Signatures of Selection in Composite Vrindavani Cattle of India

Selection signatures associated with adaptation in South African Drakensberger, Nguni, and Tuli beef breeds

In the present study 1,709 cattle, including 1,118 Drakensberger (DRB), 377 Nguni (NGI), and 214 Tuli (TUL), were genotyped using the GeneSeek® Genomic Profiler™ 150 K bovine SNP panel. A genomic data set of 122,632 quality-filtered single nucleotide polymorphisms (SNPs) were used to identify selection signatures within breeds based on conserved runs of homozygosity (ROH) and heterozygosity (ROHet) estimated with the detectRUNS R package. The mean number of ROH per animal varied across breeds ranging from 36.09 ± 12.82 (NGI) to 51.82 ± 21.01 (DRB), and the mean ROH length per breed ranged between 2.31 Mb (NGI) and 3.90 Mb (DRB). The smallest length categories i.e., ROH < 4 Mb were most frequent, indicating historic inbreeding effects for all breeds. The ROH based inbreeding coefficients (FROH) ranged between 0.033 ± 0.024 (NGI) and 0.081 ± 0.046 (DRB). Genes mapped to candidate regions were associated with immunity (ADAMTS12, LY96, WDPCP) and adaptation (FKBP4, CBFA2T3, TUBB3) in cattle and genes previously only reported for immunity in mice and human (EXOC3L1, MYO1G). The present study contributes to the understanding of the genetic mechanisms of adaptation, providing information for potential molecular application in genetic evaluation and selection programs.

Assessment of Genomic Diversity and Selective Pressures in Crossbred Dairy Cattle of Pakistan

Improving the low productivity levels of native cattle breeds in smallholder farming systems is a pressing concern in Pakistan. Crossbreeding high milk-yielding holstein friesian (HF) breed with the adaptability and heat tolerance of Sahiwal cattle has resulted in offspring that are well-suited to local conditions and exhibit improved milk yield. The exploration of how desirable traits in crossbred dairy cattle are selected has not yet been investigated. This study aims to provide the first overview of the selective pressures on the genome of crossbred dairy cattle in Pakistan. A total of eighty-one crossbred, thirty-two HF and twenty-four Sahiwal cattle were genotyped, and additional SNP genotype data for HF and Sahiwal were collected from a public database to equate the sample size in each group. Within-breed selection signatures in crossbreds were investigated using the integrated haplotype score. Crossbreds were also compared to each of their parental breeds to discover between-population signatures of selection using two approaches: cross-population extended haplotype homozygosity and fixation index. We identified several overlapping genes associated with production, immunity, and adaptation traits, including U6, TMEM41B, B4GALT7, 5S_rRNA, RBM27, POU4F3, NSD1, PRELID1, RGS14, SLC34A1, TMED9, B4GALT7, OR2AK3, OR2T16, OR2T60, OR2L3, and CTNNA1. Our results suggest that regions responsible for milk traits have generally experienced stronger selective pressure than others.

Identification of genetic variants affecting reproduction traits in Vrindavani cattle

Genome-wide association studies (GWAS) are one of the best ways to look into the connection between single-nucleotide polymorphisms (SNPs) and the phenotypic performance. This study aimed to identify the genetic variants that significantly affect the important reproduction traits in Vrindavani cattle using genome-wide SNP chip array data. In this study, 96 randomly chosen Vrindavani cows were genotyped using the Illumina Bovine50K BeadChip platform. A linear regression model of the genome-wide association study was fitted in the PLINK program between genome-wide SNP markers and reproduction traits, including age at first calving (AFC), inter-calving period (ICP), dry days (DD), and service period (SP) across the first three lactations. Information on different QTLs and genes, overlapping or adjacent to genomic coordinates of significant SNPs, was also mined from relevant databases in order to identify the biological pathways associated with reproductive traits in bovine. The Bonferroni correction resulted in total 39 SNP markers present on different chromosomes being identified that significantly affected the variation in AFC (6 SNPs), ICP (7 SNPs), DD (9 SNPs), and SP (17 SNPs). Novel potential candidate genes associated with reproductive traits that were identified using the GWAS methodology included UMPS, ITGB5, ADAM2, UPK1B, TEX55, bta-mir-708, TMPO, TDRD5, MAPRE2, PTER, AP3B1, DPP8, PLAT, TXN2, NDUFAF1, TGFA, DTNA, RSU1, KCNQ1, ADAM32, and CHST8. The significant SNPs and genes associated with the reproductive traits and the enriched genes may be exploited as candidate biomarkers in animal improvement programs, especially for improved reproduction performance in bovines.

Ancestral alleles defined for 70 million cattle variants using a population-based likelihood ratio test

BACKGROUND

The study of ancestral alleles provides insights into the evolutionary history, selection, and genetic structures of a population. In cattle, ancestral alleles are widely used in genetic analyses, including the detection of signatures of selection, determination of breed ancestry, and identification of admixture. Having a comprehensive list of ancestral alleles is expected to improve the accuracy of these genetic analyses. However, the list of ancestral alleles in cattle, especially at the whole genome sequence level, is far from complete. In fact, the current largest list of ancestral alleles (~ 42 million) represents less than 28% of the total number of detected variants in cattle. To address this issue and develop a genomic resource for evolutionary studies, we determined ancestral alleles in cattle by comparing prior derived whole-genome sequence variants to an out-species group using a population-based likelihood ratio test.

RESULTS

Our study determined and makes available the largest list of ancestral alleles in cattle to date (70.1 million) and includes 2.3 million on the X chromosome. There was high concordance (97.6%) of the determined ancestral alleles with those from previous studies when only high-probability ancestral alleles were considered (29.8 million positions) and another 23.5 million high-confidence ancestral alleles were novel, expanding the available reference list to improve the accuracies of genetic analyses involving ancestral alleles. The high concordance of the results with previous studies implies that our approach using genomic sequence variants and a likelihood ratio test to determine ancestral alleles is appropriate.

CONCLUSIONS

Considering the high concordance of ancestral alleles across studies, the ancestral alleles determined in this study including those not previously listed, particularly those with high-probability estimates, may be used for further genetic analyses with reasonable accuracy. Our approach that used predetermined variants in species and the likelihood ratio test to determine ancestral alleles is applicable to other species for which sequence level genotypes are available.

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.

Genetic analysis of first lactation and lifetime performance traits in composite Vrindavani cattle: important considerations for higher milk production

The present study was aimed to evaluate the influence of non-genetic factors on several first lactation and lifetime performance traits and elucidate their genetic parameters in an organized Vrindavani cattle population. Data on eight first-lactation and thirteen lifetime traits were collected on 2400 cows with pedigree records that were reared during 33-year period (1989-2021). The first-lactation traits included age at first calving (AFC), total milk yield (FTMY), standard milk yield (FSMY305), peak yield (FPY), lactation length (FLL), dry period (FDP), service period (FSP) and calving interval (FCI). Whereas, the lifetime traits mainly included total lifetime milk yield (TLMY), total standard milk yield (TSMY), number of lactations completed (NL), total lactation length (TLL), herd life (HL), productive life (PL), average milk yield per day of herd life (TLMY/HL), average milk yield per day of productive life (TLMY/PL), average milk yield per day of productive life (TLMY/TLL). Other lifetime production traits included average service period (ASP), average dry period (ADP), average calving interval (ACI) and unproductive days (UD). The heritability estimates of first-lactation traits ranged between 0.026 and 0.228 and were found to be low for AFC (0.180 ± 0.042), FCI (0.191 ± 0.125), FSMY305 (0.145 ± 0.061), FTMY (0.165 ± 0.048), FDP (0.052 ± 0.049) and FSP (0.026 ± 0.033); however, FLL (0.229 ± 0.044) and FPY (0.202 ± 0.046) showed moderate heritability. Positive phenotypic correlation (p < 0.001) was revealed among FTMY, TLMY, TLL, HL and PL. The AFC produced a significant effect (p < 0.05) on several traits i,e, TLL, TLMY/HL, FSMY305, FPY, TLMY, HL and TLMY/PL. Lower AFC was associated with higher TLMY, TLL and TLMY/HL; while FSMY305, FPY, HL and TLMY/PL were higher in heifers that calved late in their life. The results revealed that AFC may be optimized with first lactation and lifetime traits for this population.

Milk exosomal microRNA profiling identified miR-375 and miR-199-5p for regulation of immune response during subclinical mastitis of crossbred cattle

BACKGROUND

The dairy industry has experienced significant economic losses as a result of mastitis, an inflammatory disease of cows, including both subclinical and clinical cases. Milk exosome microRNAs have gained attention due to their stable and selective wrapping nature, offering potential for the prognosis and diagnosis of bovine mastitis, the most common pathological condition of the mammary gland.

METHODS AND RESULTS

 In the present investigation, the microRNA profile of milk exosomes was explored using high-throughput small RNA sequencing data in sub-clinical mastitic and healthy crossbred Vrindavani cattle. In both groups, 349 microRNAs were identified, with 238 (68.19%) microRNAs co-expressed; however, 35 and 76 distinct microRNAs were found in subclinical mastitic and healthy cattle, respectively. Differential expression analysis revealed 11 microRNAs upregulated, and 18 microRNAs were downregulated in sub-clinical mastitic cattle. The functional annotation of the target genes of differentially expressed known and novel microRNAs including bta-miR-375, bta-miR-199-5p and bta-miR-12030 reveals their involvement in the regulation of immune response and inflammatory mechanisms and could be involved in development of mastitis.

CONCLUSIONS

The analysis of milk exosomal miRNAs cargos hold great promise as an approach to study the underlying molecular mechanisms associated with mastitis in high milk producing dairy cattle. Concurrently, the significantly downregulated miR-375 may upregulate key target genes, including CTLA4, IHH, IRF1, and IL7R. These genes are negative regulators of immune response pathways, which could be associated with impaired inflammatory mechanisms in mammary cells. According to the findings, bta-miR-375 could be a promising biomarker for the development of mastitis in dairy cattle.

Unraveling the Genomic Association for Milk Production Traits and Signatures of Selection of Cattle in a Harsh Tropical Environment

A study was designed to identify the genomic regions associated with milk production traits in a dairy cattle population reared by smallholder farmers in the harsh and challenging tropical savanna climate of Bengaluru, India. This study is a first-of-its-kind attempt to identify the selection sweeps for the dairy cattle breeds reared in such an environment. Two hundred forty lactating dairy cows reared by 68 farmers across the rural-urban transiting regions of Bengaluru were selected for this study. A genome-wide association study (GWAS) was performed to identify candidate genes for test-day milk yield, solids-not-fat (SNF), milk lactose, milk density and clinical mastitis. Furthermore, the cross-population extended haplotype homozygosity (XP-EHH) methodology was adopted to scan the dairy cattle breeds (Holstein Friesian, Jersey and Crossbred) in Bengaluru. Two SNPs, rs109340659 and rs41571523, were observed to be significantly associated with test-day milk yield. No significant SNPs were observed for the remaining production traits. The GWAS for milk lactose revealed one SNP (rs41634101) that was very close to the threshold limit, though not significant. The potential candidate genes fibrosin-like 1 (FBRSL) and calcium voltage-gated channel auxiliary subunit gamma 3 (CACN) were identified to be in close proximity to the SNP identified for test-day milk yield. These genes were observed to be associated with milk production traits based on previous reports. Furthermore, the selection signature analysis revealed a number of regions under selection for the breed-group comparisons (Crossbred-HF, Crossbred-J and HF-J). Functional analysis of these annotated genes under selection indicated pathways and mechanisms involving ubiquitination, cell signaling and immune response. These findings point towards the probable selection of dairy cows in Bengaluru for thermotolerance.

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.

Genome-wide screening for selection signatures in native and cosmopolitan cattle breeds reared in Türkiye

Via long-term natural and artificial selection pressure, homozygosity may extend across the genome, leaving genomic patterns called selection signatures. This study is the first attempt to assess genome-wide selection signatures in six native Turkish and two cosmopolitan cattle breeds by 211.119 bi-allelic SNPs recovered using the double digest restriction associated DNA sequencing method. The integrated haplotype score (iHS) statistic was utilised to reveal selection signatures within populations, whereas the cross-population extended haplotype homozygosity (XP-EHH) and fixation index (FST ) approaches were preferred to reveal differently fixed genomic regions between native Turkish and cosmopolitan cattle breeds. Selection signatures in 142 genomic regions containing 305 genes were detected within eight cattle breeds by iHS statistics. The XP-EHH and FST approaches revealed that 197 and 114 SNPs were under selection pressure, respectively, which overlapped with 144 and 190 genes, respectively. A total of 18 genes were detected by at least two approaches. Six genes related to disease resistance (TTP2), meat yield (DIAPH3 and METTL21C), meat quality (ZNF24 and ZNF397) and first calving interval (ZSCAN30) turned out to be differently fixed between native Turkish and cosmopolitan cattle breeds, as they were identified by both XP-EHH and FST approaches. In addition, the iHS approach revealed that eight genes associated with visual modality (LSGN), olfaction (MOXD2, OR4C1F and OR4C1F), and immune response (TRBV3-1 and CLDN10) were under selection pressure in both native and cosmopolitan cattle breeds. Owing to their being significantly related to survival traits, these regions may have played a key role in cattle genome evolution. Future studies utilising denser genetic data are required to obtain deeper knowledge on effects of natural and artificial selection in Anatolian cattle breeds. © 2023 Stichting International Foundation for Animal Genetics.

Progress and future perspectives of livestock genomics in India: a mini review

The field of genetics has evolved a lot after the emergence of molecular and advanced genomic technologies. The advent of Next Generation Sequencing, SNP genotyping platforms and simultaneous reduction in the cost of sequencing had opened the door to genomic research in farm animals. There are various applications of genomics in livestock, such as the use of genomic data: (i) to investigate genetic diversity and breed composition/population structure (ii) to identify genetic variants and QTLs related to economically important and ecological traits, genome-wide association studies (GWAS) and genomic signatures of selection; (iii) to enhance breeding programs by genomic selection. Compared to traditional methods, genomic selection is expected to improve selection response by increasing selection accuracy and reducing the generation interval due to early selection. Genomic selection (GS) in developed countries has led to rapid genetic gains, especially in dairy cattle, due to a well-established genetic evaluation system. Indian livestock system is still lagging behind developed nations in adopting these technologies. This review discusses the current status, challenges, and future perspectives of livestock genomics in India.

A look under the hood of genomic-estimated breed compositions for brangus cattle: What have we learned?

The Brangus cattle were developed to utilize the superior traits of Angus and Brahman cattle. Their genetic compositions are expected to be stabilized at 3/8 Brahman and 5/8 Angus. Previous studies have shown more than expected Angus lineage with Brangus cattle, and the reasons are yet to be investigated. In this study, we revisited the breed compositions for 3,605 Brangus cattle from three perspectives: genome-wise (GBC), per chromosomes (CBC), and per chromosome segments (SBC). The former (GBC) depicted an overall picture of the “mosaic” genome of the Brangus attributable to their ancestors, whereas the latter two criteria (CBC and SBC) corresponded to local ancestral contributions. The average GBC for the 3,605 Brangus cattle were 70.2% Angus and 29.8% Brahman. The K-means clustering supported the postulation of the mixture of 1/2 Ultrablack (UB) animals in Brangus. For the non-UB Brangus animals, the average GBC were estimated to be 67.4% Angus and 32.6% Brahman. The 95% confidence intervals of their overall GBC were 60.4%–73.5% Angus and 26.5%–39.6% Brahman. Possibly, genetic selection and drifting have resulted in an approximately 5% average deviation toward Angus lineage. The estimated ancestral contributions by chromosomes were heavily distributed toward Angus, with 27 chromosomes having an average Angus CBC greater than 62.5% but only two chromosomes (5 and 20) having Brahman CBC greater than 37.5%. The chromosomal regions with high Angus breed proportions were prevalent, tending to form larger blocks on most chromosomes. In contrast, chromosome segments with high Brahman breed proportion were relatively few and isolated, presenting only on seven chromosomes. Hence, genomic hitchhiking effects were strong where Angus favorable alleles resided but weak where Brahman favorable alleles were present. The functions of genes identified in the chromosomal regions with high (≥75%) Angus compositions were diverse yet may were related to growth and body development. In contrast, the genes identified in the regions with high (≥37.5%) Brahman compositions were primarily responsible for disease resistance. In conclusion, we have addressed the questions concerning the Brangus genetic make-ups. The results can help form a dynamic picture of the Brangus breed formation and the genomic reshaping.

Exploring haplotype block structure, runs of homozygosity, and effective population size among dairy cattle breeds of India

The present study aimed to explore haplotype structure, runs of homozygosity (ROH), effective population size and persistence of gametic phase among three indigenous dairy cattle breeds, viz., Sahiwal (n = 19), Tharparkar (n = 17), and Gir (n = 16) by using BovineHD single nucleotide polymorphism (SNP) genotyping assay. The filtered SNPs after quality control ranged from 44% in Sahiwal to 53% in Gir. The highest number of haplotype blocks was observed in Tharparkar (15,640) and the lowest in Sahiwal (8027) spanning 17.3% and 7.8% of genome, respectively. The average block length was found close to 26 kb which suggests that multiple recombination events fragmented the ancestral haplotypes into smaller sizes. Gir cattle had the largest number of runs of homozygosity (ROH) regions (1762) followed by Tharparkar (1528) and Sahiwal (1138). Without pedigree information, inbreeding coefficients estimated from ROH (F_ROH) revealed that Gir had the highest F_ROH (0.099) proposing more inbreeding rate in this population. Effective population size (N_e) decreased slowly over the last 60 generations and at 13 generations ago; N_e was estimated as 70 for all the three dairy breeds. The highest gametic phase correlation (r = 0.78) was observed for Sahiwal and Tharparkar breed pair suggesting formulation of multi-breed reference population for successful implementation of genomic selection among dairy breeds. The decline in effective population size among native Indian cattle breeds may help in formulating strategies for conservation and genetic improvement of native germplasm for future use.

Trajectory of livestock genomics in South Asia: A comprehensive review

Livestock plays a central role in sustaining human livelihood in South Asia. There are numerous and distinct livestock species in South Asian countries. Several of them have experienced genetic development in recent years due to the application of genomic technologies and effective breeding programs. This review discusses genomic studies on cattle, buffalo, sheep, goat, pig, horse, camel, yak, mithun, and poultry. The frontiers covered in this review are genetic diversity, admixture studies, selection signature research, QTL discovery, genome-wide association studies (GWAS), and genomic selection. The review concludes with recommendations for South Asian livestock systems to increasingly leverage genomic technologies, based on the lessons learned from the numerous case studies. This paper aims to present a comprehensive analysis of the dichotomy in the South Asian livestock sector and argues that a realistic approach to genomics in livestock can ensure long-term genetic advancements.

Whole genome resequencing reveals the genetic contribution of Kazakh and Swiss Brown cattle to a population of Xinjiang Brown cattle

Xinjiang Brown cattle is characterized by wide environmental adaptation from its female parent (Kazakh cattle) and good production performance from its male parent (Swiss Brown cattle). However, the genetic basis underlying these characteristics hasnotbeenexplored. Here we compared 50 genomes of Xinjiang Brown cattle to the genomes of other eight breeds worldwide to analyze patterns of genetic variation in the Xinjiang Brown cattle. We found canonical genomic characteristics of cross breed with the lowest linkage disequilibrium and the highest effective population size. At the global level, Xinjiang Brown cattle had 9.88% Kazakh cattle and 90.12% Swiss Brown cattle inheritance. Our local ancestry inference revealed the segments with the excess of Kazakh cattle blood enriched in genes or pathways involved in digestion,absorption,metabolism and disease. More importantly, we also observed the completely fixed haplotypes inherited from Swiss Brown cattle harboring genes (LCORL, GHR, MEF2D, PCSK1 and MSRB3), KEGG pathways, cattle QTLs or human NHGRIGWAS catalog related to body measurement and growth traits. Our findings will not only help understand the process of cross breeding but can provide basic materials for further QTL mapping and improvement of important traits in Xinjiang Brown cattle.

Genome-wide elucidation of CNV regions and their association with production and reproduction traits in composite Vrindavani cattle

The present study was aimed to analyze the genome-wide copy number variations (CNVs) in Vrindavani composite cattle and concatenate them into CNV regions (CNVRs), and finally test the association of CNVRs with different production and reproduction traits. Genotypic data, generated on BovineSNP50 Beadchip (v3) array for 96 Vrindavani animals, was used to elucidate the CNVs at the genome level. Intensity data covering over 53,218 SNP genotypes on bovine genome was used. Algorithm based on Hidden Markov Model was employed in PennCNV program to detect, normalize and filter CNVs across the genome. 252 putative CNVs, detected via PennCNV program, in different individuals were concatenated into 71 CNV regions (CNVRs) using CNVRuler program. Association of CNVRs with important (re)production traits in Vrindavani animals was assessed using linear regression. Five CNVRs were found to be significantly associated with ten important (re)production traits. The genes harbored in these regions provided useful insights into the association of CNVRs with genes and ultimately the variation at phenotype level. Important genes that overlapped with CNVRs included WASHC4, HS6ST3, MBNL2, TOLLIP, PIDD1 and TSPAN4. Furthermore, the CNVRs were found to overlap with important QTLs available in AnimalQTL database which affect milk yield and composition along with reproduction and immune function traits. The copy number states of three enes were validated using digital droplet PCR technique. The results from the present study significantly enhance the understanding about CNVs in Vrindavani cattle and should help establish its CNV map. The study will also enable further investigation on association of these variants with important traits of economic interest including disease incidence.

Genome-Wide Selection Signatures and Human-Mediated Introgression Events in Bos taurus indicus-influenced Composite Beef Cattle

Genetic introgression from interbreeding hybridization of European Bos taurus taurus (EBT) and Indian Bos taurus indicus (IBI) cattle breeds have been widely used to combine the climatic resilience of the IBI cattle and the higher productivity of EBT when forming new composite beef cattle (CB) populations. The subsequent breeding strategies have shifted their initial genomic compositions. To uncover population structure, signatures of selection, and potential introgression events in CB populations, high-density genotypes [containing 492,954 single nucleotide polymorphisms (SNPs) after the quality control] of 486 individuals from 15 cattle breeds, including EBT, IBI, and CB populations, along with two Bos grunniens genotypes as outgroup were used in this study. Then, in-depth population genetics analyses were performed for three CB breeds of Beefmaster, Brangus, and Santa Gertrudis. Neighbor-joining, principal components, and admixture analyses confirmed the historical introgression of EBT and IBI haplotypes into CB breeds. The f_dM statistics revealed that only 12.9% of CB populations' genetic components are of IBI origin. The results of signatures of selection analysis indicated different patterns of selection signals in the three CB breeds with primary pressure on pathways involved in protein processing and stress response in Beefmaster, cell proliferation regulation and immune response in Brangus, and amino acids and glucose metabolisms in Santa Gertrudis. An average of >90% of genomic regions underlying selection signatures were of EBT origin in the studied CB populations. Investigating the CB breeds' genome allows the estimation of EBT and IBI ancestral proportions and the locations within the genome where either taurine or indicine origin alleles are under selective pressure. Such findings highlight various opportunities to control the selection process more efficiently and explore complementarity at the genomic level in CB populations.

Selection Signatures in South African Nguni and Bonsmara Cattle Populations Reveal Genes Relating to Environmental Adaptation

Climate change is a major influencing factor in beef production. The greenhouse gases produced from livestock production systems contribute to the overall greenhouse gas emissions. The aim of this study was to identify selection signatures within and between Nguni and Bonsmara cattle in relation to production and adaptation. For this purpose, genomic 150 K single nucleotide polymorphism data from Nguni (n = 231) and Bonsmara (n = 252) cattle in South Africa were used. Extended haplotype homozygosity (EHH) based analysis was executed within each population using integrated haplotype score (iHS). The R package rehh was used for detecting selection signatures across the two populations with cross population EHH (XP-EHH). Total of 121 regions of selection signatures were detected (p < 0.0001) in the Bonsmara and Nguni populations. Several genes relating to DNA methylation, heat stress, feed efficiency and nitrogen metabolism were detected within and between each population. These regions also included QTLs associated with residual feed intake, residual gain, carcass weight, stature and body weight in the Bonsmara, while QTLs associated with conception rate, shear force, tenderness score, juiciness, temperament, heat tolerance, feed efficiency and age at puberty were identified in Nguni. Based on the results of the study it is recommended that the Nguni and Bonsmara be utilized in crossbreeding programs as they have beneficial traits that may allow them to perform better in the presence of climate change. Results of this study coincide with Nguni and Bonsmara breed characteristics and performance, and furthermore support informative crossbreeding programs to enhance livestock productivity in South Africa.

Genome Wide Scan to Identify Potential Genomic Regions Associated With Milk Protein and Minerals in Vrindavani Cattle

In this study, genome-wide association study (GWAS) was conducted for identifying significantly associated genomic regions/SNPs with milk protein and minerals in the 96 taurine-indicine crossbred (Vrindavani) cows using 50K SNP Chip. After quality control, a total of 41,427 SNPs were retained and were further analyzed using a single-SNP additive linear model. Lactation stage, parity, test day milk yield and proportion of exotic inheritance were included as fixed effects in GWAS model. Across all traits, 13 genome-wide significant (p < 1.20 x 10⁻⁰⁶) and 49 suggestive significant (p < 2.41 x 10⁻⁰⁵) SNPs were identified which were located on 18 different autosomes. The strongest association for protein percentage, calcium (Ca), phosphorus (P), copper (Cu), zinc (Zn), and iron (Fe) were found on BTA 18, 7, 2, 3, 14, and 2, respectively. No significant SNP was detected for manganese (Mn). Several significant SNPs identified were within or close proximity to CDH13, BHLHE40, EDIL3, HAPLN1, INHBB, USP24, ZFAT, and IKZF2 gene, respectively. Enrichment analysis of the identified candidate genes elucidated biological processes, cellular components, and molecular functions involved in metal ion binding, ion transportation, transmembrane protein, and signaling pathways. This study provided a groundwork to characterize the molecular mechanism for the phenotypic variation in milk protein percentage and minerals in crossbred cattle. Further work is required on a larger sample size with fine mapping of identified QTL to validate potential candidate regions.

Signatures of selection reveal candidate genes involved in production traits in Chinese crossbred buffaloes

Identification of selection signature is important for a better understanding of genetic mechanisms that affect phenotypic differentiation in livestock. However, the genome-wide selection responses have not been investigated for the production traits of Chinese crossbred buffaloes. In this study, an SNP data set of 133 buffaloes (Chinese crossbred buffalo, n = 45; Chinese local swamp buffalo, n = 88) was collected from the Dryad Digital Repository database (https://datadryad.org/stash/). Population genetics analysis showed that these buffaloes were divided into the following 2 groups: crossbred buffalo and swamp buffalo. The crossbred group had higher genetic diversity than the swamp group. Using 3 complementary statistical methods (integrated haplotype score, cross population extended haplotype homozygosity, and composite likelihood ratio), a total of 31 candidate selection regions were identified in the Chinese crossbred population. Here, within these candidate regions, 25 genes were under the putative selection. Among them, several candidate genes were reported to be associated with production traits. In addition, we identified 13 selection regions that overlapped with bovine QTLs that were mainly involved in milk production and composition traits. These results can provide useful insights regarding the selection response for production traits of Chinese crossbred buffalo, as identified candidate genes influence production performance.

Assessing the Genetic Background and Selection Signatures of Huaxi Cattle Using High-Density SNP Array

Huaxi cattle, a specialized beef cattle breed in China, has the characteristics of fast growth, high slaughter rate, and net meat rate, good reproductive performance, strong stress resistance, and wide adaptability. In this study, we evaluated the genetic diversity, population structure, and genetic relationships of Huaxi cattle and its ancestor populations at the genome-wide level, as well as detecting the selection signatures of Huaxi cattle. Principal component analysis (PCA) and phylogenetic analysis revealed that Huaxi cattle were obviously separated from other cattle populations. The admixture analysis showed that Huaxi cattle has distinct genetic structures among all populations at K = 4. It can be concluded that Huaxi cattle has formed its own unique genetic features. Using integrated haplotype score (iHS) and composite likelihood ratio (CLR) methods, we identified 143 and 199 potentially selected genes in Huaxi cattle, respectively, among which nine selected genes (KCNK1, PDLIM5, CPXM2, CAPN14, MIR2285D, MYOF, PKDCC, FOXN3, and EHD3) related to ion binding, muscle growth and differentiation, and immunity were detected by both methods. Our study sheds light on the unique genetic feature and phylogenetic relationship of Huaxi cattle, provides a basis for the genetic mechanism analysis of important economic traits, and guides further intensive breeding improvement of Huaxi cattle.

Estimation of linkage disequilibrium levels and allele frequency distribution in crossbred Vrindavani cattle using 50K SNP data

The objective of this study was to calculate the extent and decay of linkage disequilibrium (LD) in 96 crossbred Vrindavani cattle genotyped with Bovine SNP50K Bead Chip. After filtering, 43,821 SNPs were retained for final analysis, across 2500.3 Mb of autosome. A significant percentage of SNPs was having minor allele frequency of less than 0.20. The extent of LD between autosomal SNPs up to 10 Mb apart across the genome was measured using r² statistic. The mean r² value was 0.43, if pairwise distance of marker was less than10 kb and it decreased further to 0.21 for 25–50 kb markers distance. Further, the effect of minor allele frequency and sample size on LD estimate was investigated. The LD value decreased with the increase in inter-marker distance, and increased with the increase of minor allelic frequency. The estimated inbreeding coefficient and effective population size were 0.04, and 46 for present generation, which indicated small and unstable population of Vrindavani cattle. These findings suggested that a denser or breed specific SNP panel would be required to cover all genome of Vrindavani cattle for genome wide association studies (GWAS).

Comparative Signatures of Selection Analyses Identify Loci Under Positive Selection in the Murrah Buffalo of India

India is home to a large and diverse buffalo population. The Murrah breed of North India is known for its milk production, and it has been used in breeding programs in several countries. Selection signature analysis yield valuable information about how the natural and artificial selective pressures have shaped the genomic landscape of modern-day livestock species. Genotype information was generated on six buffalo breeds of India, namely, Murrah, Bhadawari, Mehsana, Pandharpuri, Surti, and Toda using ddRAD sequencing protocol. Initially, the genotypes were used to carry out population diversity and structure analysis among the six breeds, followed by pair-wise comparisons of Murrah with the other five breeds through XP-EHH and F _ST methodologies to identify regions under selection in Murrah. Admixture results showed significant levels of Murrah inheritance in all the breeds except Pandharpuri. The selection signature analysis revealed six regions in Murrah, which were identified in more than one pair-wise comparison through both XP-EHH and F _ST analyses. The significant regions overlapped with QTLs for milk production, immunity, and body development traits. Genes present in these regions included SLC37A1, PDE9A, PPBP, CXCL6, RASSF6, AFM, AFP, ALB, ANKRD17, CNTNAP2, GPC5, MYLK3, and GPT2. These genes emerged as candidates for future polymorphism studies of adaptability and performance traits in buffaloes. The results also suggested ddRAD sequencing as a useful cost-effective alternative for whole-genome sequencing to carry out diversity analysis and discover selection signatures in Indian buffalo breeds.

The Quest for Genes Involved in Adaptation to Climate Change in Ruminant Livestock

Livestock radiated out from domestication centres to most regions of the world, gradually adapting to diverse environments, from very hot to sub-zero temperatures and from wet and humid conditions to deserts. The climate is changing; generally global temperature is increasing, although there are also more extreme cold periods, storms, and higher solar radiation. These changes impact livestock welfare and productivity. This review describes advances in the methodology for studying livestock genomes and the impact of the environment on animal production, giving examples of discoveries made. Sequencing livestock genomes has facilitated genome-wide association studies to localize genes controlling many traits, and population genetics has identified genomic regions under selection or introgressed from one breed into another to improve production or facilitate adaptation. Landscape genomics, which combines global positioning and genomics, has identified genomic features that enable animals to adapt to local environments. Combining the advances in genomics and methods for predicting changes in climate is generating an explosion of data which calls for innovations in the way big data sets are treated. Artificial intelligence and machine learning are now being used to study the interactions between the genome and the environment to identify historic effects on the genome and to model future scenarios.

Genome-Wide Scanning for Signatures of Selection Revealed the Putative Genomic Regions and Candidate Genes Controlling Milk Composition and Coat Color Traits in Sahiwal Cattle

Background

In the evolutionary time scale, selection shapes the genetic variation and alters the architecture of genome in the organisms. Selection leaves detectable signatures at the genomic coordinates that provide clues about the protein-coding regions. Sahiwal is a valuable indicine cattle adapted to tropical environments with desirable milk attributes. Insights into the genomic regions under putative selection may reveal the molecular mechanisms affecting the quantitative and other important traits. To understand this, the present investigation was undertaken to explore signatures of selection in the genome of Sahiwal cattle using a medium-density genotyping INDUS chip.

Result

De-correlated composite of multiple selection signals (DCMS), which combines five different univariate statistics, was computed in the dataset to detect the signatures of selection in the Sahiwal genome. Gene annotations, Quantitative Trait Loci (QTL) enrichment, and functional analyses were carried out for the identification of significant genomic regions. A total of 117 genes were identified, which affect a number of important economic traits. The QTL enrichment analysis highlighted 14 significant [False Discovery Rate (FDR)-corrected p-value ≤ 0.05] regions on chromosomes BTA 1, 3, 6, 11, 20, and 21. The top three enriched QTLs were found on BTA 6, 20, and 23, which are associated with exterior, health, milk production, and reproduction traits. The present study on selection signatures revealed some key genes related with coat color (PDGFRA, KIT, and KDR), facial pigmentation (LEF), milk fat percent (MAP3K1, HADH, CYP2U1, and SGMS2), sperm membrane integrity (OSTC), lactation persistency (MRPS30, NNT, CCL28, HMGCS1, NIM1K, ZNF131, and CCDC152), milk yield (GHR and ZNF469), reproduction (NKX2-1 and DENND1A), and bovine tuberculosis susceptibility (RNF144B and PAPSS1). Further analysis of candidate gene prioritization identified four hub genes, viz., KIT, KDR, MAP3K1, and LEF, which play a role in coat color, facial pigmentation, and milk fat percentage in cattle. Gene enrichment analysis revealed significant Gene ontology (GO) terms related to breed-specific coat color and milk fat percent.

Conclusion

The key candidate genes and putative genomic regions associated with economic traits were identified in Sahiwal using single nucleotide polymorphism data and the DCMS method. It revealed selection for milk production, coat color, and adaptability to tropical climate. The knowledge about signatures of selection and candidate genes affecting phenotypes have provided a background information that can be further utilized to understand the underlying mechanism involved in these traits in Sahiwal cattle.

Identification of genes affecting milk fat and fatty acid composition in Vrindavani crossbred cattle using 50 K SNP-Chip

The aim of this study was to identify candidate genes associated with milk fat per cent and fatty acid (FA) composition in Vrindavani cattle using the Illumina 50 K single-nucleotide polymorphism (SNP) array. After quality control, a total of 41,427 informative and high-quality SNPs were used for a genome-wide association study (GWAS) for milk fat percentage and 16 different types of fatty acids. Lactation stage, parity, test day milk yield, and proportion of exotic inheritance were included as fixed effects in the GWAS model. A total of 67 genome-wide significant (P < 1.20 × 10^-06) SNPs and 176 suggestive significant (P < 2.41 × 10^-05) SNPs were identified. Out of these, 15 SNPs were associated with more than one trait. The strongest associations were found on BTA14 for milk fat percentage and on BTA2 and BTA16 for polyunsaturated fatty acids. Several significant SNPs were identified close to or within the genes ELOVL6, FABP4, PMP2, PLIN1, MFGE8, GHRL2, and LDLRAD3 which are known to be associated with fat percentage and FA composition in dairy cattle breeds. This study is a step forward to better characterize the molecular mechanisms of phenotypic variation in milk fatty acids in a taurine-indicine composite cattle breed reared in tropical environments.