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The pig industry is usually considered an intensive livestock industry, mainly supported by hybrid breeding between commercial pig breeds. However, people's pursuit of a more natural environment and higher meat quality has led to an increasing demand for eco-friendly and diverse pig feeding systems. Therefore, the importance of rearing and conserving local pig breeds is increasing. The Livni pig is a local breed with good adaptability to the environmental and fodder conditions in central Russia. In this study, we aimed to analyze the genetic diversity and population structure of Livni pigs using whole-genome single nucleotide polymorphism (SNP) data. We utilized the Porcine GGP HD BeadChip on genotype samples from old (n = 32, 2004) and modern (n = 32, 2019) populations of Livni pigs. For the museum samples of Livni pigs (n = 3), we extracted DNA from their teeth, performed genomic sequencing, and obtained SNP genotypes from the whole-genome sequences. SNP genotypes of Landrace (n = 32) and Large White (n = 32) pigs were included for comparative analysis. We observed that the allelic richness of Livni pigs was higher than those of Landrace and Large White pigs (AR = 1.775-1.798 vs. 1.703 and 1.668, respectively). The effective population size estimates (NE5 = 108 for Livni pigs, NE5 = 59 for Landrace and Large White pigs) confirmed their genetic diversity tendency. This was further supported by the length and number of runs of homozygosity, as well as the genomic inbreeding coefficient (almost twofold lower in Livni pigs compared to Landrace and Large White pigs). These findings suggest that the Livni pig population exhibits higher genetic diversity and experiences lower selection pressure compared to commercial pig populations. Furthermore, both principal component and network tree analyses demonstrated a clear differentiation between Livni pigs and transboundary commercial pigs. The TreeMix results indicated gene flow from Landrace ancestors to Livni pigs (2019) and from Large White ancestors to Livni pigs (2004), which was consistent with their respective historical breeding backgrounds. The comparative analysis of museum, old, and modern Livni pigs indicated that the modern Livni pig populations have preserved their historical genomic components, suggesting their potential suitability for future design selection programs.
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Breeding improvements and quantitative trait genetics are essential to the advancement of broiler production. The impact of artificial selection on genomic architecture and the genetic markers sought remains a key area of research. Here, we used whole-genome resequencing data to analyze the genomic architecture, diversity, and selective sweeps in Cornish White (CRW) and Plymouth Rock White (PRW) transboundary breeds selected for meat production and, comparatively, in an aboriginal Russian breed of Ushanka (USH). Reads were aligned to the reference genome bGalGal1.mat.broiler.GRCg7b and filtered to remove PCR duplicates and low-quality reads using BWA-MEM2 and bcftools software; 12,563,892 SNPs were produced for subsequent analyses. Compared to CRW and PRW, USH had a lower diversity and a higher genetic distinctiveness. Selective sweep regions and corresponding candidate genes were examined based on ZFST, hapFLK, and ROH assessment procedures. Twenty-seven prioritized chicken genes and the functional projection from human homologs suggest their importance for selection signals in the studied breeds. These genes have a functional relationship with such trait categories as body weight, muscles, fat metabolism and deposition, reproduction, etc., mainly aligned with the QTLs in the sweep regions. This information is pivotal for further executing genomic selection to enhance phenotypic traits.
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Galinhas , Polimorfismo de Nucleotídeo Único , Seleção Genética , Animais , Galinhas/genética , Locos de Características Quantitativas , Cruzamento , Federação Russa , Sequenciamento Completo do Genoma/métodosRESUMO
The search for SNPs and candidate genes that determine the manifestation of major selected traits is one crucial objective for genomic selection aimed at increasing poultry production efficiency. Here, we report a genome-wide association study (GWAS) for traits characterizing meat performance in the domestic quail. A total of 146 males from an F2 reference population resulting from crossing a fast (Japanese) and a slow (Texas White) growing breed were examined. Using the genotyping-by-sequencing technique, genomic data were obtained for 115,743 SNPs (92,618 SNPs after quality control) that were employed in this GWAS. The results identified significant SNPs associated with the following traits at 8 weeks of age: body weight (nine SNPs), daily body weight gain (eight SNPs), dressed weight (33 SNPs), and weights of breast (18 SNPs), thigh (eight SNPs), and drumstick (three SNPs). Also, 12 SNPs and five candidate genes (GNAL, DNAJC6, LEPR, SPAG9, and SLC27A4) shared associations with three or more traits. These findings are consistent with the understanding of the genetic complexity of body weight-related traits in quail. The identified SNPs and genes can be used in effective quail breeding as molecular genetic markers for growth and meat characteristics for the purpose of genetic improvement.
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Coturnix , Estudo de Associação Genômica Ampla , Masculino , Animais , Coturnix/genética , Polimorfismo de Nucleotídeo Único/genética , Carne/análise , Peso Corporal/genéticaRESUMO
Traces of long-term artificial selection can be detected in genomes of domesticated birds via whole-genome screening using single-nucleotide polymorphism (SNP) markers. This study thus examined putative genomic regions under selection that are relevant to the development history, divergence and phylogeny among Japanese quails of various breeds and utility types. We sampled 99 birds from eight breeds (11% of the global gene pool) of egg (Japanese, English White, English Black, Tuxedo and Manchurian Golden), meat (Texas White and Pharaoh) and dual-purpose (Estonian) types. The genotyping-by-sequencing analysis was performed for the first time in domestic quails, providing 62,935 SNPs. Using principal component analysis, Neighbor-Net and Admixture algorithms, the studied breeds were characterized according to their genomic architecture, ancestry and direction of selective breeding. Japanese and Pharaoh breeds had the smallest number and length of homozygous segments indicating a lower selective pressure. Tuxedo and Texas White breeds showed the highest values of these indicators and genomic inbreeding suggesting a greater homozygosity. We revealed evidence for the integration of genomic and performance data, and our findings are applicable for elucidating the history of creation and genomic variability in quail breeds that, in turn, will be useful for future breeding improvement strategies.
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A study for genomic variation that may reflect putative selective signaling and be associated with economically important traits is instrumental for obtaining information about demographic and selection history in domestic animal species and populations. A rich variety of the Russian chicken gene pool breeds warrants a further detailed study. Specifically, their genomic features can derive implications from their genome architecture and selective footprints for their subsequent breeding and practical efficient exploitation. In the present work, whole genome genotyping of 19 chicken breeds (20 populations with up to 71 samples each) was performed using the Chicken 50 K BeadChip DNA chip. The studied breed sample included six native Russian breeds of chickens developed in the 17th-19th centuries, as well as eight Russian chicken breeds, including the Russian White (RW), created in the 20th century on the basis of improving local chickens using breeds of foreign selection. Five specialized foreign breeds of chickens, including the White Leghorn (WL), were used along with other breeds representing the Russian gene pool. The characteristics of the genetic diversity and phylogenetic relationships of the native breeds of chickens were represented in comparison with foreign breeds. It was established that the studied native breeds demonstrate their own genetic structure that distinguishes them from foreign breeds, and from each other. For example, we previously made an assumption on what could cause the differences between two RW populations, RW1 and RW2. From the data obtained here, it was verified that WL was additionally crossed to RW2, unlike RW1. Thus, inherently, RW1 is a purer population of this improved Russian breed. A significant contribution of the gene pool of native breeds to the global genetic diversity of chickens was shown. In general, based on the results of a multilateral survey of this sample of breeds, it can be concluded that phylogenetic relationships based on their genetic structure and variability robustly reflect the known, previously postulated and newly discovered patterns of evolution of native chickens. The results herein presented will aid selection and breeding work using this gene pool.
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BACKGROUND: The genomes of worldwide poultry breeds divergently selected for performance and other phenotypic traits may also be affected by, and formed due to, past and current admixture events. Adaptation to diverse environments, including acclimation to harsh climatic conditions, has also left selection footprints in breed genomes. RESULTS: Using the Chicken 50K_CobbCons SNP chip, we genotyped four divergently selected breeds: two aboriginal, cold tolerant Ushanka and Orloff Mille Fleur, one egg-type Russian White subjected to artificial selection for cold tolerance, and one meat-type White Cornish. Signals of selective sweeps were determined in the studied breeds using three methods: (1) assessment of runs of homozygosity islands, (2) FST based population differential analysis, and (3) haplotype differentiation analysis. Genomic regions of true selection signatures were identified by two or more methods or in two or more breeds. In these regions, we detected 540 prioritized candidate genes supplemented them with those that occurred in one breed using one statistic and were suggested in other studies. Amongst them, SOX5, ME3, ZNF536, WWP1, RIPK2, OSGIN2, DECR1, TPO, PPARGC1A, BDNF, MSTN, and beta-keratin genes can be especially mentioned as candidates for cold adaptation. Epigenetic factors may be involved in regulating some of these important genes (e.g., TPO and BDNF). CONCLUSION: Based on a genome-wide scan, our findings can help dissect the genetic architecture underlying various phenotypic traits in chicken breeds. These include genes representing the sine qua non for adaptation to harsh environments. Cold tolerance in acclimated chicken breeds may be developed following one of few specific gene expression mechanisms or more than one overlapping response known in cold-exposed individuals, and this warrants further investigation.
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The objective of this study was to identify the SNPs and candidate genes related to body weight and seven body conformation traits at the age of 8 months in the Russian aboriginal Karachai goats (n = 269) by conducting genome-wide association studies (GWAS), using genotypes generated by Goat SNP BeadChip (Illumina Inc., USA). We identified 241 SNPs, which were significantly associated with the studied traits, including 47 genome-wide SNPs (p < 10−5) and 194 suggestive SNPs (p < 10−4), distributed among all goat autosomes except for autosome 23. Fifty-six SNPs were common for two and more traits (1 SNP for six traits, 2 SNPs for five traits, 12 SNPs for four traits, 20 SNPs for three traits, and 21 SNPs for two traits), while 185 SNPs were associated with single traits. Structural annotation within a window of 0.4 Mb (±0.2 Mb from causal SNPs) revealed 238 candidate genes. The largest number of candidate genes was identified at Chr13 (33 candidate genes for the five traits). The genes identified in our study were previously reported to be associated with growth-related traits in different livestock species. The most significant genes for body weight were CRADD, HMGA2, MSRB3, MAX, HACL1 and RAB15, which regulate growth processes, body sizes, fat deposition, and average daily gains. Among them, the HMGA2 gene is a well-known candidate for prenatal and early postnatal development, and the MSRB3 gene is proposed as a candidate gene affecting the growth performance. APOB, PTPRK, BCAR1, AOAH and ASAH1 genes associated with withers height, rump height and body length, are involved in various metabolic processes, including fatty acid metabolism and lipopolysaccharide catabolism. In addition, WDR70, ZBTB24, ADIPOQ, and SORCS3 genes were linked to chest width. KCNG4 was associated with rump height, body length and chest perimeter. The identified candidate genes can be proposed as molecular markers for growth trait selection for genetic improvement in Karachai goats.
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Estudo de Associação Genômica Ampla , Cabras , Animais , Cabras/genética , Lipopolissacarídeos , Genômica , Peso Corporal/genética , Ácidos Graxos , Apolipoproteínas B/genéticaRESUMO
Poaching is one of the major types of wildlife crime in Russia. Remnants of goats (presumably the wild endemic species, the Caucasian tur) were found in an area of the Caucasian mountains. The case study involves a suspected poacher whose vehicle was found to have two duffel bags containing pieces of a carcass, which he claimed was that of a goat from his flock. The aim of the forensic genetic analysis for this case was to (i) establish individual identity and (ii) perform species identification. DNA typing based on fourteen microsatellites revealed that STR-genotypes generated from pieces of evidence found at crime scene fully matched those obtained from the evidence seized from the suspect. The results of genome-wide SNP-genotyping, using Illumina Goat SNP50 BeadChip, provided evidence that the poached animal was a wild Caucasian tur (Capra caucasica). Thus, based on comprehensive molecular genetic analysis, evidence of poaching was obtained and sent to local authorities. To our knowledge, this case study is the first to attempt to use DNA chips in wildlife forensics of ungulates.
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Comparison of genomic footprints in chicken breeds with different selection history is a powerful tool in elucidating genomic regions that have been targeted by recent and more ancient selection. In the present work, we aimed at examining and comparing the trajectories of artificial selection in the genomes of the native egg-type Russian White (RW) and meat-type White Cornish (WC) breeds. Combining three different statistics (top 0.1% SNP by FST value at pairwise breed comparison, hapFLK analysis, and identification of ROH island shared by more than 50% of individuals), we detected 45 genomic regions under putative selection including 11 selective sweep regions, which were detected by at least two different methods. Four of such regions were breed-specific for each of RW breed (on GGA1, GGA5, GGA8, and GGA9) and WC breed (on GGA1, GGA5, GGA8, and GGA28), while three remaining regions on GGA2 (two sweeps) and GGA3 were common for both breeds. Most of identified genomic regions overlapped with known QTLs and/or candidate genes including those for body temperatures, egg productivity, and feed intake in RW chickens and those for growth, meat and carcass traits, and feed efficiency in WC chickens. These findings were concordant with the breed origin and history of their artificial selection. We determined a set of 188 prioritized candidate genes retrieved from the 11 overlapped regions of putative selection and reviewed their functions relative to phenotypic traits of interest in the two breeds. One of the RW-specific sweep regions harbored the known domestication gene, TSHR. Gene ontology and functional annotation analysis provided additional insight into a functional coherence of genes in the sweep regions. We also showed a greater candidate gene richness on microchromosomes relative to macrochromosomes in these genomic areas. Our results on the selection history of RW and WC chickens and their key candidate genes under selection serve as a profound information for further conservation of their genomic diversity and efficient breeding.
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Native cattle breeds can carry specific signatures of selection reflecting their adaptation to the local environmental conditions and response to the breeding strategy used. In this study, we comprehensively analysed high-density single nucleotide polymorphism (SNP) genotypes to characterise the population structure and detect the selection signatures in Russian native Yaroslavl and Kholmogor dairy cattle breeds, which have been little influenced by introgression with transboundary breeds. Fifty-six samples of pedigree-recorded purebred animals, originating from different breeding farms and representing different sire lines, of the two studied breeds were genotyped using a genome-wide bovine genotyping array (Bovine HD BeadChip). Three statistical analyses-calculation of fixation index (FST) for each SNP for the comparison of the pairs of breeds, hapFLK analysis, and estimation of the runs of homozygosity (ROH) islands shared in more than 50% of animals-were combined for detecting the selection signatures in the genome of the studied cattle breeds. We confirmed nine and six known regions under putative selection in the genomes of Yaroslavl and Kholmogor cattle, respectively; the flanking positions of most of these regions were elucidated. Only two of the selected regions (localised on BTA 14 at 24.4-25.1 Mbp and on BTA 16 at 42.5-43.5 Mb) overlapped in Yaroslavl, Kholmogor and Holstein breeds. In addition, we detected three novel selection sweeps in the genome of Yaroslavl (BTA 4 at 4.74-5.36 Mbp, BTA 15 at 17.80-18.77 Mbp, and BTA 17 at 45.59-45.61 Mbp) and Kholmogor breeds (BTA 12 at 82.40-81.69 Mbp, BTA 15 at 16.04-16.62 Mbp, and BTA 18 at 0.19-1.46 Mbp) by using at least two of the above-mentioned methods. We expanded the list of candidate genes associated with the selected genomic regions and performed their functional annotation. We discussed the possible involvement of the identified candidate genes in artificial selection in connection with the origin and development of the breeds. Our findings on the Yaroslavl and Kholmogor breeds obtained using high-density SNP genotyping and three different statistical methods allowed the detection of novel putative genomic regions and candidate genes that might be under selection. These results might be useful for the sustainable development and conservation of these two oldest Russian native cattle breeds.
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Bovinos/genética , Polimorfismo de Nucleotídeo Único , Seleção Artificial , Animais , Seleção GenéticaRESUMO
Analysis of ancient and historical DNA has great potential to trace the genetic diversity of local cattle populations during their centuries-long development. Forty-nine specimens representing five cattle breeds (Kholmogor, Yaroslavl, Great Russian, Novgorod, and Holland), dated from the end of the 19th century to the first half of the 20th century, were genotyped for nine polymorphic microsatellite loci. Using a multiple-tube approach, we determined the consensus genotypes of all samples/loci analysed. Amplification errors, including allelic drop-out (ADO) and false alleles (FA), occurred with an average frequency of 2.35% and 0.79%, respectively. A significant effect of allelic length on ADO rate (r2 = 0.620, p = 0.05) was shown. We did not observe significant differences in genetic diversity among historical samples and modern representatives of Kholmogor and Yaroslavl breeds. The unbiased expected heterozygosity values were 0.726-0.774 and 0.708-0.739; the allelic richness values were 2.716-2.893 and 2.661-2.758 for the historical and modern samples, respectively. Analyses of FST and Jost's D genetic distances, and the results of STRUCTURE clustering, showed the maintenance of a part of historical components in the modern populations of Kholmogor and Yaroslavl cattle. Our study contributes to the conservation of biodiversity in the local Russian genetic resources of cattle.