2021
DOI: 10.1111/1755-0998.13484
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A genome‐wide SNP genotyping resource for tropical pine tree species

Abstract: We performed gene and genome targeted SNP discovery towards the development of a genome-wide, multispecies genotyping array for tropical pines. Pooled RNA-seq data from shoots of seedlings from five tropical pine species was used to identify transcript-based SNPs resulting in 1.3 million candidate Affymetrix SNP probe sets.

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Cited by 12 publications
(10 citation statements)
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“…More than 45% of SNPs are within the PHR category, which are considered the most informative markers. This highlights the benefit of prior evaluation of candidate SNPs on a screening array, similar to what has been reported by other conifer groups [27,42,43] where conversion rates have improved from 39% on the screening array to 96% on the genotyping array.…”
Section: Performance Of the Genotyping Arraysupporting
confidence: 79%
See 1 more Smart Citation
“…More than 45% of SNPs are within the PHR category, which are considered the most informative markers. This highlights the benefit of prior evaluation of candidate SNPs on a screening array, similar to what has been reported by other conifer groups [27,42,43] where conversion rates have improved from 39% on the screening array to 96% on the genotyping array.…”
Section: Performance Of the Genotyping Arraysupporting
confidence: 79%
“…As part of an international Conifer SNP Consortium (CSC) [27,[41][42][43], we have developed a 36K SNP array for radiata pine using the Axiom™ platform. Fixed array platforms are regarded as the gold standard for robust and reliable high throughput genotyping.…”
Section: Introductionmentioning
confidence: 99%
“…All non‐pine origin sequences and unannotated contigs were discarded to produce the final transcriptomes for P. oocarpa (Pioo_v1.0), P. greggii (Pigr_v1.0) and P. maximinoi (Pima_v1.0). Remaining protein sequences were additionally annotated using Mercator (Lohse et al, 2014) to allow visualisation of expression in MapMan v3.5.1R2 (Thimm et al, 2014), as well as GhostKOALA (Kanehisa et al, 2016) to predict Kyoto Encyclopaedia of Genes and Genomes (KEGG) orthology (KO) of proteins. Benchmarking Universal Single Copy Orthologs (BUSCO) v3.0.2 (Simão et al, 2015; Waterhouse et al, 2017), with the eukaryote ( n = 255), viridiplantae ( n = 425) and embryophyte ( n = 1,614) OrthoDB 10 databases, was used to determine the completeness and contiguity of assemblies.…”
Section: Methodsmentioning
confidence: 99%
“…Phylogenetic reconstruction using a small number of genes is susceptible to random errors (Hedtke et al, 2006;Zhang et al, 2015). Transcriptomes and genomes are widely used in phylogenetic and evolutionary studies of plants (Jackson et al, 2022) and animals (Bi et al, 2021;Meyer et al, 2021). However, due to the giga-genome of pine trees, it is difficult to assemble genomes and use them to study evolution in Pinaceae.…”
Section: Introductionmentioning
confidence: 99%