Biology subjects

Segura, V.

Publications and source records attributed to Segura, V..

21 records · Page 2Linked to original sources

bioRxiv2020

Hypomethylated poplars show higher tolerance to water deficit and highlight a dual role for DNA methylation in shoot meristem: regulation of stress response and genome integrity

As fixed and long living organisms subjected to repeated environmental stresses, trees have developed mechanisms such as phenotypic plasticity that help them to cope with fluctuating environmental conditions. Here, we tested the role DNA methylation as a hub of integration, linking plasticity and physiological response to water deficit in the shoot apical meristem of the model tree poplar (Populus). Using a reverse genetic approach, we compared hypomethylated RNAi-ddm1 lines to wild-type trees for drought tolerance. An integrative analysis was realized with phytohormone balance, methylomes, transcriptomes and mobilomes. Hypomethylated lines were more tolerant when subjected to moderate water deficit and were intrinsically more tolerant to drought-induced cavitation. The alteration of the DDM1 machinery induced variation in DNA methylation in a cytosine context dependent manner, both in genes and transposable elements. Hypomethylated lines subjected to water deficit showed altered expression of genes involved in phytohormone pathways, such as salicylic acid and modified hormonal balance. Several transposable elements showed stress- and/or line-specific patterns of reactivation, and we could detect copy number variations for two of them in stressed ddm1 lines. Overall, our data highlight two major roles for DNA methylation in the shoot apical meristem: control of stress response and plasticity through transduction of hormone signaling and maintenance of genome integrity through the control of transposable elements.

plant biology↗

bioRxiv2019

Gene Expression Predictions and Networks in Natural Populations Supports the Omnigenic Theory

Recent literature on the differential role of genes within networks distinguishes core from peripheral genes. If previous works have shown contrasting features between them, whether such categorization matters for phenotype prediction remains to be studied. We sequenced RNA in a Populus nigra collection and built co-expression networks to define core and peripheral genes. We found that cores were more differentiated between populations than peripherals while being less variable, suggesting that they have been constrained through potentially divergent selection. We also showed that while cores were overrepresented in a subset of genes deemed important for trait prediction, they did not systematically predict better than peripherals or even random genes. Our work is the first attempt to assess the importance of co-expression network connectivity in phenotype prediction. While highly connected core genes appear to be important, they do not bear enough information to systematically predict better quantitative traits than other gene sets.

genomics↗

bioRxiv2018

Phenomic selection: a low-cost and high-throughput alternative to genomic selection

Genomic selection - the prediction of breeding values using DNA polymorphisms - is a disruptive method that has widely been adopted by animal and plant breeders to increase productivity. It was recently shown that other sources of molecular variations such as those resulting from transcripts or metabolites could be used to accurately predict complex traits. These endophenotypes have the advantage of capturing the expressed genotypes and consequently the complex regulatory networks that occur in the different layers between the genome and the phenotype. However, obtaining such omics data at very large scales, such as those typically experienced in breeding, remains challenging. As an alternative, we proposed using near-infrared spectroscopy (NIRS) as a high-throughput, low cost and non-destructive tool to indirectly capture endophenotypic variants and compute relationship matrices for predicting complex traits and coined this new approach \"phenomic selection\" (PS). We tested PS on two species of economic interest (Triticum aestivum L. and Populus nigra L.) using NIRS on various tissues (grains, leaves, wood). We showed that one could reach predictions as accurate as with molecular markers, for developmental, tolerance and productivity traits, even in environments radically different from the one in which NIRS were collected. Our work constitutes a proof of concept and provides new perspectives for the breeding community, as PS is theoretically applicable to any organism at low cost and does not require any molecular information.\n\nARTICLE SUMMARYDespite its widely adopted interest in breeding, genomic selection - the prediction of breeding values using DNA polymorphisms - remains difficult to implement for many species because of genotyping costs. As an alternative or complement depending on the context, we propose \"phenomic selection\" (PS) as the use of low-cost and high-throughput phenotypic records to reconstruct similarities between genotypes and predict their performances. As a proof of concept of PS, we made use of near infrared spectroscopy applied to different tissues in poplar and wheat to predict various key traits and showed that PS could reach predictions as accurate as with molecular markers.

genetics↗