De novo construction of a "Gene-space" for diploid plant genome rich in repetitive sequences by an iterative Process of Extraction and Assembly of NGS reads (iPEA protocol) with limited computing resources. (December 2016)

• Record Type: Journal Article
• Authors: Aluome, Christelle; Aubert, Grégoire; Alves Carvalho, Susete; Paslier, Marie-Christine; Burstin, Judith; Brunel, Dominique
• Is Part Of: BMC research notes. Volume 9:Number 1(2016)
• Page Start: 1
• Page End: 9
• Publication Date: 2016-12
• Subjects: Gene-space -- Unigene -- Next-generation sequencing NGS -- Assembly -- Iterative process -- Limited computing resources; Medicine -- Periodicals; Biology -- Periodicals; 610.5
• DOI: 10.1186/s13104-016-1903-z
• Languages: English
• ISSNs: 1756-0500

Abstract

Abstract Background The continuing increase in size and quality of the "short reads" raw data is a significant help for the quality of the assembly obtained through various bioinformatics tools. However, building a reference genome sequence for most plant species remains a significant challenge due to the large number of repeated sequences which are problematic for a whole-genome quality de novo assembly. Furthermore, for most SNP identification approaches in plant genetics and breeding, only the "Gene-space" regions including the promoter, exon and intron sequences are considered. Results We developed the iPea protocol to produce a de novo Gene-space assembly by reconstructing, in an iterative way, the non-coding sequence flanking the Unigene cDNA sequence through addition of next-generation DNA-seq data. The approach was elaborated with the large diploid genome of pea (Pisum sativum L.), rich in repetitive sequences. The final Gene-space assembly included 35, 400 contigs (97 Mb), covering 88 % of the 40, 227 contigs (53.1 Mb) of the PsCam_low-copy Unigen set. Its accuracy was validated by the results of the built GenoPea 13.2 K SNP Array. Conclusion The iPEA protocol allows the reconstruction of a Gene-space based from RNA-Seq and DNA-seq data with limited computing resources.