A multi-tissue transcriptome strategy for genomic resource development in Pinus edulis

Premise:: Conifers comprise one-sixth of global forests and landscape genomic studies are urgently needed to understand their biology, yet relatively few conifer species have reference genomes. Targeted exon-capture is a practical alternative to whole-genome sequencing, but selecting loci without a reference genome remains a barrier. We developed a multi-tissue reference transcriptome for pi non pine (Pinus edulis) to ask how multi-tissue sampling improves probe design, and what is lost under a conventional single-tissue approach. Methods: We assembled a reference transcriptome from four diploid tissues (needle, phloem, root, vegetative bud) and one haploid tissue (megagametophyte), using the latter as a pseudo-guide. We designed a target-capture probe-set by prioritizing highly expressed P. edulis transcripts and transcripts matching a conifer exon database. Results: We recovered 76% of conserved plant genes with few duplicated transcripts. Filtering yielded 15,664 transcripts totaling 31.4 Mb, ~0.1% of the genome. Tissue-specific expression was substantial: 27.4% of transcripts occurred exclusively in non-needle tissues. Functional annotation confirmed complementary contributions, including seed-desiccation and germination genes from megagametophytes, and defense- and stress-associated genes from roots and phloem. Discussion: We built a transcriptome and efficient probe set using a roadmap suitable for other non-model plants with large genomes; keys to success were prioritizing complementary tissues and using expression-based filtering.