Design and evaluation of a sequence capture system for genome-wide SNP genotyping in highly heterozygous plant genomes: a case study with a keystone Neotropical hardwood tree genome

Abstract

Targeted sequence capture coupled to high-throughput sequencing has become a powerful method for the study of genome-wide sequence variation. Following our recent development of a genome assembly for the Pink Ipê tree (Handroanthus impetiginosus), a widely distributed Neotropical timber species, we now report the development of a set of 24,751 capture probes for single-nucleotide polymorphisms (SNPs) characterization and genotyping across 18,216 distinct loci, sampling more than 10 Mbp of the species genome. This system identifies nearly 200,000 SNPs located inside or in close proximity to almost 14,000 annotated protein-coding genes, generating quality genotypic data in populations spanning wide geographic distances across the species native range. To provide recommendations for future developments of similar systems for highly heterozygous plant genomes we investigated issues such as probe design, sequencing coverage and bioinformatics, including the evaluation of the capture efficiency and a reassessment of the technical reproducibility of the assay for SNPs recall and genotyping precision. Our results highlight the value of a detailed probe screening on a preliminary genome assembly to produce reliable data for downstream genetic studies. This work should inspire and assist the development of similar genomic resources for other orphan crops and forest trees with highly heterozygous genomes.

A genome-wide scan shows evidence for local adaptation in a widespread keystone Neotropical forest tree

“…Scaffold, SNP position, and affected gene were obtained from the genome assembly and annotation (Silva-Junior et al 2018a, 2018b). SNPEff annotation identifies the SNP position with respect to the genes annotated in the H. impetiginosus genome.…”

“…A set of 14,135 120-mer probe sequences targeting 11,026 distinct loci of the 30,271 predicted protein-coding genes across the genome assembly of H. impetiginosus (Silva-Junior et al 2018a, b) was used for DNA target enrichment to direct genotype SNPs in 128 individual trees. Targeted DNA enrichment, capture and sequencing were carried out as described earlier (Silva-Junior et al 2018b).…”

“…A set of 14,135 120-mer probe sequences targeting 11,026 distinct loci of the 30,271 predicted protein-coding genes across the genome assembly of H. impetiginosus (Silva-Junior et al 2018a, b) was used for DNA target enrichment to direct genotype SNPs in 128 individual trees. Targeted DNA enrichment, capture and sequencing were carried out as described earlier (Silva-Junior et al 2018b). Sequence data analysis and screening for polymorphism were performed with GATK-HaplotypeCaller (McKenna et al 2010) after all reads were aligned to the whole-genome assembly of H. impetiginosus with BWA software (Li and Durbin, 2009).…”

“…In this study, we carried out a population genomics survey of H. impetiginosus based on a capture-based target-enrichment system (Silva-Junior et al 2018b) targeting 10,246 loci across the genome of H. impetiginosus (Silva-Junior et al 2018a). With this system, 75,838 SNPs were genotyped in 128 individuals across 13 populations.…”

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

“…While targeted enrichment by sequence capture do provide generally reliable and portable SNP genotyping data in highly heterozygous species [8], several are the challenges of restriction enzyme based methods for robust SNP genotyping due to variable sequencing coverage, irregular sampling of loci and lack of a reference genome, causing frequent allele dropout and variable genotype reproducibility [9]. The final number of robust and portable SNPs across experiments is typically only a small fraction of the initial set, defeating the alleged cost advantage and possibly biasing genetic diversity measures [10,11].…”