Comparative population genomics analysis for chicken body sizes using genome-wide SNPs.

Objective: This study aims to investigate the selection history, genome regions, and candidate genes associated with different chicken body sizes, thereby providing insights into the genetic basis of complex economic traits such as chicken body size and growth. Methods: In this study, a total of 217 individuals from eight breeds were selected. According to body size, they were divided into two groups: large chickens and bantam chickens, with four breeds in each group. Firstly, we investigate population structure by principal component analysis (PCA), phylogenetic tree, and ancestry component analysis. Next, we recognize runs of homozygosity (ROH) islands through calculating ROH. Finally, we carry out selection signatures analysis utilizing population differentiation index and nucleic acid diversity. Results: The population structure analysis show that large and bantam chickens are clearly separated. Large chickens are clustered together, the bantam chickens are relatively dispersed. The results of ROH island analysis show that 48 and 56 ROH islands were identified in large and bantam chickens respectively. Among the interesting ROH islands, a total of eight candidate genes were identified. In selection signatures analysis, a total of 322 selected genes were annotated in large chickens, such as POU1F1, BMP10, enrichment in 16 GO terms. In bantam chickens, a total of 447 selected genes were annotated, such as IGF1, GRB10, enrichment in 20 GO terms and 2 KEGG pathways. The haplotype analysis results show that GRB10 has differences in chickens of different body sizes. Conclusion: By population structure, ROH islands, and selection signatures analysis, we have identified multiple genes associated with chicken body size, growth, and development (such as BMP10, IGF1, GRB10, etc). This provides a theoretical reference for the subsequent development of molecular markers for chicken body size and the analysis of the genetic mechanism of chicken body size.

RNA-Seq based selection signature analysis for identifying genomic footprints associated with the fat-tail phenotype in sheep.

Understanding the genetic background behind fat-tail development in sheep can be useful to develop breeding programs for genetic improvement, while the genetic basis of fat-tail formation is still not well understood. Here, to identify genomic regions influencing fat-tail size in sheep, a comprehensive selection signature identification analysis was performed through comparison of fat- and thin-tailed sheep breeds. Furthermore, to gain the first insights into the potential use of RNA-Seq for selection signature identification analysis, SNP calling was performed using RNA-Seq datasets. In total, 45 RNA-Seq samples from seven cohort studies were analyzed, and the FST method was used to detect selection signatures. Our findings indicated that RNA-Seq could be of potential utility for selection signature identification analysis. In total, 877 SNPs related to 103 genes were found to be under selection in 92 genomic regions. Functional annotation analysis reinforced the hypothesis that genes involved in fatty acid oxidation May modulate fat accumulation in the tail of sheep and highlighted the potential regulatory role of angiogenesis process in the fat deposition. In agreement with most previous studies, our results re-emphasize that the BMP2 gene is targeted by selection during sheep evolution. Further gene annotation analysis of the regions targeted by the sheep evolution process revealed that a large number of genes included in these regions are directly associated with fat metabolism, including those previously reported as candidates involved in sheep fat-tail morphology, such as NID2, IKBKG, RGMA, IGFBP7, UBR5, VEGFD and WLS. Moreover, a number of genes, including BDH2, ECHS1, AUH, ERBIN and CYP4V2 were of particular interest because they are well-known fat metabolism-associated genes and are considered novel candidates involved in fat-tail size. Consistent with the selection signature identification analysis, principal component analysis clustered the samples into two completely separate groups according to fat- and thin-tailed breeds. Our results provide novel insights into the genomic basis of phenotypic diversity related to the fat-tail of sheep breeds and can be used to determine directions for improving breeding strategies in the future.

Genetic Diversity, Selection Signatures, and Genome-Wide Association Study Identify Candidate Genes Related to Litter Size in Hu Sheep.

Hu sheep is a renowned prolific local sheep breed in China, widely distributed across the country due to its excellent reproductive performance. Deciphering the molecular mechanisms underlying the high fecundity of Hu sheep is crucial for improving the litter size of ewes. In this study, we genotyped 830 female Hu sheep using the Illumina OvineSNP50 BeadChip and performed genetic diversity analysis, selection signature detection, and a genome-wide association study (GWAS) for litter size. Our results revealed that the Hu sheep population exhibits relatively high genetic diversity. A total of 4927 runs of homozygosity (ROH) segments were detected, with the majority (74.73%) being short in length. Different genomic inbreeding coefficients (FROH, FHOM, FGRM, and FUNI) ranged from -0.0060 to 0.0126, showing low levels of inbreeding in this population. Additionally, we identified 91 candidate genomic regions through three complementary selection signature methods, including ROH, composite likelihood ratio (CLR), and integrated haplotype score (iHS), and annotated 189 protein-coding genes. Moreover, we observed two significant SNPs related to the litter size of Hu sheep using GWAS analysis based on a repeatability model. Integrating the selection signatures and the GWAS results, we identified 15 candidate genes associated with litter size, among which BMPR1B and UNC5C were particularly noteworthy. These findings provide valuable insights for improving the reproductive performance and breeding of high-fecundity lines of Hu sheep.

Population structure and selective signature of Kirghiz sheep by Illumina Ovine SNP50 BeadChip.

Objective: By assessing the genetic diversity and associated selective traits of Kirghiz sheep (KIR), we aim to uncover the mechanisms that contribute to sheep's adaptability to the Pamir Plateau environment. Methods: This study utilized Illumina Ovine SNP50 BeadChip data from KIR residing in the Pamir Plateau, Qira Black sheep (QBS) inhabiting the Taklamakan Desert, and commonly introduced breeds including Dorper sheep (DOR), Suffolk sheep (SUF), and Hu sheep (HU). The data was analyzed using principal component analysis, phylogenetic analysis, population admixture analysis, kinship matrix analysis, linkage disequilibrium analysis, and selective signature analysis. We employed four methods for selective signature analysis: fixation index (Fst), cross-population extended homozygosity (XP-EHH), integrated haplotype score (iHS), and nucleotide diversity (Pi). These methods aim to uncover the genetic mechanisms underlying the germplasm resources of Kirghiz sheep, enhance their production traits, and explore their adaptation to challenging environmental conditions. Results: The test results unveiled potential selective signals associated with adaptive traits and growth characteristics in sheep under harsh environmental conditions, and annotated the corresponding genes accordingly. These genes encompass various functionalities such as adaptations associated with plateau, cold, and arid environment (ETAA1, UBE3D, TLE4, NXPH1, MAT2B, PPARGC1A, VEGFA, TBX15 and PLXNA4), wool traits (LMO3, TRPS1, EPHA5), body size traits (PLXNA2, EFNA5), reproductive traits (PPP3CA, PDHA2, NTRK2), and immunity (GATA3). Conclusion: Our study identified candidate genes associated with the production traits and adaptation to the harsh environment of the Pamir Plateau in Kirghiz sheep. These findings provide valuable resources for local sheep breeding programs. The objective of this study is to offer valuable insights for the sustainable development of the Kirghiz sheep industry.

SNP Markers: Analysis of Genetic Diversity and Identification of Genomic Regions in Pantaneiro Sheep and Texel Sheep Under Natural Selection.

BACKGROUND: Sheep farming is growing substantially in Brazil, driven by the increasing demand for sheep meat. This rising demand has heightened the focus on sheep, making them the subject of numerous studies, including those centered on genetic analysis. A notable research area involves Pantaneiro sheep, which are indigenous to the Pantanal region of Mato Grosso do Sul and other locations. These sheep are of particular interest due to their adaptation to the unique environmental conditions of the Pantanal, a floodplain characterized by its distinctive climatic and ecological features. This study primarily aimed to conduct a comprehensive genomic analysis of Pantanal sheep subjected to natural selection within the Pantanal region and compare different sample herds using methodological approaches. METHODS: Genomic analysis was performed to examine genetic diversity and structure via GGP50K single nucleotide polymorphism (SNP) analysis. A sample of 192 adult sheep over 4 years old was categorized into seven populations based on location: Six populations comprised Pantaneiro sheep with one Texel sheep population. Outlier SNPs were assessed to pinpoint regions under natural selection, with comparisons between the Pantaneiro and the commercial Texel breeds. All data analyses were conducted using the R programming language, employing specialized genetic analysis packages. These outlier SNPs were detected using three methodologies, PCAdapt, OutFLANK, and FDIST2/fsthet, with false discovery rate (FDR) corrections applied to ensure result accuracy. Each method was evaluated, and the genes associated with the identified SNPs were cross-referenced with the most recent sheep genome database, focusing specifically on genes with known phenotypic traits. RESULTS: Analysis of a sample comprising 192 adult individuals revealed greater genetic variability within the Pantaneiro breed than the Texel breed, highlighting the adaptation of the Pantaneiro breed to the unique Pantanal environment. Conversely, the Texel breed exhibited significantly higher levels of inbreeding, attributed to its controlled breeding practices. Outlier SNPs were detected with notable variation across different methodologies, underscoring the importance of FDR correction in ensuring the reliability and concentration of identified outliers. These outlier SNPs facilitated the identification of genes associated with key phenotypic traits, including hair growth, tissue regeneration, pigmentation regulation, and muscle capacity. CONCLUSION: The integrated analysis of methodologies demonstrated significant efficiency in elucidating the genomic landscape of Pantanal sheep, highlighting the genetic richness inherent in sheep from the Pantanal region of Mato Grosso do Sul. The techniques employed effectively identified outlier SNPs associated with phenotypically relevant genes. These findings, which reveal greater genetic variability and adaptability, underscore the potential of these animals for future research and their significance within Brazilian sheep farming. The Texel breed served as a valuable comparative group, illustrating the limited genetic variability in highly controlled breeding environments.

Whole-Genome Resequencing Reveals Signatures of Adaptive Evolution in Acanthopagrus latus and Rhabdosargus sarba.

Acanthopagrus latus and Rhabdosargus sarba are economically important marine species along the coast of China, with similar external morphological characteristics and living habits, with wide distribution and strong adaptability. To investigate the molecular mechanisms underlying the adaptive evolution of these two species, we conducted whole-genome resequencing of 10 individuals of both species from the coastal waters of Wuyu Island, Fujian, China, using high-throughput sequencing technology. We obtained SNP, InDel, CNV, and SV variation information and annotated these variations, constructing a genomic variation database for both species. By comparing the resequencing data with reference genomes, we identified 9,829,511 SNP loci in the population of A. latus and 34,051,056 SNP loci in the population of R. sarba. Using whole-genome SNP data, we employed Fst and ROD methods to identify candidate genomic regions under selection. Functional annotation and enrichment analysis using GO and KEGG databases revealed potential adaptive evolution in R. sarba associated with immune response, feeding, growth and development, and locomotion, while A. latus showed potential adaptive evolution associated with immune response, nervous system, growth and development, and metabolism.

Genome-Wide Analysis of Genetic Diversity and Selection Signatures in Zaobei Beef Cattle.

This investigation provides a comprehensive analysis of genomic diversity and selection signatures in Zaobei beef cattle, an indigenous breed known for its adaptation to hot and humid climates and superior meat quality. Whole-genome resequencing was conducted on 23 Zaobei cattle, compared with 46 Simmental cattle to highlight genetic distinctions. Population structure analysis confirmed the genetic uniqueness of Zaobei cattle. Using methods such as DASDC v1.01, XPEHH, and θπ ratio, we identified 230, 232, and 221 genes through DASDC, including hard sweeps, soft sweeps, and linkage sweeps, respectively. Coincidentally, 109 genes were identified when using XPEHH and θπ ratio methods. Together, these analyses revealed eight positive selection genes (ARHGAP15, ZNF618, USH2A, PDZRN4, SPATA6, ROR2, KCNIP3, and VWA3B), which are linked to critical traits such as heat stress adaptation, fertility, and meat quality. Moreover, functional enrichment analyses showed pathways related to autophagy, immune response, energy metabolism, and muscle development. The comprehensive genomic insights gained from this study provide valuable knowledge for breeding programs aimed at enhancing the beneficial traits in Zaobei cattle.

Global and Local Ancestry and its Importance: A Review.

The fastest way to significantly change the composition of a population is through admixture, an evolutionary mechanism. In animal breeding history, genetic admixture has provided both short-term and long-term advantages by utilizing the phenomenon of complementarity and heterosis in several traits and genetic diversity, respectively. The traditional method of admixture analysis by pedigree records has now been replaced greatly by genome-wide marker data that enables more precise estimations. Among these markers, SNPs have been the popular choice since they are cost-effective, not so laborious, and automation of genotyping is easy. Certain markers can suggest the possibility of a population's origin from a sample of DNA where the source individual is unknown or unwilling to disclose their lineage, which are called Ancestry-Informative Markers (AIMs). Revealing admixture level at the locus-specific level is termed as local ancestry and can be exploited to identify signs of recent selective response and can account for genetic drift. Considering the importance of genetic admixture and local ancestry, in this mini-review, both concepts are illustrated, encompassing basics, their estimation/identification methods, tools/software used and their applications.

Identifying selection signatures for immune response and resilience to Aleutian disease in mink using genotype data.

Aleutian disease (AD) brings tremendous financial losses to the mink industry. Selecting AD-resilient mink has been conducted to control AD. Such selections could have altered the patterns of genetic variation responding to selection pressures. This study aimed to identify selection signatures for immune response (IRE) and resilience to AD. A total of 1,411 mink from an AD-positive facility were used. For IRE, 264 animals were categorized according to the combined results of enzyme-linked immunosorbent assay (ELISA) and counterimmunoelectrophoresis (CIEP). For resilience, two grouping methods were used: 1) general resilience performance (GRP, n = 30) was evaluated based on the feed conversion ratio, Kleiber ratio, and pelt quality; and 2) female reproductive performance (FRP, n = 36) was measured based on the number of kits alive 24 h after birth. Detection methods were the pairwise fixation index, nucleotide diversity, and cross-population extended haplotype homozygosity. A total of 619, 569, and 526 SNPs were identified as candidates for IRE, GRP, and FRP, respectively. The annotated genes were involved in immune system process, growth, reproduction, and pigmentation. Two olfactory-related Gene Ontology (GO) terms were significant (q < 0.05) for all traits, suggesting the impact of AD on the sense of smell of infected mink. Differences in detected genes and GO terms among different color types for IRE indicated variations in immune response to AD among color types. The mitogen-activated protein kinase (MAPK) signaling pathway was significant (q < 0.05) for FRP, suggesting that AD may disrupt MAPK signaling and affect FRP. The findings of this research contribute to our knowledge of the genomic architecture and biological mechanisms underlying AD resilience in mink.

Scans for Signatures of Selection in Genomes of Wagyu and Buryat Cattle Breeds Reveal Candidate Genes and Genetic Variants for Adaptive Phenotypes and Production Traits.

Past and ongoing selection shapes the genomes of livestock breeds. Identifying such signatures of selection allows for uncovering the genetic bases of affected phenotypes, including economically important traits and environmental adaptations, for the further improvement of breed genetics to respond to climate and economic challenges. Turano-Mongolian cattle are a group of taurine breeds known for their adaptation to extreme environmental conditions and outstanding production performance. Buryat Turano-Mongolian cattle are among the few breeds adapted to cold climates and poor forage. Wagyu, on the other hand, is famous for high productivity and unique top-quality marbled meat. We used hapFLK, the de-correlated composite of multiple signals (DCMS), PBS, and FST methods to search for signatures of selection in their genomes. The scans revealed signals in genes related to cold adaptation (e.g., STAT3, DOCK5, GSTM3, and CXCL8) and food digestibility (SI) in the Buryat breed, and growth and development traits (e.g., RBFOX2 and SHOX2) and marbling (e.g., DGAT1, IQGAP2, RSRC1, and DIP2B) in Wagyu. Several putatively selected genes associated with reproduction, immunity, and resistance to pathogens were found in both breed genomes. The results of our work could be used for creating new productive adapted breeds or improving the extant breeds.

Genome-wide analysis reveals genomic diversity and signatures of selection in Qinchuan beef cattle.

BACKGROUND: Indigenous Chinese cattle have abundant genetic diversity and a long history of artificial selection, giving local breeds advantages in adaptability, forage tolerance and resistance. The detection of selective sweeps and comparative genome analysis of selected breeds and ancestral populations provide a basis for understanding differences among breeds and for the identification and utilization of candidate genes. We investigated genetic diversity, population structure, and signatures of selection using genome-wide sequencing data for a new breed of Qinchuan cattle (QNC, n = 21), ancestral Qinchuan cattle (QCC, n = 20), and Zaosheng cattle (ZSC, n = 19). RESULTS: A population structure analysis showed that the ancestry components of QNC and ZSC were similar. In addition, the QNC and ZSC groups showed higher proportions of European taurine ancestry than that of QCC, and this may explain the larger body size of QNC, approaching that of European cattle under long-term domestication and selection. A neighbor-joining tree revealed that QCC individuals were closely related, whereas QNC formed a distinct group. To search for signatures of selection in the QNC genome, we evaluated nucleotide diversity (θπ), the fixation index (FST) and Tajima's D. Overlapping selective sweeps were enriched for one KEGG pathway, the apelin signaling pathway, and included five candidate genes (MEF2A, SMAD2, CAMK4, RPS6, and PIK3CG). We performed a comprehensive review of genomic variants in QNC, QCC, and ZSC using whole-genome sequencing data. QCC was rich in novel genetic diversity, while diversity in QNC and ZSC cattle was reduced due to strong artificial selection, with divergence from the original cattle. CONCLUSIONS: We identified candidate genes associated with production traits. These results support the success of selective breeding and can guide further breeding and resource conservation of Qinchuan cattle.

Genome-wide comparative analysis reveals selection signatures for reproduction traits in prolific Suffolk sheep.

The identification of genome-wide selection signatures can reveal the potential genetic mechanisms involved in the generation of new breeds through natural or artificial selection. In this study, we screened the genome-wide selection signatures of prolific Suffolk sheep, a new strain of multiparous mutton sheep, to identify candidate genes for reproduction traits and unravel the germplasm characteristics and population genetic evolution of this new strain of Suffolk sheep. Whole-genome resequencing was performed at an effective sequencing depth of 20× for genomic diversity and population structure analysis. Additionally, selection signatures were investigated in prolific Suffolk sheep, Suffolk sheep, and Hu sheep using fixation index (F ST) and heterozygosity H) analysis. A total of 5,236.338 Gb of high-quality genomic data and 28,767,952 SNPs were obtained for prolific Suffolk sheep. Moreover, 99 selection signals spanning candidate genes were identified. Twenty-three genes were significantly associated with KEGG pathway and Gene Ontology terms related to reproduction, growth, immunity, and metabolism. Through selective signal analysis, genes such as ARHGEF4, CATIP, and CCDC115 were found to be significantly correlated with reproductive traits in prolific Suffolk sheep and were highly associated with the mTOR signaling pathway, the melanogenic pathway, and the Hippo signaling pathways, among others. These results contribute to the understanding of the evolution of artificial selection in prolific Suffolk sheep and provide candidate reproduction-related genes that may be beneficial for the establishment of new sheep breeds.

Identification of Copy Number Variations and Selection Signatures in Wannan Spotted Pigs by Whole Genome Sequencing Data: A Preliminary Study.

Copy number variation (CNV) is an important structural variation used to elucidate complex economic traits. In this study, we sequenced 25 Wannan spotted pigs (WSPs) to detect their CNVs and identify their selection signatures compared with those of 10 Asian wild boars. A total of 14,161 CNVs were detected in the WSPs, accounting for 0.72% of the porcine genome. The fixation index (Fst) was used to identify the selection signatures, and 195 CNVs with the top 1% of the Fst value were selected. Eighty genes were identified in the selected CNV regions. Functional GO and KEGG analyses revealed that the genes within these selected CNVs are associated with key traits such as reproduction (GAL3ST1 and SETD2), fatty acid composition (PRKG1, ACACA, ACSL3, UGT8), immune system (LYZ), ear size (WIF1), and feed efficiency (VIPR2). The findings of this study contribute novel insights into the genetic CNVs underlying WSP characteristics and provide essential information for the protection and utilization of WSP populations.

Genome-wide scans for selection signatures in indigenous chickens reveal candidate genes associated with local adaptation.

Population growth and climate change pose challenges to the sustainability of poultry farming. The emphasis on high-yield traits in commercialized breeds has led to a decline in their adaptability. Chicken varieties adapted to the local environment, possessing traits that facilitate adaptation to climate change, such as disease resistance and tolerance to extreme weather conditions, can improve hybridization outcomes. In this study, we conducted an analysis of the population structure and genetic diversity of 110 chickens representing indigenous breeds from southern China and two different commercial breeds. Further, we performed comparative population genomics, utilizing nucleotide diversity and fixation statistics, to characterize genomic features of natural selection and to identify unique genetic traits and potential selection markers developed by indigenous breeds after adapting to the local environment. Results based on genetic diversity and population structure analyses showed that indigenous varieties exhibited high levels of genetic diversity. Commercial breeds that have been indigenously bred demonstrated higher levels of genetic diversity than those that have not, and breeds with different selection practices displayed significant differences in genetic structure. Additionally, we further searched for potential genomic regions in native chicken ecotypes, uncovering several candidate genes related to ecological adaptations affecting local breeds, such as IKBKB, S1PR1, TSHR, IL1RAPL1 and AMY2A, which are involved in disease resistance, heat tolerance, immune regulation and behavioral traits. This work provides important insights into the genomic characterization of ecotypes of native chicken in southern China. The identification of candidate genes associated with traits such as disease resistance, heat tolerance, immunomodulation, and behavioral traits is a significant outcome. These candidate genes may contribute to the understanding of the molecular basis of the adaptation of the southern native chicken to the local environment. It is recommended that these genes be integrated into chicken breeding programs to enhance sustainable agriculture and promote effective conservation and utilization strategies.

Comparative whole-genome resequencing to uncover selection signatures linked to litter size in Hu Sheep and five other breeds.

Hu sheep (HS), a breed of sheep carrying the FecB mutation gene, is known for its "year-round estrus and multiple births" and is an ideal model for studying the high fecundity mechanisms of livestock. Through analyzing and comparing the genomic selection features of Hu sheep and other sheep breeds, we identified a series of candidate genes that may play a role in Hu sheep's high fecundity mechanisms. In this study, we conducted whole-genome resequencing on six breeds and screened key mutations significantly correlated with high reproductive traits in sheep. Notably, the CC2D1B gene was selected by the fixation index (FST) and the cross-population composite likelihood ratio (XP-CLR) methods in HS and other five breeds. It was worth noting that the CC2D1B gene in HS was different from that in other sheep breeds, and seven missense mutations have been identified. Furthermore, the linkage disequilibrium (LD) analysis revealed a strong linkage disequilibrium in this specific gene region. Subsequently, by performing different grouping based on FecB genotypes in Hu sheep, genome-wide selective signal analysis screened several genes related to reproduction, such as BMPR1B and PPM1K. Besides, FST analysis identified functional genes related to reproductive traits, including RHEB, HSPA2, PPP1CC, HVCN1, and CCDC63. Additionally, a missense mutation was found in the CCDC63 gene and the haplotype was different between the high reproduction (HR) group and low reproduction (LR) group in HS. In summary, we discovered genetic differentiation among six distinct breeding sheep breeds at the whole genome level. Additionally, we identified a set of genes which were associated with reproductive performance in Hu sheep and visualized how these genes differed in different breeds. These findings laid a theoretical foundation for understanding genetic mechanisms behind high prolific traits in sheep.

Selective sweep analysis of the adaptability of the Yarkand hare (Lepus yarkandensis) to hot arid environments using SLAF-seq.

The Yarkand hare (Lepus yarkandensis) inhabits arid desert areas and is endemic to China. It has evolved various adaptations to survive in hot arid environments, including stress responses, the ability to maintain water homeostasis and heat tolerance. Here, we performed a selective sweep analysis to identify the candidate genes for adaptation to hot arid environments in the Yarkand hare. A total of 397 237 single-nucleotide polymorphisms were obtained from 80 Yarkand hares, which inhabit hot arid environments, and 36 Tolai hares (Lepus tolai), which inhabit environments with a mild climate, via specific-locus amplified fragment sequencing. We identified several candidate genes that were associated with the heat stress response (HSPE1), oxidative stress response (SLC23A and GLRX2), immune response (IL1R1 and IRG1), central nervous system development (FGF13, THOC2, FMR1 and MECP2) and regulation of water homeostasis (CDK1) according to fixation index values and θπ ratios in the selective sweep analysis, and six of these genes (GLRX2, IRG1, FGF13, FMR1, MECP2 and CDK1) are newly discovered genes. To the best of our knowledge, this is the first study to identify candidate genes for adaptation to hot arid environments in the Yarkand hare. The results of this study enhance our understanding of the adaptation of the Yarkand hare to hot arid environments and will aid future studies aiming to functionally verify these candidate genes.

Whole-genome selection signature differences between Chaohu and Ji'an red ducks.

Assessing the genetic structure of local varieties and understanding their genetic data are crucial for effective management and preservation. However, the genetic differences among local breeds require further explanation. To enhance our understanding of their population structure and genetic diversity, we conducted a genome-wide comparative study of Chaohu and Ji'an Red ducks using genome sequence and restriction site-associated DNA sequencing technology. Our analysis revealed a distinct genetic distinction between the two breeds, leading to divided groups. The phylogenetic tree for Chaohu duck displayed two branches, potentially indicating minimal impact from artificial selection. Additionally, our ROH (runs of homozygosity) analysis revealed that Chaohu ducks had a lower average inbreeding coefficient than Ji'an Red ducks. We identified several genomic regions with high genetic similarity in these indigenous duck breeds. By conducting a selective sweep analysis, we identified 574 candidate genes associated with muscle growth (BMP2, ITGA8, MYLK, and PTCH1), fat deposits (ELOVL1 and HACD2), and pigmentation (ASIP and LOC101797494). These results offer valuable insights for the further enhancement and conservation of Chinese indigenous duck breeds.

Genomic Inbreeding and Runs of Homozygosity Analysis of Cashmere Goat.

Cashmere goats are valuable genetic resources which are famous worldwide for their high-quality fiber. Runs of homozygosity (ROHs) have been identified as an efficient tool to assess inbreeding level and identify related genes under selection. However, there is limited research on ROHs in cashmere goats. Therefore, we investigated the ROH pattern, assessed genomic inbreeding levels and examined the candidate genes associated with the cashmere trait using whole-genome resequencing data from 123 goats. Herein, the Inner Mongolia cashmere goat presented the lowest inbreeding coefficient of 0.0263. In total, we identified 57,224 ROHs. Seventy-four ROH islands containing 50 genes were detected. Certain identified genes were related to meat, fiber and milk production (FGF1, PTPRM, RERE, GRID2, RARA); fertility (BIRC6, ECE2, CDH23, PAK1); disease or cold resistance and adaptability (PDCD1LG2, SVIL, PRDM16, RFX4, SH3BP2); and body size and growth (TMEM63C, SYN3, SDC1, STRBP, SMG6). 135 consensus ROHs were identified, and we found candidate genes (FGF5, DVL3, NRAS, KIT) were associated with fiber length or color. These findings enhance our comprehension of inbreeding levels in cashmere goats and the genetic foundations of traits influenced by selective breeding. This research contributes significantly to the future breeding, reservation and use of cashmere goats and other goat breeds.

Dissecting Selective Signatures and Candidate Genes in Grandparent Lines Subject to High Selection Pressure for Broiler Production and in a Local Russian Chicken Breed of Ushanka.

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.