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

The CogBIAS longitudinal study protocol: cognitive and genetic factors influencing psychological functioning in adolescence.

BACKGROUND: Optimal psychological development is dependent upon a complex interplay between individual and situational factors. Investigating the development of these factors in adolescence will help to improve understanding of emotional vulnerability and resilience. The CogBIAS longitudinal study (CogBIAS-L-S) aims to combine cognitive and genetic approaches to investigate risk and protective factors associated with the development of mood and impulsivity-related outcomes in an adolescent sample. METHODS: CogBIAS-L-S is a three-wave longitudinal study of typically developing adolescents conducted over 4 years, with data collection at age 12, 14 and 16. At each wave participants will undergo multiple assessments including a range of selective cognitive processing tasks (e.g. attention bias, interpretation bias, memory bias) and psychological self-report measures (e.g. anxiety, depression, resilience). Saliva samples will also be collected at the baseline assessment for genetic analyses. Multilevel statistical analyses will be performed to investigate the developmental trajectory of cognitive biases on psychological functioning, as well as the influence of genetic moderation on these relationships. DISCUSSION: CogBIAS-L-S represents the first longitudinal study to assess multiple cognitive biases across adolescent development and the largest study of its kind to collect genetic data. It therefore provides a unique opportunity to understand how genes and the environment influence the development and maintenance of cognitive biases and provide insight into risk and protective factors that may be key targets for intervention.This work was supported by the European Research Council (ERC) under the European Union’s Seventh Framework Programme (FP7/2007–2013)/ERC grant agreement no: [324176]

An intragenic mutagenesis strategy in Physcomitrella patens to preserve intron splicing

This is an Open Access article licensed under a Creative Commons Attribution 4.0 International License) and originally published in Scientific Reports. You can access the article on the publiser's website by following this link: https://www.nature.com/articles/s41598-017-05309-w Dette er en vitenskapelig, fagfellevurdert artikkel som opprinnelig ble publisert i Scientific Reports. Artikkelen er publisert under lisensen Creative Commons Attribution 4.0 International License. Du kan også få tilgang til artikkelen på utgivers hjemmeside ved å følge denne lenken: https://www.nature.com/articles/s41598-017-05309-wGene targeting is a powerful reverse genetics technique for site-specific genome modification. Intrinsic homologous recombination in the moss Physcomitrella patens permits highly effective gene targeting, a characteristic that makes this organism a valuable model for functional genetics. Functional characterization of domains located within a multi-domain protein depends on the ability to generate mutants harboring genetic modifications at internal gene positions while maintaining the reading-frames of the flanking exons. In this study, we designed and evaluated different gene targeting constructs for targeted gene manipulation of sequences corresponding to internal domains of the DEFECTIVE KERNEL1 protein in Physcomitrella patens. Our results show that gene targeting-associated mutagenesis of introns can have adverse effects on splicing, corrupting the normal reading frame of the transcript. We show that successful genetic modification of internal sequences of multi-exon genes depends on gene-targeting strategies which insert the selection marker cassette into the 5′ end of the intron and preserve the nucleotide sequence of the targeted intron

The Physcomitrella patens gene atlas project: large scale RNA-seq based expression data

High-throughput RNA sequencing (RNA-seq) has recently become the method of choice to define and analyze transcriptomes. For the model moss Physcomitrella patens, although this method has been used to help analyze specific perturbations, no overall reference dataset has yet been established. In the framework of the Gene Atlas project, the Joint Genome Institute selected P.patens as a flagship genome, opening the way to generate the first comprehensive transcriptome dataset for this moss. The first round of sequencing described here is composed of 99 independent libraries spanning 34 different developmental stages and conditions. Upon dataset quality control and processing through read mapping, 28509 of the 34361 v3.3 gene models (83%) were detected to be expressed across the samples. Differentially expressed genes (DEGs) were calculated across the dataset to permit perturbation comparisons between conditions. The analysis of the three most distinct and abundant P.patens growth stages - protonema, gametophore and sporophyte - allowed us to define both general transcriptional patterns and stage-specific transcripts. As an example of variation of physico-chemical growth conditions, we detail here the impact of ammonium supplementation under standard growth conditions on the protonemal transcriptome. Finally, the cooperative nature of this project allowed us to analyze inter-laboratory variation, as 13 different laboratories around the world provided samples. We compare differences in the replication of experiments in a single laboratory and between different laboratories

Balance between inbreeding and outcrossing in a nannandrous species, the moss Homalothecium lutescens.

Epiphytic dwarf males on the females present a possible solution to the problem of short fertilization distances in mosses. However, leptokurtic spore dispersal makes dwarf males likely to be closely related to their host shoot, with an accompanying risk of inbreeding. The capacity of a female to harbour a high number of different dwarf males suggests that there may be mechanisms in place that counteract inbreeding, such as polyandry and post-fertilization selection. We have genotyped sporophytes, female host shoots and dwarf males in four populations of the moss Homalothecium lutescens. We found no evidence of selective sporophyte abortion based on level of heterozygosity. The occurrence of entirely homozygous sporophytes together with significantly positive inbreeding coefficients in three of the populations (mean FIS between 0.48 and 0.64) suggest frequent mother-son mating events. However, 23% of all sampled sporophytes had a higher level of heterozygosity compared with the mean expected heterozygosity at the population level. Polyandry was frequent, on average 59% of the sporophytes on a female shoot were sired by distinct fathers. In conclusion, sporadic fertilizations by dwarf males originating from nonhost female shoots appear to counteract strong inbreeding.Heredity advance online publication, 2 September 2015; doi:10.1038/hdy.2015.79

Epigenetic differences in monozygotic twins discordant for major depressive disorder

Although monozygotic (MZ) twins share the majority of their genetic makeup, they can be phenotypically discordant on several traits and diseases. DNA methylation is an epigenetic mechanism that can be influenced by genetic, environmental and stochastic events and may have an important impact on individual variability. In this study we explored epigenetic differences in peripheral blood samples in three MZ twin studies on major depressive disorder (MDD). Epigenetic data for twin pairs were collected as part of a previous study using 8.1-K-CpG microarrays tagging DNA modification in white blood cells from MZ twins discordant for MDD. Data originated from three geographical regions: UK, Australia and the Netherlands. Ninety-seven MZ pairs (194 individuals) discordant for MDD were included. Different methods to address non independently-and-identically distributed (non-i.i.d.) data were evaluated. Machine-learning methods with feature selection centered on support vector machine and random forest were used to build a classifier to predict cases and controls based on epivariations. The most informative variants were mapped to genes and carried forward for network analysis. A mixture approach using principal component analysis (PCA) and Bayes methods allowed to combine the three studies and to leverage the increased predictive power provided by the larger sample. A machine-learning algorithm with feature reduction classified affected from non-affected twins above chance levels in an independent training-testing design. Network analysis revealed gene networks centered on the PPAR-γ (NR1C3) and C-MYC gene hubs interacting through the AP-1 (c-Jun) transcription factor. PPAR-γ (NR1C3) is a drug target for pioglitazone, which has been shown to reduce depression symptoms in patients with MDD. Using a data-driven approach we were able to overcome challenges of non-i.i.d. data when combining epigenetic studies from MZ twins discordant for MDD. Individually, the studies yielded negative results but when combined classification of the disease state from blood epigenome alone was possible. Network analysis revealed genes and gene networks that support the inflammation hypothesis of MDD