PHENOPSIS DB: an Information System for Arabidopsis thaliana phenotypic data in an environmental context

<p>Abstract</p> <p>Background</p> <p>Renewed interest in plant × environment interactions has risen in the post-genomic era. In this context, high-throughput phenotyping platforms have been developed to create reproducible environmental scenarios in which the phenotypic responses of multiple genotypes can be analysed in a reproducible way. These platforms benefit hugely from the development of suitable databases for storage, sharing and analysis of the large amount of data collected. In the model plant <it>Arabidopsis thaliana</it>, most databases available to the scientific community contain data related to genetic and molecular biology and are characterised by an inadequacy in the description of plant developmental stages and experimental metadata such as environmental conditions. Our goal was to develop a comprehensive information system for sharing of the data collected in PHENOPSIS, an automated platform for <it>Arabidopsis thaliana </it>phenotyping, with the scientific community.</p> <p>Description</p> <p>PHENOPSIS DB is a publicly available (URL: <url>http://bioweb.supagro.inra.fr/phenopsis/</url>) information system developed for storage, browsing and sharing of online data generated by the PHENOPSIS platform and offline data collected by experimenters and experimental metadata. It provides modules coupled to a Web interface for (i) the visualisation of environmental data of an experiment, (ii) the visualisation and statistical analysis of phenotypic data, and (iii) the analysis of <it>Arabidopsis thaliana </it>plant images.</p> <p>Conclusions</p> <p>Firstly, data stored in the PHENOPSIS DB are of interest to the <it>Arabidopsis thaliana </it>community, particularly in allowing phenotypic meta-analyses directly linked to environmental conditions on which publications are still scarce. Secondly, data or image analysis modules can be downloaded from the Web interface for direct usage or as the basis for modifications according to new requirements. Finally, the structure of PHENOPSIS DB provides a useful template for the development of other similar databases related to genotype × environment interactions.</p

EG9PP_IBD.Rdata

IBD kinship matrices of oil palm multiparental population Eg9P

Continuous shrinkage priors for fixed and random e↵ects selection in linear mixed models: application to genetic mapping

The identification of random factors to include in a linear mixed model is crucial for modeling dependence structures while avoiding over-fitting. Random e↵ects selection can be achieved by shrinking non-relevant variance parameters towards zero. We propose extending the horseshoe prior for variance components selection in a folded version. Motivated by two applications, the folded-horseshoe prior is evaluated either in a genetic breeding or in a functional mapping context. In the latter, we use a polar parametrization of the correlation matrix of random e↵ects, using sinusoidal priors for angular parameters. Finally, we design e cient MCMC algorithms taking advantage of Kronecker product properties. From a statistical point of view, we show that the folded-horseshoe prior outperforms the folded-Cauchy when the number of parameters is close to the sample size. For variance component selection, it performs as well as the folded-spike-and-slab but it is computationally more e cient. We also show the impact of erroneous dependence structures assumptions on the selection and the estimation of variance components. From a genetic point of view, the numerical results highlight the e ciency of the folded-horseshoe prior. In particular, this prior selects molecular markers already identified in these data but also new markers. Finally, we discuss how and why linear mixed models are an interesting alternative to usual functional mapping approaches

Combined Genetic and Modeling Approaches Reveal That Epidermal Cell Area and Number in Leaves Are Controlled by Leaf and Plant Developmental Processes in Arabidopsis1[W]

Both leaf production and leaf expansion are tightly linked to cell expansion and cell division, but the functional relationships between all these variables are not clearly established. To get insight into these relationships, a quantitative genetic analysis was performed in 118 recombinant inbred lines derived from a cross between the Landsberg erecta and Antwerp accessions and was combined with a structural equation modeling approach. Main effects and epistatic interactions at the quantitative trait locus (QTL) level were detected for rosette area, rosette leaf number, leaf 6 area, epidermal cell area and number. A QTL at ERECTA marker (ER) controlled cell expansion and cell division, in interaction with two other QTLs at SNP295 and SNP21 markers. Moreover, both the screening for marker association involved in the variation of the relationships between leaf growth variables and the test of alternative functional models by structural equation modeling revealed that the allelic value at ER controlled epidermal cell area and epidermal cell number in a leaf. These effects are driven both by a whole plant mechanism associated with leaf production and by a single leaf mechanism associated with leaf expansion. The complex effects of the QTL at ER were validated in selected heterogeneous inbred families. The ERECTA gene, which is mutated in the Landsberg erecta parental line, was found to be a putative candidate responsible for these mapped effects by phenotyping mutants of this gene at the cellular level. Together, these results give insight into the complex determination of leaf epidermal cell number and area

Identification of Fusarium wilt resistance loci in two major genetic backgrounds for oil palm breeding

International audienceFusarium wilt (FW) caused by Fusarium oxysporum f. sp. elaeidis is the main disease of oil palm in Africa and is a latent threat to other producing regions. A long-term work based on a genetic survey of FW resistance using field observations and pre-nursery screening tests with inoculation resulted in FW resistant planting material whose resistance has not been overcome in 40 years. The genetic determinism of FW resistance has never been studied. Such information would eventually enable marker assisted selection (MAS) to ensure continuous improvement of planting material, through multi-trait selection (yield and disease or multiple diseases) and diversification of the genetic base. In this study, we used a pedigree-based QTL mapping approach that took advantage of the extensive pre-nursery FW resistance data recorded in the framework of a reciprocal recurrent selection program in Benin Republic. Eight QTL regions were mapped in two major genetic backgrounds and favorable QTL alleles were identified in the current breeding populations. The QTL pattern was specific to the population studied in terms of number, location and genetic variance explained, highlighting the different genetic architecture of FW resistance depending on the genetic background. To investigate a putative trade-off between FW resistance and yield, FW resistance QTL genotypes were predicted in a population that was formerly evaluated for yield in the field. The effects on yield of a FW QTL were offset in the commercial planting material thanks to different effects on different yield components in both heterotic groups. These results shed light on FW resistance in oil palm and provide valuable information for the implementation of MAS in the breeding program. Considering that prenursery screening tests are widely used, the approach presented here could be implemented in other breeding programs to provide further insights into FW resistance, especially in the context of wider genetic diversity