BackgroundField pea (Pisum sativum L.) is a cool-season grain legume that is cultivated world-wide for both human consumption and stock-feed purposes. Enhancement of genetic and genomic resources for field pea will permit improved understanding of the control of traits relevant to crop productivity and quality. Advances in second-generation sequencing and associated bioinformatics analysis now provide unprecedented opportunities for the development of such resources. The objective of this study was to perform transcriptome sequencing and characterisation from two genotypes of field pea that differ in terms of seed and plant morphological characteristics.ResultsTranscriptome sequencing was performed with RNA templates from multiple tissues of the field pea genotypes Kaspa and Parafield. Tissue samples were collected at various growth stages, and a total of 23 cDNA libraries were sequenced using Illumina high-throughput sequencing platforms. A total of 407 and 352 million paired-end reads from the Kaspa and Parafield transcriptomes, respectively were assembled into 129,282 and 149,272 contigs, which were filtered on the basis of known gene annotations, presence of open reading frames (ORFs), reciprocal matches and degree of coverage. Totals of 126,335 contigs from Kaspa and 145,730 from Parafield were subsequently selected as the reference set. Reciprocal sequence analysis revealed that c. 87 % of contigs were expressed in both cultivars, while a small proportion were unique to each genotype. Reads from different libraries were aligned to the genotype-specific assemblies in order to identify and characterise expression of contigs on a tissue-specific basis, of which 87 % were expressed in more than one tissue, while others showed distinct expression patterns in specific tissues, providing unique transcriptome signatures.ConclusionThis study provided a comprehensive assembled and annotated transcriptome set for field pea that can be used for development of genetic markers, in order to assess genetic diversity, construct linkage maps, perform trait-dissection and implement whole-genome selection strategies in varietal improvement programs, as well to identify target genes for genetic modification approaches on the basis of annotation and expression analysis. In addition, the reference field pea transcriptome will prove highly valuable for comparative genomics studies and construction of a finalised genome sequence.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-1815-7) contains supplementary material, which is available to authorized users.
Field pea (Pisum sativum L.) is an important grain legume consumed both as human food and animal feed. However, productivity in low rainfall regions can be significantly reduced by inferior soils containing high levels of boron and/or salinity. Furthermore, powdery mildew (PM) (Erysiphe pisi) disease also causes significant yield loss in warmer regions. Breeding for tolerance to these abiotic and biotic stresses are major aims for pea breeding programs and the application of molecular markers for these traits could greatly assist in developing improved germplasm at a faster rate. The current study reports the evaluation of a near diagnostic marker, PsMlo, associated with PM resistance and boron (B) tolerance as well as linked markers associated with salinity tolerance across a diverse set of pea germplasm. The PsMlo1 marker predicted the PM and B phenotypic responses with high levels of accuracy (>80%) across a wide range of field pea genotypes, hence offers the potential to be widely adapted in pea breeding programs. In contrast, linked markers for salinity tolerance were population specific; therefore, application of these markers would be suitable to relevant crosses within the program. Our results also suggest that there are possible new sources of salt tolerance present in field pea germplasm that could be further exploited.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.