Dataset Information

Molecular characterization of coat color gene in Sahiwal versus Karan Fries bovine.

ABSTRACT:

Background

Melanocortin-1-receptor gene (MC1R) plays a significant role in signaling cascade of melanin production. In cattle, the coat colors, such as red and black, are an outcome of eumelanin and pheomelanin pigments, respectively. The coat colors have become critical factors in the animal selection process. This study is therefore aimed at the molecular characterization of reddish-brown coat-colored Sahiwal cattle in comparison to the black and white-colored Karan Fries.

Results

The Sequence length of the MC1R gene was 954 base pairs in Sahiwal cattle. The sequences were examined and submitted to GenBank Acc.No. MG373575 to MG373605. Alignment of both (Sahiwal and Karan Fries) protein sequences by applying ClustalO multiple sequence alignment programs revealed 99.8-96.8% sequence similarity within the bovine. MC1R gene phylogenetic studies were analyzed by MEGA X. The gene MC1R tree, protein confines, and hereditary difference of cattle were derived from Ensemble Asia Cow Genome Browser 97. One unique single-nucleotide polymorphism (c.844C>A) (SNP) was distinguished. Single amino acid changes were detected in the seventh transmembrane structural helix region, with SNP at p.281?T>N of MC1R gene in Karan Fries cattle.

Conclusions

In this current research, we first distinguished the genomic sequence of the MC1R gene regions that showed evidence of coat variation between Indian indigenous Sahiwal cattle breed correlated with crossbreed Karan Fries. These variations were found in the Melanocortin 1 receptor coding regions of the diverse SNPs. The conclusions of this research provide new insights into understanding the coat color variation in crossbreed compared to the Indian Sahiwal cattle.

SUBMITTER: Goud TS

PROVIDER: S-EPMC7846656 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Molecular characterization of coat color gene in Sahiwal versus Karan Fries bovine.

Goud Talla Sridhar TS Upadhyay Ramesh Chandra RC Pichili Vijaya Bhaskar Reddy VBR Onteru Suneel Kumar SK Chadipiralla Kiranmai K

Journal, genetic engineering & biotechnology 20210129 1

<h4>Background</h4>Melanocortin-1-receptor gene (MC1R) plays a significant role in signaling cascade of melanin production. In cattle, the coat colors, such as red and black, are an outcome of eumelanin and pheomelanin pigments, respectively. The coat colors have become critical factors in the animal selection process. This study is therefore aimed at the molecular characterization of reddish-brown coat-colored Sahiwal cattle in comparison to the black and white-colored Karan Fries.<h4>Results</ ...[more]

PMID: 33512595

Similar Datasets

Project description:BackgroundIn the evolutionary time scale, selection shapes the genetic variation and alters the architecture of genome in the organisms. Selection leaves detectable signatures at the genomic coordinates that provide clues about the protein-coding regions. Sahiwal is a valuable indicine cattle adapted to tropical environments with desirable milk attributes. Insights into the genomic regions under putative selection may reveal the molecular mechanisms affecting the quantitative and other important traits. To understand this, the present investigation was undertaken to explore signatures of selection in the genome of Sahiwal cattle using a medium-density genotyping INDUS chip.ResultDe-correlated composite of multiple selection signals (DCMS), which combines five different univariate statistics, was computed in the dataset to detect the signatures of selection in the Sahiwal genome. Gene annotations, Quantitative Trait Loci (QTL) enrichment, and functional analyses were carried out for the identification of significant genomic regions. A total of 117 genes were identified, which affect a number of important economic traits. The QTL enrichment analysis highlighted 14 significant [False Discovery Rate (FDR)-corrected p-value ≤ 0.05] regions on chromosomes BTA 1, 3, 6, 11, 20, and 21. The top three enriched QTLs were found on BTA 6, 20, and 23, which are associated with exterior, health, milk production, and reproduction traits. The present study on selection signatures revealed some key genes related with coat color (PDGFRA, KIT, and KDR), facial pigmentation (LEF), milk fat percent (MAP3K1, HADH, CYP2U1, and SGMS2), sperm membrane integrity (OSTC), lactation persistency (MRPS30, NNT, CCL28, HMGCS1, NIM1K, ZNF131, and CCDC152), milk yield (GHR and ZNF469), reproduction (NKX2-1 and DENND1A), and bovine tuberculosis susceptibility (RNF144B and PAPSS1). Further analysis of candidate gene prioritization identified four hub genes, viz., KIT, KDR, MAP3K1, and LEF, which play a role in coat color, facial pigmentation, and milk fat percentage in cattle. Gene enrichment analysis revealed significant Gene ontology (GO) terms related to breed-specific coat color and milk fat percent.ConclusionThe key candidate genes and putative genomic regions associated with economic traits were identified in Sahiwal using single nucleotide polymorphism data and the DCMS method. It revealed selection for milk production, coat color, and adaptability to tropical climate. The knowledge about signatures of selection and candidate genes affecting phenotypes have provided a background information that can be further utilized to understand the underlying mechanism involved in these traits in Sahiwal cattle.

Project description:Background and Aim:Probiotics are the living microorganism which when administered improves the digestion and health of the animal. Saccharomyces cerevisiae (SC) improves the humoral and innate immunity of the animal. Prilled fat is a hydrogenated palm oil triglyceride which has been reported to promote the release of cytokines from macrophages. The aim of the study was to evaluate the immunomodulatory effect of probiotic and prilled fat during transition stage in Karan Fries (KF) cows. Materials and Methods:A total of 12 KF cows at 21 days prepartum were selected and divided into two groups of six animals each. The control group was fed as per the standard feeding practices and the supplemented group cows were supplemented daily with prilled fat at 100 g/cow, SC at 25 g/cow, and sweetener at 1 g/cow in addition to the standard feeding practices from -30 days of prepartum to 21 days of lactation. The sweetener was added to improve the palatability of the feed. The natural sweetener of an African plant leave had 105 times more sweetness than glucose with good aroma. The dry matter intake of the animal was recorded. Plasma samples were collected weekly from all cows for the analysis of blood metabolite beta-hydroxybutyric acid (BHBA). Lymphocytes were isolated from the blood for studying the expression of tumor necrosis factor alpha (TNF-?) and interleukin-1? (IL-1?) and for estimating lymphocyte proliferation index (LPI). Results:The upregulated IL-1? and TNF-? around calving might be possibly associated to the metabolic changes occurring during the transition period and suggest a higher degree of inflammation around parturition. High concentrations of BHBA caused increased expression and synthesis of the pro-inflammatory factors such as TNF-? and IL-1? in supplemented group in primary calf hepatocytes. The LPI was higher in supplemented group as compared to control which suggests a stimulatory effect of unsaturated fatty acids on mitogen-stimulated T-cell proliferation. Conclusion:Dietary supplementation of probiotics, prilled fat, and sweetener alleviated negative energy balance by stimulating feed intake and modulating hepatic lipid metabolism; and both of these additives improved the postpartum health (antioxidant status and immune function) of transition dairy cows.

Project description:The present study sought to evaluate mRNA expression profiles in the cultured dermal fibroblasts of Tharparkar (zebu) and Karan-Fries (zebu, Tharparkar × taurine, Holstein Friesian) cattle in response to heat stress. Bioinformatics' analysis identified temperature-regulated biological processes and pathways. Biological processes overrepresented among the earliest genes induced by temperature stress include regulation of stress responses, protein repair, metabolism, protein transport, cell division, and apoptosis. The present microarray platform contains 51,338 synthesized oligonucleotide probes corresponding to at least 36,713 unigenes. A total of 11,183 and 8126 transcripts were differentially expressed with a fold change of ≥ 2 in Tharparkar and Karan-Fries cattle, respectively. Randomly selected real-time validation showed 83.33% correlation with microarray data. Functional annotation and pathway study of the differentially expressed transcripts or genes (DEGs) reveal that upregulated genes significantly (P < 0.05) affect protein processing and NOD-like receptor pathways (NLRs), while downregulated genes were significantly (P < 0.05) found to be associated with cell cycle, metabolism, and protein transport. Gene expression changes include activation of heat shock factors (HSFs), increased expression of heat shock proteins (HSPs), and apoptosis, while decreasing protein synthesis and another metabolism. These findings provide insights into the underlying mechanism of the physiology of heat stress in Tharparkar and Karan-Fries cattle. Understanding the biology and mechanisms of heat stress is critical to developing approaches to ameliorate current production issues for improving animal performance and agriculture economics in tropical climatic conditions. In conclusion, the present study indicates that heat stress differentially affects the expression of the significant number of genes associated with stress response, metabolism, apoptosis, and protein transport in dermal fibroblasts of Tharparkar and Karan-Fries cattle.

Dataset Information

Molecular characterization of coat color gene in Sahiwal versus Karan Fries bovine.

Background

Results

Conclusions

Publications

Molecular characterization of coat color gene in Sahiwal versus Karan Fries bovine.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets