Genome-wide association study for milk production in Egyptian buffalo

Transcriptome-Wide Association Study Reveals Potentially Candidate Genes Responsible for Milk Production Traits in Buffalo

Identifying key causal genes is critical for unraveling the genetic basis of complex economic traits, yet it remains a formidable challenge. The advent of large-scale sequencing data and computational algorithms, such as transcriptome-wide association studies (TWASs), offers a promising avenue for identifying potential causal genes. In this study, we harnessed the power of TWAS to identify genes potentially responsible for milk production traits, including daily milk yield (MY), fat percentage (FP), and protein percentage (PP), within a cohort of 100 buffaloes. Our approach began by generating the genotype and expression profiles for these 100 buffaloes through whole-genome resequencing and RNA sequencing, respectively. Through comprehensive genome-wide association studies (GWAS), we pinpointed a total of seven and four single nucleotide polymorphisms (SNPs) significantly associated with MY and FP traits, respectively. By using TWAS, we identified 55, 71, and 101 genes as significant signals for MY, FP, and PP traits, respectively. To delve deeper, we conducted protein-protein interaction (PPI) analysis, revealing the categorization of these genes into distinct PPI networks. Interestingly, several TWAS-identified genes within the PPI network played a vital role in milk performance. These findings open new avenues for identifying potentially causal genes underlying important traits, thereby offering invaluable insights for genomics and breeding in buffalo populations.

TWAS revealed significant causal loci for milk production and its composition in Murrah buffaloes

Milk yield is the most complex trait in dairy animals, and mapping all causal variants even with smallest effect sizes has been difficult with the genome-wide association study (GWAS) sample sizes available in geographical regions with small livestock holdings such as Indian sub-continent. However, Transcriptome-wide association studies (TWAS) could serve as an alternate for fine mapping of expression quantitative trait loci (eQTLs). This is a maiden attempt to identify milk production and its composition related genes using TWAS in Murrah buffaloes (Bubalus bubalis). TWAS was conducted on a test (N = 136) set of Murrah buffaloes genotyped through ddRAD sequencing. Their gene expression level was predicted using reference (N = 8) animals having both genotype and mammary epithelial cell (MEC) transcriptome information. Gene expression prediction was performed using Elastic-Net and Dirichlet Process Regression (DPR) model with fivefold cross-validation and without any cross-validation. DPR model without cross-validation predicted 80.92% of the total genes in the test group of Murrah buffaloes which was highest compared to other methods. TWAS in test individuals based on predicted gene expression, identified a significant association of one unique gene for Fat%, and two for SNF% at Bonferroni corrected threshold. The false discovery rates (FDR) corrected P-values of the top ten SNPs identified through GWAS were comparatively higher than TWAS. Gene ontology of TWAS-identified genes was performed to understand the function of these genes, it was revealed that milk production and composition genes were mainly involved in Relaxin, AMPK, and JAK-STAT signaling pathway, along with CCRI, and several key metabolic processes. The present study indicates that TWAS offers a lower false discovery rate and higher significant hits than GWAS for milk production and its composition traits. Hence, it is concluded that TWAS can be effectively used to identify genes and cis-SNPs in a population, which can be used for fabricating a low-density genomic chip for predicting milk production in Murrah buffaloes.

A Single-Step Genome-Wide Association Study for Semen Traits of Egyptian Buffalo Bulls

The present study aimed to contribute to the limited research on buffalo (Bubalus bubalis) semen traits by incorporating genomic data. A total of 8465 ejaculates were collected. The genotyping procedure was conducted using the Axiom® Buffalo Genotyping 90 K array designed by the Affymetrix Expert Design Program. After conducting a quality assessment, we utilized 67,282 SNPs genotyped in 192 animals. We identified several genomic loci explaining high genetic variance by employing single-step genomic evaluation. The aforementioned regions were located on buffalo chromosomes no. 3, 4, 6, 7, 14, 16, 20, 22, and the X-chromosome. The X-chromosome exhibited substantial influence, accounting for 4.18, 4.59, 5.16, 5.19, and 4.31% of the genomic variance for ejaculate volume, mass motility, livability, abnormality, and concentration, respectively. In the examined genomic regions, we identified five novel candidate genes linked to male fertility and spermatogenesis, four in the X-chromosome and one in chromosome no. 16. Additional extensive research with larger sample sizes and datasets is imperative to validate these findings and evaluate their applicability for genomic selection.

Genome-wide association study revealed suggestive QTLs for production and reproduction traits in Indian Murrah buffalo

The present study was aimed to identify the genome-wide SNPs associated with production and reproduction traits in 96 Indian Murrah buffalo genotyped based on ddRAD approach using Genome-Wide Association Study (GWAS) along with phenotypes of contemporary animals using mixed linear model for production and reproduction traits. A total of 27,735 SNPs identified using ddRAD approach in 96 Indian Murrah buffaloes were used for GWAS. A total of 28 SNPs were found to be associated with production and reproductive traits. Among these, 14 SNPs were present in the intronic region of AK5, BACH2, DIRC2, ECPAS, MPZL1, MYO16, QRFPR, RASGRF1, SLC9A4, TANC1, and TRIM67 genes and one SNP in long non-coding region of LOC102414911. Out of these 28 SNPs, 9 SNPs were found to have pleiotropic effect over milk production traits and were present in chromosome number BBU 1, 2, 4, 6, 9, 10, 12, 19, and 20. SNPs in the intronic region of AK5, TRIM67 genes were found to be associated with milk production traits. Eleven and five SNPs in the intergenic region were associated with milk production and reproduction traits respectively. The above genomic information may be used for selection of Murrah animals for genetic improvement.

Whole-genome selective scans detect genes associated with important phenotypic traits in goat (Capra hircus)

Goats with diverse economic phenotypic traits play an important role in animal husbandry. However, the genetic mechanisms underlying complex phenotypic traits are unclear in goats. Genomic studies of variations provided a lens to identify functional genes. In this study, we focused on the worldwide goat breeds with outstanding traits and used whole-genome resequencing data in 361 samples from 68 breeds to detect genomic selection sweep regions. We identified 210-531 genomic regions with six phenotypic traits, respectively. Further gene annotation analysis revealed 332, 203, 164, 300, 205, and 145 candidate genes corresponding with dairy, wool, high prolificacy, poll, big ear, and white coat color traits. Some of these genes have been reported previously (e.g., KIT, KITLG, NBEA, RELL1, AHCY, and EDNRA), while we also discovered novel genes, such as STIM1, NRXN1, LEP, that may be associated with agronomic traits like poll and big ear morphology. Our study found a set of new genetic markers for genetic improvement in goats and provided novel insights into the genetic mechanisms of complex traits.

An Integrative Genomic Prediction Approach for Predicting Buffalo Milk Traits by Incorporating Related Cattle QTLs

Background: The 90K Axiom Buffalo SNP Array is expected to improve and speed up various genomic analyses for the buffalo (Bubalus bubalis). Genomic prediction is an effective approach in animal breeding to improve selection and reduce costs. As buffalo genome research is lagging behind that of the cow and production records are also limited, genomic prediction performance will be relatively poor. To improve the genomic prediction in buffalo, we introduced a new approach (pGBLUP) for genomic prediction of six buffalo milk traits by incorporating QTL information from the cattle milk traits in order to help improve the prediction performance for buffalo. Results: In simulations, the pGBLUP could outperform BayesR and the GBLUP if the prior biological information (i.e., the known causal loci) was appropriate; otherwise, it performed slightly worse than BayesR and equal to or better than the GBLUP. In real data, the heritability of the buffalo genomic region corresponding to the cattle milk trait QTLs was enriched (fold of enrichment > 1) in four buffalo milk traits (FY270, MY270, PY270, and PM) when the EBV was used as the response variable. The DEBV as the response variable yielded more reliable genomic predictions than the traditional EBV, as has been shown by previous research. The performance of the three approaches (GBLUP, BayesR, and pGBLUP) did not vary greatly in this study, probably due to the limited sample size, incomplete prior biological information, and less artificial selection in buffalo. Conclusions: To our knowledge, this study is the first to apply genomic prediction to buffalo by incorporating prior biological information. The genomic prediction of buffalo traits can be further improved with a larger sample size, higher-density SNP chips, and more precise prior biological information.

Whole-Genome-Based Web Genomic Resource for Water Buffalo (Bubalus bubalis)

Water buffalo (Bubalus bubalis), belonging to the Bovidae family, is an economically important animal as it is the major source of milk, meat, and drought in numerous countries. It is mainly distributed in tropical and subtropical regions with a global population of approximately 202 million. The advent of low cost and rapid sequencing technologies has opened a new vista for global buffalo researchers. In this study, we utilized the genomic data of five commercially important buffalo breeds, distributed globally, namely, Mediterranean, Egyptian, Bangladesh, Jaffrarabadi, and Murrah. Since there is no whole-genome sequence analysis of these five distinct buffalo breeds, which represent a highly diverse ecosystem, we made an attempt for the same. We report the first comprehensive, holistic, and user-friendly web genomic resource of buffalo (BuffGR) accessible at http://backlin.cabgrid.res.in/buffgr/, that catalogues 6028881 SNPs and 613403 InDels extracted from a set of 31 buffalo tissues. We found a total of 7727122 SNPs and 634124 InDels distributed in four breeds of buffalo (Murrah, Bangladesh, Jaffarabadi, and Egyptian) with reference to the Mediterranean breed. It also houses 4504691 SSR markers from all the breeds along with 1458 unique circRNAs, 37712 lncRNAs, and 938 miRNAs. This comprehensive web resource can be widely used by buffalo researchers across the globe for use of markers in marker trait association, genetic diversity among the different breeds of buffalo, use of ncRNAs as regulatory molecules, post-transcriptional regulations, and role in various diseases/stresses. These SNPs and InDelscan also be used as biomarkers to address adulteration and traceability. This resource can also be useful in buffalo improvement programs and disease/breed management.

The Candidate Chromosomal Regions Responsible for Milk Yield of Cow: A GWAS Meta-Analysis

Milk yield (MY) is highly heritable and an economically important trait in dairy livestock species. To increase power to detect candidate genomic regions for this trait, we carried out a meta-analysis of genome-wide association studies (GWAS). In the present study, we identified 19 studies in PubMed for the meta-analysis. After review of the studies, 16 studies passed the filters for meta-analysis, and the number of chromosomes, detected markers and their positions, number of animals, and p-values were extracted from these studies and recorded. The final data set based on 16 GWAS studies had 353,698 cows and 3950 markers and was analyzed using METAL software. Our findings revealed 1712 significant (p-value < 2.5 × 10−6) genomic loci related to MY, with markers associated with MY found on all autosomes and sex chromosomes and the majority of them found on chromosome 14. Furthermore, gene ontology (GO) annotation was used to explore biological functions of the genes associated with MY; therefore, different regions of this chromosome may be suitable as genomic regions for further research into gene expression.

Whole-Genome Sequencing and Characterization of Buffalo Genetic Resources: Recent Advances and Future Challenges

The buffalo was domesticated around 3000-6000 years ago and has substantial economic significance as a meat, dairy, and draught animal. The buffalo has remained underutilized in terms of the development of a well-annotated and assembled reference genome de novo. It is mandatory to explore the genetic architecture of a species to understand the biology that helps to manage its genetic variability, which is ultimately used for selective breeding and genomic selection. Morphological and molecular data have revealed that the swamp buffalo population has strong geographical genomic diversity with low gene flow but strong phenotypic consistency, while the river buffalo population has higher phenotypic diversity with a weak phylogeographic structure. The availability of recent high-quality reference genome and genotyping marker panels has invigorated many genome-based studies on evolutionary history, genetic diversity, functional elements, and performance traits. The increasing molecular knowledge syndicate with selective breeding should pave the way for genetic improvement in the climatic resilience, disease resistance, and production performance of water buffalo populations globally.

Genetic Association of PPARGC1A Gene Single Nucleotide Polymorphism with Milk Production Traits in Italian Mediterranean Buffalo

PPARGC1A gene plays an important role in the activation of various important hormone receptors and transcriptional factors involved in the regulation of adaptive thermogenesis, gluconeogenesis, fiber-type switching in skeletal muscle, mitochondrial biogenesis, and adipogenesis, regulating the reproduction and proposed as a candidate gene for milk-related traits in cattle. This study identified polymorphisms in the PPARGC1A gene in Italian Mediterranean buffaloes and their associations to milk production and quality traits (lactation length, peak milk yield, fat and protein yield, and percentage). As a result, a total of seven SNPs (g.-78A>G, g.224651G>C, g.286986G>A, g.304050G>A, g.325647G>A, g.325817T>C, and g.325997G>A) were identified by DNA pooled sequencing. Analysis of productivity traits within the genotyped animals revealed that the g.286986G>A located at intron 4 was associated with milk production traits, but the g.325817T>C had no association with milk production. Polymorphisms in g.-78A>G was associated with peak milk yield and milk yield, while g.304050G>A and g.325997 G>A were associated with both milk yield and protein percentage. Our findings suggest that polymorphisms in the buffalo PPARGC1A gene are associated with milk production traits and can be used as a candidate gene for milk traits and marker-assisted selection in the buffalo breeding program.

The distribution of runs of homozygosity in the genome of river and swamp buffaloes reveals a history of adaptation, migration and crossbred events

Background

Water buffalo is one of the most important livestock species in the world. Two types of water buffalo exist: river buffalo (Bubalus bubalis bubalis) and swamp buffalo (Bubalus bubalis carabanensis). The buffalo genome has been recently sequenced, and thus a new 90 K single nucleotide polymorphism (SNP) bead chip has been developed. In this study, we investigated the genomic population structure and the level of inbreeding of 185 river and 153 swamp buffaloes using runs of homozygosity (ROH). Analyses were carried out jointly and separately for the two buffalo types.

Results

The SNP bead chip detected in swamp about one-third of the SNPs identified in the river type. In total, 18,116 ROH were detected in the combined data set (17,784 SNPs), and 16,251 of these were unique. ROH were present in both buffalo types mostly detected (~ 59%) in swamp buffalo. The number of ROH per animal was larger and genomic inbreeding was higher in swamp than river buffalo. In the separated datasets (46,891 and 17,690 SNPs for river and swamp type, respectively), 19,760 and 10,581 ROH were found in river and swamp, respectively. The genes that map to the ROH islands are associated with the adaptation to the environment, fitness traits and reproduction.

Conclusions

Analysis of ROH features in the genome of the two water buffalo types allowed their genomic characterization and highlighted differences between buffalo types and between breeds. A large ROH island on chromosome 2 was shared between river and swamp buffaloes and contained genes that are involved in environmental adaptation and reproduction.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12711-021-00616-3.

Prospecting genomic regions associated with milk production traits in Egyptian buffalo

The objectives of the current study were to detect putative genomic loci and to identify candidate genes associated with milk production traits in Egyptian buffalo. A total number of 161 479 daily milk yield (DMY) records and 60 318 monthly measures for fat and protein percentages (FP and PP, respectively), along with fat and protein yields (FY and PY, respectively) from 1670 animals were used. Genotyping was performed using Axiom® Buffalo Genotyping 90 K array. Genome-wide association study (GWAS) for each trait was performed using PLINK. After Bonferroni correction, 47 SNPs were associated with one or more milk production traits. These SNPs were distributed over 36 quantitative trait loci (QTL) and located on 20 buffalo chromosomes (BBU). For the 47 SNPs, one was overlapped for three traits (DMY, FY, and PY), six were associated with two traits (one for PP and PY and five for FY and PY) while the rest were associated with only one trait. Out of 36 identified QTL, eleven were overlapped with previously reported loci in buffalo and/or cattle populations. Some of these SNPs are placed within or close to potential candidate genes, for example: TPD52, ZBTB10, RALYL and SNX16 on BBU15, ADGRD1 on BBU17, ESRRG on BBU5 and GRIP1 on BBU4. This is the first reported study between genome-wide markers and milk components in Egyptian buffalo. Our findings provide useful information to explore the genetic mechanisms and relevant genes contributing to the variation in milk production traits. Further confirmation studies with larger population size are necessary to validate the findings and detect the causal genetic variants.

Identification of genomic regions related to age at first calving and first calving interval in water buffalo using single-step GBLUP

In Brazil, water buffaloes have been used to produce milk for mozzarella cheese production. Consequently, the main selection criterion applied for the buffalo genetic improvement is the estimated mozzarella yield as a function of milk, fat and protein production. However, given the importance of reproductive traits in production systems, this study aimed to use techniques for identifying genomic regions that affect the age at first calving (AFC) and first calving interval (FCI) in buffalo cows and to select candidate genes for the identification of QTL and gene expression studies. The single-step GBLUP method was used for the identification of genomic regions. Windows of 1 Mb containing single-nucleotide polymorphisms were constructed and the 10 windows that explained the greatest proportion of genetic variance were considered candidate regions for each trait. Genes present into the selected windows were identified using the UOA_WB_1 assembly as the reference, and their ontology was defined with the Panther tool. Candidate regions for both traits were identified on BBU 3, 12, 21 and 22; for AFC, candidates were detected on BBU 6, 7, 8, 9 and 15 and for first calving interval on BBU 4, 14 and 19. This study identified regions with great contribution to the additive genetic variance of age at first calving and first calving interval in the population of buffalo cows studied. The ROCK2, PMVK, ADCY2, MAP2K6, BMP10 and GFPT1 genes are main candidates for reproductive traits in water dairy buffaloes, and these results may have future applications in animal breeding programs or in gene expression studies of the species.

The development of genome-wide single nucleotide polymorphisms in blue wildebeest using the DArTseq platform

Blue wildebeest (Connochaetes taurinus taurinus) are economically important antelope that are widely utilised in the South African wildlife industry. However, very few genomic resources are available for blue wildebeest that can assist in breeding management and facilitate research. This study aimed to develop a set of genome-wide single nucleotide polymorphism (SNP) markers for blue wildebeest. The DArTseq genotyping platform, commonly used in polyploid plant species, was selected for SNP discovery. A limited number of published articles have described the use of the DArTseq platform in animals and, therefore, this study also provided a unique opportunity to assess the performance of the DArTseq platform in an animal species. A total of 20,563 SNPs, each located within a 69 bp sequence, were generated. The developed SNP markers had a high average scoring reproducibility (>99%) and a low percentage missing data (~9.21%) compared to other reduced representation sequencing approaches that have been used in animal studies. Furthermore, the number of candidate SNPs per nucleotide position decreased towards the 3' end of sequence reads, and the ratio of transitions (Ts) to transversions (Tv) remained similar for each read position. These observations indicate that there was no read position bias, such as the identification of false SNPs due to low sequencing quality, towards the tail-end of sequencing reads. The DArTseq platform was also successful in identifying a large number of informative SNPs with desirable polymorphism parameters such as a high minor allele frequency (MAF). The Bos taurus genome was used for the in silico mapping of the marker sequences and a total of 6020 (29.28%) sequences were successfully mapped against the bovine genome. The marker sequences mapped to all of the bovine chromosomes establishing the genome-wide distribution of the SNPs. Moreover, the high observed Ts:Tv ratio (2.84:1) indicate that the DArTseq platform targeted gene-rich regions of the blue wildebeest genome. Finally, functional annotation of the marker sequences revealed a wide range of different putative functions indicating that these SNP markers can be useful in functional gene studies. The DArTseq platform, therefore, represents a high-throughput, robust and cost-effective genotyping platform, which may find adoption in several other African antelope and animal species.

Genome-wide identification of Diacylglycerol Acyltransferases (DGAT) family genes influencing Milk production in Buffalo

Background

The diacylglycerol acyltransferases (DGAT) are a vital group of enzymes in catalyzing triacylglycerol biosynthesis. DGAT genes like DGAT1 and DGAT2, have been identified as two functional candidate genes affecting milk production traits, especially for fat content in milk. Buffalo milk is famous for its excellent quality, which is rich in fat and protein content. Therefore, this study aimed to characterize DGAT family genes in buffalo and to find candidate markers or DGAT genes influencing lactation performance.

Results

We performed a genome-wide study and identified eight DGAT genes in buffalo. All the DGAT genes classified into two distinct clades (DGAT1 and DGAT2 subfamily) based on their phylogenetic relationships and structural features. Chromosome localization displayed eight buffalo DGAT genes distributed on five chromosomes. Collinearity analysis revealed that the DGAT family genes were extensive homologous between buffalo and cattle. Afterward, we discovered genetic variants loci within the genomic regions that DGAT genes located in buffalo. Seven haplotype blocks were constructed and were associated with buffalo milk production traits. Single marker association analyses revealed four most significant single nucleotide polymorphisms (SNPs) mainly affecting milk protein percentage or milk fat yield in buffalo. Genes functional analysis indicated that these DGAT family genes could influence lactation performance in the mammal through regulating lipid metabolism.

Conclusion

In the present study, we performed a comprehensive analysis for the DGAT family genes in buffalo, which including identification, structural characterization, phylogenetic classification, chromosomal distribution, collinearity analysis, association analysis, and functional analysis. These findings provide useful information for an in-depth study to determine the role of DGAT family gens play in the regulation of milk production and milk quality improvement in buffalo.

Genome-wide analysis reveals genetic diversity, linkage disequilibrium, and selection for milk production traits in Chinese buffalo breeds

The water buffalo is an important dual-purpose livestock that is widespread throughout central and southern China. However, there has been no characterization of the population genetics of Chinese buffalo. Using an Axiom buffalo genotyping array (Thermo Fisher Scientific, Wilmington, DE), we analyzed the genetic diversity, linkage disequilibrium pattern, and signature of selection in 176 Chinese buffaloes from 13 breeds. A total of 35,547 SNP passed quality control and were used for further analyses. Population genetic analysis revealed a clear separation between swamp and river types. Ten Chinese indigenous breeds were clustered into the swamp group, the Murrah and Nili-Ravi breeds were clustered into the river group, and the crossbred breed was closer to the river group. Genetic diversity analysis showed that the swamp group had a lower average expected heterozygosity. Linkage disequilibrium decay distance was much shorter in the swamp group compared with the river group, with an average square of correlation coefficient value of 0.2 of approximately 50 kb. Analysis of runs of homozygosity indicated extensive remote and recent inbreeding within swamp and river groups, respectively. Moreover, one genomic region under selection was detected between the river and swamp groups. Our findings contribute to our understanding of the characterization of population genetics in Chinese buffaloes, which in turn may be used in buffalo breeding programs.

Genomic measures of inbreeding coefficients and genome-wide scan for runs of homozygosity islands in Iranian river buffalo, Bubalus bubalis

Background

Consecutive homozygous fragments of a genome inherited by offspring from a common ancestor are known as runs of homozygosity (ROH). ROH can be used to calculate genomic inbreeding and to identify genomic regions that are potentially under historical selection pressure. The dataset of our study consisted of 254 Azeri (AZ) and 115 Khuzestani (KHZ) river buffalo genotyped for ~ 65,000 SNPs for the following two purposes: 1) to estimate and compare inbreeding calculated using ROH (F_ROH), excess of homozygosity (F_HOM), correlation between uniting gametes (F_UNI), and diagonal elements of the genomic relationship matrix (F_GRM); 2) to identify frequently occurring ROH (i.e. ROH islands) for our selection signature and gene enrichment studies.

Results

In this study, 9102 ROH were identified, with an average number of 21.2 ± 13.1 and 33.2 ± 15.9 segments per animal in AZ and KHZ breeds, respectively. On average in AZ, 4.35% (108.8 ± 120.3 Mb), and in KHZ, 5.96% (149.1 ± 107.7 Mb) of the genome was autozygous. The estimated inbreeding values based on F_HOM, F_UNI and F_GRM were higher in AZ than they were in KHZ, which was in contrast to the F_ROH estimates. We identified 11 ROH islands (four in AZ and seven in KHZ). In the KHZ breed, the genes located in ROH islands were enriched for multiple Gene Ontology (GO) terms (P ≤ 0.05). The genes located in ROH islands were associated with diverse biological functions and traits such as body size and muscle development (BMP2), immune response (CYP27B1), milk production and components (MARS, ADRA1A, and KCTD16), coat colour and pigmentation (PMEL and MYO1A), reproductive traits (INHBC, INHBE, STAT6 and PCNA), and bone development (SUOX).

Conclusion

The calculated F_ROH was in line with expected higher inbreeding in KHZ than in AZ because of the smaller effective population size of KHZ. Thus, we find that F_ROH can be used as a robust estimate of genomic inbreeding. Further, the majority of ROH peaks were overlapped with or in close proximity to the previously reported genomic regions with signatures of selection. This tells us that it is likely that the genes in the ROH islands have been subject to artificial or natural selection.

Genome-wide association study applied to type traits related to milk yield in water buffaloes (Bubalus bubalis)

This research aimed to estimate genetic parameters for milk yield and type traits [withers height (WH), croup height (CH), body length (BL), croup length (CL), iliac width (ILW), ischial width (ISW), and thoracic circumference] in Murrah buffaloes and to identify genomic regions related to type traits by applying a single-step genome-wide association study. Data used to estimate the genetic parameters consisted of 601 records of milk yield in the first lactation and the aforementioned type traits. For the single-step genome-wide association study, 322 samples genotyped with a 90K Axiom Buffalo Genotyping array (Thermo Fisher Scientific, Santa Clara, CA) were used. Bivariate analysis revealed that heritability for milk yield (kg) at 305 d was 0.31 ± 0.11, whereas it ranged from 0.22 ± 0.07 to 0.34 ± 0.09 for the studied conformation traits. Based on the percentages of genetic variance explained by windows of 10 markers, there were 16 genomic regions explaining more than 0.5% of the variance for WH, CH, BL, CL, ILW, ISW, and thoracic circumference. Between those regions, 4 were associated with more than 1 trait, suggesting pleiotropic roles for some genes of Bos taurus autosome (BTA) 12 on CL and WH, BTA13 on ISW and ILW, BTA23 on CH and BL, and BTA28 on ISW and BL. Most of these regions coincide with known quantitative trait loci for milk traits. Thus, further studies based on sequence data will help to validate the association of this region with type traits and likely identify the causal mutations.

Systematic analyses for candidate genes of milk production traits in water buffalo (Bubalus Bubalis)

Water buffalo (Bubalus bubalis) is of great economic importance as a provider of milk and meat in many countries. However, the milk yield of buffalo is much lower than that of Holstein cows. Selection of candidate genes related to milk production traits can be applied to improve buffalo milk performance. A systematic review of studies of these candidate genes will be greatly beneficial for researchers to timely and efficiently understand the research development of molecular markers for buffalo milk production traits. Here, we identified and classified the candidate genes associated with buffalo milk production traits. A total of 517 candidate genes have been identified as being associated with milk performance in different buffalo breeds. Nineteen candidate genes containing 47 mutation sites have been identified using the candidate gene approach. In addition, 499 candidate genes have been identified in six genome-wide association studies (GWASes) including two studies performed with the bovine SNP chip and four studies with the buffalo SNP chip. Genes CTNND2 (catenin delta 2), APOB (apolipoprotein B), FHIT (fragile histidine triad) and ESRRG (estrogen related receptor gamma) were identified in at least two GWASes. These four genes, especially APOB, deserve further study to explore regulatory roles in buffalo milk production. With growth in the number of buffalo genomic studies, more candidate genes associated with buffalo milk production traits will be identified. Therefore, future studies, such as those investigating gene location and functional analyses, are necessary to facilitate the exploitation of genetic potential and the improvement of buffalo milk performance.

Integrative Analysis of Transcriptome and GWAS Data to Identify the Hub Genes Associated With Milk Yield Trait in Buffalo

The mammary gland is the production organ in mammals that is of great importance for milk production and quality. However, characterization of the buffalo mammary gland transcriptome and identification of the valuable candidate genes that affect milk production is limited. Here, we performed the differential expressed genes (DEGs) analysis of mammary gland tissue on day 7, 50, 140, and 280 after calving and conducted gene-based genome-wide association studies (GWAS) of milk yield in 935 Mediterranean buffaloes. We then employed weighted gene co-expression network analysis (WGCNA) to identify specific modules and hub genes related to milk yield based on gene expression profiles and GWAS data. The results of the DEGs analysis showed that a total of 1,420 DEGs were detected across different lactation points. In the gene-based analysis, 976 genes were found to have genome-wide association (P ≤ 0.05) that could be defined as the nominally significant GWAS geneset (NSGG), 9 of which were suggestively associated with milk yield (P < 10⁻⁴). Using the WGCNA analysis, 544 and 225 genes associated with milk yield in the turquoise module were identified from DEGs and NSGG datasets, respectively. Several genes (including BNIPL, TUBA1C, C2CD4B, DCP1B, MAP3K5, PDCD11, SRGAP1, GDPD5, BARX2, SCARA3, CTU2, and RPL27A) were identified and considered as the hub genes because they were involved in multiple pathways related to milk production. Our findings provide an insight into the dynamic characterization of the buffalo mammary gland transcriptome, and these potential candidate genes may be valuable for future functional characterization of the buffalo mammary gland.

Use of single-step genome-wide association studies for prospecting genomic regions related to milk production and milk quality of buffalo

The aim of this research communication was to identify chromosome regions and genes that could be related to milk yield (MY), milk fat (%F) and protein percentage (%P) in Brazilian buffalo cows using information from genotyped and non-genotyped animals. We used the 90 K Axiom® Buffalo Genotyping array. A repeatability model was used. An iterative process was performed to calculate the weights of markers as a function of the squared effects of Single Nucleotide Polymorphism (SNP) and allele frequencies. The 10 SNPs with the largest effects for MY, %F and %P were studied and they explained 7·48, 9·94 and 6·56% of the genetic variance, respectively. These regions harbor genes with biological functions that could be related to the traits analyzed. The identification of such regions and genes will contribute to a better understanding of their influence on milk production and milk quality traits of buffaloes.

Genome-wide association studies to identify quantitative trait loci affecting milk production traits in water buffalo

Water buffalo is the second largest resource of milk supply around the world, and it is well known for its distinctive milk quality in terms of fat, protein, lactose, vitamin, and mineral contents. Understanding the genetic architecture of milk production traits is important for future improvement by the buffalo breeding industry. The advance of genome-wide association studies (GWAS) provides an opportunity to identify potential genetic variants affecting important economical traits. In the present study, GWAS was performed for 489 buffaloes with 1,424 lactation records using the 90K Affymetrix Buffalo SNP Array (Affymetrix/Thermo Fisher Scientific, Santa Clara, CA). Collectively, 4 candidate single nucleotide polymorphisms (SNP) in 2 genomic regions were found to associate with buffalo milk production traits. One region affecting milk fat and protein percentage was located on the equivalent of Bos taurus autosome (BTA)3, spanning 43.3 to 43.8 Mb, which harbored the most likely candidate genes MFSD14A, SLC35A3, and PALMD. The other region on the equivalent of BTA14 at 66.5 to 67.0 Mb contained candidate genes RGS22 and VPS13B and influenced buffalo total milk yield, fat yield, and protein yield. Interestingly, both of the regions were reported to have quantitative trait loci affecting milk performance in dairy cattle. Furthermore, we suggest that buffaloes with the C allele at AX-85148558 and AX-85073877 loci and the G allele at AX-85106096 locus can be selected to improve milk fat yield in this buffalo-breeding program. Meanwhile, the G allele at AX-85063131 locus can be used as the favorable allele for improving milk protein percentage. Genomic prediction showed that the reliability of genomic estimated breeding values (GEBV) of 6 milk production traits ranged from 0.06 to 0.22, and the correlation between estimated breeding values and GEBV ranged from 0.23 to 0.35. These findings provide useful information to understand the genetic basis of buffalo milk properties and may play a role in accelerating buffalo breeding programs using genomic approaches.

Genomic differentiation between swamp and river buffalo using a cattle high-density single nucleotide polymorphisms panel

Buffalo (Bubalus bubalis) is an important livestock species in many tropical and subtropical regions. In recent decades, the interest in buffalo's milk have expanded and intensive buffalo farms start to emerge. However, breeding programs and population genetics information for this species is scarce or inexistent. The present study aims to test the suitability of the commercial high-density single nucleotide polymorphisms (SNP) genotyping panel, the Illumina BovineHD BeadChip, to estimate population genetics parameters, pedigree control and identification of common variants in major production candidate genes. From a total of 777 962 SNPs included in the panel, 20 479 were polymorphic in water buffalo at a call rate of 86% and an average expected heterozygosity (HE) of 0.306. From these, 357 were mapped within or around the flanking regions of several major candidate genes. A principal components analysis identified three different clusters, each representing pure swamp buffalo type, pure river buffalo type and admixed river buffalo. The hybrids between swamp and river buffalo were clearly identified as an intermediary cluster. The suitability of these SNPs data set for parentage and identity testing demonstrated that the combination of just 30 to 50 SNPs were enough to attain high probabilities of parentage exclusion (0.9999) in both types and identity (2.3×10-5 and 2.0×10-7) for river and swamp buffalo, respectively. Our analysis confirms the suitability of the BovineHD BeadChip to assess population structure, hybridization and identity of the water buffalo populations.