Approaches to variant discovery for conifer transcriptome sequencing

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 divers...

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Bibliographic Details
Published in:PloS one 2018-11, Vol.13 (11), p.e0205835-e0205835
Main Authors: Telfer, Emily, Graham, Natalie, Macdonald, Lucy, Sturrock, Shane, Wilcox, Phillip, Stanbra, Lisa
Format: Article
Language:English
Subjects:
Bioinformatics
Biology and Life Sciences
Breeding
Computer and Information Sciences
Conifers
Datasets
Deoxyribonucleic acid
DNA
Engineering and Technology
Exons
Gene expression
Gene polymorphism
Gene sequencing
Genetic analysis
Genetic diversity
Genetic markers
Genetics
Genomes
Genomics
Genotypes
Introduced species
Markers
Molecular biology
Pedigree
Pine trees
Polymorphism
Realignment
Research and Analysis Methods
Ribonucleic acid
RNA
Single-nucleotide polymorphism
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Summary: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.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0205835