4.2 Article

Pilot RNA-seq data from 24 species of vascular plants at Harvard Forest

Journal

APPLICATIONS IN PLANT SCIENCES
Volume 9, Issue 2, Pages -

Publisher

WILEY
DOI: 10.1002/aps3.11409

Keywords

community transcriptomics; NEON; polyploidy; RNA‐ seq; transcriptome assembly

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Funding

  1. National Science Foundation [NSF 1550838, NSF 1750280]

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This study involved generating and analyzing RNA-seq data for 24 vascular plant species, highlighting the challenges of collecting RNA data from diverse plant communities and revealing no significant differences in transcriptome quality between diploid and polyploid species. The findings provide opportunities for future large-scale studies at the intersection of ecology and genomics.
Premise Large-scale projects such as the National Ecological Observatory Network (NEON) collect ecological data on entire biomes to track climate change. NEON provides an opportunity to launch community transcriptomic projects that ask integrative questions in ecology and evolution. We conducted a pilot study to investigate the challenges of collecting RNA-seq data from diverse plant communities. Methods We generated >650 Gbp of RNA-seq for 24 vascular plant species representing 12 genera and nine families at the Harvard Forest NEON site. Each species was sampled twice in 2016 (July and August). We assessed transcriptome quality and content with TransRate, BUSCO, and Gene Ontology annotations. Results Only modest differences in assembly quality were observed across multiple k-mers. On average, transcriptomes contained hits to >70% of loci in the BUSCO database. We found no significant difference in the number of assembled and annotated transcripts between diploid and polyploid transcriptomes. Discussion We provide new RNA-seq data sets for 24 species of vascular plants in Harvard Forest. Challenges associated with this type of study included recovery of high-quality RNA from diverse species and access to NEON sites for genomic sampling. Overcoming these challenges offers opportunities for large-scale studies at the intersection of ecology and genomics.

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