Development and Validation of a 36K SNP Array for Radiata Pine (Pinus radiata D.Don)

Abstract

Radiata pine (Pinus radiata D.Don) is one of the world’s most domesticated pines and a key economic species in New Zealand. Thus, the development of genomic resources for radiata pine has been a high priority for both research and commercial breeding. Leveraging off a previously developed exome capture panel, we tested the performance of 438,744 single nucleotide polymorphisms (SNPs) on a screening array (NZPRAD01) and then selected 36,285 SNPs for a final genotyping array (NZPRAD02). These SNPs aligned to 15,372 scaffolds from the Pinus taeda L. v. 1.01e assembly, and 20,039 contigs from the radiata pine transcriptome assembly. The genotyping array was tested on more than 8000 samples, including material from archival progenitors, current breeding trials, nursery material, clonal lines, and material from Australia. Our analyses indicate that the array is performing well, with sample call rates greater than 98% and a sample reproducibility of 99.9%. Genotyping in two linkage mapping families indicated that the SNPs are well distributed across the 12 linkage groups. Using genotypic data from this array, we were also able to differentiate representatives of the five recognized provenances of radiata pine, Año Nuevo, Monterey, Cambria, Cedros and Guadalupe. Furthermore, principal component analysis of genotyped trees revealed clear patterns of population structure, with the primary axis of variation driven by provenance ancestry and the secondary axis reflecting breeding activities. This represents the first commercial use of genomics in a radiata pine breeding program.

Genomics-Enabled Management of Genetic Resources in Radiata Pine

“…In our analyses, as few as 2000-5000 markers were sufficient to reach a plateau in predictive ability, which is not surprising given the high level of relatedness within and across the populations we used and is consistent with both theoretical [75] and empirical results [71]. It is also possible that linkage disequilibrium caused by the recent admixture of breeding populations developed in New Zealand, including the surprisingly high proportion of trees with island ancestry [32], made it possible to achieve moderate GBLP predictive abilities with a relatively small number of markers. Genomic prediction in more homogeneous populations of distantly related individuals indicate that the number of markers needed to saturate predictive ability is both trait-and population-specific [47,83,84].…”

“…This platform allowed us to generate data for 50,917 SNP markers. Second, a subset of the GBS markers were used to develop a custom radiata pine Affymetrix Axiom 36K array, NZPRAD02, which included 36,285 SNPs [32].…”

What matters most? Assessment of within-canopy factors influencing the needle microbiome of the model conifer, Pinus radiata

“…In these systems, metagenomic methods are unlikely to be effective. For example, the Pinus radiata genome is approximately 25 billion base pairs in size [ 70 ] (or ~ 8 x the human genome); the detection let alone assembly of microbial genomes that are 1000’s of times smaller and far less abundant in DNA concentration than that of the host, will be challenging (and expensive). Regardless, the benefit of conducting culture-based isolation and genome sequencing is the capacity to gain direct information from the culture itself, from fundamental physiological information (e.g.…”

Whole‐genome resequencing facilitates the development of a 50K single nucleotide polymorphism genotyping array for Scots pine (Pinus sylvestris L.) and its transferability to other pine species

“…In forest tree species, SNP arrays have been developed in the last decade for economically important genera like Populus , Eucalyptus , and several conifers (Ahmar et al., 2021; Grattapaglia, 2022). However, most recently developed SNP arrays in conifer species were exclusively based on transcriptomic data (RNA‐seq, exome capture sequencing, and candidate genes), thus representing only coding, genic regions (Chancerel et al., 2013; Graham et al., 2022; Howe et al., 2020; Kastally et al., 2022; Pavy et al., 2013; Perry et al., 2020; Plomion et al., 2016). A few studies have used genome‐wide reduced‐representation sequencing as a complement to transcriptomic sources for conifer SNP array development (Caballero et al., 2021; Jackson et al., 2022).…”

“…Breeding of Scots pine in Sweden started with the selection of plus trees in the 1940s and 1950s, and a further expansion of the breeding populations occurred in the 1980s (Haapanen et al., 2015). Until recently, conifer SNP arrays have been limited to a couple thousand SNPs, and are currently based on RNA sequencing, exome capture, or candidate gene sequencing (Chancerel et al., 2013; Graham et al., 2022; Howe et al., 2020; Kastally et al., 2022; Pavy et al., 2013; Perry et al., 2020; Plomion et al., 2016; reviewed in Ahmar et al., 2021; Grattapaglia, 2022). Markers in such SNP arrays thus only represent coding sequences, leaving out all the intergenic space, which constitutes the bigger part of the genome and is an integral part of population genetics studies.…”