« Back
Bovine RNA-seq data analysis of liver and pituitary gland
Poster Title: Bovine RNA-seq data analysis of liver and pituitary gland
Submitted on 12 May 2015
Author(s): Pareek CS12, Smoczyński R12, Dziuba P12, Sikora M12, Gołębiewski M2, Blaszczyk P12, Gelfand B3, Yaping F3, Kumar D3.
Affiliations: (1) Functional Genomics Lab. Faculty of Biology and Environmental Protection, Nicolaus Copernicus University, Torun, Poland, (2) Interdisciplinary Centre of Modern Technology, Nicolaus Copernicus University, Torun, Poland, (3) Genomics Core Facility, Waksman Institute of Microbiology, New Jersey, NJ, USA
This poster was presented at Advances in Next Generation Sequencing 28-29 May 2015, Sheraton Bangalore Hotel at Brigade Gateway Bangalore, India.
Poster Views: 3,705
View poster »

Poster Information
Abstract: An experimental design representing young growing bulls of three cattle breeds at three different developmental ages were sequenced in context to bovine body growth and developmental trait using Illumina NextSeq platform. Approximately 40-50 million paired-end reads were obtained per library (n=36). For each tissue, 18 breed-specific and age dependent-specific libraries were sequenced. Using a computational pipeline, tissue-specific transcripts were mapped to bovine reference genome (UMD3.1 assembly). Mapping tools ( was used to align the reads to the reference cattle genome. Results of transcriptome mapping of liver in Polish Red bulls revealed 98.88% mapping reads (400453035 map reads out of 408045666) and transcriptome mapping of pituitary gland in Hereford bulls revealed 97.80% mapping reads (337471226 map reads out of 345069302). However, paired end transcripts of pituitary gland (Hereford) and liver (Polish red) were properly paired @ of 82.22% and 79.56% respectively. Study provides a glimpse into the tissue specific mRNA content of bovine pituitary gland and liver which will eventually facilitate future experimental trait-associated studies to unravel the putative ESTs and/or causal SNPs for bovine body growth and developmental process.Summary: Two key applications of RNA-seq i.e., i) transcriptome read mapping to a reference genome and ii) SNP detections were investigated to analysis of bovine liver and pituitary gland transcriptome. Here, we have presented ONLY the obtained results of bovine pituitary gland.References: 1. M. Martin. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet.journal, North America, 17, May 2011. Available at:
2. Li H. and Durbin R. (2009) Fast and accurate short read alignment with Burrows-Wheeler Transform. Bioinformatics, 25:1754-60. [PMID: 19451168]
3. Li H.*, Handsaker B.*, Wysoker A., Fennell T., Ruan J., Homer N., Marth G., Abecasis G., Durbin R. and 1000 Genome Project Data Processing Subgroup (2009) The Sequence alignment/map (SAM) format and SAMtools. Bioinformatics, 25, 2078-9. [PMID: 19505943]
4. Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, Batut P, Chaisson M, Gingeras TR. (2013). STAR: ultrafast universal RNA-seq aligner. Bioinformatics, 29: 15-21
5. Dobin, A. (2015). Star manual 2.4.1a, Released on April, 2015:
Report abuse »
Ask the author a question about this poster.
Ask a Question »

Creative Commons