Massive Analysis of cDNA Ends (MACE) for transcript-based marker design in pea (Pisum sativum L.)

Publication Overview
TitleMassive Analysis of cDNA Ends (MACE) for transcript-based marker design in pea (Pisum sativum L.)
AuthorsZhernakov A, Rotter B, Winter P, Borisov A, Tikhonovich I, Zhukov V
TypeJournal Article
Journal NameGenomics data
Volume11
Year2017
Page(s)75-76
CitationZhernakov A, Rotter B, Winter P, Borisov A, Tikhonovich I, Zhukov V. Massive Analysis of cDNA Ends (MACE) for transcript-based marker design in pea (Pisum sativum L.). Genomics data. 2017 Mar; 11:75-76.

Abstract

Aimed at gene-based markers design, we generated and analyzed transcriptome sequencing datasets for six pea (Pisum sativum L.) genetic lines that have not previously been massively genotyped. Five cDNA libraries obtained from nodules or nodulated roots of genetic lines Finale, Frisson, Sparkle, Sprint-2 and NGB1238 were sequenced using a versatile 3'-RNA-seq protocol called MACE (Massive Analysis of cDNA Ends). MACE delivers a single next-generation sequence from the 3'-end of each individual cDNA molecule that precisely quantifies the respective transcripts. Since the contig generated from the 3'-end of the cDNA by assembling all sequences encompasses the highly polymorphic 3'-untranslated region (3'-UTR), MACE efficiently detects single nucleotide variants (SNVs). Mapping MACE reads to the reference nodule transcriptome assembly of the pea line SGE (Transcriptome Shotgun Assembly GDTM00000000.1) resulted in characterization of over 34,000 polymorphic sites in more than 9700 contigs. Several of these SNVs were located within recognition sequences of restriction endonucleases which allowed the design of co-dominant CAPS markers for the particular transcript. Cleaned reads of sequenced libraries are available from European Nucleotide Archive (http://www.ebi.ac.uk/) under accessions PRJEB18101, PRJEB18102, PRJEB18103, PRJEB18104, PRJEB17691.

Properties
Additional details for this publication include:
Property NameValue
Publication ModelElectronic-eCollection
Publication Date2017 Mar
Journal AbbreviationGenom Data
DOI10.1016/j.gdata.2016.12.004
Elocation10.1016/j.gdata.2016.12.004
LanguageEnglish
Language Abbreng
Publication TypeJournal Article
Journal CountryUnited States