Cultivar-specific transcriptome and pan-transcriptome reconstruction of tetraploid potato

Abstract

Although the reference genome of Solanum tuberosum Group Phureja double-monoploid (DM) clone is available, knowledge on the genetic diversity of the highly heterozygous tetraploid Group Tuberosum, representing most cultivated varieties, remains largely unexplored. This lack of knowledge hinders further progress in potato research. In conducted investigation, we first merged and manually curated the two existing partially-overlapping DM genome-based gene models, creating a union of genes in Phureja scaffold. Next, we compiled available and newly generated RNA-Seq datasets (cca. 1.5 billion reads) for three tetraploid potato genotypes (cultivar Désirée, cultivar Rywal, and breeding clone PW363) with diverse breeding pedigrees. Short-read transcriptomes were assembled using several de novo assemblers under different settings to test for optimal outcome. For cultivar Rywal, PacBio Iso-Seq full-length transcriptome sequencing was also performed. EvidentialGene redundancy-reducing pipeline complemented with in-house developed scripts was employed to produce accurate and complete cultivar-specific transcriptomes, as well as to attain the pan-transcriptome. The generated transcriptomes and pan-transcriptome represent a valuable resource for potato gene variability exploration, high-throughput omics analyses, and breeding programmes.

De novo Transcriptome Assembly and Comprehensive Annotation of Two Tree Tomato Cultivars (Solanum betaceum Cav.) with Different Fruit Color

“…The number of transcripts of these accessions was slightly higher than those obtained in previous transcriptome studies in other related Solanaceae species such as tomato, potato or pepino (Solanum muricatum Aiton) [14,38,39], but it was similar to others obtained in plant species of the same family, such as S. commersonii Dunal and S. aculeatissimum [40,41], suggesting the high quality and reliability of our assemblies. Furthermore, the assembly and annotation completeness was quantitatively confirmed by the high percentage values (>98%) of the BUSCO assessment, values that were comparable or even higher than those of other recent Solanum transcriptomes, which exhibited values of 97% for S. tuberosum and 93% for S. chilense [42,43].…”

Precision transcriptomics of viral foci reveals the spatial regulation of immune‐signaling genes and identifies RBOHD as an important player in the incompatible interaction between potato virus Y and potato

“…Quality control was performed in CLC GENOMICS WORKBENCH 12.0 (Qiagen). The merging of overlapping pairs, the mapping of reads to the potato genome (Petek et al, 2020) and read counting were performed in both CLC GENOMICS and STAR. Differential expression analysis was performed in r (R Core Team, 2020; version 3.2.2), using the R package LIMMA (Ritchie et al, 2015), trimmed mean of M values (TMM) normalization and voom function.…”

pISA-tree - a data management framework for life science research projects using a standardised directory tree

“…The second example is an implementation of pISA-tree in a large-scale dry-lab project ("Solanum tuberosum Reference Transcriptomes", https://fairdomhub.org/projects/161). This project's aim was to construct a pan-transcriptome from high-volume data accessible from publicly available resources and in-house defined workflows in a collaborative way (Petek, Zagorščak, et al, 2020) The project consists of a single investigation, four studies and a plethora of data files (Fig. 4), encompassing four consecutive bioinformatics procedures: (1) high-throughput sequencing acquisition and pre-processing, (2) de novo assembly, (3) cultivar-specific transcriptomes generation and annotation, and (4) pan-transcriptome generation and annotation.…”

“…The second example is an implementation of pISA-tree in a large-scale dry-lab project ("Solanum tuberosum Reference Transcriptomes", https://fairdomhub.org/projects/161). This project's aim was to construct a pan-transcriptome from high-volume data accessible from publicly available resources and in-house defined workflows in a collaborative way (Petek, Zagorščak, et al, 2020).…”