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Large-Scale Transcriptome Analysis in Faba Bean (Vicia faba L.) under Ascochyta fabae Infection

AutorOcaña-Moral, Sara; Seoane, Pedro; Bautista, Rocío; Palomino, Carmen ; Claros, Gonzalo M.; Torres, Ana M.; Madrid, Eva
Fecha de publicación12-ago-2015
EditorPublic Library of Science
CitaciónPLoS ONE 10(8): e0135143 (2015)
ResumenFaba bean is an important food crop worldwide. However, progress in faba bean genomics lags far behind that of model systems due to limited availability of genetic and genomic information. Using the Illumina platform the faba bean transcriptome from leaves of two lines (29H and Vf136) subjected to Ascochyta fabae infection have been characterized. De novo transcriptome assembly provided a total of 39,185 different transcripts that were functionally annotated, and among these, 13,266 were assigned to gene ontology against Arabidopsis. Quality of the assembly was validated by RT-qPCR amplification of selected transcripts differentially expressed. Comparison of faba bean transcripts with those of better-characterized plant genomes such as Arabidopsis thaliana, Medicago truncatula and Cicer arietinum revealed a sequence similarity of 68.3%, 72.8% and 81.27%, respectively. Moreover, 39,060 single nucleotide polymorphism (SNP) and 3,669 InDels were identified for genotyping applications. Mapping of the sequence reads generated onto the assembled transcripts showed that 393 and 457 transcripts were overexpressed in the resistant (29H) and susceptible genotype (Vf136), respectively. Transcripts involved in plant-pathogen interactions such as leucine rich proteins (LRR) or plant growth regulators involved in plant adaptation to abiotic and biotic stresses were found to be differently expressed in the resistant line. The results reported here represent the most comprehensive transcript database developed so far in faba bean, providing valuable information that could be used to gain insight into the pathways involved in the resistance mechanism against A. fabae and to identify potential resistance genes to be further used in marker assisted selection.
Versión del editorhttp://doi.org/10.1371/journal.pone.0135143
URIhttp://hdl.handle.net/10261/158427
DOI10.1371/journal.pone.0135143
ISSN1932-6203
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