Dataset Information

Variations in the Regulatory Region of Alpha S1-Casein Milk Protein Gene among Tropically Adapted Indian Native (Bos Indicus) Cattle.

ABSTRACT: Regulatory region of milk protein alpha S1-casein (?S1-CN) gene was sequenced, characterized, and analyzed to detect variations among 13 Indian cattle (Bos indicus) breeds. Comparative analysis of 1,587?bp region comprising promoter (1,418?bp), exon-I (53?bp), and partial intron-I (116?bp) revealed 35 nucleotide substitutions (32 within promoter region, 1 in exon-I, and 2 in partial intron-I region) and 4 Indels. Within promoter, 15 variations at positions -1399 (A?>?G), -1288 (G?>?A), -1259 (T?>?C), -1158 (T?>?C), -1016 (A?>?T), -941 (T?>?G), -778 (C?>?T), -610 (G?>?A), -536 (A?>?G), -521 (A?>?G), -330 (A?>?C), -214 (A?>?G), -205 (A?>?T), -206 (C?>?A), and -175 (A?>?G) were located within the potential transcription factor binding sites (TFBSs), namely, NF-?E1/c-Myc, GATA-1, GATA-1/NF-E, Oct-1/POU3F2, MEF-2/YY1, GATA-1, AP-1, POU1F1a/GR, TMF, GAL4, YY1/Oct-1, HNF-1, GRalpha/AR, GRalpha/AR, and AP-1, respectively. Seventy-four percent (26/35) of the observed SNPs were novel to Indian cattle and 11 of these novel SNPs were located within one or more TFBSs. Collectively, these might influence the binding affinity towards their respective nuclear TFs thus modulating the level of transcripts in milk and affecting overall protein composition. The study provides information on several distinct variations across indicine and taurine ?S1-CN regulatory domains.

SUBMITTER: Kishore A

PROVIDER: S-EPMC4393073 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Variations in the Regulatory Region of Alpha S1-Casein Milk Protein Gene among Tropically Adapted Indian Native (Bos Indicus) Cattle.

Kishore Amit A Mukesh Manishi M Sobti Ranbir C RC Mishra Bishnu P BP Sodhi Monika M

ISRN biotechnology 20130114

Regulatory region of milk protein alpha S1-casein (αS1-CN) gene was sequenced, characterized, and analyzed to detect variations among 13 Indian cattle (Bos indicus) breeds. Comparative analysis of 1,587 bp region comprising promoter (1,418 bp), exon-I (53 bp), and partial intron-I (116 bp) revealed 35 nucleotide substitutions (32 within promoter region, 1 in exon-I, and 2 in partial intron-I region) and 4 Indels. Within promoter, 15 variations at positions -1399 (A > G), -1288 (G > A), -1259 (T ...[more]

PMID: 25937984

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Project description:BACKGROUND: Nellore cattle play an important role in beef production in tropical systems and there is great interest in determining if genomic selection can contribute to accelerate genetic improvement of production and fertility in this breed. We present the first results of the implementation of genomic prediction in a Bos indicus (Nellore) population. METHODS: Influential bulls were genotyped with the Illumina Bovine HD chip in order to assess genomic predictive ability for weight and carcass traits, gestation length, scrotal circumference and two selection indices. 685 samples and 320 238 single nucleotide polymorphisms (SNPs) were used in the analyses. A forward-prediction scheme was adopted to predict the genomic breeding values (DGV). In the training step, the estimated breeding values (EBV) of bulls were deregressed (dEBV) and used as pseudo-phenotypes to estimate marker effects using four methods: genomic BLUP with or without a residual polygenic effect (GBLUP20 and GBLUP0, respectively), a mixture model (Bayes C) and Bayesian LASSO (BLASSO). Empirical accuracies of the resulting genomic predictions were assessed based on the correlation between DGV and dEBV for the testing group. RESULTS: Accuracies of genomic predictions ranged from 0.17 (navel at weaning) to 0.74 (finishing precocity). Across traits, Bayesian regression models (Bayes C and BLASSO) were more accurate than GBLUP. The average empirical accuracies were 0.39 (GBLUP0), 0.40 (GBLUP20) and 0.44 (Bayes C and BLASSO). Bayes C and BLASSO tended to produce deflated predictions (i.e. slope of the regression of dEBV on DGV greater than 1). Further analyses suggested that higher-than-expected accuracies were observed for traits for which EBV means differed significantly between two breeding subgroups that were identified in a principal component analysis based on genomic relationships. CONCLUSIONS: Bayesian regression models are of interest for future applications of genomic selection in this population, but further improvements are needed to reduce deflation of their predictions. Recurrent updates of the training population would be required to enable accurate prediction of the genetic merit of young animals. The technical feasibility of applying genomic prediction in a Bos indicus (Nellore) population was demonstrated. Further research is needed to permit cost-effective selection decisions using genomic information.

Dataset Information

Variations in the Regulatory Region of Alpha S1-Casein Milk Protein Gene among Tropically Adapted Indian Native (Bos Indicus) Cattle.

Publications

Variations in the Regulatory Region of Alpha S1-Casein Milk Protein Gene among Tropically Adapted Indian Native (Bos Indicus) Cattle.

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