The domestic water buffalo is native to the Asian continent but through historical migrations and recent importations, nowadays has a worldwide distribution. The two types of water buffalo, i.e., river and swamp, display distinct morphological and behavioral traits, different karyotypes and also have different purposes and geographical distributions. River buffaloes from Pakistan, Iran, Turkey, Egypt, Romania, Bulgaria, Italy, Mozambique, Brazil and Colombia, and swamp buffaloes from China, Thailand, Philippines, Indonesia and Brazil were genotyped with a species-specific medium-density 90K SNP panel. We estimated the levels of molecular diversity and described population structure, which revealed historical relationships between populations and migration events. Three distinct gene pools were identified in pure river as well as in pure swamp buffalo populations. Genomic admixture was seen in the Philippines and in Brazil, resulting from importations of animals for breed improvement. Our results were largely consistent with previous archeological, historical and molecular-based evidence for two independent domestication events for river- and swamp-type buffaloes, which occurred in the Indo-Pakistani region and close to the China/Indochina border, respectively. Based on a geographical analysis of the distribution of diversity, our evidence also indicated that the water buffalo spread out of the domestication centers followed two major divergent migration directions: river buffaloes migrated west from the Indian sub-continent while swamp buffaloes migrated from northern Indochina via an east-south-eastern route. These data suggest that the current distribution of water buffalo diversity has been shaped by the combined effects of multiple migration events occurred at different stages of the post-domestication history of the species.

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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.

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.

BackgroundFertility is a complex trait that has a major impact on the development of the buffalo industry. Genome-wide association study (GWAS) has increased the ability to detect genes influencing complex traits, and many important genes related to reproductive traits have been identified in ruminants. However, reproductive traits are influenced by many factors. The development of the follicle is one of the most important internal processes affecting fertility. Genes found by GWAS to be associated with follicular development may directly affect fertility. The present study combined GWAS and RNA-seq of follicular granulosa cells to identify important genes which may affect fertility in the buffalo.ResultsThe 90 K Affymetrix Axiom Buffalo SNP Array was used to identify the SNPs, genomic regions, and genes that were associated with reproductive traits. A total of 40 suggestive loci (related to 28 genes) were identified to be associated with six reproductive traits (first, second and third calving age, calving interval, the number of services per conception and open days). Interestingly, the mRNA expressions of 25 of these genes were also observed in buffalo follicular granulosa cells. The IGFBP7 gene showed high level of expression during whole antral follicle growth. The knockdown of IGFBP7 in buffalo granulosa cells promoted cell apoptosis and hindered cell proliferation, and increased the production of progesterone and estradiol. Furthermore, a notable signal was detected at 2.3–2.7 Mb on the equivalent of bovine chromosome 5 associated with age at second calving, calving interval, and open days.ConclusionsThe genes associated with buffalo reproductive traits in this study may have effect on fertility by regulating of follicular growth. These results may have important implications for improving buffalo breeding programs through application of genomic information.Electronic supplementary materialThe online version of this article (10.1186/s12864-018-5208-6) contains supplementary material, which is available to authorized users.

Linkage disequilibrium (LD) is a useful parameter for guiding the accuracy and power of both genome-wide association studies (GWAS) and genomic selection (GS) among different livestock species. The present study evaluated the extent of LD, persistence of phase and effective population size (Ne) for the purebred (Mediterranean buffalo; n = 411) and crossbred [Mediterranean × Jianghan × Nili-Ravi buffalo, n = 9; Murrah × Nili-Ravi × local (Xilin or Fuzhong) buffalo, n = 36] buffalo populations using the 90K Buffalo SNP genotyping array. The results showed that the average square of correlation coefficient (r2) between adjacent SNP was 0.13 ± 0.19 across all autosomes for purebred and 0.09 ± 0.13 for crossbred, and the most rapid decline in LD was observed over the first 200 kb. Estimated r2 ≥ 0.2 extended up to ~50 kb in crossbred and 170 kb in purebred populations, while average r2 values ≥0.3 were respectively observed in the ~10 and 60 kb in the crossbred and purebred populations. The largest phase correlation (RP, C = 0.47) was observed at the distance of 100 kb, suggesting that this phase was not actively preserved between the two populations. Estimated Ne for the purebred and crossbred population at the current generation was 387 and 113 individuals, respectively. These findings may provide useful information to guide the GS and GWAS in buffaloes.

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