RNA-seq based SNP discovery in gluteus medius muscle of Polish Landrace pigs
DOI:
https://doi.org/10.12775/TRVS.2019.004Keywords
Single nucleotide variations, SNPs, paired-end, genetic markers, RNA-seq, illumina, paired-end read, GATK, SAMtools, mapping, bioinformatics, NGS, transcriptome, gluteus medius muscle, Landrace, pig, Omega-6 and omega-3 polyunsaturated fatty acidAbstract
Background
Single nucleotide polymorphisms (SNPs) are the well-known molecular markers in genetics and breeding studies applied to veterinary sciences and livestock production. Advancement of next generation sequencing (NGS) provides a high-throughput means of potential putative SNP discovery. The aim of the study was to identify the putative genetic variants in gluteus medius muscle transcriptome of Polish Landrace pigs.
Methods
RNA-seq based NGS experiment was performed on Polish Landrace pigs fed with omega-6 and omega-3 polyunsaturated fatty acids (PUFAs) and normal diets. Isolation of total RNA from gluteus medius muscle was performed on low PUFAs (n=6) and High PUFAs dietary group of Polish Landrace pigs. The RNA-seq libraries were constructed by mRNA enrichment, mRNA fragmentation, second strand cDNA synthesis, adaptor ligation, size selection and PCR amplification using the illumina TruSeq RNA Sample Prep Kit v2 (Illumina, San Diego CA, USA), followed by NGS sequencing on MiSeq illumina platform. The quality control of raw RNA-seq data was performed using the Trimmomatic and FastQC tools. High QC paired-end RNA-seq data of gluteus medius muscle transcriptome were mapped to the reference genome Sus scrofa v.10.2. Finally, the SNPs discovery was performed using GATK and SAMtools bioinformatics SNPs caller tools.
Results
The Fastq RNA-seq data generated from two pooled paired-end libraries (151bp) of gluteus medius muscle tissue of Polish Landrace pigs were submitted to NCBI SRA database (https://www.ncbi.nlm.nih.gov/sra). Study identified a total of 50.5 million paired-end reads (32.5 million low PUFAs dietary group and 18 million reads high PUFAs dietary group) of gluteus medius muscle transcriptome of Polish Landrace pigs. SNP discovery identified a total of 35436 homozygous and 28644 heterozygous cSNPs in gluteus medius muscle transcriptomes representing both dietary groups of Polish Landrace pig. Moreover, a total of 25187 and 5488 cSNP were identified as synonymous SNPs, and 18005 and 4780 cSNP were identified as nonsynonymous SNPs. Finally, single nucleotide variation (SNV) representing substitutions of all four possibilities (A,T,G,C) were identified ranging 2935 to 3227 SNVs (high PUFAs) and 3528 to 3882 SNVs (low PUFAs) for the heterozygous cSNPs and 2712 to 4058 (high PUFAs) and 4169 to 5692 SNVs (low PUFAs) for the heterozygous SNPs in gluteus medius muscle transcriptomes of Polish Landrace pigs.
Conclusions
Study concluded that identification of cSNPs dataset representing the gluteus medius muscle transcriptome of Polish Landrace pigs fed with a control diet (low) and pigs fed with a PUFAs diet (high) may be helpful to develop a new set of genetic markers specific to Polish Landrace pig breed. Such cSNP markers eventually can be utilized in genome-wide association studies (GWAS) and to finally implement on marker assisted selection (MAS) and genomics selection (GS) program in active breeding population of Polish Landrace pigs in Poland.
References
Zwane AA, Schnabel RD, Hoff J, Choudhury A, Makgahlela ML, Maiwashe A, Van Marle-Koster E, Taylor JF. Genome-Wide SNP Discovery in Indigenous Cattle Breeds of South Africa. Front Genet. 2019;10: 273.
Wang W, Gan J, Fang D, Tang H, Wang H, Yi J, Fu M. Genome-wide SNP discovery and evaluation of genetic diversity among six Chinese indigenous cattle breeds in Sichuan. PLoS One. 2018;13:e0201534.
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, Smoczyński R, Kadarmideen HN, Dziuba P, Błaszczyk P, Sikora M, Walendzik P, Grzybowski T, Pierzchała M, Horbańczuk J, Szostak A, Ogluszka M, Zwierzchowski L, Czarnik U, Fraser L, Sobiech P, Wąsowicz K, Gelfand B, Feng Y, Kumar D. Single Nucleotide Polymorphism Discovery in Bovine Pituitary Gland Using RNA-Seq Technology. PLoS One. 2016;11:e0161370.
Doran AG, Creevey CJ. Snpdat: easy and rapid annotation of results from de novo snp discovery projects for model and non-model organisms. BMC Bioinformatics. 2013;14:45.
DePristo MA, Banks E, Poplin R, Garimella KV, Maguire JR, Hartl C, Philippakis AA, Del Angel G, Rivas MA, Hanna M, et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat Genet. 2011;43:491–498.
Stothard P, Choi JW, Basu U, Sumner-Thomson JM, Meng Y, Liao X, Moore SS. Whole genome resequencing of black Angus and Holstein cattle for SNP and CNV discovery. BMC Genomics. 2011;12:559.
Zhang Q, Zhao S, Chen H, Zhang L, Zhang L, Li F, Wang X. SNP discovery and haplotype analysis in the bovine PRKAA2 gene. Mol Biol Rep. 2011;38:1551-6.
Cánovas A, Rincon G, Islas-Trejo A, Wickramasinghe S, Medrano JF. SNP discovery in the bovine milk transcriptome using RNA-Seq technology. Mamm Genome. 2010;21:592-598.
Brookes AJ. The essence of SNPs. Gene. 1999;234:177–186.
Trick M, Long Y, Meng J, Bancroft I. Single nucleotide polymorphism (SNP) discovery in the polyploidy Brassica napus using Solexa transcriptome sequencing. Plant Biotechnol J. 2009;7:334–346.
Jehan T, Lakhanpaul S. Single nucleotide polymorphism (SNP) – methods and applications in plant genetics: a review. Indian J Biotechnol. 2006;5:435–459.
Hiremath PJ, Kumar A, Penmetsa RV, Farmer A, Schlueter JA, Chamarthi SK, Whaley AM, Carrasquilla-Garcia N, Gaur PM, Upadhyaya HD, et al. Large-scale development of cost-effective SNP marker assays for diversity assessment and genetic mapping in chickpea and comparative mapping in legumes. Plant Biotechnol J. 2012;10:1–17.
Garrido-Cardenas JA, Mesa-Valle C, Manzano-Agugliaro F. Trends in plant research using molecular markers. Planta. 2018;247:543–557.
Seeb JE, Carvalho G, Hauser L, Naish K, Roberts S, Seeb LW. Single-nucleotide polymorphism (SNP) discovery and applications of SNP genotyping in nonmodel organisms. Mol Ecol Resour. 2011;11:1–8.
Suh Y, Vijg J. SNP discovery in associating genetic variation with human disease phenotypes. Mutat Res. 2005;573:41-53.
Stouffer K, Nahorski M, Moreno P, Sarveswaran N, Menon D, Lee M, Geoffrey Woods C. Functional SNP allele discovery (fSNPd): an approach to find highly penetrant, environmental-triggered genotypes underlying complex human phenotypes. BMC Genomics. 2017;18:944.
Kumar S, Banks TW, Cloutier S. SNP discovery through next-generation sequencing and its applications. Int J Plant Genomics. 2012;2012:1–15.
Davey JW, Hohenlohe PA, Etter PD, Boone JQ, Catchen JM, Blaxter ML. Genome-wide genetic marker discovery and genotyping using next-generation sequencing. Nat Rev Genet. 2011;12:499–510.
Pareek CS, Smoczynski R, Pierzchala M, Czarnik U, Tretyn A. From genotype to phenotype in bovine functional genomics. Brief Funct Genomics. 2011;10:165-171.
Quinn EM, Cormican P, Kenny EM, Hill M, Anney R, Gill M, Corvin AP, Morris DW. Development of strategies for SNP detection in RNA-Seq data: application to lymphoblastoid cell lines and evaluation using 1000 genomes data. PLoS One. 2013;8: e58815.
Ogłuszka M, Szostak A, Te Pas MFW, Poławska E, Urbański P, Blicharski T, Pareek CS, Juszczuk-Kubiak E, Dunkelberger JR, Horbańczuk JO, Pierzchała M. A porcine gluteus medius muscle genome-wide transcriptome analysis: dietary effects of omega-6 and omega-3 fatty acids on biological mechanisms. Genes Nutr. 2017;12: 4.
Huber LA, Hooda S, Fisher-Heffernan RE, Karrow NA, de Lange CFM. Effect of reducing the ratio of omega-6-to-omega-3 fatty acids in diets of low protein quality on nursery pig growth performance and immune response. J Anim Sci. 2018;96: 4348-4359.
D'Alessandro E, Giosa D, Sapienza I, Giuffrè L, Cigliano RA, Romeo O, Zumbo A. [PROVISIONAL] Whole genome SNPs discovery in Nero Siciliano pig. Genet Mol Biol. 2019;pii: S1415-47572019005021102.
Chomczynski P., Sacchi N. Single-step method of RNA isolation by acid guanidinium thiocyanate-phenol-chloroform extraction. Anal. Biochem. 1987;162:156–159.
Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30: 2114-2120.
Wingett SW, Andrews S. FastQ Screen: A tool for multi-genome mapping and quality control. Version 2. F1000Res. 2018;7 :1338.
Pareek CS, Sachajko M, Szczepański A, Buszewska-Forajta M, Zarczynska K, Sobiech P, Juszczuk-Kubiak E, Shahzad Q, Lu YQ, Ogłuszka M, Poławska E, PierzchałaM. Quality control assessment of the RNA-Seq data generated from liver and pituitary transcriptome of Hereford bulls using StrandNGS software. Trans Res vet Sci. 2019;2:
do Valle ÍF, Giampieri E, Simonetti G, Padella A, Manfrini M, Ferrari A, Papayannidis C, Zironi I, Garonzi M, Bernardi S, Delledonne M, Martinelli G, Remondini D, Castellani G. Optimized pipeline of MuTect and GATK tools to improve the detection of somatic single nucleotide polymorphisms in whole-exome sequencing data. BMC Bioinformatics. 2016;17: 341.
Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R, 1000 Genome Project Data Processing Subgroup The sequence alignment/map format and SAMtools. Bioinformatics. 2009;25: 2078–2079.
Downloads
Published
How to Cite
Issue
Section
License
Title, logo and layout of TR in VS are reserved trademarks of TR in VR.
Stats
Number of views and downloads: 541
Number of citations: 0