Exploring MicroRNA biogenesis, applications and bioinformatics analysis in livestock: A comprehensive review.

Small non-coding RNAs called microRNAs (miRNAs) control the expression of genes post-transcriptionally. Their correlation with commercial economic traits including milk, meat and egg production, as well as their effective role in animal productivity, fertility, embryo survival and disease resistance, make them significant in livestock research. The miRNAs exhibit distinct spatial and temporal expression patterns, offering insights into their functional roles within cells and tissues. Aberrant miRNA production can disrupt vital cellular processes and genetic networks, contributing to conditions like metabolic disorders and viral diseases. These short RNA molecules are present in extracellular fluids, displaying remarkable stability against RNA degradation enzymes and extreme environmental conditions. miRNAs preservation is facilitated through packaging in lipid vesicles or complex formation with RNA-binding proteins. Numerous studies have illuminated the roles of miRNAs in diverse physiological processes, including embryonic stem cell differentiation, haematopoietic stem cell proliferation and differentiation and the coordinated development of organ systems. The integration of miRNA profiling, next-generation sequencing and bioinformatics analysis paves the way for transformative advancements in livestock research and industry. The present review underscores the applications of miRNAs in livestock, showcasing their potential to improve breeding strategies, diagnose diseases and enhance our understanding of fundamental biological processes.

Genetic improvement of economic traits in Murrah buffalo using significant SNPs from genome-wide association study.

GWAS helps to identify QTL and candidate genes of specific traits. Buffalo breeding has primarily focused on milk production, but its negative correlation with reproduction traits resulted in unfavorable decline of reproductive performance among buffaloes. A genome wide scan was performed on a total of 120 Murrah buffaloes genotyped by ddRAD sequencing for 13 traits related to female fertility, production, and growth. The identified 25 significant single nucleotide polymorphisms (SNPs) (P <1×106) are associated with age at first calving (AFC), age at first service (AFS), period from calving to 1st Artifical Insemination (AI), service period (SP) and 6 month body weight (6M). Fifteen genetic variants overlapped with different QTL regions of reported studies. Among the associated loci, outstanding candidate genes for fertility, including AQP1, TRNAE-CUC, NRIP1, CPNE4, and VOPP1, have effect in different fertility traits. AQP1 gene is expressed in ovulatory phase and various stages of pregnancy. TRNAE-CUC gene is associated with AFC and number . of calvings after 4 years of age. Glycogen content-associated gene CPNE4 regulates muscle glycogen and is upregulated during early pregnancy. NRIP1 generegulates ovulation, corpus luteum at pregnancy, and mammary gland development. The objective is to identify potential genomic regions and genetic variants associated with economic traits and to select the most significant SNP which have positive effect on all the traits.

Genomic clues of association between clinical mastitis and SNPs identified by ddRAD sequencing in Murrah buffaloes.

The total milk production of India is 209.96 MT out of which 45% is contributed by the indigenous buffalo and due to their high producing virtue, the prevalence of mastitis is 5-20%. Despite the increasing level of technological advancement, mastitis is still an issue of concern for dairy industry in India as well as across the world. Therefore, the present study aimed to identify the SNPs and associate them with the incidence of clinical mastitis in Murrah buffalo using the ddRAD sequencing approach taking mastitis incidence data of 96 Murrah buffaloes. A total of 246 million quality controlled reads were obtained with an average alignment rate of 99.01% and at a read depth of 10, quality controlled SNPs obtained were 18,056. The logistic regression model was used and a total of seven SNPs were found significantly associated (p < 0.001) with mastitis incidence and seven genes were identified viz., NCBP1, FOXN3, TPK1, XYLT2, CPXM2, HERC1, and OPCML. The majority of them were having tumor suppressing action, related to immunogenetics or glycolytic and energy production. Conclusively, the SNPs identified in this study may be useful for future studies on mastitis incidence in Murrah buffalo and the SNP associations can be further validated.