Gene Expression Patterns of Oxidative Phosphorylation Complex I Subunits Are Organized in Clusters

After the radiation of eukaryotes, the NUO operon, controlling the transcription of the NADH dehydrogenase complex of the oxidative phosphorylation system (OXPHOS complex I), was broken down and genes encoding this protein complex were dispersed across the nuclear genome. Seven genes, however, were retained in the genome of the mitochondrion, the ancient symbiote of eukaryotes. This division, in combination with the three-fold increase in subunit number from bacteria (N = ∼14) to man (N = 45), renders the transcription regulation of OXPHOS complex I a challenge. Recently bioinformatics analysis of the promoter regions of all OXPHOS genes in mammals supported patterns of co-regulation, suggesting that natural selection favored a mechanism facilitating the transcriptional regulatory control of genes encoding subunits of these large protein complexes. Here, using real time PCR of mitochondrial (mtDNA)- and nuclear DNA (nDNA)-encoded transcripts in a panel of 13 different human tissues, we show that the expression pattern of OXPHOS complex I genes is regulated in several clusters. Firstly, all mtDNA-encoded complex I subunits (N = 7) share a similar expression pattern, distinct from all tested nDNA-encoded subunits (N = 10). Secondly, two sub-clusters of nDNA-encoded transcripts with significantly different expression patterns were observed. Thirdly, the expression patterns of two nDNA-encoded genes, NDUFA4 and NDUFA5, notably diverged from the rest of the nDNA-encoded subunits, suggesting a certain degree of tissue specificity. Finally, the expression pattern of the mtDNA-encoded ND4L gene diverged from the rest of the tested mtDNA-encoded transcripts that are regulated by the same promoter, consistent with post-transcriptional regulation. These findings suggest, for the first time, that the regulation of complex I subunits expression in humans is complex rather than reflecting global co-regulation

A genetic and molecular approach to identify transcription factors controlling maize root adaptive response to water deficit

International audienceWater stress is recognized as the most severe abiotic stress for agricultural productivity. Root traits play a key role in tolerance to water stress but have largely been neglected in selection schemes. In order to identify the maize genetic bases of the root adaptive responses to water deficit (WD), we used a MAGIC mapping population of 400 lines based on the intercrossing of 16 genotypes. The fine phenotyping of the different genotypes was performed under contrasting water supply on the French root phenotyping platform (4PMI). On the 16 founder genotypes, in addition of phenotyping, we sampled different root tissues daily over 7 days after irrigation arrest and performed RNAseq. On the basis of these 448 transcriptomes, we identified 6945 differentially expressed genes between axial and lateral roots and in response to WD and inferred a regulatory gene network to identify transcription factors (TF). Using a hierarchical clustering, we split the network in 35 clusters homogeneous in their expression pattern. Fine analysis of individual cluster pointed out, without prior knowledge, already known FTs responding to WD and identified new candidates. Functional validation of Arabidopisis orthologues has been initiated and many genotypes have an altered root developmental response to in vitro osmotic stress. In parallel, the phenotyping and a transcriptomic analysis by RNAseq of the genotypes of the mapping population under optimal conditions and water deficit enabled a GWAS and an eQTL analysis. Both approaches identified polymorphisms in genes of interest and identified SNPs colocating near transcription factors also identified by the gene network approach. Taken together all the data identified candidate genes and alleles potentially controlling adaptive root development that can be interesting target for breeding. This work was supported by the European Research Council (ERC) (HyArchi to CM; grant agreement No 788553

A genetic and molecular approach to identify transcription factors controlling maize root adaptive response to water deficit

International audienceWater stress is recognized as the most severe abiotic stress for agricultural productivity. Root traits play a key role in tolerance to water stress but have largely been neglected in selection schemes. In order to identify the maize genetic bases of the root adaptive responses to water deficit (WD), we used a MAGIC mapping population of 400 lines based on the intercrossing of 16 genotypes. The fine phenotyping of the different genotypes was performed under contrasting water supply on the French root phenotyping platform (4PMI). On the 16 founder genotypes, in addition of phenotyping, we sampled different root tissues daily over 7 days after irrigation arrest and performed RNAseq. On the basis of these 448 transcriptomes, we identified 6945 differentially expressed genes between axial and lateral roots and in response to WD and inferred a regulatory gene network to identify transcription factors (TF). Using a hierarchical clustering, we split the network in 35 clusters homogeneous in their expression pattern. Fine analysis of individual cluster pointed out, without prior knowledge, already known FTs responding to WD and identified new candidates. Functional validation of Arabidopisis orthologues has been initiated and many genotypes have an altered root developmental response to in vitro osmotic stress. In parallel, the phenotyping and a transcriptomic analysis by RNAseq of the genotypes of the mapping population under optimal conditions and water deficit enabled a GWAS and an eQTL analysis. Both approaches identified polymorphisms in genes of interest and identified SNPs colocating near transcription factors also identified by the gene network approach. Taken together all the data identified candidate genes and alleles potentially controlling adaptive root development that can be interesting target for breeding. This work was supported by the European Research Council (ERC) (HyArchi to CM; grant agreement No 788553

Genetic diversity of nodulated root structure in a very diverse pea collection

National audienceThe root system is responsible for nitrogen (N) acquisition, which in legumes, combines mineral acquisition and symbiotic fixation in nodules. Despite these two complementary pathways, N nutrition may be a limiting factor of legumes yield because nodules are very sensitive to their local environment and N fixing legume root system is poorly developed which may limit soil exploration [1]. Pea establishes in root nodules a symbiotic association with Rhizobium leguminosarum sv viciae bacteria (Rlv) [2]. This study assessed the potential of naturally occurring genetic variability of nodulated root structure and functioning traits to improve yield pea performance. Two successive glasshouse experiments were performed on a wide 336-pea panel consisted of wild, landraces and cultivars from diverse geographic origins [3]. Plants were inoculated by a mixture of strains representative of the Rlv diversity and grown in innovative RhizoTubes© on the 4PMI high throughput phenotyping platform allowing daily automatic imaging of shoots and nodulated root systems and their analysis [4]. Significant variations between pea accessions were observed for traits describing shoot and nodulated root system architecture. After genotyping of the pea panel by exome capture, genome wide association analyses were performed using 3.9 millions SNPs to identify the genetic determinants of these traits. They will be useful for breeding new pea cultivars with increased root system size, sustained nodule number, and improved N nutrition

Development of new genetic resources for faba bean (Vicia faba L.) breeding through the discovery of gene-based SNP markers and the construction of a high-density consensus map

National audienceFaba bean (Vicia faba L.) is a pulse crop of high nutritional value and high importance for sustainable agriculture and soil protection. With the objective of identifying gene-based SNPs, transcriptome sequencing was performed in order to reduce faba bean genome complexity. A set of 1,819 gene-based SNP markers polymorphic in three recombinant line populations was selected to enable the construction of a high-density consensus genetic map encompassing 1,728 markers well distributed in six linkage groups and spanning 1,547.71 cM with an average inter-marker distance of 0.89 cM. Orthology-based comparison of the faba bean consensus map with legume genome assemblies highlighted synteny patterns that partly reflected the phylogenetic relationships among species. Solid blocks of macrosynteny were observed between faba bean and the most closely-related sequenced legume species such as pea, barrel medic or chickpea. Numerous blocks could also be identified in more divergent species such as common bean or cowpea. The genetic tools developed in this work can be used in association mapping, genetic diversity, linkage disequilibrium or comparative genomics and provide a backbone for map-based cloning. This will make the identification of candidate genes of interest more efficient and will accelerate marker-assisted selection (MAS) and genomic-assisted breeding (GAB) in faba bean

Towards bruchid resistance in pulses

National audienceSeed weevils (Bruchus spp.) are major pests of pulses, causing yield losses and affecting marketability 1,2 . Available insecticides have low efficiency and important negative impacts on the environment, humans and non-target organisms. Therefore, breeding resistant varieties represent the most promising strategy to overcome seed weevils. The pyramiding of several resistance genes in cultivars is an important objective because this will make the resistance more durable and suitable for sustainable agriculture. The PeaMUST project (ANR-11-BTBR0002) aims at discovering the mechanisms of tolerance and resistance to bruchids in pea (Pisum sativum L.) and faba bean (Vicia faba L.) crops and identifying the functional candidate genes for future implementation in Genomics-Assisted Breeding (GAB). A multidisciplinary approach that includes Genome- Wide Association Studies (GWAS), Quantitative trait locus (QTLs) mapping, RNA sequencing (RNA-Seq), shotgun proteomics and Volatile Organic Compounds (VOCs) analysis has been used to identify potential candidate genes for resistance to bruchids. The results will provide (i) original basic knowledge about resistance strategies in pea and faba bean, the candidate genes underlying quantitative resistance to bruchids and its conservation in other legume species, as well as, (ii) innovative applied knowledge and tools for breeding pea and faba bean varieties resistant to bruchids, which will be useful in future strategies of durable resistance management

The Pea genome and after …

International audienceHaving a genome sequence available is a critical step towards unravelling functional diversity andestablishing genome-enabled breeding. The recently generated pea genome sequence represents a great toolfor genomicists, geneticists and breeders not only for the pea community but also for legume research. In thegenome project, re-sequencing data revealed the considerable diversity present in the Pisum genus. In thePeaMUST project, an unprecedented effort was made to genotype large pea collections using the exomecapture technology. This high-density SNP data was exploited in genome-wide association studies (GWAS) ona large number of traits related to yield, as well as response to biotic and abiotic stresses. Comparative GWASand meta-QTL analysis identified important putative loci involved in the control of yield and its components inpea. Furthermore, genomic selection strategies have been developed in order to tackle complex traits such asyield regularity and improve selection efficiency. We will present snapshots of these results and discusspotential transfer of knowledge from pea to related crops

The Pea genome and after …

International audienceHaving a genome sequence available is a critical step towards unravelling functional diversity andestablishing genome-enabled breeding. The recently generated pea genome sequence represents a great toolfor genomicists, geneticists and breeders not only for the pea community but also for legume research. In thegenome project, re-sequencing data revealed the considerable diversity present in the Pisum genus. In thePeaMUST project, an unprecedented effort was made to genotype large pea collections using the exomecapture technology. This high-density SNP data was exploited in genome-wide association studies (GWAS) ona large number of traits related to yield, as well as response to biotic and abiotic stresses. Comparative GWASand meta-QTL analysis identified important putative loci involved in the control of yield and its components inpea. Furthermore, genomic selection strategies have been developed in order to tackle complex traits such asyield regularity and improve selection efficiency. We will present snapshots of these results and discusspotential transfer of knowledge from pea to related crops