Approaches to variant discovery for conifer transcriptome sequencing

PLoS One. 2018 Nov 5;13(11):e0205835. doi: 10.1371/journal.pone.0205835. eCollection 2018.

Abstract

There is a wide diversity of bioinformatic tools available for the assembly of next generation sequence and subsequence variant calling to identify genetic markers at scale. Integration of genomics tools such as genomic selection, association studies, pedigree analysis and analysis of genetic diversity, into operational breeding is a goal for New Zealand's most widely planted exotic tree species, Pinus radiata. In the absence of full reference genomes for large megagenomes such as in conifers, RNA sequencing in a range of genotypes and tissue types, offers a rich source of genetic markers for downstream application. We compared nine different assembler and variant calling software combinations in a single transcriptomic library and found that Single Nucleotide Polymorphism (SNPs) discovery could vary by as much as an order of magnitude (8,061 SNPs up to 86,815 SNPs). The assembler with the best realignment of the packages trialled, Trinity, in combination with several variant callers was then applied to a much larger multi-genotype, multi-tissue transcriptome and identified 683,135 in silico SNPs across a predicted 449,951 exons when mapped to the Pinus taeda ver 1.01e reference.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Genotype
  • Polymorphism, Single Nucleotide / genetics*
  • RNA, Plant / genetics
  • RNA, Plant / isolation & purification
  • Sequence Analysis, RNA*
  • Software
  • Transcriptome / genetics*

Substances

  • RNA, Plant

Grants and funding

The financial support for this project has come from an agency that has since undergone a name change. The original financial support came from Foundation for Research, Science and Technology (FRST) Contract number CO4X0703 and has since been supported by our internally allocated Strategic Science Investment Fund (SSIF), allocated to New Zealand Forest Research Institute LTD, trading as Scion from the Ministry of Business, Innovation and Employment.