Camille Lepoittevin

French National Institute for Agricultural Research, Lutetia Parisorum, Île-de-France, France

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Publications (6)19.39 Total impact

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    ABSTRACT: Association mapping is a recommended method to dissect the genetic basis of naturally occurring trait variation in non-model tree species with outcrossing mating systems and large population sizes. We report here the results of the first association-mapping study in maritime pine (Pinus pinaster Ait.), a conifer species of economical importance for timber and pulp production in south-western Europe. Two association samples were examined: 160 plus trees belonging to the first generation breeding population (G0, resulting from mass selection for overall good growth and form in the forest of South West of France) and 162 trees from the second generation breeding population (G1, resulting from biparental crosses between G0 trees). These samples were (1) genotyped for 184 in vitro SNPs discovered in 40 candidate genes for plant cell wall formation or drought stress resistance and 200 in silico SNPs detected in 146 contigs from the maritime pine EST database and (2) phenotyped for growth, stem straightness and wood chemistry traits in progeny or clonal experimental designs (from 768 to 5,080 phenotypes depending on the trait). First, SNP data were used to test for putative stratification in the breeding population. Then, two different approaches using pedigree records to account for inbreeding were used to test for associations. Despite the a priori low power of the designs, we identified two mutations that were significantly associated, one with variation in growth (in a HD-Zip III transcription factor) and the other with variation in wood cellulose content (in a fasciclin-like arabinogalactan protein).
    Tree Genetics & Genomes 01/2012; 8:113-126. · 2.40 Impact Factor
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    ABSTRACT: Microsatellites have been popular molecular markers ever since their advent in the late eighties. Despite growing competition from new genotyping and sequencing techniques, the use of these versatile and cost-effective markers continues to increase, boosted by successive technical advances. First, methods for multiplexing PCR have considerably improved over the last years, thereby decreasing genotyping costs and increasing throughput. Second, next-generation sequencing technologies allow the identification of large numbers of microsatellite loci at reduced cost in non-model species. As a consequence, more stringent selection of loci is possible, thereby further enhancing multiplex quality and efficiency. However, current practices are lagging behind. By surveying recently published population genetic studies relying on simple sequence repeats, we show that more than half of the studies lack appropriate quality controls and do not make use of multiplex PCR. To make the most of the latest technical developments, we outline the need for a well-established strategy including standardized high-throughput bench protocols and specific bioinformatic tools, from primer design to allele calling.
    Molecular Ecology Resources 07/2011; 11(4):591-611. · 7.43 Impact Factor
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    ABSTRACT: Single nucleotide polymorphisms (SNPs) are the most abundant source of genetic variation among individuals of a species. New genotyping technologies allow examining hundreds to thousands of SNPs in a single reaction for a wide range of applications such as genetic diversity analysis, linkage mapping, fine QTL mapping, association studies, marker-assisted or genome-wide selection. In this paper, we evaluated the potential of highly-multiplexed SNP genotyping for genetic mapping in maritime pine (Pinus pinaster Ait.), the main conifer used for commercial plantation in southwestern Europe. We designed a custom GoldenGate assay for 1,536 SNPs detected through the resequencing of gene fragments (707 in vitro SNPs/Indels) and from Sanger-derived Expressed Sequenced Tags assembled into a unigene set (829 in silico SNPs/Indels). Offspring from three-generation outbred (G2) and inbred (F2) pedigrees were genotyped. The success rate of the assay was 63.6% and 74.8% for in silico and in vitro SNPs, respectively. A genotyping error rate of 0.4% was further estimated from segregating data of SNPs belonging to the same gene. Overall, 394 SNPs were available for mapping. A total of 287 SNPs were integrated with previously mapped markers in the G2 parental maps, while 179 SNPs were localized on the map generated from the analysis of the F2 progeny. Based on 98 markers segregating in both pedigrees, we were able to generate a consensus map comprising 357 SNPs from 292 different loci. Finally, the analysis of sequence homology between mapped markers and their orthologs in a Pinus taeda linkage map, made it possible to align the 12 linkage groups of both species. Our results show that the GoldenGate assay can be used successfully for high-throughput SNP genotyping in maritime pine, a conifer species that has a genome seven times the size of the human genome. This SNP-array will be extended thanks to recent sequencing effort using new generation sequencing technologies and will include SNPs from comparative orthologous sequences that were identified in the present study, providing a wider collection of anchor points for comparative genomics among the conifers.
    BMC Genomics 01/2011; 12:368. · 4.40 Impact Factor
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    ABSTRACT: Introduction Tree breeding is giving an increasing attention to wood properties in order to better fit the requirements of the saw, board, pulp and paper industries. In particular, it has been reported that lignin and cellulose content display moderate to high heritabilities making them prime candidates for genetic improvement of wood chemistry. Moreover, these traits have been shown to be negatively correlated at both phenotypic and genetic levels. However, they have generally been evaluated against a narrow genetic background, and little is known about their correlations with mandatory selection criteria such as growth and straightness. Materials and methods In this study, we first investigated the performance of near-infrared (NIR) spectroscopy combined with a non-destructive sampling method to assess chemical properties of wood in maritime pine. We afterwards estimated genetic parameters of growth, stem form and wood chemistry traits across a large genetic background in a progeny trial and clonally replicated progenies. Results Our results showed that removal of extractives prior to NIR spectra acquisition is highly recommended for achieving high accuracy in NIRS-PLSR prediction for wood chemistry traits in maritime pine. We further observed moderate heritabilities (0.15–0.55) for the studied traits. Wood chemistry traits were genetically inter-correlated (e.g., negatively between lignin and cellulose), whereas correlations with growth were not significant, indicating that growth and chemical properties could be improved independently.
    Annals of Forest Science 01/2011; 68:873-884. · 1.63 Impact Factor
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    ABSTRACT: There is considerable interest in the high-throughput discovery and genotyping of single nucleotide polymorphisms (SNPs) to accelerate genetic mapping and enable association studies. This study provides an assessment of EST-derived and resequencing-derived SNP quality in maritime pine (Pinus pinaster Ait.), a conifer characterized by a huge genome size ( approximately 23.8 Gb/C). A 384-SNPs GoldenGate genotyping array was built from i/ 184 SNPs originally detected in a set of 40 re-sequenced candidate genes (in vitro SNPs), chosen on the basis of functionality scores, presence of neighboring polymorphisms, minor allele frequencies and linkage disequilibrium and ii/ 200 SNPs screened from ESTs (in silico SNPs) selected based on the number of ESTs used for SNP detection, the SNP minor allele frequency and the quality of SNP flanking sequences. The global success rate of the assay was 66.9%, and a conversion rate (considering only polymorphic SNPs) of 51% was achieved. In vitro SNPs showed significantly higher genotyping-success and conversion rates than in silico SNPs (+11.5% and +18.5%, respectively). The reproducibility was 100%, and the genotyping error rate very low (0.54%, dropping down to 0.06% when removing four SNPs showing elevated error rates). This study demonstrates that ESTs provide a resource for SNP identification in non-model species, which do not require any additional bench work and little bio-informatics analysis. However, the time and cost benefits of in silico SNPs are counterbalanced by a lower conversion rate than in vitro SNPs. This drawback is acceptable for population-based experiments, but could be dramatic in experiments involving samples from narrow genetic backgrounds. In addition, we showed that both the visual inspection of genotyping clusters and the estimation of a per SNP error rate should help identify markers that are not suitable to the GoldenGate technology in species characterized by a large and complex genome.
    PLoS ONE 01/2010; 5(6):e11034. · 3.53 Impact Factor
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    BMC proceedings 5(7).