Single-molecule real-time sequencing identifies massive full-length cDNAs and alternative-splicing events that facilitate comparative and functional genomics study in the hexaploid crop sweet potato.

Single-molecule real-time sequencing identifies massive full-length cDNAs and alternative-splicing events that facilitate comparative and functional genomics study in the hexaploid crop sweet potato.

Ding, Na;Cui, Huihui;Miao, Ying;Tang, Jun;Cao, Qinghe;Luo, Yonghai;
PeerJ 2019 Vol. 7 pp. e7933
236
ding2019singlemoleculepeerj

Abstract

Sweet potato ( (L.) Lam.) is one of the most important crops in many developing countries and provides a candidate source of bioenergy. However, neither a complete reference genome nor large-scale full-length cDNA sequences for this outcrossing hexaploid crop are available, which in turn impedes progress in research studies in functional genomics and molecular breeding.In this study, we sequenced full-length transcriptomes in and its diploid ancestor by single-molecule real-time sequencing and Illumina second-generation sequencing technologies. With the generated datasets, we conducted comprehensive intraspecific and interspecific sequence analyses and experimental characterization.A total of 53,861/51,184 high-quality long-read transcripts were obtained, which covered about 10,439/10,452 loci in the / genome. These datasets enabled us to predict open reading frames successfully in 96.83%/96.82% of transcripts and identify 34,963/33,637 full-length cDNA sequences, 1,401/1,457 transcription factors, 25,315/27,090 simple sequence repeats, 1,656/1,389 long non-coding RNAs, and 5,251/8,901 alternative splicing events. Approximately, 32.34%/38.54% of transcripts and 46.22%/51.18% multi-exon transcripts underwent alternative splicing in /. Moreover, we validated one alternative splicing event in each of 10 genes and identified tuberous-root-specific expressed isoforms from a starch-branching enzyme, an alpha-glucan phosphorylase, a neutral invertase, and several ABC transporters. Overall, the collection and analysis of large-scale long-read transcripts generated in this study will serve as a valuable resource for the research community, which may accelerate the progress in its structural, functional, and comparative genomics studies.

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