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      Genome-wide patterns of segregation and linkage disequilibrium: the construction of a linkage genetic map of the poplar rust fungus Melampsora larici-populina

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          Abstract

          The poplar rust fungus Melampsora larici-populina causes significant yield reduction and severe economic losses in commercial poplar plantations. After several decades of breeding for qualitative resistance and subsequent breakdown of the released resistance genes, breeders now focus on quantitative resistance, perceived to be more durable. But quantitative resistance also can be challenged by an increase of aggressiveness in the pathogen. Thus, it is of primary importance to better understand the genetic architecture of aggressiveness traits. To this aim, our goal is to build a genetic linkage map for M. larici-populina in order to map quantitative trait loci related to aggressiveness. First, a large progeny of M. larici-populina was generated through selfing of the reference strain 98AG31 (which genome sequence is available) on larch plants, the alternate host of the poplar rust fungus. The progeny's meiotic origin was validated through a segregation analysis of 115 offspring with 14 polymorphic microsatellite markers, of which 12 segregated in the expected 1:2:1 Mendelian ratio. A microsatellite-based linkage disequilibrium analysis allowed us to identify one potential linkage group comprising two scaffolds. The whole genome of a subset of 47 offspring was resequenced using the Illumina HiSeq 2000 technology at a mean sequencing depth of 6X. The reads were mapped onto the reference genome of the parental strain and 144,566 SNPs were identified across the genome. Analysis of distribution and polymorphism of the SNPs along the genome led to the identification of 2580 recombination blocks. A second linkage disequilibrium analysis, using the recombination blocks as markers, allowed us to group 81 scaffolds into 23 potential linkage groups. These preliminary results showed that a high-density linkage map could be constructed by using high-quality SNPs based on low-coverage resequencing of a larger number of M. larici-populina offspring.

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          Pathogen population genetics, evolutionary potential, and durable resistance.

          We hypothesize that the evolutionary potential of a pathogen population is reflected in its population genetic structure. Pathogen populations with a high evolutionary potential are more likely to overcome genetic resistance than pathogen populations with a low evolutionary potential. We propose a flexible framework to predict the evolutionary potential of pathogen populations based on analysis of their genetic structure. According to this framework, pathogens that pose the greatest risk of breaking down resistance genes have a mixed reproduction system, a high potential for genotype flow, large effective population sizes, and high mutation rates. The lowest risk pathogens are those with strict asexual reproduction, low potential for gene flow, small effective population sizes, and low mutation rates. We present examples of high-risk and low-risk pathogens. We propose general guidelines for a rational approach to breed durable resistance according to the evolutionary potential of the pathogen.
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            Pivoting the plant immune system from dissection to deployment.

            Diverse and rapidly evolving pathogens cause plant diseases and epidemics that threaten crop yield and food security around the world. Research over the last 25 years has led to an increasingly clear conceptual understanding of the molecular components of the plant immune system. Combined with ever-cheaper DNA-sequencing technology and the rich diversity of germ plasm manipulated for over a century by plant breeders, we now have the means to begin development of durable (long-lasting) disease resistance beyond the limits imposed by conventional breeding and in a manner that will replace costly and unsustainable chemical controls.
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              High-throughput genotyping by whole-genome resequencing.

              The next-generation sequencing technology coupled with the growing number of genome sequences opens the opportunity to redesign genotyping strategies for more effective genetic mapping and genome analysis. We have developed a high-throughput method for genotyping recombinant populations utilizing whole-genome resequencing data generated by the Illumina Genome Analyzer. A sliding window approach is designed to collectively examine genome-wide single nucleotide polymorphisms for genotype calling and recombination breakpoint determination. Using this method, we constructed a genetic map for 150 rice recombinant inbred lines with an expected genotype calling accuracy of 99.94% and a resolution of recombination breakpoints within an average of 40 kb. In comparison to the genetic map constructed with 287 PCR-based markers for the rice population, the sequencing-based method was approximately 20x faster in data collection and 35x more precise in recombination breakpoint determination. Using the sequencing-based genetic map, we located a quantitative trait locus of large effect on plant height in a 100-kb region containing the rice "green revolution" gene. Through computer simulation, we demonstrate that the method is robust for different types of mapping populations derived from organisms with variable quality of genome sequences and is feasible for organisms with large genome sizes and low polymorphisms. With continuous advances in sequencing technologies, this genome-based method may replace the conventional marker-based genotyping approach to provide a powerful tool for large-scale gene discovery and for addressing a wide range of biological questions.
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                Author and article information

                Contributors
                Journal
                Front Plant Sci
                Front Plant Sci
                Front. Plant Sci.
                Frontiers in Plant Science
                Frontiers Media S.A.
                1664-462X
                10 September 2014
                2014
                : 5
                : 454
                Affiliations
                [1] 1Interactions Arbres - Micro organismes, Institut national de la recherche agronomique, UMR1136 Champenoux, France
                [2] 2Interactions Arbres - Micro organismes, Université de Lorraine, UMR1136 Vandoeuvre-lès-Nancy, France
                Author notes

                Edited by: Ton Bisseling, Wageningen University, Netherlands

                Reviewed by: Peter Dodds, Commonwealth Scientific and Industrial Research Organisation, Australia; Eric Kemen, Max Planck Institute for Plant Breeding Research, Germany

                *Correspondence: Pascal Frey, Interactions Arbres - Micro organismes, INRA, UMR1136, Rue d'Amance, F-54280 Champenoux, France e-mail: pascal.frey@ 123456nancy.inra.fr

                This article was submitted to Plant-Microbe Interaction, a section of the journal Frontiers in Plant Science.

                Article
                10.3389/fpls.2014.00454
                4159982
                a8549358-921f-4967-b584-7cf19e028c59
                Copyright © 2014 Pernaci, De Mita, Andrieux, Pétrowski, Halkett, Duplessis and Frey.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 31 May 2014
                : 21 August 2014
                Page count
                Figures: 6, Tables: 3, Equations: 0, References: 67, Pages: 13, Words: 10658
                Categories
                Plant Science
                Original Research Article

                Plant science & Botany
                fungal pathogen,linkage mapping,genome mapping,genome sequencing,mendelian segregation,single-nucleotide polymorphism,selfing,progeny

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