Deep mRNA sequencing for transcriptome profiling of skeletal muscle tissues

Using RNA-Seq, we aimed at analysing gene expression in muscles of two Italian cattle breeds, Maremmana (M) and Chianina (C), to uncover genes responsible for meat tenderness, an important trait for meat quality, and assess diversity of expression between breeds. Samples were classified hard and tender on the basis of phenotypic analysis. Total RNA was extracted from Longissimus dorsi skeletal muscle of young bulls of both breeds. Hard and tender samples of C vs M were compared in two individuals, for each breeds, representing the extreme degrees of tenderness in the overall sample of 32 individuals per breed. Single-end libraries were sequenced on the GAII Illumina sequencing platform. Our deeply sampled RNA-Seq generated 38,904,560 short sequence reads. We pre-processed and assayed the reads quality with specialized tools as FastQC and FASTX-Toolkit. We used the short read aligner Bowtie to align reads on genome and TopHat pipeline to map splice junctions in RNA-Seq reads. Finally, using Cufflinks we estimated transcripts abundance and tested for differential expression and regulation in RNA-Seq samples. Preliminary inter breed comparison of hard muscle RNA revealed 28,451 transcripts (88.3% with known annotation) distributed into 451 significant transcripts corresponding to 318 genes. RNA comparison of tender samples resulted in 30,850 transcripts (87.1% with known annotation) distributed into 592 significant transcripts corresponding to 425 genes. These findings may help i. elucidating the mechanisms of meat tenderness, one of the most important market drivers; ii. assess the between breeds diversity; iii. and pave the way for a gene assisted selection.