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Translational Research in Veterinary Science

Data set for transcriptome analysis of liver in cattle breeds
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Data set for transcriptome analysis of liver in cattle breeds

Authors

  • Mateusz Sachajko Institute of Veterinary Medicine, Faculty of Biological and Veterinary Sciences, Nicolaus Copernicus University, Torun, Poland https://orcid.org/0000-0003-1901-6101
  • Magdalena Herudzińska Institute of Veterinary Medicine, Faculty of Biological and Veterinary Sciences, Nicolaus Copernicus University, Torun, Poland https://orcid.org/0000-0002-2279-9234
  • Jedrzej M. Jaskowski Institute of Veterinary Medicine, Faculty of Biological and Veterinary Sciences, Nicolaus Copernicus University, Torun, Poland. https://orcid.org/0000-0002-4676-7990
  • Joanna Szczepanek Division of Functional genomics in biological and biomedical research, Centre for Modern Interdisciplinary Technologies, Nicolaus Copernicus University, Torun, Poland https://orcid.org/0000-0002-4287-5353
  • Magdalena Buszewska-Forajta Voluntary author, Institute of Veterinary Medicine, Faculty of Biological and Veterinary Sciences, Nicolaus Copernicus University, Torun, Poland. https://orcid.org/0000-0003-1401-2558
  • Yaping Feng Waksman Institute of Microbiology, Rutgers, The state university of New Jersey, Piscataway, NJ 08 854, USA
  • Dibyendu Kumar Waksman Institute of Microbiology, Rutgers, The State University of New Jersey, Piscataway, NJ 08 854, USA. https://orcid.org/0000-0002-0827-5952
  • Chandra Shekhar Pareek Institute of Veterinary Medicine, Faculty of Biological and Veterinary Sciences, Nicolaus Copernicus University, Torun, Poland. Division of Functional genomics in biological and biomedical research, Centre for Modern Interdisciplinary Technologies, Nicolaus Copernicus University, Torun, Poland. https://orcid.org/0000-0002-0329-787X

DOI:

https://doi.org/10.12775/TRVS.2019.009

Keywords

RNA-seq, cattle, liver, breeds, NGS, SNPs, DEGs, DEseq, EdgeR, FDR, SAMtools, BWA, FASTq, SRA, NCBI, GEO

Abstract

Transcriptome analysis using high-throughput next-generation sequencing (HT-NGS) technology provides the capability to understand global gene expression variations through a wide range of tissue samples in domesticated animals. We provide raw and analysed data for transcriptomic analysis of liver tissues from Polish-HF, Polish Red and Hereford cattle breeds, obtained by RNA-seq. High-quality sequencing data have been analysed using our bioinformatics pipeline which consists of FastQC for quality controls, Trimmomatic for trimming, and BWA version 0.7.5-r404 for alignment to the Bos taurus reference genome, SAMtools for SNPs identifications, and differentially expressed genes (DEGs) identification using DEseq and edgeR pipelines after adjustment for false-discovery rate (FDR) with adjusted two-sided p values <0.01 and the trimmed mean of M values (TMM) normalisation method. The data accompanying the published manuscript describing the SNPs and DEGs identification in the bovine liver transcriptome of cattle breeds. Raw FASTq files for the RNA-seq libraries are deposited in the NCBI Sequence Read Archive (SRA) and have been assigned BioProject accession PRJNA312148. Raw and processed RNA-seq data were deposited and made publicly available on the Gene Expression Omnibus (GEO; GSE114233).

References

Pareek CS, Błaszczyk P, Dziuba P, Czarnik U, Fraser L, Sobiech P, Pierzchała M, Feng Y, Kadarmideen HN, Kumar D. Single nucleotide polymorphism discovery in bovine liver using RNA-seq technology. PLoS One. 2017;12:e0172687.

Pareek CS, Sachajko M, Jaskowski JM, Herudzinska M, Skowronski M, Domagalski K, Szczepanek J, Czarnik U, Sobiech P, Wysocka D, Pierzchala M, Polawska E, Stepanow K, Ogłuszka M, Juszczuk-Kubiak E, Feng Y, Kumar D. Comparative Analysis of the Liver Transcriptome among Cattle Breeds Using RNA-seq. Vet Sci. 2019;6:36.

Lisowski P, Kościuczuk EM, Gościk J, Pierzchała M, Rowińska B, ZwierzchowskiL. Hepatic transcriptome profiling identifies differences in expression of genes associated with changes in metabolism and postnatal growth between Hereford and Holstein-Friesian bulls. Anim Genet. 2014;45:288-92.

Salleh MS, Mazzoni G, Höglund JK, Olijhoek DW, Lund P, Løvendahl P, Kadarmideen HN. RNA-Seq transcriptomics and pathway analyses reveal potential regulatory genes and molecular mechanisms in high- and low-residual feed intake in Nordic dairy cattle. BMC Genomics. 2017;18:258.

Salleh SM, Mazzoni G, Løvendahl P, Kadarmideen HN. Gene co-expression networks from RNA sequencing of dairy cattle identifies genes and pathways affecting feed efficiency. BMC Bioinformatics. 2018;19:513.

Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics. 2009;25:1754–60.

Anders S, Pyl PT, Huber W. HTSeq—a Python framework to work with high-throughput sequencing data. Bioinformatics, 2015;1:166-169.

Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, et al. 1000 Genome Project Data Processing Subgroup. The Sequence alignment/map (SAM) format and SAMtools. Bioinformatics. 2009;25:2078-2079.

Anders S., Huber W. Differential expression analysis for sequence count data. Genome Biol. 2010;11:R106.

Robinson M.D., McCarthy D.J., Smyth G.K. edgeR: A Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139–140.

Translational Research in Veterinary Science

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Published

2020-01-16

How to Cite

1.
SACHAJKO, Mateusz, HERUDZIŃSKA, Magdalena, JASKOWSKI, Jedrzej M., SZCZEPANEK, Joanna, BUSZEWSKA-FORAJTA, Magdalena, FENG, Yaping, KUMAR, Dibyendu and PAREEK, Chandra Shekhar. Data set for transcriptome analysis of liver in cattle breeds. Translational Research in Veterinary Science. Online. 16 January 2020. Vol. 2, no. 2, pp. 51-56. [Accessed 11 August 2026]. DOI 10.12775/TRVS.2019.009.
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Vol. 2 No. 2 (2019)

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Research Articles

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