A high-density exome capture genotype-by-sequencing panel for forestry breeding in Pinus radiata

Abstract

Development of genome-wide resources for application in genomic selection or genome-wide association studies, in the absence of full reference genomes, present a challenge to the forestry industry, where longer breeding cycles could benefit from the accelerated selection possible through marker-based breeding value predictions. In particular, large conifer megagenomes require a strategy to reduce complexity, whilst ensuring genome-wide coverage is achieved. Using a transcriptome-based reference template, we have successfully developed a high density exome capture genotype-by-sequencing panel for radiata pine (Pinus radiata D.Don), capable of capturing in excess of 80,000 single nucleotide polymorphism (SNP) markers with a minor allele frequency above 0.03 in the population tested. This represents approximately 29,000 gene models from a core set of 48,914 probes. A set of 704 SNP markers capable of pedigree reconstruction and differentiating individual genotypes were tested within two full-sib mapping populations. While as few as 70 markers could reconstruct parentage in almost all cases, the impact of missing genotypes was noticeable in several offspring. Therefore, 60 sets of 110 randomly selected SNP markers were compared for both parentage reconstruction and clone differentiation. The performance in parentage reconstruction showed little variation over 60 iterations. However, there was notable variation in discriminatory power between closely related individuals, indicating a higher density SNP marker panel may be required to elucidate hidden relationships in complex pedigrees.

A 3K Axiom®SNP array from a transcriptome-wide SNP resource sheds new light on the genetic diversity and structure of the iconic subtropical conifer treeAraucaria angustifolia(Bert.) Kuntze

“…When all filters are considered, the final efficiency of RNA-seq in terms of assayable SNPs per quality raw sequence read was 1.6X higher than RAD-seq (0.012% versus 0.0075%). RNA-seq or exome-capture with RNA-derived probes has been the method of choice for SNP discovery and SNP array development in the very large and complex conifer genomes [38,39,42,43,75]. Our results confirm that RNA-seq is an efficient strategy for the identification of bona fide sequence variants.…”

A 3K Axiom SNP array from a transcriptome-wide SNP resource sheds new light on the genetic diversity and structure of the iconic subtropical conifer tree Araucaria angustifolia (Bert.) Kuntze

“…When all filters are considered, the final efficiency of RNA-seq in terms of assayable SNPs per quality raw sequence read was 1.6X higher than RAD-seq (0.012% versus 0.0075%). RNA-seq or exome-capture with RNA-derived probes has been the method of choice for SNP discovery and SNP array development in the very large and complex conifer genomes [38,39,42,43,76]. Our results confirm that RNA-seq is an efficient strategy for the identification of bona fide sequence variants.…”

Effect of trait’s expression level on single-step genomic evaluation of resistance to Dothistroma needle blight

“…Genomic data were generated through exome capture -genotyping-by-sequencing approach [21] using genomic resources based on resequencing of transcriptome extracted from compression wood xylem, spring xylem, summer xylem, summer phloem, spring buds, autumn buds, healthy needles, needles infected by Phytophtora pluvialis, seedling phloem and seedling xylem [66]. Captured markers were removed if heterozygosity shown in megagametophyte tissues was higher than 5%, average read depth less than 10, multiallelic status, singletons and additionally each datapoint was classified as missing if ratio between reference and alternative allele was lower than 0.1 and number of read was less that 10 [67]. The marker data were further refined for minor allele frequency (MAF) ≥0.05, and missing data were replaced by the mean genotype.…”