Transcriptome profiling of Arabian horse blood during training regimens View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2017-12

AUTHORS

Katarzyna Ropka-Molik, Monika Stefaniuk-Szmukier, Kacper Żukowski, Katarzyna Piórkowska, Artur Gurgul, Monika Bugno-Poniewierska

ABSTRACT

BACKGROUND: Arabian horses are believed to be one of the oldest and most influential horse breeds in the world. Blood is the main tissue involved in maintaining body homeostasis, and it is considered a marker of the processes taking place in the other tissues. Thus, the aim of our study was to identify the genetic basis of changes occurring in the blood of Arabian horses subjected to a training regimen and to compare the global gene expression profiles between different training periods (T1: after a slow canter phase that is considered a conditioning phase, T2: after an intense gallop phase, and T3: at the end of the racing season) and between trained and untrained horses (T0). RNA sequencing was performed on 37 samples with a 75-bp single-end run on a HiScanSQ platform (Illumina), and differentially expressed genes (DEGs) were identified based on DESeq2 (v1.11.25) software. RESULTS: An increase in the number of DEGs between subsequent training periods was observed, and the highest amount of DEGs (440) was detected between untrained horses (T0) and horses at the end of the racing season (T3). The comparisons of the T2 vs. T3 transcriptomes and the T0 vs. T3 transcriptomes showed a significant gain of up-regulated genes during long-term exercise (up-regulation of 266 and 389 DEGs in the T3 period compared to T2 and T0, respectively). Forty differentially expressed genes were detected between the T1 and T2 periods, and 296 between T2 and T3. Functional annotation showed that the most abundant genes up-regulated in exercise were involved in pathways regulating cell cycle (PI3K-Akt signalling pathway), cell communication (cAMP-dependent pathway), proliferation, differentiation and apoptosis, as well as immunity processes (Jak-STAT signalling pathway). CONCLUSIONS: We investigated whether training causes permanent transcriptome changes in horse blood as a reflection of adaptation to conditioning and the maintenance of fitness to compete in flat races. The present study identified the overrepresented molecular pathways and genes that are essential for maintaining body homeostasis during long-term exercise in Arabian horses. Selected DEGs should be further investigated as markers that are potentially associated with racing performance in Arabian horses. More... »

PAGES

31

References to SciGraph publications

  • 2009-12. Transcriptional adaptations following exercise in Thoroughbred horse skeletal muscle highlights molecular mechanisms that lead to muscle hypertrophy in BMC GENOMICS
  • 2010-12. Characterization of the equine skeletal muscle transcriptome identifies novel functional responses to exercise training in BMC GENOMICS
  • 2008-12. Exercise induced stress in horses: Selection of the most stable reference genes for quantitative RT-PCR normalization in BMC MOLECULAR BIOLOGY
  • 2014-05. FoxO transcription factors: their roles in the maintenance of skeletal muscle homeostasis in CELLULAR AND MOLECULAR LIFE SCIENCES
  • 2002-12. The limit fold change model: A practical approach for selecting differentially expressed genes from microarray data in BMC BIOINFORMATICS
  • 2014-12. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2 in GENOME BIOLOGY
  • 2012-12. Whole transcriptome analyses of six thoroughbred horses before and after exercise using RNA-Seq in BMC GENOMICS
  • 2010-12. A genome-wide SNP-association study confirms a sequence variant (g.66493737C>T) in the equine myostatin (MSTN) gene as the most powerful predictor of optimum racing distance for Thoroughbred racehorses in BMC GENOMICS
  • 2011-12. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome in BMC BIOINFORMATICS
  • 2009-12. Molecular profiles of Quadriceps muscle in myostatin-null mice reveal PI3K and apoptotic pathways as myostatin targets in BMC GENOMICS
  • 2001-11. Akt/mTOR pathway is a crucial regulator of skeletal muscle hypertrophy and can prevent muscle atrophy in vivo in NATURE CELL BIOLOGY
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/s12863-017-0499-1

    DOI

    http://dx.doi.org/10.1186/s12863-017-0499-1

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1084612330

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/28381206


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