Landmarks in the history of selective sweeps

Intraspecific variation and functional study of VERL polymorphism in Pacific abalone (Haliotis discus hannai Ino) and giant abalone (H. gigantea Gmelin)

Sperm and eggs have interacting proteins on their surfaces that affect their compatibility during fertilization. These gamete recognition proteins (GRPs) are typically polymorphic within species, resulting in variations in gamete affinity. This study presents the full-length sequence of VERL, an egg vitelline envelope receptor for sperm lysin, in Pacific abalone (Haliotis discus hannai Ino) and giant abalone (Haliotis gigantea Gmelin). The full-length VERL cDNA sequence in Pacific abalone (11,373 bp) encodes 3790 amino acids, most of which are organized into 21 tandem repeats. In giant abalone, the VERL spans 9405 bp and encodes 3134 amino acids, including 17 tandem repeats. By resolving the nucleotide polymorphisms from resequencing data into haplotypes, high allelic diversity was found in VERL domain repeats 1-2 in both species. Further analysis of intraspecific variation in this region revealed that the alleles of VERL repeats 1-2 in Pacific abalone clustered into two clades, yet no significant divergence was observed among the three Pacific abalone geographic populations. In contrast, alleles in giant abalone were subdivided into two distinct branches, separated by a maximum of 12 amino acid substitutions. Notably, this study provides the first evidence of assortative mating between male and female gametes based on VERL genotypes in giant abalone. Overall, this study revealed the amino acid polymorphism of VERL in two abalone species and its functional effects on fertilization potential. These findings provide a foundation for future research on gamete recognition mechanisms and support selective breeding strategies to enhance abalone reproductive efficiency.

Genome-wide insights into selection signatures for transcription factor binding sites in cattle ROH regions

Runs of Homozygosity (ROH) regions are characterized by homozygous genotypes inherited from a common ancestor, often arising from positive selection for adaptive traits. These homozygous regions may arise due to inbreeding, selective breeding, or demographic events like population bottlenecks. Transcription factor binding sites (TFBS) are short, specific DNA sequences where transcription factors bind to regulate the expression of nearby genes. These sites are essential for controlling biological processes such as development, metabolism, and immune response. TFBS act as key regulatory elements, and their variations can influence gene activity, contributing to phenotypic differences and adaptation. ROH often encompass regulatory elements, including TFBS, suggesting a functional connection between these genomic features. This study investigates TFBS within ROH regions in 297 animals of six cattle breeds: Gir (48), Tharparkar (72), Vrindavani (72), Frieswal (14), Holstein Friesian (63), and Jersey (28). Utilizing genotyped data of these animals, we identified genomic regions enriched with ROH. We focused on the central 10 kb regions of 50 ROH regions common across all breeds. Within these regions, 450 motifs were examined, identifying 168 transcription factors potentially binding to these regions. The results emphasize the role of TFBS in gene regulation and adaptive processes. By linking ROH patterns to regulatory elements, this study enhances our understanding of the genetic architecture underlying phenotypic traits and their adaptation to environmental pressures. These findings provide insights into the molecular mechanisms influencing genetic variation in cattle populations.

Genetic diversity and selection signatures in sheep breeds

Natural and artificial selection in domesticated animals can cause specific changes in genomic regions known as selection signatures. Our study used the integrated haplotype score (iHS) and Tajima's D tests within non-overlapping windows of 100 kb to identify selection signatures, in addition to genetic diversity and linkage disequilibrium estimates in 9498 sheep from breeds in Ireland (Belclare, Charollais, Suffolk, Texel, and Vendeen). The mean observed and expected heterozygosity for all the sheep breeds were 0.353 and 0.355, respectively. Suffolk had the least genetic variation and, along with Texel, had slower linkage disequilibrium decay. iHS and Tajima's D detected selection signatures for all breeds, with some regions overlapping, thus forming longer segments of selection signatures. Common selection signatures were identified across iHS and Tajima's D methods for all breeds, with Belclare and Texel having several common regions under positive selection. Several genes were detected within the selection signature regions, including ITGA4, TLR3, and TGFB2 related to the immune system against endoparasites; DLG1, ROBO2, MXI1, MTMR2, CEP57, and FAM78B related to reproductive traits; WDR70 related to milk traits; SCHM1 and MYH15 related to meat traits; and TAS2R4, TAS2R39, and TAS2R40 related to adaptive traits. In conclusion, our results demonstrated moderate genetic diversity in the sheep breeds and detected and characterized selection signatures harboring genes associated with reproductive traits, milk production, meat production, and adaptive traits such as endoparasite resistance.

Deciphering the Population Characteristics of Leiqiong Cattle Using Whole-Genome Sequencing Data

Long-term geographic isolation and breeding programs both influence population characteristics. Leiqiong cattle, a native breed from the southernmost region of China, are renowned for disease and heat resistance, with two subgroups on Hainan Island and the Leizhou Peninsula. However, the genomic differences between them remain unexplored. In this study, we conducted genomic comparisons using whole-genome sequencing data from the two subgroups of Leiqiong cattle and three commercial breeds to assess their population structures. Leiqiong cattle in Hainan exhibited lower genetic diversity and a pure ancestral content due to their isolation from the mainland. In contrast, the subgroup in Guangdong displayed higher genetic diversity and mixed ancestry, influenced by the intrusion of commercial breeds. The genetic divergence between them was evaluated by estimating a genetic distance of 0.08 and a split time of 3400 to 4250 years ago, highlighting the role of geographical barriers in speciation. Notably, two candidate genes were identified through selection sweeps, including PIP4K2A, potentially related to immunity, and TNFSF4, possibly involved in hair follicle development. Our findings reveal the different genetic structures and genomic characteristics in the two subgroups of Leiqiong cattle, providing valuable insights into their evolutionary history and establishing a foundation for future breeding strategies.

Analysis of genetic structure and identification of important genes associated with muscle growth in Fujian Muscovy duck

Fujian Muscovy duck is a well-known meat waterfowl in Fujian Province due to its high meat production, superior breeding potential, and strong resistance. To fully explore the genetic characteristics of these advantages, Fujian black Muscovy duck and white Muscovy duck were used for whole-genome re-sequencing and transcriptome analyses. Population structure analysis showed significant differentiation between the two feather strains. Runs of homozygosity analysis indicated a stronger artificial influence on the black-feathered strain, with ROH island genes notably enriched in muscle tissue-related terms and pathways. Selective sweep and transcriptome analysis revealed a significant enrichment of genes linked to muscle tissue and muscle fiber-related terms and pathways. Key candidate genes identified, such as MEF2C, MYOZ2, and METTL21C, are believed to play crucial roles in meat production in Fujian Muscovy duck. This study offers a new perspective on improving meat production in Fujian Muscovy duck, which can benefit breeding strategies and production management.

iHDSel software: The price equation and the population stability index to detect genomic patterns compatible with selective sweeps. An example with SARS-CoV-2

A large number of methods have been developed and continue to evolve for detecting the signatures of selective sweeps in genomes. Significant advances have been made, including the combination of different statistical strategies and the incorporation of artificial intelligence (machine learning) methods. Despite these advances, several common problems persist, such as the unknown null distribution of the statistics used, necessitating simulations and resampling to assign significance to the statistics. Additionally, it is not always clear how deviations from the specific assumptions of each method might affect the results. In this work, allelic classes of haplotypes are used along with the informational interpretation of the Price equation to design a statistic with a known distribution that can detect genomic patterns caused by selective sweeps. The statistic consists of Jeffreys divergence, also known as the population stability index, applied to the distribution of allelic classes of haplotypes in two samples. Results with simulated data show optimal performance of the statistic in detecting divergent selection. Analysis of real severe acute respiratory syndrome coronavirus 2 genome data also shows that some of the sites playing key roles in the virus's fitness and immune escape capability are detected by the method. The new statistic, called JHAC , is incorporated into the iHDSel (informed HacDivSel) software available at https://acraaj.webs.uvigo.es/iHDSel.html.

Signatures of selection analyses reveal genomic differences among three heavy pig breeds that constitute the genetic backbone of a dry-cured ham production system

The Italian pig farming industry is unique in its focus on raising heavy pigs primarily for the production of high-quality dry-cured hams. These products require pigs to be slaughtered at a live weight of around 170 kg at 9 months of age. The primary breeds used in this system are Italian Duroc, Italian Landrace, and Italian Large White which are crossed to produce lines that meet standard requirements. Over the past four decades, selection and breeding programmes for these breeds have been subjected to distinct selective pressures to highlight the characteristics of each breed. In this study, we investigated the genome of these breeds by analysing high-density single nucleotide polymorphism data from over 9 000 pigs to scan for signatures of selection using four different methods, two within breeds and two across breeds. This allowed to identify the genomic regions that differentiate these breeds as well as any relevant genes and biological terms. On a global scale, we found that the Italian Duroc breed exhibited a higher genetic differentiation from the Italian Landrace and Italian Large White breeds, with a pairwise FST value of 0.20 compared with the 0.13 between Italian Landrace and Italian Large White. This may reflect either their different origins or the different breeding goals, which are more similar for the Italian Landrace and Italian Large White breeds. Despite these genetic differences at a global level, few signatures of selection regions reached complete fixation, possibly due to challenges in detecting selection linked to quantitative polygenic traits. The differences among the three breeds are confirmed by the low level of overlap in the regions detected. Genetic enrichment analyses of the three breeds revealed pathways and genes related to various productive traits associated with growth and fat deposition. This may indicate a common selection direction aimed at enhancing specific production traits, though different biological mechanisms are likely targeted by the same directional selection in these three breeds. Therefore, these genes may play a critical role in determining the distinctive characteristics of Italian Duroc, Italian Landrace, and Italian Large White, and potentially influence the traits in crossbred pigs derived from them. Overall, the insights gained from this study will contribute to understanding how directional selection has shaped the genome of these heavy pig breeds and to better address selection strategies aimed at enhancing the meat processing industry linked with dry-cured ham production chains.

Genomic patterns of selection in morphometric traits across diverse Indian cattle breeds

This study seeks a comprehensive exploration of genome-wide selective processes impacting morphometric traits across diverse cattle breeds, utilizing an array of statistical methods. Morphometric traits, encompassing both qualitative and quantitative variables, play a pivotal role in characterizing and selecting livestock breeds based on their external appearance, size, and physical attributes. While qualitative traits, such as color, horn structure, and coat type, contribute to adaptive features and breed identification, quantitative traits like body weight and conformation measurements bear a closer correlation with production characteristics. This study employs advanced genotyping technologies, including the Illumina BovineSNP50 Bead Chip and next-generation sequencing methods like Reduced Representation sequencing, to identify genomic signatures associated with these traits. We applied four intra-population methods to find evidence of selection, such as Tajima's D, CLR, iHS, and ROH. We found a total of 40 genes under the selection signature, that were associated with morphometric traits in five cattle breeds (Kankrej, Tharparkar, Nelore, Sahiwal, and Gir). Crucial genes such as ADIPDQ, DPP6, INSIG1, SLC35D2 in Kankrej, LPL, ATP6V1B2, CDC14B in Tharparkar, HPSE2, PLAG1 in Nelore, PCSK1, PRKD1 in Sahiwal, and GNAQ, HPCAL1 in Gir were identified in our study. This approach provides valuable insights into the genetic basis of variations in body weight and conformation traits, facilitating informed selection processes and offering a deeper understanding of the evolutionary and domestication processes in diverse cattle breeds.

Whole-genome resequencing deciphers patterns of genetic diversity, phylogeny, and evolutionary dynamics in Kashmir cattle

Kashmir cattle, which were kept by local pastoralists for centuries, are exceptionally resilient and adaptive to harsh environments. Despite its significance, the genomic characteristics of this cattle breed remain elusive. This study utilized whole genome sequences of Kashmir cattle (n = 20; newly sequenced) alongside published whole genomes of 32 distinct breeds and seven core cattle populations (n = 135). The analysis identified ~25.87 million biallelic single nucleotide polymorphisms in Kashmir cattle, predominantly in intergenic and intron regions. Population structure analyses revealed distinct clustering patterns of Kashmir cattle with proximity to the South Asian, African and Chinese indicine cattle populations. Genetic diversity analysis of Kashmir cattle demonstrated lower inbreeding and greater nucleotide diversity than analyzed global breeds. Homozygosity runs indicated less consanguineous mating in Kashmir cattle compared with European taurine breeds. Furthermore, six selection sweep detection methods were used within Kashmir cattle and other cattle populations to identify genes associated with vital traits, including immunity (BOLA-DQA5, BOLA-DQB, TNFAIP8L, FCRL4, AOAH, HIF1AN, FBXL3, MPEG1, CDC40, etc.), reproduction (GOLGA4, BRWD1, OSBP2, LEO1 ADCY5, etc.), growth (ADPRHL1, NRG2, TCF12, TMOD4, GBP4, IGF2, RSPO3, SCD, etc.), milk composition (MRPS30 and CSF1) and high-altitude adaptation (EDNRA, ITPR2, AGBL4 and SCG3). These findings provide essential genetic insights into the characteristics and establish the foundation for the scientific conservation and utilization of Kashmir cattle breed.

Selection signatures of wool color in Gangba sheep revealed by genome-wide SNP discovery

BACKGROUND

Gangba sheep as a famous breed of Tibetan sheep, its wool color is mainly white and black. Gangba wool is economically important as a high-quality raw material for Tibetan blankets and Tibetan serge. However, relatively few studies have been conducted on the wool color of Tibetan sheep.

RESULTS

To fill this research gap, this study conducted an in-depth analysis of two populations of Gangba sheep (black and white wool color) using whole genome resequencing to identify genetic variation associated with wool color. Utilizing PCA, Genetic Admixture, and N-J Tree analyses, the present study revealed a consistent genetic relationship and structure between black and white wool colored Gangba sheep populations, which is consistent with their breed history. Analysis of selection signatures using multiple methods (FST, π ratio, Tajima's D), 370 candidate genes were screened in the black wool group (GBB vs GBW); among them, MC1R, MLPH, SPIRE2, RAB17, SMARCA4, IRF4, CAV1, USP7, TP53, MYO6, MITF, MC2R, TET2, NF1, JAK1, GABRR1 genes are mainly associated with melanin synthesis, melanin delivery, and distribution. The enrichment results of the candidate genes identified 35 GO entries and 19 KEGG pathways associated with the formation of the black phenotype. 311 candidate genes were screened in the white wool group (GBW vs GBB); among them, REST, POU2F1, ADCY10, CCNB1, EP300, BRD4, GLI3, and SDHA genes were mainly associated with interfering with the differentiation of neural crest cells into melanocytes, affecting the proliferation of melanocytes, and inhibiting melanin synthesis. 31 GO entries and 22 KEGG pathways were associated with the formation of the white phenotype.

CONCLUSIONS

This study provides important information for understanding the genetic mechanism of wool color in Gangba, and provides genetic knowledge for improving and optimizing the wool color of Tibetan sheep. Genetic improvement and selective breeding to produce wool of specific colors can meet the demand for a diversity of wool products in the Tibetan wool textile market.

Genome-wide mining of diversity and evolutionary signatures revealed selective hotspots in Indian Sahiwal cattle

The Sahiwal cattle breed is the best indigenous dairy cattle breed, and it plays a pivotal role in the Indian dairy industry. This is due to its exceptional milk-producing potential, adaptability to local tropical conditions, and its resilience to ticks and diseases. The study aimed to identify selective sweeps and estimate intrapopulation genetic diversity parameters in Sahiwal cattle using ddRAD sequencing-based genotyping data from 82 individuals. After applying filtering criteria, 78,193 high-quality SNPs remained for further analysis. The population exhibited an average minor allele frequency of 0.221 ± 0.119. Genetic diversity metrics, including observed (0.597 ± 0.196) and expected heterozygosity (0.433 ± 0.096), nucleotide diversity (0.327 ± 0.114), the proportion of polymorphic SNPs (0.726), and allelic richness (1.323 ± 0.134), indicated ample genomic diversity within the breed. Furthermore, an effective population size of 74 was observed in the most recent generation. The overall mean linkage disequilibrium (r2) for pairwise SNPs was 0.269 ± 0.057. Moreover, a greater proportion of short Runs of Homozygosity (ROH) segments were observed suggesting that there may be low levels of recent inbreeding in this population. The genomic inbreeding coefficients, computed using different inbreeding estimates (FHOM, FUNI, FROH, and FGROM), ranged from -0.0289 to 0.0725. Subsequently, we found 146 regions undergoing selective sweeps using five distinct statistical tests: Tajima's D, CLR, |iHS|, |iHH12|, and ROH. These regions, located in non-overlapping 500 kb windows, were mapped and revealed various protein-coding genes associated with enhanced immune systems and disease resistance (IFNL3, IRF8, BLK), as well as production traits (NRXN1, PLCE1, GHR). Notably, we identified interleukin 2 (IL2) on Chr17: 35217075-35223276 as a gene linked to tick resistance and uncovered a cluster of genes (HSPA8, UBASH3B, ADAMTS18, CRTAM) associated with heat stress. These findings indicate the evolutionary impact of natural and artificial selection on the environmental adaptation of the Sahiwal cattle population.

Single cell RNA-seq: a novel tool to unravel virus-host interplay

Over the last decade, single cell RNA sequencing (scRNA-seq) technology has caught the momentum of being a vital revolutionary tool to unfold cellular heterogeneity by high resolution assessment. It evades the inadequacies of conventional sequencing technology which was able to detect only average expression level among cell populations. In the era of twenty-first century, several epidemic and pandemic viruses have emerged. Being an intracellular entity, viruses totally rely on host. Complex virus-host dynamics result when the virus tend to obtain factors from host cell required for its replication and establishment of infection. As a prevailing tool, scRNA-seq is able to understand virus-host interplay by comprehensive transcriptome profiling. Because of technological and methodological advancement, this technology is capable to recognize viral genome and host cell response heterogeneity. Further development in analytical methods with multiomics approach and increased availability of accessible scRNA-seq datasets will improve the understanding of viral pathogenesis that can be helpful for development of novel antiviral therapeutic strategies.

Dissecting the genomic regions of selection on the X chromosome in different cattle breeds

Mammalian X and Y chromosomes independently evolved from various autosomes approximately 300 million years ago (MYA). To fully understand the relationship between genomic composition and phenotypic diversity arising due to the course of evolution, we have scanned regions of selection signatures on the X chromosome in different cattle breeds. In this study, we have prepared the datasets of 184 individuals of different cattle breeds and explored the complete X chromosome by utilizing four within-population and two between-population methods. There were 23, 25, 30, 17, 17, and 12 outlier regions identified in Tajima's D, CLR, iHS, ROH, FST, and XP-EHH. Bioinformatics analysis showed that these regions harbor important candidate genes like AKAP4 for reproduction in Brown Swiss, MBTS2 for production traits in Brown Swiss and Guernsey, CXCR3 and CITED1 for health traits in Jersey and Nelore, and BMX and CD40LG for regulation of X chromosome inactivation in Nelore and Gir. We identified genes shared among multiple methods, such as TRNAC-GCA and IL1RAPL1, which appeared in Tajima's D, ROH, and iHS analyses. The gene TRNAW-CCA was found in ROH, CLR and iHS analyses. The X chromosome exhibits a distinctive interaction between demographic factors and genetic variations, and these findings may provide new insight into the X-linked selection in different cattle breeds.

Unique footprints of balancing selection in bovine genome

Balancing selection is the process of selection that preserves various alleles within a population. Studying the areas undergoing balancing selection is essential, because it preserves genetic diversity in a population. Finding genes that exhibit signs of balancing selection during the domestication of cattle is the goal of this study. To identify regions where polymorphism has persisted in the cattle population for millions of years, we examined the genome of cattle. In this study, we used bovine SNP 50 k data to conduct a detailed genome-wide assessment of selection signatures for balancing selection. We have included the genotyped data from 427 animals, including five taurines, two crossbreds, and eight Indian cattle breeds. For this study, we employed Tajima's D approach to identify signature regions undergoing balancing selection. Using the NCBI database, PANTHER 17.0, and CattleQTL database, the annotation was carried out after finding the relevant areas under balancing selection. The number of genomic regions undergoing balancing selection in Ayrshire, Brown-Swiss, Frieswal, Gir, Guernsey, Hariana, Holstein Friesian, Jersey, Kankrej, Nelore, Ongole, Red Sindhi, Sahiwal, Tharparkar, and Vrindavani was 11, 13, 13, 19, 18, 11, 17, 14, 14, 12, 10, 12, 13, 13, and 11, respectively. We have observed multiple immune system-related genes going through balancing selection, including KIT, NFATC2, GBP4, LRRC32, SYT7, RAG1, RAG2, LOC513659, and ZBTB17. In our study, we found that the majority of the immune-related genes and a few genes associated with growth, reproduction, production, and adaptation are undergoing balancing selection.

Deciphering climate resilience in Indian cattle breeds by selection signature analyses

The signature of selection is a crucial concept in evolutionary biology that refers to the pattern of genetic variation which arises in a population due to natural selection. In the context of climate adaptation, the signature of selection can reveal the genetic basis of adaptive traits that enable organisms to survive and thrive in changing environmental conditions. Breeds living in diverse agroecological zones exhibit genetic "footprints" within their genomes that mirror the influence of climate-induced selective pressures, subsequently impacting phenotypic variance. It is assumed that the genomes of animals residing in these regions have been altered through selection for various climatic adaptations. These regions are known as signatures of selection and can be identified using various summary statistics. We examined genotypic data from eight different cattle breeds (Gir, Hariana, Kankrej, Nelore, Ongole, Red Sindhi, Sahiwal, and Tharparkar) that are adapted to diverse regional climates. To identify selection signature regions in this investigation, we used four intra-population statistics: Tajima's D, CLR, iHS, and ROH. In this study, we utilized Bovine 50 K chip data and four genome scan techniques to assess the genetic regions of positive selection for high-temperature adaptation. We have also performed a genome-wide investigation of genetic diversity, inbreeding, and effective population size in our target dataset. We identified potential regions for selection that are likely to be caused by adverse climatic conditions. We observed many adaptation genes in several potential selection signature areas. These include genes like HSPB2, HSPB3, HSP20, HSP90AB1, HSF4, HSPA1B, CLPB, GAP43, MITF, and MCHR1 which have been reported in the cattle populations that live in varied climatic regions. The findings demonstrated that genes involved in disease resistance and thermotolerance were subjected to intense selection. The findings have implications for marker-assisted breeding, understanding the genetic landscape of climate-induced adaptation, putting breeding and conservation programs into action.

Comprehensive selection signature analyses in dairy cattle exploiting purebred and crossbred genomic data

The main objective of the current research was to locate, annotate, and highlight specific areas of the bovine genome that are undergoing intense positive selection. Here, we are analyzing selection signatures in crossbred (Bos taurus X Bos indicus), taurine (Bos taurus), and indicine (Bos indicus) cattle breeds. Indicine cattle breeds found throughout India are known for their higher heat tolerance and disease resilience. More breeds and more methods can provide a better understanding of the selection signature. So, we have worked on nine distinct cattle breeds utilizing seven different summary statistics, which is a fairly extensive approach. In this study, we carried out a thorough genome-wide investigation of selection signatures using bovine 50K SNP data. We have included the genotyped data of two taurine, two crossbreds, and five indicine cattle breeds, for a total of 320 animals. During the 1950s, these indicine (cebuine) cattle breeds were exported with the aim of enhancing the resilience of taurine breeds in Western countries. For this study, we employed seven summary statistics, including intra-population, i.e., Tajima's D, CLR, iHS, and ROH and inter-population statistics, i.e., FST, XP-EHH, and Rsb. The NCBI database, PANTHER 17.0, and CattleQTL database were used for annotation after finding the important areas under selection. Some genes, including EPHA6, CTNNA2, NPFFR2, HS6ST3, NPR3, KCNIP4, LIPK, SDCBP, CYP7A1, NSMAF, UBXN2B, UGDH, UBE2K, and DAB1, were shown to be shared by three or more different approaches. Therefore, it gives evidence of the most intense selection in these areas. These genes are mostly linked to milk production and adaptability traits. This study also reveals selection regions that contain genes which are crucial to numerous biological functions, including those associated with milk production, coat color, glucose metabolism, oxidative stress response, immunity and circadian rhythms.