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      A survey of lineage‐specific genes in Triticeae reveals de novo gene evolution from genomic raw material

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          Abstract

          Diploid plant genomes typically contain ~35,000 genes, almost all belonging to highly conserved gene families. Only a small fraction are lineage‐specific, which are found in only one or few closely related species. Little is known about how genes arise de novo in plant genomes and how often this occurs; however, they are believed to be important for plants diversification and adaptation. We developed a pipeline to identify lineage‐specific genes in Triticeae, using newly available genome assemblies of wheat, barley, and rye. Applying a set of stringent criteria, we identified 5942 candidate Triticeae‐specific genes (TSGs), of which 2337 were validated as protein‐coding genes in wheat. Differential gene expression analyses revealed that stress‐induced wheat TSGs are strongly enriched in putative secreted proteins. Some were previously described to be involved in Triticeae non‐host resistance and cold response. Additionally, we show that 1079 TSGs have sequence homology to transposable elements (TEs), ~68% of them deriving from regulatory non‐coding regions of Gypsy retrotransposons. Most importantly, we demonstrate that these TSGs are enriched in transmembrane domains and are among the most highly expressed wheat genes overall. To summarize, we conclude that de novo gene formation is relatively rare and that Triticeae probably possess ~779 lineage‐specific genes per haploid genome. TSGs, which respond to pathogen and environmental stresses, may be interesting candidates for future targeted resistance breeding in Triticeae. Finally, we propose that non‐coding regions of TEs might provide important genetic raw material for the functional innovation of TM domains and the evolution of novel secreted proteins.

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          edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

          Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data. Availability: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org). Contact: mrobinson@wehi.edu.au
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            Salmon: fast and bias-aware quantification of transcript expression using dual-phase inference

            We introduce Salmon, a method for quantifying transcript abundance from RNA-seq reads that is accurate and fast. Salmon is the first transcriptome-wide quantifier to correct for fragment GC content bias, which we demonstrate substantially improves the accuracy of abundance estimates and the reliability of subsequent differential expression analysis. Salmon combines a new dual-phase parallel inference algorithm and feature-rich bias models with an ultra-fast read mapping procedure.
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              PAML 4: phylogenetic analysis by maximum likelihood.

              PAML, currently in version 4, is a package of programs for phylogenetic analyses of DNA and protein sequences using maximum likelihood (ML). The programs may be used to compare and test phylogenetic trees, but their main strengths lie in the rich repertoire of evolutionary models implemented, which can be used to estimate parameters in models of sequence evolution and to test interesting biological hypotheses. Uses of the programs include estimation of synonymous and nonsynonymous rates (d(N) and d(S)) between two protein-coding DNA sequences, inference of positive Darwinian selection through phylogenetic comparison of protein-coding genes, reconstruction of ancestral genes and proteins for molecular restoration studies of extinct life forms, combined analysis of heterogeneous data sets from multiple gene loci, and estimation of species divergence times incorporating uncertainties in fossil calibrations. This note discusses some of the major applications of the package, which includes example data sets to demonstrate their use. The package is written in ANSI C, and runs under Windows, Mac OSX, and UNIX systems. It is available at -- (http://abacus.gene.ucl.ac.uk/software/paml.html).
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                Author and article information

                Contributors
                wicker@botinst.uzh.ch
                Journal
                Plant Direct
                Plant Direct
                10.1002/(ISSN)2475-4455
                PLD3
                Plant Direct
                John Wiley and Sons Inc. (Hoboken )
                2475-4455
                16 March 2023
                March 2023
                : 7
                : 3 ( doiID: 10.1002/pld3.v7.3 )
                : e484
                Affiliations
                [ 1 ] Department of Plant and Microbial Biology University of Zurich Zurich Switzerland
                [ 2 ] Department of Biology University of Fribourg Fribourg Switzerland
                [ 3 ] Centro de Biotecnología y Genómica de Plantas Universidad Politécnica de Madrid (UPM)–Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA) Madrid Spain
                Author notes
                [*] [* ] Correspondence

                Thomas Wicker, Department of Plant and Microbial Biology, University of Zurich, Zurich, Switzerland.

                Email: wicker@ 123456botinst.uzh.ch

                Author information
                https://orcid.org/0000-0001-6915-2238
                https://orcid.org/0000-0002-9133-4406
                https://orcid.org/0000-0002-6777-7135
                Article
                PLD3484
                10.1002/pld3.484
                10020141
                36937792
                6cc28ac7-ac1e-4abb-aa04-55847fa486ba
                © 2023 The Authors. Plant Direct published by American Society of Plant Biologists and the Society for Experimental Biology and John Wiley & Sons Ltd.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

                History
                : 26 January 2023
                : 27 June 2022
                : 27 January 2023
                Page count
                Figures: 6, Tables: 2, Pages: 16, Words: 12330
                Funding
                Funded by: University of Zurich , doi 10.13039/501100006447;
                Funded by: University of Zurich Research Priority Program
                Award ID: U‐702‐21‐01
                Funded by: Swiss National Foundation , doi 10.13039/501100001711;
                Award ID: 31003A_163325
                Categories
                Original Research
                Original Research
                Custom metadata
                2.0
                March 2023
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.2.6 mode:remove_FC converted:17.03.2023

                de novo gene evolution,stress adaptation,transposable elements, triticeae‐specific genes

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