University of Rennes

About: University of Rennes is a education organization based out in Rennes, France. It is known for research contribution in the topics: Population & Crystal structure. The organization has 18404 authors who have published 40374 publications receiving 995327 citations.

The importance of the microbiome of the plant holobiont

Abstract: Plants can no longer be considered as standalone entities and a more holistic perception is needed. Indeed, plants harbor a wide diversity of microorganisms both inside and outside their tissues, in the endosphere and ectosphere, respectively. These microorganisms, which mostly belong to Bacteria and Fungi, are involved in major functions such as plant nutrition and plant resistance to biotic and abiotic stresses. Hence, the microbiota impact plant growth and survival, two key components of fitness. Plant fitness is therefore a consequence of the plant per se and its microbiota, which collectively form a holobiont. Complementary to the reductionist perception of evolutionary pressures acting on plant or symbiotic compartments, the plant holobiont concept requires a novel perception of evolution. The interlinkages between the plant holobiont components are explored here in the light of current ecological and evolutionary theories. Microbiome complexity and the rules of microbiotic community assemblage are not yet fully understood. It is suggested that the plant can modulate its microbiota to dynamically adjust to its environment. To better understand the level of plant dependence on the microbiotic components, the core microbiota need to be determined at different hierarchical scales of ecology while pan-microbiome analyses would improve characterization of the functions displayed.

Analysis of immune-related loci identifies 48 new susceptibility variants for multiple sclerosis

Abstract: Using the ImmunoChip custom genotyping array, we analyzed 14,498 subjects with multiple sclerosis and 24,091 healthy controls for 161,311 autosomal variants and identified 135 potentially associated regions (P < 10 × 10(-4)) In a replication phase, we combined these data with previous genome-wide association study (GWAS) data from an independent 14,802 subjects with multiple sclerosis and 26,703 healthy controls In these 80,094 individuals of European ancestry, we identified 48 new susceptibility variants (P < 50 × 10(-8)), 3 of which we found after conditioning on previously identified variants Thus, there are now 110 established multiple sclerosis risk variants at 103 discrete loci outside of the major histocompatibility complex With high-resolution Bayesian fine mapping, we identified five regions where one variant accounted for more than 50% of the posterior probability of association This study enhances the catalog of multiple sclerosis risk variants and illustrates the value of fine mapping in the resolution of GWAS signals

Integrated analysis of somatic mutations and focal copy-number changes identifies key genes and pathways in hepatocellular carcinoma

Abstract: Hepatocellular carcinoma (HCC) is the most common primary liver malignancy. Here, we performed high-resolution copy-number analysis on 125 HCC tumors and whole-exome sequencing on 24 of these tumors. We identified 135 homozygous deletions and 994 somatic mutations of genes with predicted functional consequences. We found new recurrent alterations in four genes (ARID1A, RPS6KA3, NFE2L2 and IRF2) not previously described in HCC. Functional analyses showed tumor suppressor properties for IRF2, whose inactivation, exclusively found in hepatitis B virus (HBV)-related tumors, led to impaired TP53 function. In contrast, inactivation of chromatin remodelers was frequent and predominant in alcohol-related tumors. Moreover, association of mutations in specific genes (RPS6KA3-AXIN1 and NFE2L2-CTNNB1) suggested that Wnt/β-catenin signaling might cooperate in liver carcinogenesis with both oxidative stress metabolism and Ras/mitogen-activated protein kinase (MAPK) pathways. This study provides insight into the somatic mutational landscape in HCC and identifies interactions between mutations in oncogene and tumor suppressor gene mutations related to specific risk factors.