Biology subjects

Frouin, J.

Publications and source records attributed to Frouin, J..

6 recordsLinked to original sources

bioRxiv2023

Characterization of adaptation mechanisms in sorghum using a multi-reference back-cross nested association mapping design and envirotyping

The identification of haplotypes influencing traits of agronomic interest, with well-defined effects across environments, is of key importance to develop varieties adapted to their context of use. It requires advanced crossing schemes, multi-environment characterization and relevant statistical tools. Here we present a sorghum multi-reference back-cross nested association mapping (BCNAM) population composed of 3901 lines produced by crossing 24 diverse parents to three elite parents from West and Central Africa (WCA-BCNAM). The population was characterized in environments contrasting for photoperiod, rainfall, temperature, and soil fertility. To analyse this multi-parental and multi-environment design, we developed a new methodology for QTL detection and parental effect estimation. In addition, envirotyping data were mobilized to determine the influence of specific environmental covariables on the genetic effects, which allowed spatial projections of the QTL effects. We mobilized this strategy to analyse the genetic architecture of flowering time and plant height, which represent key adaptation mechanisms in environments like West Africa. Our results allowed a better characterisation of well-known genomic regions influencing flowering time concerning their response to photoperiod with Ma6 and Ma1 being photoperiod sensitive and candidate gene Elf3 being insensitive. We also accessed a better understanding of plant height genetic determinism with the combined effects of phenology dependent (Ma6) and independent (qHT7.1 and Dw3) genomic regions. Therefore, we argue that the WCA-BCNAM constitutes a key genetic resource to feed breeding programs in relevant elite parental lines and develop climate-smart varieties.

genetics↗

bioRxiv2022

Extensive immune receptor repertoire diversity in disease-resistant rice landraces

Plants have powerful defence mechanisms, and extensive immune receptor repertoires, yet crop monocultures are prone to epidemic diseases. Rice is susceptible to many diseases, such as rice blast caused by Magnaporthe oryzae. Varietal resistance of rice to blast relies on intracellular nucleotide binding, leucine-rich repeat (NLR) receptors that recognize specific pathogen molecules and trigger immune responses. In the Yuanyang terraces in south-west China, rice landraces rarely show severe losses to disease whereas commercial inbred lines show pronounced field susceptibility. Here, we investigate within-landrace NLR sequence diversity of nine rice landraces and eleven modern varieties of indica, japonica and aus using complexity reduction techniques. We find that NLRs display high sequence diversity in landraces, consistent with balancing selection, and that balancing selection at NLRs is more pervasive in landraces than modern varieties. Notably, modern varieties lack many ancient NLR haplotypes that are retained in some landraces. Our study emphasises the value of standing genetic variation that is maintained in farmer landraces as resource to make modern crops and agroecosystems less prone to disease.

evolutionary biology↗

bioRxiv2022

High-frequency synthetic apomixis in hybrid rice

Introducing asexual reproduction through seeds - apomixis - into crop species could revolutionize agriculture by allowing F1 hybrids with enhanced yield and stability to be clonally propagated. Engineering synthetic apomixis has proven feasible in inbred rice through the inactivation of three genes (MiMe), which results in the conversion of meiosis into mitosis in a line ectopically expressing the BABYBOOM1 (BBM1) parthenogenetic trigger in egg cells. However, only 10-30% of the seeds were clonal. We show here that synthetic apomixis can be induced in a F1 hybrid of rice by inducing MiMe mutations and egg cell expression of BBM1 in a single step. We generated hybrid plants that produced more than 95% of clonal seeds across multiple generations. Clonal apomictic plants maintained the phenotype of the F1 hybrid along successive generations. Our results demonstrate that there is no barrier to almost fully penetrant synthetic apomixis in an important crop species, rendering it compatible with use in agriculture.

plant biology↗

bioRxiv2022

Genome scan of landrace populations of the self-fertilizing crop species rice, collected across time, revealed climate changes' selective footprints in the genes network regulating flowering time.

Analysis of the genetic bases of adaptation to climate changes are often conducted on natural populations. We report here on a study based on diachronic sampling (1980 & 2010) of the self-fertilising crop species, Oryza sativa (Asian rice) and Oryza glaberrima (African rice), in the tropical forest and the Sudanian savannah of West Africa. First, using historical meteorological data we confirmed changes in temperatures (+1{degrees}C on average) and rainfall regime (less predictable and reduced amount) in the target area. Second, phenotyping the populations for phenology, we observed significantly earlier heading time (up to 10 days) in the 2010 samples. Third, we implemented two genome-scan methods, one of which specially developed for selfing species, and detected 31 independent selection footprints. These loci showed significant enrichment in genes involved in reproductive processes and bore known heading time QTLs and genes, including OsGI, Hd1 and OsphyB. This rapid adaptive evolution, originated from subtle changes in the standing variation in genetic network regulating heading time, did not translate into predominance of multilocus genotypes, as it is often the case in selfing plants, and into notable selective sweeps. We argue that this high adaptive potential results from the multiline genetic structure of the rice landraces, and the rather large and imbricated genetic diversity of the rice meta-population at the farm, the village and the region levels, that hosted the adaptive variants in multiple genetic backgrounds well before the advent of the environmental selective pressure. The complex selection footprints observed in this empirical study calls for further model development on genetic bases of plant adaptation to environmental changes.

genetics↗

bioRxiv2018

Selection of trait-specific markers and multi-environment models improve genomic predictive ability in rice

Developing high yielding rice varieties that are tolerant to drought stress is crucial for the sustainable livelihood of rice farmers in rainfed rice cropping ecosystems. Genomic selection (GS) promises to be an effective breeding option for these complex traits. We evaluated the effectiveness of two rather new options in the implementation of GS: trait and environment-specific marker selection and the use of multi-environment prediction models. A reference population of 280 rainfed lowland accessions endowed with 215k SNP markers data was phenotyped under a favorable and two managed drought environments. Trait-specific SNP subsets (28k) were selected for each trait under each environment, using results of GWAS performed with the complete genotype dataset. Performances of single-environment and multi-environment genomic prediction models were compared using kernel regression based methods (GBLUP and RKHS) under two cross validation scenario: availability (CV2) or not (CV1) of phenotypic data for the validation set, in one of the environments. The most realistic trait-specific marker selection strategy achieved predictive ability (PA) of genomic prediction was up to 22% higher than markers selected on the bases of neutral linkage disequilibrium (LD). Tolerance to drought stress was up to 32% better predicted by multi-environment models (especially RKHS based models) under CV2 strategy. Under the less favorable CV1 strategy, the multi-environment models achieved similar PA than the single-environment predictions. We also showed that reasonable PA could be obtained with as few as 3,000 SNP markers, even in a population of low LD extent, provided marker selection is based on pairwise LD. The implications of these findings for breeding for drought tolerance are discussed. The most resource sparing option would be accurate phenotyping of the reference population in a favorable environment and under a managed drought, while the candidate population would be phenotyped only under one of those environments.

genetics↗

bioRxiv2018

Genomic prediction offers the most effective marker assisted breeding approach for ability to prevent arsenic accumulation in rice grains

The high concentration of arsenic in the paddy fields and, consequently, in the rice grains is a critical issue in many rice-growing areas. Breeding arsenic tolerant rice varieties that prevent As uptake and its accumulation in the grains is a major mitigation options. However, the genetic control of the trait is complex, involving large number of gene of limited individual effect, and raises the question of the most efficient breeding method. Using data from three years of experiment in a naturally arsenic-reach field, we analysed the performances of the two major breeding methods: conventional, quantitative trait loci based, selection targeting loci involved in arsenic tolerance, and the emerging, genomic selection, predicting genetic values without prior hypotheses on causal relationships between markers and target traits. We showed that once calibrated in a reference population the accuracy of genomic prediction of arsenic content in the grains of the breeding population was rather high, ensuring genetic gains per time unite close to phenotypic selection. Conversely, selection targeting quantitative loci proved to be less robust as, though in agreement with the literature on the genetic bases of arsenic tolerance, few target loci identified in the reference population could be validated in the breeding population.

genetics↗