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  • Title: Gene-based single nucleotide polymorphism discovery in bovine muscle using next-generation transcriptomic sequencing.
    Author: Djari A, Esquerré D, Weiss B, Martins F, Meersseman C, Boussaha M, Klopp C, Rocha D.
    Journal: BMC Genomics; 2013 May 07; 14():307. PubMed ID: 23651547.
    Abstract:
    BACKGROUND: Genetic information based on molecular markers has increasingly being used in cattle breeding improvement programmes, as a mean to improve conventionally phenotypic selection. Advances in molecular genetics have led to the identification of several genetic markers associated with genes affecting economic traits. Until recently, the identification of the causative genetic variants involved in the phenotypes of interest has remained a difficult task. The advent of novel sequencing technologies now offers a new opportunity for the identification of such variants. Despite sequencing costs plummeting, sequencing whole-genomes or large targeted regions is still too expensive for most laboratories. A transcriptomic-based sequencing approach offers a cheaper alternative to identify a large number of polymorphisms and possibly to discover causative variants. In the present study, we performed a gene-based single nucleotide polymorphism (SNP) discovery analysis in bovine Longissimus thoraci, using RNA-Seq. To our knowledge, this represents the first study done in bovine muscle. RESULTS: Messenger RNAs from Longissimus thoraci from three Limousin bull calves were subjected to high-throughput sequencing. Approximately 36-46 million paired-end reads were obtained per library. A total of 19,752 transcripts were identified and 34,376 different SNPs were detected. Fifty-five percent of the SNPs were found in coding regions and ~22% resulted in an amino acid change. Applying a very stringent SNP quality threshold, we detected 8,407 different high-confidence SNPs, 18% of which are non synonymous coding SNPs. To analyse the accuracy of RNA-Seq technology for SNP detection, 48 SNPs were selected for validation by genotyping. No discrepancies were observed when using the highest SNP probability threshold. To test the usefulness of the identified SNPs, the 48 selected SNPs were assessed by genotyping 93 bovine samples, representing mostly the nine major breeds used in France. Principal component analysis indicates a clear separation between the nine populations. CONCLUSIONS: The RNA-Seq data and the collection of newly discovered coding SNPs improve the genomic resources available for cattle, especially for beef breeds. The large amount of variation present in genes expressed in Limousin Longissimus thoracis, especially the large number of non synonymous coding SNPs, may prove useful to study the mechanisms underlying the genetic variability of meat quality traits.
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