A multi-tissue transcriptome strategy for genomic resource development in Pinus edulis
- 1University of California, Berkeley
Abstract
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.
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BibTeX
@misc{macias2026multitissue,
title = {{A multi-tissue transcriptome strategy for genomic resource development in Pinus edulis}},
author = {D. S. Macias and E. F. Gyllenhaal and J. A. Kleinkopf and W. T. Pockman and H. E. Marx},
howpublished = {bioRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.05.756810},
url = {https://www.biorxiv.org/content/10.64898/2026.10.05.756810v1},
note = {CC BY-NC},
}
RIS
TY - UNPB
TI - A multi-tissue transcriptome strategy for genomic resource development in Pinus edulis
AU - D. S. Macias
AU - E. F. Gyllenhaal
AU - J. A. Kleinkopf
AU - W. T. Pockman
AU - H. E. Marx
PY - 2026
DA - 2026/10/05
PB - bioRxiv
DO - 10.64898/2026.10.05.756810
UR - https://www.biorxiv.org/content/10.64898/2026.10.05.756810v1
AB - 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.
ER -