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Background Domestication and centuries of selective breeding have changed genomes of sheep breeds to respond to environmental challenges and human needs. The genomes of local breeds, therefore, are valuable sources of genomic variants to be used to understand mechanisms of response to adaptation and artificial selection. As a step toward this we performed a high-density genotyping and comprehensive scans for signatures of selection in the genomes from 15 local sheep breeds reared across Russia. Results Results demonstrated that the genomes of Russian sheep breeds contain multiple regions under putative selection. More than 50% of these regions matched with intervals identified in previous scans for selective sweeps in sheep genomes. These regions contain well-known candidate genes related to morphology, adaptation, and domestication (e.g., KITLG, KIT, MITF, and MC1R ), wool quality and quantity (e.g., DSG@ , DSC@ , and KRT@ ), growth and feed intake (e.g., HOXA@, HOXC@, LCORL, NCAPG, LAP3, and CCSER1 ), reproduction (e.g., CMTM6, HTRA1, GNAQ, UBQLN1, and IFT88 ), and milk-related traits (e.g., ABCG2, SPP1, ACSS1, and ACSS2 ). In addition, multiple genes that are putatively related to environmental adaptations were top-ranked in selected intervals (e.g., EGFR, HSPH1, NMUR1 , EDNRB , PRL, TSHR, and ADAMTS5 ). Moreover, we observed that multiple key genes involved in human hereditary sensory and autonomic neuropathies, and genetic disorders accompanied with an inability to feel pain and environmental temperatures, were top-ranked in multiple or individual sheep breeds from Russia pointing to a possible mechanism of adaptation to harsh climatic conditions. Conclusions Our work represents the first comprehensive scan for signatures of selection in genomes of local sheep breeds from the Russian Federation of both European and Asian origins. We confirmed that the genomes of Russian sheep contain previously identified signatures of selection, demonstrating the robustness of our integrative approach. Multiple novel signatures of selection were found near genes which could be related to adaptation to the harsh environments of Russia. Our study forms a basis for future work on using Russian sheep genomes to spot specific genetic variants or haplotypes to be used in efforts on developing next-generation highly productive breeds, better suited to diverse Eurasian environments.

Background Russia has a diverse variety of native and locally developed sheep breeds with coarse, fine, and semi-fine wool, which inhabit different climate zones and landscapes that range from hot deserts to harsh northern areas. To date, no genome-wide information has been used to investigate the history and genetic characteristics of the extant local Russian sheep populations. To infer the population structure and genome-wide diversity of Russian sheep, 25 local breeds were genotyped with the OvineSNP50 BeadChip. Furthermore, to evaluate admixture contributions from foreign breeds in Russian sheep, a set of 58 worldwide breeds from publicly available genotypes was added to our data. Results We recorded similar observed heterozygosity (0.354–0.395) and allelic richness (1.890–1.955) levels across the analyzed breeds and they are comparable with those observed in the worldwide breeds. Recent effective population sizes estimated from linkage disequilibrium five generations ago ranged from 65 to 543. Multi-dimensional scaling, admixture, and neighbor-net analyses consistently identified a two-step subdivision of the Russian local sheep breeds. A first split clustered the Russian sheep populations according to their wool type (fine wool, semi-fine wool and coarse wool). The Dagestan Mountain and Baikal fine-fleeced breeds differ from the other Merino-derived local breeds. The semi-fine wool cluster combined a breed of Romanian origin, Tsigai, with its derivative Altai Mountain, the two Romney-introgressed breeds Kuibyshev and North Caucasian, and the Lincoln-introgressed Russian longhaired breed. The coarse-wool group comprised the Nordic short-tailed Romanov, the long-fat-tailed outlier Kuchugur and two clusters of fat-tailed sheep: the Caucasian Mountain breeds and the Buubei, Karakul, Edilbai, Kalmyk and Tuva breeds. The Russian fat-tailed breeds shared co-ancestry with sheep from China and Southwestern Asia (Iran). Conclusions In this study, we derived the genetic characteristics of the major Russian local sheep breeds, which are moderately diverse and have a strong population structure. Pooling our data with a worldwide genotyping set gave deeper insight into the history and origin of the Russian sheep populations.

Indigenous pig breeds are mainly associated with the adaptive capacity that is necessary to respond adequately to climate change, food security, and livelihood needs, and natural resources conservation. Livni pigs are an indigenous fat-type breed farmed in a single farm in the Orel region and located in the Central European part of the Russian Federation. To determine the genomic regions and genes that are affected by artificial selection, we conducted the comparative study of two pig breeds with different breeding histories and breeding objectives, i.e., the native fat-type Livni and meat-type Duroc breeds using the Porcine GGP HD BeadChip, which contains ~80,000 SNPs. To check the Livni pigs for possible admixture, the Landrace and the Large White breeds were included into the study of genetic diversity as these breeds participated in the formation of the Livni pigs. We observed the highest level of genetic diversity in Livni pigs compared to commercial breeds (UHE = 0.409 vs. 0.319–0.359, p < 0.001; AR = 1.995 vs. 1.894–1.964, p < 0.001). A slight excess of heterozygotes was found in all of the breeds. We identified 291 candidate genes, which were localized within the regions under putative selection, including 22 and 228 genes, which were specific for Livni and Duroc breeds, respectively, and 41 genes common for both breeds. A detailed analysis of the molecular functions identified the genes, which were related to the formation of meat and fat traits, and adaptation to environmental stress, including extreme temperatures, which were different between breeds. Our research results are useful for conservation and sustainable breeding of Livni breed, which shows a high level of genetic diversity. This makes Livni one of the valuable national pig genetic resources.

Avian eggs are products of consumer demand, with modern methodologies for their morphometric analysis used for improving quality, productivity and marketability. Such studies open up numerous prospects for the introduction of artificial intelligence (AI) and deep learning (DL). We first consider the state of the art of DL in the poultry industry, e.g., image recognition and applications for the detection of egg cracks, egg content and freshness. We comment on how algorithms need to be properly trained and ask what information can be gleaned from egg shape. Considering the geometry of egg profiles, we revisit the Preston–Biggins egg model, the Hügelschäffer’s model, universal egg models, principles of egg universalism and “The Main Axiom”, proposing a series of postulates to evaluate the legitimacy and practical application of various mathematical models. We stress that different models have pros and cons, and using them in combination may yield more useful results than individual use. We consider the classic egg shape index alongside other alternatives, drawing conclusions about the importance of indices in the context of applying DL going forward. Examining egg weight, volume, surface area and air cell calculations, we consider how DL might be applied, e.g., for egg storage. The value of DL in egg studies is in pre-incubation egg sorting, the optimization of storage periods and incubation regimes, and the index representation of dimensional characteristics. Each index can thus be combined to provide a synergy that is on the threshold of many scientific discoveries, technological achievements and industrial successes facilitated through AI and DL.

Sheep farming has been an important sector of the UK’s economy and rural life for many centuries. It is the favored source of wool, meat and milk products. In the era of exponential progress in genomic technologies, we can now address the questions of what is special about UK sheep breed genotypes and how they differ genetically form one another and from other countries. We can reflect how their natural history has been determined at the level of their genetic code and what traces have been left in their genomes because of selection for phenotypic traits. These include adaptability to certain environmental conditions and management, as well as resistance to disease. Application of these advancements in genetics and genomics to study sheep breeds of British domestic selection has begun and will continue in order to facilitate conservation solutions and production improvement.

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.

Egg components, including weight of yolk, albumen, and eggshell, are economically important traits in poultry breeding and production, and we thus conducted a genome-wide association study (GWAS) for them. We used an F2 resource population of hens (n = 142) in different periods of laying, obtained by crossing breeds with contrasting phenotypes, and then genotyped them using the Illumina Chicken 60K iSelect BeadChip. Significant associations were found between 33 single nucleotide polymorphisms (SNPs) and yolk weight at 18–28 weeks of age (YW1). Eighty-seven SNPs were associated with thick albumen weight at 18–28 (TAW1) and 29–42 (TAW2) weeks of age. Four SNPs were associated with eggshell weight at 18–28 weeks of age (ESW1). Fifty-three candidate genes were identified in the positions of these SNPs, and seven prioritized candidate genes (PGCs) were revealed in regions where 2–4 SNPs associated with the studied traits were localized. These were as follows: SYTL5 (YW1, TAW1), FRY (TAW1), GABRG3 (YW1, TAW1), ALDH1A3 (YW1), VCL (YW1), HYDIN (YW1), and TIMP4 (TAW1). Allelic variants at the ALDH1A3, VCL, HYDIN, FRY, and TIMP4 loci were associated with higher YW1 and TAW1. These SNPs and PGCs are potential genetic markers for characterizing egg weight parameters and their components in chicken breeding to achieve egg production improvements.

Background The origin of native and locally developed Russian cattle breeds is linked to the historical, social, cultural, and climatic features of the diverse geographical regions of Russia. In the present study, we investigated the population structure of nine Russian cattle breeds and their relations to the cattle breeds from around the world to elucidate their origin. Genotyping of single nucleotide polymorphisms (SNPs) in Bestuzhev (n = 26), Russian Black-and-White (n = 21), Kalmyk (n = 14), Kholmogor (n = 25), Kostromsky (n = 20), Red Gorbatov (n = 23), Suksun (n = 20), Yakut (n = 25), and Yaroslavl cattle breeds (n = 21) was done using the Bovine SNP50 BeadChip. SNP profiles from an additional 70 breeds were included in the analysis as references. Results The observed heterozygosity levels were quite similar in eight of the nine studied breeds (H O  = 0.337–0.363) except for Yakut (Ho = 0.279). The inbreeding coefficients F IS ranged from -0.028 for Kalmyk to 0.036 for Russian Black-and-White and were comparable to those of the European breeds. The nine studied Russian breeds exhibited taurine ancestry along the C1 axis of the multidimensional scaling (MDS)-plot, but Yakut was clearly separated from the European taurine breeds on the C2 axis. Neighbor-Net and admixture analyses, discriminated three groups among the studied Russian breeds. Yakut and Kalmyk were assigned to a separate group because of their Turano-Mongolian origin. Russian Black-and-White, Kostromsky and Suksun showed transboundary European ancestry, which originated from the Holstein, Brown Swiss, and Danish Red breeds, respectively. The lowest level of introgression of transboundary breeds was recorded for the Kholmogor, Yaroslavl, Red Gorbatov and Bestuzhev breeds, which can be considered as an authentic genetic resource. Conclusions Whole-genome SNP analysis revealed that Russian native and locally developed breeds have conserved authentic genetic patterns in spite of the considerable influence of Eurasian taurine cattle. In this paper, we provide fundamental genomic information that will contribute to the development of more accurate breed conservation programs and genetic improvement strategies.

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) F ST 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.

The aim of the current study was to assess the female metabolic rate and test the hypothesis that there is a relationship between the egg productivity of Japanese quails from eight breeds and their morphometric, or growth, parameters. Parameters measured were body weight (B), volume (V), and surface area (S), as well as the metabolism level expressed by the ratio S/V. The collected egg performance traits were as follows: the number of eggs produced (N), the average egg weight (W), and the total egg mass (M) (i.e., N multiplied by W). To measure the S and V values, a novel technique was developed that takes into account the similarity of the quail’s body to an ellipsoid. An analysis of the relationships between productivity indicators allowed us to introduce a new index called the metabolic index, B·S/V, based on all three main growth parameters in quails. Using the values of this index, we were then able to judge indirectly the level of quails’ egg productivity. We went on to assess the N, W, and M values, not only depending on the size of the bird’s growth parameters but also according to the degree of their changes during quail growth. These changes were expressed as the slope angles of trend lines describing the growth process data. This approach produced more accurate results for predicting the egg productivity in terms of W and M.