Whole transcriptome analyses of six thoroughbred horses before and after exercise using RNA-Seq
- Equal contributors
1 Department of Biotechnology, Hankyong National University, Anseong, 456-749, Republic of Korea
2 Personal Genomics Institute, Genome Research Foundation, 443-270, Suwon, Republic of Korea
3 Theragen BiO Institute, TheragenEtex, 443-270, Suwon, Republic of Korea
4 Department of Biological Sciences, College of Natural Sciences, Pusan National University, Busan, 609-735, Republic of Korea
5 Department of Animal Science, College of Life Sciences, Pusan National University, Miryang, 627-702, Republic of Korea
6 Department of Pathology, School of Medicine, and Institute of Biomedical Science and Technology, Konkuk University, Seoul, 143-701, Republic of Korea
7 Department of Nanomedical Engineering, College of Nanoscience and Nanotechnology, Pusan National University, Miryang, 627-702, Republic of Korea
8 Korean Bioinformation Center, Korea Research Institute of Bioscience and Biotechnology, 305-806, Daejeon, Republic of Korea
BMC Genomics 2012, 13:473 doi:10.1186/1471-2164-13-473Published: 12 September 2012
Thoroughbred horses are the most expensive domestic animals, and their running ability and knowledge about their muscle-related diseases are important in animal genetics. While the horse reference genome is available, there has been no large-scale functional annotation of the genome using expressed genes derived from transcriptomes.
We present a large-scale analysis of whole transcriptome data. We sequenced the whole mRNA from the blood and muscle tissues of six thoroughbred horses before and after exercise. By comparing current genome annotations, we identified 32,361 unigene clusters spanning 51.83 Mb that contained 11,933 (36.87%) annotated genes. More than 60% (20,428) of the unigene clusters did not match any current equine gene model. We also identified 189,973 single nucleotide variations (SNVs) from the sequences aligned against the horse reference genome. Most SNVs (171,558 SNVs; 90.31%) were novel when compared with over 1.1 million equine SNPs from two SNP databases. Using differential expression analysis, we further identified a number of exercise-regulated genes: 62 up-regulated and 80 down-regulated genes in the blood, and 878 up-regulated and 285 down-regulated genes in the muscle. Six of 28 previously-known exercise-related genes were over-expressed in the muscle after exercise. Among the differentially expressed genes, there were 91 transcription factor-encoding genes, which included 56 functionally unknown transcription factor candidates that are probably associated with an early regulatory exercise mechanism. In addition, we found interesting RNA expression patterns where different alternative splicing forms of the same gene showed reversed expressions before and after exercising.
The first sequencing-based horse transcriptome data, extensive analyses results, deferentially expressed genes before and after exercise, and candidate genes that are related to the exercise are provided in this study.