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.

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.

In this Research Communication we describe the effect of temperature and humidity index (THI) on various physiological traits, the plasma heat shock protein 70 (HSP70), heat shock protein 90 (HSP90) and cortisol levels and other blood parameters in crossbred buffalo (Nili-Ravi × Murrah) and Mediterranean buffalo to compare their tolerance to heat stress. As expected, crossbred buffalo had a significantly higher rectal temperature (RT), body surface temperature (BT), respiratory rate (RR), HSP70 and HSP90 levels in summer compared to spring and winter. RT and BT were also significantly higher in spring compared to winter. A significant correlation existed between THI and RT (r = 0·81) and RR (r = 0·84). Importantly, in summer the crossbred buffalo had a significantly lower RT, BT and RR and higher HSP70, HSP90 and cortisol levels than the Mediterranean buffalo. In conclusion, higher THI was associated with significant increase in RT, RR, BT, HSP70, HSP90 and cortisol levels, and the crossbred buffalo were more heat tolerant than Mediterranean buffalo.

Heat stress affects the physiology and production performance of Chinese Holstein dairy cows. As such, the selection of heat tolerance in cows and elucidating its underlying mechanisms are vital to the dairy industry. This study aimed to investigate the heat tolerance associated genes and molecular mechanisms in Chinese Holstein dairy cows using a high-throughput sequencing approach and bioinformatics analysis. Heat-induced physiological indicators and milk yield changes were assessed to determine heat tolerance levels in Chinese Holstein dairy cows by Principal Component Analysis method following Membership Function Value Analysis. Results indicated that rectal temperature (RT), respiratory rate (RR), and decline in milk production were significantly lower (p < 0.05) in heat tolerant (HT) cows while plasma levels of heat shock protein (HSP: HSP70, HSP90), and cortisol were significantly higher (p < 0.05) when compared to non-heat tolerant (NHT) Chinese Holstein dairy cows. By applying RNA-Seq analysis, we identified 200 (81 down-regulated and 119 up-regulated) significantly (|log2fold change| ≥ 1.4 and p ≤ 0.05) differentially expressed genes (DEGs) in HT versus NHT Chinese Holstein dairy cows. In addition, 14 of which were involved in protein–protein interaction (PPI) network. Importantly, several hub genes (OAS2, MX2, IFIT5 and TGFB2) were significantly enriched in immune effector process. These findings might be helpful to expedite the understanding for the mechanism of heat tolerance in Chinese Holstein dairy cows.

Exposure to the stress (HS) negatively affects physiology, performance, reproduction and welfare of buffalo. However, the mechanisms by which HS negatively affects rumen bacteria and its associated metabolism in buffalo are not well known yet. This study aimed to gain insight into the adaption of bacteria and the complexity of the metabolome in the rumen of six buffalo during HS using 16S rDNA and gas chromatography metabolomics analyses. HS increased respiratory rate (p < 0.05) and skin temperature (p < 0.01), and it decreased the content of acetic acid (p < 0.05) and butyric acid (p < 0.05) in the rumen. Omics sequencing revealed that the relative abundances of Lachnospirales, Lachnospiraceae, Lachnospiraceae_NK3A20_group and Clostridia_UCG-014 were significantly (p < 0.01) higher under HS than non-heat stress conditions. Several bacteria at different levels, such as Lactobacillales, Streptococcus, Leuconostocaceae and Leissella, were significantly (p < 0.05) more abundant in the rumen of the non-heat stress than HS condition. Thirty-two significantly different metabolites closely related to HS were identified (p < 0.05). Metabolic pathway analysis revealed four key pathways: D-Alanine metabolism; Lysine degradation, Tropane; piperidine and pyridine alkaloid biosynthesis; and Galactose metabolism. In summary, HS may negatively affected rumen fermentation efficiency and changed the composition of rumen community and metabolic function.

Heat stress has a detrimental effect on the physiological and production performance of buffaloes. Elucidating the underlying mechanisms of heat stress is challenging, therefore identifying candidate genes is urgent and necessary. We evaluated the response of buffaloes (n = 30) to heat stress using the physiological parameters, ELISA indexes, and hematological parameters. We then performed mRNA and microRNA (miRNA) expression profiles analysis between heat tolerant (HT, n = 4) and non-heat tolerant (NHT, n = 4) buffaloes, as well as the specific modules, significant genes, and miRNAs related to the heat tolerance identified using the weighted gene co-expression network analysis (WGCNA). The results indicated that the buffaloes in HT had a significantly lower rectal temperature (RT) and respiratory rate (RR) and displayed a higher plasma heat shock protein (HSP70 and HSP90) and cortisol (COR) levels than those of NHT buffaloes. Differentially expressed analysis revealed a total of 753 differentially expressed genes (DEGs) and 16 differentially expressed miRNAs (DEmiRNAs) were identified between HT and NHT. Using the WGCNA analysis, these DEGs assigned into 5 modules, 4 of which were significantly correlation with the heat stress indexes. Interestingly, 158 DEGs associated with heat tolerance in the turquoise module were identified, 35 of which were found within the protein-protein interaction network. Several hub genes (IL18RAP, IL6R, CCR1, PPBP, IL1B, and IL1R1) were identified that significantly enriched in the Cytokine-cytokine receptor interaction. The findings may help further elucidate the underlying mechanisms of heat tolerance in buffaloes.

No abstract

This Research Communication describes the polymorphisms in the coding region of DGAT1 gene in Riverine buffalo, Swamp buffalo and crossbred buffalo, and associations between polymorphisms and milk production performance in Riverine buffalo. Two polymorphisms of DGAT1were identified, located in exon 13 and exon 17, respectively. The distribution of the genotypes of the two SNP loci in different buffalo population varied, especially the polymorphism located in exon 13 which was not found in the Swamp buffalo. Moreover, SNP located in exon 17 was a nonsynonymous switch resulting in the animo acid sequence changed from an arginine (Arg) to a histidine (His) at position 484. Both SNPs were in Hardy-Weinberg equilibrium, and the polymorphism of g.8330T>C in the exon 13 was significantly associated with peak milk yield, total milk yield and protein percentage. The C variant was associated with an increase in milk yield and peak yield but less in protein percentage compared with the T variant. The polymorphisms of g.9046T>C in exon 17 were significantly associated with fat percentage, in that the buffaloes with TT genotype had a significantly higher fat percentage than those with CC genotype. These findings reveal the difference in the genetic evolution of the DGAT1 between Riverine buffalo and Swamp buffalo, and provide evidence that the DGAT1 gene has potential effects for Riverine buffalo milk production traits, which can be used as a candidate gene for marker-assisted selection in buffalo breeding.