Identification of potential candidate genes controlling pea aphid tolerance in a Pisum fulvum high-density integrated DArTseq SNP-based genetic map

Eleonora Barilli, Estefania Carrillo-Perdomo, Maria Jose Cobos, Andrzej Kilian, Jason Carling, Diego Rubiales

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

BACKGROUND Pea (Pisum sativum) is one of the most important temperate grain legumes in the world, and its production is severely constrained by the pea aphid (Acyrthosiphon pisum). Wild relatives, such as P. fulvum, are valuable sources of allelic diversity to improve the genetic resistance of cultivated pea species against A. pisum attack. To unravel the genetic control underlying resistance to the pea aphid attack, a quantitative trait loci (QTL) analysis was performed using the previously developed high density integrated genetic linkage map originated from an intraspecific recombinant inbred line (RIL) population (P. fulvum: IFPI3260 x IFPI3251). RESULTS We accurately evaluated specific resistance responses to pea aphid that allowed the identification, for the first time, of genomic regions that control plant damage and aphid reproduction. Eight QTLs associated with tolerance to pea aphid were identified in LGs I, II, III, IV and V, which individually explained from 17.0% to 51.2% of the phenotypic variation depending on the trait scored, and as a whole from 17.0% to 88.6%. The high density integrated genetic linkage map also allowed the identification of potential candidate genes co-located with the QTLs identified. CONCLUSIONS Our work shows how the survival of P. fulvum after the pea aphid attack depends on the triggering of a multi-component protection strategy that implies a quantitative tolerance. The genomic regions associated with the tolerance responses of P. fulvum during A. pisum infestation have provided six potential candidate genes that could be useful in marker-assisted selection (MAS) and genomic assisted breeding (GAB) after functional validation in the future.
Original languageEnglish
Pages (from-to)1731-1742
Number of pages12
JournalPest Management Science
Volume76
Issue number5
DOIs
Publication statusPublished - 1 May 2020

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