Bos indicus breed:Red Chittagong Cattle
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ABSTRACT:
PROVIDER: PRJNA865650 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Red Chittagong Cattle Breeding and Revealing Their Genomic Architecture Through Whole Genome Resequencing
| PRJNA971959 | ENA
Project description:Profiling of miRNA in serum of FMDV infected cattle, to understand disease pathogenesis and to identify FMD specific miRNA biomarkers to aid early pre-clinical diagnosis
2017-10-20 | GSE77489 | GEO
Project description:We reported the bovine liver gene expression database of Polish-HF, Polish-Red and Hereford cattle breeds.
2019-04-16 | GSE114233 | GEO
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.
| S-EPMC4014866 | biostudies-other
Project description:Genome assembly of Norwegian Red Cattle
| PRJEB71669 | ENA
Project description:We reported the bovine pituitary gland gene expression database of Polish-HF, Polish-Red and Hereford cattle breeds.
2019-05-09 | GSE114230 | GEO
Project description:Malnad Gidda is one among the 43 registered cattle breeds of India with unique traits and spread over Western Ghats and coastal regions of Karnataka state in India. Selection of highly elite fertile bulls for the breeding purpose is a critical control point in animal breeding programmes. Therefore, to characterize the semen proteome and to understand the semen biology of this breed, a comprehensive proteomic analysis of spermatozoa and seminal plasma has been carried out by employing SCX and bRPLC fractionation strategies in a mass-spectrometry platform. The semen samples from three Malnad Gidda bulls maintained at Southern Regional Station of ICAR-NDRI under standard managemental conditions were used in the study. The proteomic characterisation of semen from Malnad Gidda breed resulted in the identification of 5, 84,520 PSMs, from 24,467 peptides from 2,815 proteins in spermatozoa and identification of 2, 77,583 PSMs from 12,047 peptides, which resulted in 1,974 proteins from seminal plasma. Out of 2,815 proteins in spermatozoa and 1,974 proteins from seminal plasma, 969 proteins were common to both seminal plasma and spermatozoa. The biological processes and cellular localization of spermatozoa proteins were studied using DAVID tool and were further enriched the identical GO terms using REVIGO online tool. The functional enrichment analysis of identified proteins indicated their roles in the biological processes like sperm motility, spermatid development, spermatogenesis, and so on. GO studies showed the commonalities and differences in the molecular functions of the proteins exclusively identified in spermatozoa, seminal plasma and common proteins. This is the first proteomic investigation conducted on the semen samples of an Indian indigenous breed; therefore, we believe that our preliminary data should significantly advance our understanding of semen proteome of Indian cattle.
2020-06-12 | PXD014172 | Pride
Project description:Comparative transcriptome profile of genes differentially expressed in longissimus dorsi muscles between Japanese black (Wagyu) and Chinese Red Steppes cattle by RNA-seq
2020-11-28 | GSE161967 | GEO
Project description:Bos taurus isolate:JXBC | breed:Jiaxian Red Cattle Raw sequence reads
| PRJNA886448 | ENA