Exome-wide comparative analyses revealed differentiating genomic regions for performance traits in Indian native buffaloes.

In India, 20 breeds of buffalo have been identified and registered, yet limited studies have been conducted to explore the performance potential of these breeds, especially in the Indian native breeds. This study is a maiden attempt to delineate the important variants and unique genes through exome sequencing for milk yield, milk composition, fertility, and adaptation traits in Indian local breeds of buffalo. In the present study, whole exome sequencing was performed on Chhattisgarhi (n = 3), Chilika (n = 4), Gojri (n = 3), and Murrah (n = 4) buffalo breeds and after stringent quality control, 4333, 6829, 4130, and 4854 InDels were revealed, respectively. Exome-wide FST along 100-kb sliding windows detected 27, 98, 38, and 35 outlier windows in Chhattisgarhi, Chilika, Gojri, and Murrah, respectively. The comparative exome analysis of InDels and subsequent gene ontology revealed unique breed specific genes for milk yield (CAMSAP3), milk composition (CLCN1, NUDT3), fertility (PTGER3) and adaptation (KCNA3, TH) traits. Study provides insight into mechanism of how these breeds have evolved under natural selection, the impact of these events on their respective genomes, and their importance in maintaining purity of these breeds for the traits under study. Additionally, this result will underwrite to the genetic acquaintance of these breeds for breeding application, and in understanding of evolution of these Indian local breeds.

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.

Genetic group and swim-up processing affect SYBR Green real-time PCR-based porcine semen sex ratio in Landrace and its crossbred boars.

Determination of factors affecting sex ratio is important while considering application of sex ratio enrichment approach. Present study aimed to design a SYBR Green qPCR-based method for measurement of primary sex ratio and to evaluate different factors (genetic group, sire, spermiogenic cycle and processing layer) affecting boar sperm sex ratio. The qPCR was based on relative copy number analysis of sex chromosome-specific single copy gene fragments with an autosomal gene as reference and was evaluated using DNA dilution series from pigs with numerically normal karyotype. The sex ratio was estimated from genomic DNA samples isolated from boar semen collected from different genetic groups at different time points and different processing layers. The X chromosome frequencies of semen samples revealed significant effect of genetic group. However, significant variation was observed neither within same genetic group nor between ejaculates of different spermatogenic cycles. Among the processing techniques studied, swim-up technique produced a significant X sperm enrichment in comparison to control whereas, Percoll density gradient failed to show any significant difference among layers. The lower layer in swim-up technique was found to contain higher proportion of X sperms. The designed qPCR is found to be an easy, less time-consuming method and does not require high end laboratory facilities or the specialized expertise. The lower layer of swim-up processing has a scope for X sperm enrichment in boar semen with proper validation.

Selection of a stable reference gene for relative copy number profiling of porcine chromosomal genes using SYBR green qPCR.

Reference gene with stable copy number is essential for normalization in qPCR based copy number assay. Present study aims to identify a suitable reference gene in pigs for qPCR based relative copy number profiling of chromosomal genes. A total of 30 crossbred pigs of both sexes were cyto-screened and gDNA was extracted from the pigs having numerically normal karyotypes. The copy number stability was studied for 7 genes (FSHB, IL4, IGF1R, TCF24, BRMS1L, ARMC1 and SRSF4) selected on the basis of the chromosomal location, reports of single copy and lack of involvement in structural chromosomal abnormalities. The copy number was estimated from Ct values in 3 technical replicates using 6 animals from either sex for each gene. The stability was evaluated from the variations in Ct values using different (Delta Ct, geNorm, BestKeeper and normFinder) algorithms. While the moderate variation was observed among relative copy number stabilities among the genes, comprehensive ranking revealed the most stable gene for normalization (IGF1R > FSHB > TCF24 > IL4 > ARMC1> SRSF4 > BRMS1L) across the samples. The selected reference gene was validated using DNA of cyto-screened pigs to find out ratio of X and Y chromosome fragments using qPCR based copy number analysis.