Biology subjects

Bouchet, S.

Publications and source records attributed to Bouchet, S..

7 recordsLinked to original sources

bioRxiv2026

New three-dimensional preclinical models to understand and treat liver cancers activated for the β-catenin pathway

Background & aimsConstitutive activation of the {beta}-catenin pathway is a determining feature in the pathogenesis of two primary liver cancers, namely HCC and hepatoblastoma (HB). Activating alterations in CTNNB1 gene and, to a lesser extent, inhibiting alterations in APC gene are observed in 30 to 40% of HCC cases and 80 to 90% of HB cases. For both tumours, therapeutic management is far from optimal. Therefore, relevant experimental models are needed to increase our knowledge and test new therapeutic approaches. MethodsOrganoids and tumouroids were established from APC{Delta}hep and {beta}cat{Delta}ex3 mouse models, which are clinically relevant models for {beta}-catenin-activated HCC and mesenchymal HB. We developed a new methodological approach based on a dynamic suspension culture in a rotating bioreactor. Morphological and molecular characteristics and sensitivity to WNTinib, a treatment already successfully tested on human HCC and HB tumouroids, were evaluated by histology, immunohistochemistry, immunofluorescence, and RT-qPCR. ResultsThis easy-to-implement methodology allows for the rapid generation of a large number of organoids and tumouroids that are uniform in size and show no signs of cell death in their core. The robustness of the methodology is illustrated by the maintenance of the histological architecture, cell diversity and gene expression in organoids and tumouroids in comparison with the native liver tissues. In addition, the value of the HCC-derived tumouroids for evaluating cancer treatment was assessed based on their responsiveness to the {beta}-catenin antagonist WNTinib. ConclusionsThe organoids and tumouroids that we present here are new reliable in vitro cancer models, recapitulating the main features of {beta}-catenin-driven HCC and mesenchymal HB. They can be integrated into an appropriate platform for drug screening and could enable the development of "a la carte" therapies that are urgently needed for these indications. Impact and implicationsThis study addresses the critical need for representative in vitro models to investigate {beta}-catenin-driven liver cancers. The organoids and tumouroids developed here are particularly valuable for researchers seeking robust, reproducible models that accurately reflect the cellular diversity and gene expression profiles of native liver tumours. These findings have practical applications in exploring cancer mechanisms, screening new drugs, optimizing personalized treatment strategies, and reducing reliance on animal models, which ultimately benefits patients. HighlightsO_LIEasy and rapid generation of mouse liver organoids and tumouroids from {beta}-catenin activated tumours using culture in a bioreactor C_LIO_LITumouroids preserve histology, cell diversity, and gene expression of native tissue C_LIO_LIHCC-derived tumouroids respond to {beta}-catenin inhibitor WNTinib C_LIO_LIThese reliable 3D models reduce reliance on animal experiments for drug testing C_LI

cell biology↗

bioRxiv2023

Validation of cross progeny variance genomic prediction using simulations and experimental data in winter elite bread wheat

The utilization of genomic prediction is increasing in crop breeding to parental selection and mating. The Usefulness Criterion (UC) that considers Parental Mean (PM), progeny Standard Deviation (SD) and selection intensity has been shown to increase the likelihood to get outstanding progenies compared to mating using PM alone while maintaining more diversity in the germplasm for next generations. This study estimates our ability to predict UC and its two components (PM and SD) using simulations and experimental data (73-101 winter bread wheat crosses depending on the trait, with 54.8 progenies on average) including heading date, plant height, grain protein content and yield evaluation. The training population comprises 2,146 French varieties registered during the last 20 years and INRAE-AO breeding lines. According to simulations, prediction ability increases with heritability and progeny size and decreases with QTL number, most notably for SD. We used as a reference a TRUE scenario, i.e. an optimal situation where TP is infinite and where marker effects are perfectly estimated. SD was strongly impacted by the quality of marker effect estimates. In simulations, considering the error in marker effect estimates improved SD predictions for quantitative traits with low heritability. In experimental data, the interest of this method was limited. PM and UC were reasonably predicted for all traits, while SD was more challenging. This pioneering study experimentally validates genomic prediction of progeny variance. The ability of prediction depends on trait architecture while the realization of cross potential in the field necessitates a sufficient number of progenies. Key messageFrom simulations and experimental data, the quality of cross progeny variance genomic predictions may be high, but depends on trait architecture and necessitates sufficient number of progenies.

genomics↗

bioRxiv2023

Comparison of genomic-enabled cross selection criteria for the improvement of inbred line breeding populations

A crucial step in inbred plant breeding is the choice of mating design to derive high-performing inbred varieties while also maintaining a competitive breeding population to secure sufficient genetic gain in future generations. In practice, the mating design usually relies on crosses involving the best parental inbred lines to ensure high mean progeny performance. This excludes crosses involving lower performing but more complementary parents in terms of favorable alleles. We predicted crosses with putative outstanding progenies (high mean and high variance progeny distribution) using genomic prediction models to assess the value of top progeny. This study compared the benefits and drawbacks of seven genomic cross selection criteria (CSC) in terms of genetic gain for one trait and genetic diversity in the next generation. Six CSC were already published and we have proposed an improved CSC that can estimate the proportion of progeny above a threshold defined for the whole mating plan. We simulated mating designs optimized using different CSC and 835 elite parents from a real breeding program that were evaluated between 2000 and 2016. We applied constraints on parental contributions and genetic similarities between parents according to usual breeder practices. Our results showed that CSC based on progeny variance estimation increased the genetic value of superior progenies by up to 5% in the next generation compared to CSC based on the progeny mean estimation (i.e. parental genetic values) alone. It also increased the genetic gain (up to 4%) and/or maintained more genetic diversity at QTLs (up to 4% more genic variance when the marker effects were perfectly estimated).

genetics↗

bioRxiv2021

Evolution of recombination landscapes in diverging populations of bread wheat.

Reciprocal exchanges of DNA (crossovers) that occur during meiosis are mandatory to ensure the production of fertile gametes in sexually reproducing species. They also contribute to shuffle parental alleles into new combinations thereby fuelling genetic variation and evolution. However, due to biological constraints, the recombination landscape is highly heterogenous along the genome which limits the range of allelic combinations and the adaptability of populations. An approach to better understand the constraints on the recombination process is to study how it evolved in the past. In this work we tackled this question by constructing recombination profiles in four diverging bread wheat (Triticum aestivum L.) populations established from 371 landraces genotyped at 200,062 SNPs. We used linkage disequilibrium (LD) patterns to estimate in each population the past distribution of recombination along the genome and characterize its fine-scale heterogeneity. At the megabase scale, recombination rates derived from LD patterns were consistent with family-based estimates obtained from a population of 406 recombinant inbred lines. Among the four populations, recombination landscapes were significantly positively correlated between each other and shared a statistically significant proportion of highly recombinant intervals. However, this comparison also highlighted that the similarity in recombination landscapes between populations was significantly decreasing with their genetic differentiation in most regions of the genome. This observation was found to be robust to SNP ascertainment and demography and suggests a relatively rapid evolution of factors determining the fine-scale localization of recombination in bread wheat.

genetics↗

bioRxiv2020

A Genomics Resource for Genetics, Physiology, and Breeding of West African Sorghum

Local landrace and breeding germplasm is a useful source of genetic diversity for regional and global crop improvement initiatives. Sorghum (Sorghum bicolor L. Moench) in West Africa has diversified across a mosaic of cultures and end-uses, and along steep precipitation and photoperiod gradients. To facilitate germplasm utilization, a West African sorghum association panel (WASAP) of 756 accessions from national breeding programs of Niger, Mali, Senegal, and Togo was assembled and characterized. Genotyping-by-sequencing was used to generate 159,101 high-quality biallelic SNPs, with 43% in intergenic regions and 13% in genic regions. High genetic diversity was observed within the WASAP ({pi} = 0.00045), only slightly less than in a global diversity panel ({pi} = 0.00055). Linkage disequilibrium decayed to background level (r2 < 0.1) by ~50 kb in the WASAP. Genome-wide diversity was structured both by botanical type, and by populations within botanical type, with eight ancestral populations identified. Most populations were distributed across multiple countries, suggesting several potential common gene pools across the national programs. Genome-wide association studies of days to flowering and plant height revealed eight and three significant quantitative trait loci (QTL), respectively, with major height QTL at canonical height loci Dw3 and SbHT7.1. Colocalization of two of eight major flowering time QTL with flowering genes previously described in US germplasm (Ma6 and SbCN8) suggests that photoperiodic flowering in WA sorghum is conditioned by both known and novel genes. This genomic resource provides a foundation for genomics-enabled breeding of climate-resilient varieties in West Africa.

genomics↗

bioRxiv2019

BWGS: a R package for genomic selection and its application to a wheat breeding programme.

We developed an integrated R library called BWGS to enable easy computation of Genomic Estimates of Breeding values (GEBV) for genomic selection. BWGS relies on existing R-libraries, all freely available from CRAN servers. The two main functions enable to run 1) replicated random cross validations within a training set of genotyped and phenotyped lines and 2) GEBV prediction, for a set of genotyped-only lines. Options are available for 1) missing data imputation, 2) markers and training set selection and 3) genomic prediction with 15 different methods, either parametric or semi-parametric.\n\nThe usefulness and efficiency of BWGS are illustrated using a population of wheat lines from a real breeding programme. Adjusted yield data from historical trials (highly unbalanced design) were used for testing the options of BWGS. On the whole, 760 candidate lines with adjusted phenotypes and genotypes for 47 839 robust SNP were used. With a simple desktop computer, we obtained results which compared with previously published results on wheat genomic selection. As predicted by the theory, factors that are most influencing predictive ability, for a given trait of moderate heritability, are the size of the training population and a minimum number of markers for capturing every QTL information. Missing data up to 40%, if randomly distributed, do not degrade predictive ability once imputed, and up to 80% randomly distributed missing data are still acceptable once imputed with Expectation-Maximization method of package rrBLUP. It is worth noticing that selecting markers that are most associated to the trait do improve predictive ability, compared with the whole set of markers, but only when marker selection is made on the whole population. When marker selection is made only on the sampled training set, this advantage nearly disappeared, since it was clearly due to overfitting. Few differences are observed between the 15 prediction models with this dataset. Although non-parametric methods that are supposed to capture non-additive effects have slightly better predictive accuracy, differences remain small. Finally, the GEBV from the 15 prediction models are all highly correlated to each other. These results are encouraging for an efficient use of genomic selection in applied breeding programmes and BWGS is a simple and powerful toolbox to apply in breeding programmes or training activities.

genetics↗

bioRxiv2018

Worldwide phylogeography and history of wheat genetic diversity

Since its domestication in the Fertile Crescent ~8,000 to 10,000 years ago, wheat has undergone a complex history of spread, adaptation and selection. To get better insights into the wheat phylogeography and genetic diversity, we describe allele distribution through time using a set of 4,506 landraces and cultivars originating from 105 different countries genotyped with a high-density SNP array. Although the genetic structure of landraces is collinear to ancient human migration roads, we observe a reshuffling through time, related to breeding programs, with the apparition of new alleles enriched with structural variations that may be the signature of introgressions from wild relatives after 1960.\n\nOne Sentence SummaryA phylogeographical study reveals the complex history of wheat genetic diversity through time and space.

genetics↗