Glutamate receptor-like channels are essential for chemotaxis and reproduction in mosses

The deposited article version is a "Accelerated Article Preview" provided by Nature Publishing Group, and it contains attached the supplementary materials within the pdf.». This publication hasn't any creative commons license associated.Glutamate receptors are well characterized channels that mediate cell-to-cell communication during neurotransmission in animals. Nevertheless, information regarding their functional role in organisms without nervous systems is still limited. In plants, Glutamate Receptor-like (GLR) genes have been implicated in defence against pathogens, reproduction, control of stomata aperture and light signal transduction(1-5). However, the numerous GLR genes present in angiosperm genomes (20 to 70)(6) has prevented the observation of strong phenotypes in loss-of-function mutants. Here, we show that in the moss Physcomitrella patens, a basal land plant, mutation of GLR genes cause sperm failure in targeting the female reproductive organs. In addition, we show that GLR genes encode non-selective Ca(2+) permeable channels that can regulate cytoplasmic Ca(2+) and are needed to induce the expression of a BELL1-like transcription factor essential for zygote development. Our work reveals novel functions for GLRs in sperm chemotaxis and transcriptional regulation. Sperm chemotaxis is essential for fertilization in both animals and early land plants like bryophytes and pteridophytes. Therefore, our results are suggestive that ionotropic glutamate receptors may have been conserved throughout plant evolution to mediate cell-to-cell communication during sexual reproduction.Phillips University; Oxford University; University of Marburg; University of Muenster; MarieCurie ITN-Plant Origins grant: (FP7-PEOPLE-ITN-2008); FCT grants: (BEX-BCM/0376/2012; PTDC/BIA-PLA/4018/2012); NSF-US grant: (MCB 1616437/2016).info:eu-repo/semantics/acceptedVersio

Functional analysis of multiple genomic signatures demonstrates that classification algorithms choose phenotype-related genes

Gene expression signatures of toxicity and clinical response benefit both safety assessment and clinical practice; however, difficulties in connecting signature genes with the predicted end points have limited their application. The Microarray Quality Control Consortium II (MAQCII) project generated 262 signatures for ten clinical and three toxicological end points from six gene expression data sets, an unprecedented collection of diverse signatures that has permitted a wide-ranging analysis on the nature of such predictive models. A comprehensive analysis of the genes of these signatures and their nonredundant unions using ontology enrichment, biological network building and interactome connectivity analyses demonstrated the link between gene signatures and the biological basis of their predictive power. Different signatures for a given end point were more similar at the level of biological properties and transcriptional control than at the gene level. Signatures tended to be enriched in function and pathway in an end point and model-specific manner, and showed a topological bias for incoming interactions. Importantly, the level of biological similarity between different signatures for a given end point correlated positively with the accuracy of the signature predictions. These findings will aid the understanding, and application of predictive genomic signatures, and support their broader application in predictive medicine