; 3,864), Pelibuey (PL; 821), Suffolk (SU; 596) and 88 Texel (TX). The panel of genetic markers consisted of 84 SNPs, developed and validated for genetic tests in sheep (Kijas et al 2012; Heaton et al 2014); the particular characteristics of the genetic markers panel have been described by Clarke et al. (2014). The processing of the samples was carried out in a private laboratory based in New Zealand and certified by the International Society for Animal Genetics. With a different approach and objectives to the present study, alternate studies have been carried out in the database used (Dominguez-Viveros et al., 2020a), where the NOU evaluated the exclusion probabilities and defined the SNP panel to be used in testing paternity.
For population structure and genetic variability, within breed, the expected (He) and observed (Ho) heterozygosis, the polymorphic information content (PIC), effective size (Ne), Hardy Weinberg disequilibrium (HW), the Shannon Index (SI), as well as the Wright's FIS and FIT statistics were analyzed (Weir, 1996; Templeton, 2006; Waples, 2006). To analyze genetic relationships across breeds, Nei's standard genetic distance and Wright's FST statistic were calculated, with the Neighbor-Joining procedure the clusters were made to build the phylogenetic tree (Nei and Chesser, 1983; Weir and Cockerham, 1984; Nei, 1987). The analyzes were carried out with the Software LDNE (Robin et al 2008), GenAlex 6.051 (Peakall and Smouse, 2012) and Phylip (Felsenstein, 1989).
The results for the indicators of genetic diversity by breed are presented in Table 1. The average values for Ho, He, PIC, SI and Ne were 0.41, 0.42, 0.33, 0.61 and 88.73, respectively. In relation to HW, within the breed, on average 16 genetic markers presented HW disequilibrium (p < 0.05). The loss of heterozygotes associated with possible inbreeding (FIS) presented positive results in nine breeds, with a range of 0.80 % (DS) to 5.0 % (SU). The loss of heterozygotes due to non-random mating or possible subpopulations (FIT) represented positive values in eight breeds, with a general range of -0.053 to 0.097 (Table 1). The FST as genetic differentiation between populations (Table 2) ranged between 0.015 (PL-BB) and 0.099 (DB-BB), with an average value of 0.063. The genetic distance (Table 2) ranged between 0.018 (BB-PL) and 0.168 (CH-DP), with an average value of 0.10. Figure 1 shows the phylogenetic tree product of genetic distance, where the topology showed three clades: wool breeds (SU, HM, TX and CH), DB and DP clade, given their origin from DS, and the KT, BB and PL clade of hair breeds.
|
Table 1. Indicators of genetic diversity across the ten breeds of sheep evaluated |
||||||||
|
Breed |
Ho |
He |
IS |
PIC |
FIS |
FIT |
Ne |
|
|
BB |
0.408 |
0.418 |
0.605 |
0.33 |
0.026 |
0.035 |
74.6 |
|
|
CH |
0.421 |
0.434 |
0.622 |
0.34 |
0.028 |
0.003 |
45.6 |
|
|
DB |
0.382 |
0.378 |
0.556 |
0.30 |
-0.007 |
0.097 |
36.6 |
|
|
DP |
0.390 |
0.401 |
0.584 |
0.31 |
0.027 |
0.077 |
199.9 |
|
|
DS |
0.445 |
0.450 |
0.640 |
0.35 |
0.008 |
-0.053 |
49.0 |
|
|
HM |
0.430 |
0.435 |
0.623 |
0.34 |
0.013 |
-0.019 |
107.9 |
|
|
KT |
0.413 |
0.421 |
0.608 |
0.33 |
0.020 |
0.023 |
145.0 |
|
|
PL |
0.421 |
0.435 |
0.625 |
0.34 |
0.033 |
0.005 |
121.4 |
|
|
SU |
0.408 |
0.428 |
0.616 |
0.33 |
0.050 |
0.035 |
86.1 |
|
|
TX |
0.409 |
0.426 |
0.613 |
0.33 |
0.045 |
0.033 |
21.2 |
|
|
Breed: BB, Blackbelly; CH, Charollais; DB, White Dorper; DP, Dorper; DS, Dorset; HM, Hampshire; KT, Katahdin; PL, Pelibuey; SU, Suffolk; TX, Texel. Ho, observed heterozygosity. He, expected heterozygosity. SI, Shannon index. PIC, polymorphic information content. FIS, coefficient of inbreeding. FIT, loss of heterozygotes due to non-random mating or possible subpopulations. Ne, effective size |
||||||||
|
Table 2. Genetic differentiation based on the FST statistic (under the diagonal) and Nei's genetic distances (on the diagonal) in the ten populations evaluated |
||||||||||
|
Breed |
BB |
CH |
DB |
DP |
DS |
HM |
KT |
PL |
SU |
TX |
|
BB |
0.131 |
0.116 |
0.114 |
0.094 |
0.115 |
0.043 |
0.018 |
0.122 |
0.118 |
|
|
CH |
0.068 |
0.147 |
0.168 |
0.076 |
0.070 |
0.147 |
0.103 |
0.052 |
0.086 |
|
|
DB |
0.099 |
0.097 |
0.065 |
0.053 |
0.131 |
0.102 |
0.116 |
0.126 |
0.164 |
|
|
DP |
0.092 |
0.087 |
0.050 |
0.075 |
0.158 |
0.100 |
0.104 |
0.128 |
0.151 |
|
|
DS |
0.054 |
0.045 |
0.057 |
0.060 |
0.067 |
0.079 |
0.082 |
0.053 |
0.098 |
|
|
HM |
0.064 |
0.045 |
0.086 |
0.082 |
0.043 |
0.112 |
0.101 |
0.046 |
0.089 |
|
|
KT |
0.052 |
0.064 |
0.080 |
0.069 |
0.047 |
0.057 |
0.033 |
0.109 |
0.125 |
|
|
PL |
0.015 |
0.052 |
0.089 |
0.073 |
0.044 |
0.056 |
0.036 |
0.092 |
0.105 |
|
|
SU |
0.079 |
0.042 |
0.094 |
0.082 |
0.041 |
0.027 |
0.059 |
0.064 |
0.091 |
|
|
TX |
0.073 |
0.062 |
0.093 |
0.084 |
0.047 |
0.051 |
0.063 |
0.061 |
0.060 |
|
|
Breed: BB, Blackbelly; CH, Charollais; DB, White Dorper; DP, Dorper; DS, Dorset; HM, Hampshire; KT, Katahdin; PL, Pelibuey; SU, Suffolk; TX, Texel |
||||||||||
|
| Figure 1. Phylogenetic tree developed from Nei's genetic distances and the
Neighbor-Joining procedure. Breeds: BB, Blackbelly; CH, Charollais; DB, Dorper white; DP, Dorper; DS, Dorset; HM, Hampshire; KT, Katahdin; PL, Pelibuey; SU, Suffolk; TX, Texel |
The SI quantifies the heterogeneity of the population based on the possible subpopulations and their abundance, values in the interval from zero to one indicate that the populations evaluated in their context are homogeneous, with little internal differentiation and low levels of uncertainty to identify individuals. Ho is an indicator of the degree of genetic variation in the study population, in equilibrium HW, Ho and He would be equivalent (Nei, 1987; Templeton, 2006). The Ne provides information on the number of reproducers involved in changes in inbreeding and genetic variability in future generations, consider the possible effects of overlapping generations, population subdivision, and selection, among other factors associated with population genetics (Templeton, 2006).
In the populations of the present study, Domínguez-Viveros et al. (2020b) reported results for Ne and inbreeding, based on the analysis of the pedigree, that can be contrasted. The Ne was of smaller magnitude in the range of 12.2 to 73.5, the differences can be attributed to the structure and integrity of the pedigree, the test with genetic markers are not representative of the entire population and the small number of SNPs. Results in inbreeding are associated with results in FIS and FIT; within breed, the percentage of inbreeding animals fluctuated from 12.3% (DS) to 48.7% (DB), with a general average of 29.7%; the levels of inbreeding (as average of the inbreeding population) ranged from 3.9% (KT) to 14.6% (DB), with a general average of 8.0%
In DB, Ho> He and FIS were negative, which can be attributed to a possible reduction in the effective size of reproducers and the founder effect, which lead to the so-called bottleneck effect (Cornuet and Luikart, 1996). In similar studies, Blackburn et al. (2011), Curkovic et al. (2016) and Al-Atiyat et al. (2014), evaluating 28, 18 and 5 breeds, respectively, observed similar results (Ho> He; negative FIS) to those obtained with DB in one of the breeds evaluated by each group of researchers.
For studies across breeds, the main force of differentiation is attributed to genetic drift, the genetic distance products of differences in allele frequencies help to understand the relationships between populations, allow genetic characterization across breeds and provide information for the design of crosses (Nei, 1987; Templeton, 2006). Breeds with a unique evolutionary history potentially contribute the most to maintaining genetic diversity at the species level (Hall and Bradley, 1995). In breeding programs based on crossbreeding, heterosis levels are a function of differences in allelic frequencies and genetic distances between the races used (Graml and Pirchner, 1984).
Similar work has been carried out in other countries or regions with the aim of characterizing their sheep genetic resources. Farid et al. (2000) in ten breeds of sheep (DS, SU and TX included) from Canada, the genetic distance of Nei fluctuated from 0.213 to 0.792, through DS, SU and TX (breeds in common) were superior to the results of the present study. Crispin et al. (2013) evaluated eight breeds of sheep in Brazil (HM, SU, DP and DB breeds included), reported that genetic differentiation through populations (FST) ranged between 0.08 and 0.25, in the coincidence breeds it was higher than the results of the present study, in the phylogenetic tree the arrangement of DB and DP was very different from what was observed in this work. Blackburn et al. (2011), in 28 sheep breeds (including DP, DS, HM, KT, SU and TX) from the United States, published genetic distance in the range of 0.04 to 0.54, for common breeds DG and FIS were higher than of the present study. Naqvi et al. (2017) analyzed the genetic variability of five breeds from Pakistan, based on an analysis of molecular variance, they reported that 94.4% of the genetic variance was due to differences between individuals and 5.6% due to differences between breeds. Dossybayev et al. (2019) evaluated five native races adapted to the climatic conditions of Kazakhstan, for their use in local improvement plans or in other regions, reporting low genetic differentiation (FST through races less than 0.07) and medium genetic distance (all greater than 0.22 ), the phylogenetic tree showed two groupings.
All authors declare not to have a conflict of interest
We thank the Organismo de la Unidad Nacional de Ovinocultores for providing the database used in this study, within the framework of the collaboration agreement with the Universidad Autónoma de Chihuahua and the Consejo Nacional de Recursos Genéticos Pecuarios.
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