Siol M, Prosperi JM, Bonnin I, Ronfort J.. How multilocus genotypic pattern helps to understand the history of selfing populations: a case study in Medicago truncatula. Heredity 100: 517-525

UMR 1097 Diversité et Adaptations des Plantes Cultivées, INRA Montpellier, Domaine de Melgueil, Mauguio, France.
Heredity (Impact Factor: 3.81). 06/2008; 100(5):517-25. DOI: 10.1038/hdy.2008.5
Source: PubMed


The occurrence of populations exhibiting high genetic diversity in predominantly selfing species remains a puzzling question, since under regular selfing genetic diversity is expected to be depleted at a faster rate than under outcrossing. Fine-scale population genetics approaches may help to answer this question. Here we study a natural population of the legume Medicago truncatula in which both the fine-scale spatial structure and the selfing rate are characterized using three different methods. Selfing rate estimates were very high ( approximately 99%) irrespective of the method used. A clear pattern of isolation by distance reflecting small seed dispersal distances was detected. Combining genotypic data over loci, we could define 34 multilocus genotypes. Among those, six highly inbred genotypes (lines) represented more than 75% of the individuals studied and harboured all the allelic variation present in the population. We also detected a large set of multilocus genotypes resembling recombinant inbred lines between the most frequent lines occurring in the population. This finding illustrates the importance of rare recombination in redistributing available allelic diversity into new genotypic combinations. This study shows how multilocus and fine-scale spatial analyses may help to understand the population history of self-fertilizing species, especially to make inferences about the relative role of foundation/migration and recombination events in such populations.

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Available from: Jean-Marie Prosperi, Oct 01, 2015
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    • "The > 70% of reads calling a variant means that no heterozygous sites were identified within individuals. This should have minor effects given high selfing rates in natural populations (> 95%; Bonnin et al., 2001; Siol et al., 2008) and ≥ 3 generations of selfing before DNA extraction. "
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    ABSTRACT: • The use of quantitative disease resistance (QDR) is a promising strategy to promote durable resistance to plant pathogens, but genes involved in QDR are largely unknown. To identify genetic components and accelerate improvement of QDR in legumes to the root pathogen Aphanomyces euteiches, we took advantage of both the recently generated massive genomic data for Medicago truncatula and natural variation of this model legume. • A high density (≈5.1 million Single Nucleotide Polymorphisms - SNPs) Genome-Wide Association Study (GWAS) was performed with both in vitro and greenhouse phenotyping data collected on 179 lines. • GWAS identified several candidate genes, and pinpointed two independent major loci on the top of chromosome 3 that were detected in both phenotyping methods. Candidate SNPs in the most significant locus (σ2A = 23%) were in the promoter and coding regions of an F-box protein coding gene. Subsequent qRT-PCR and bioinformatic analyses performed on 20 lines demonstrated that resistance is associated with mutations directly affecting the interaction domain of the F-box protein rather than gene expression. • These results refine the position of previously identified QTL to specific candidate genes, suggest potential molecular mechanisms, and identify new loci explaining QDR to A. euteiches.
    New Phytologist 11/2013; 201(4). DOI:10.1111/nph.12611 · 7.67 Impact Factor
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    • "The >70% of reads calling a variant means that there are no heterozygous sites within individuals. This should have minor effects given high selfing rates in natural populations (>95%) [45], [46] and ≥3 generations of selfing prior to DNA extraction. Positions with >1000 (deep 26) or >500 unique reads for shallow accessions were excluded to prevent variant calling SNPs in repetitive regions that appear only once in the reference genome. "
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    ABSTRACT: Genome-wide association study (GWAS) has revolutionized the search for the genetic basis of complex traits. To date, GWAS have generally relied on relatively sparse sampling of nucleotide diversity, which is likely to bias results by preferentially sampling high-frequency SNPs not in complete linkage disequilibrium (LD) with causative SNPs. To avoid these limitations we conducted GWAS with >6 million SNPs identified by sequencing the genomes of 226 accessions of the model legume Medicago truncatula. We used these data to identify candidate genes and the genetic architecture underlying phenotypic variation in plant height, trichome density, flowering time, and nodulation. The characteristics of candidate SNPs differed among traits, with candidates for flowering time and trichome density in distinct clusters of high linkage disequilibrium (LD) and the minor allele frequencies (MAF) of candidates underlying variation in flowering time and height significantly greater than MAF of candidates underlying variation in other traits. Candidate SNPs tagged several characterized genes including nodulation related genes SERK2, MtnodGRP3, MtMMPL1, NFP, CaML3, MtnodGRP3A and flowering time gene MtFD as well as uncharacterized genes that become candidates for further molecular characterization. By comparing sequence-based candidates to candidates identified by in silico 250K SNP arrays, we provide an empirical example of how reliance on even high-density reduced representation genomic makers can bias GWAS results. Depending on the trait, only 30-70% of the top 20 in silico array candidates were within 1 kb of sequence-based candidates. Moreover, the sequence-based candidates tagged by array candidates were heavily biased towards common variants; these comparisons underscore the need for caution when interpreting results from GWAS conducted with sparsely covered genomes.
    PLoS ONE 05/2013; 8(5):e65688. DOI:10.1371/journal.pone.0065688 · 3.23 Impact Factor
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    • "Then, for only the MLGs shared by multiple populations, the number of each MLG was compiled per population. To gain insight into the number of independent origins of glyphosate resistance, MLGs in highly resistant populations were classified as nonrecombinant or recombinant with respect to other MLGs within the populations (Siol et al. 2008). Population structure was further investigated using the model-based Bayesian clustering program InStruct (Gao et al. 2007). "
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    ABSTRACT: Recent increases in glyphosate use in perennial crops of California, USA, are hypothesized to have led to an increase in selection and evolution of resistance to the herbicide in Conyza canadensis populations. To gain insight into the evolutionary origins and spread of resistance and to inform glyphosate resistance management strategies, we investigated the geographical distribution of glyphosate resistance in C. canadensis across and surrounding the Central Valley, its spatial relationship to groundwater protection areas (GWPA), and the genetic diversity and population structure and history using microsatellite markers. Frequencies of resistant individuals in 42 sampled populations were positively correlated with the size of GWPA within counties. Analyses of population genetic structure also supported spread of resistance in these areas. Bayesian clustering and approximate Bayesian computation (ABC) analyses revealed multiple independent origins of resistance within the Central Valley. Based on parameter estimation in the ABC analyses, resistant genotypes underwent expansion after glyphosate use began in agriculture, but many years before it was detected. Thus, diversity in weed control practices prior to herbicide regulation in GWPA probably kept resistance frequencies low. Regionally coordinated efforts to reduce seed dispersal and selection pressure are needed to manage glyphosate resistance in C. canadensis.
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