Unique genes in plants: specificities and conserved features throughout evolution

<p>Abstract</p> <p>Background</p> <p>Plant genomes contain a high proportion of duplicated genes as a result of numerous whole, segmental and local duplications. These duplications lead up to the formation of gene families, which are the usual material for many evolutionary studies. However, all characterized genomes include single-copy (unique) genes that have not received much attention. Unlike gene duplication, gene loss is not an unspecific mechanism but is rather influenced by a functional selection. In this context, we have established and used stringent criteria in order to identify suitable sets of unique genes present in plant proteomes. Comparisons of unique genes in the green phylum were used to characterize the gene and protein features exhibited by both conserved and species-specific unique genes.</p> <p>Results</p> <p>We identified the unique genes within both <it>A. thaliana </it>and <it>O. sativa </it>genomes and classified them according to the number of homologs in the alternative species: none (U{1:0}), one (U{1:1}) or several (U{1:m}). Regardless of the species, all the genes in these groups present some conserved characteristics, such as small average protein size and abnormal intron number. In order to understand the origin and function of unique genes, we further characterized the U{1:1} gene pairs. The possible involvement of sequence convergence in the creation of U{1:1} pairs was discarded due to the frequent conservation of intron positions. Furthermore, an orthology relationship between the two members of each U{1:1} pair was strongly supported by a high conservation in the protein sizes and transcription levels. Within the promoter of the unique conserved genes, we found a number of TATA and TELO boxes that specifically differed from their mean number in the whole genome. Many unique genes have been conserved as unique through evolution from the green alga <it>Ostreococcus lucimarinus </it>to higher plants. Plant unique genes may also have homologs in bacteria and we showed a link between the targeting towards plastids of proteins encoded by plant nuclear unique genes and their homology with a bacterial protein.</p> <p>Conclusion</p> <p>Many of the <it>A. thaliana </it>and <it>O. sativa </it>unique genes are conserved in plants for which the ancestor diverged at least 725 million years ago (MYA). Half of these genes are also present in other eukaryotic and/or prokaryotic species. Thus, our results indicate that (i) a strong negative selection pressure has conserved a number of genes as unique in genomes throughout evolution, (ii) most unique genes are subjected to a low divergence rate, (iii) they have some features observed in housekeeping genes but for most of them there is no functional annotation and (iv) they may have an ancient origin involving a possible gene transfer from ancestral chloroplasts or bacteria to the plant nucleus.</p

Exploration of plant genomes in the FLAGdb++ environment

Background : In the contexts of genomics, post-genomics and systems biology approaches, data integration presents a major concern. Databases provide crucial solutions: they store, organize and allow information to be queried, they enhance the visibility of newly produced data by comparing them with previously published results, and facilitate the exploration and development of both existing hypotheses and new ideas. Results : The FLAGdb++ information system was developed with the aim of using whole plant genomes as physical references in order to gather and merge available genomic data from in silico or experimental approaches. Available through a JAVA application, original interfaces and tools assist the functional study of plant genes by considering them in their specific context: chromosome, gene family, orthology group, co-expression cluster and functional network. FLAGdb++ is mainly dedicated to the exploration of large gene groups in order to decipher functional connections, to highlight shared or specific structural or functional features, and to facilitate translational tasks between plant species (Arabidopsis thaliana, Oryza sativa, Populus trichocarpa and Vitis vinifera). Conclusion : Combining original data with the output of experts and graphical displays that differ from classical plant genome browsers, FLAGdb++ presents a powerful complementary tool for exploring plant genomes and exploiting structural and functional resources, without the need for computer programming knowledge. First launched in 2002, a 15th version of FLAGdb++ is now available and comprises four model plant genomes and over eight million genomic features

Analysis of CATMA transcriptome data identifies hundreds of novel functional genes and improves gene models in the Arabidopsis genome

<p>Abstract</p> <p>Background</p> <p>Since the finishing of the sequencing of the <it>Arabidopsis thaliana </it>genome, the Arabidopsis community and the annotator centers have been working on the improvement of gene annotation at the structural and functional levels. In this context, we have used the large CATMA resource on the Arabidopsis transcriptome to search for genes missed by different annotation processes. Probes on the CATMA microarrays are specific gene sequence tags (GSTs) based on the CDS models predicted by the Eugene software. Among the 24 576 CATMA v2 GSTs, 677 are in regions considered as intergenic by the TAIR annotation. We analyzed the cognate transcriptome data in the CATMA resource and carried out data-mining to characterize novel genes and improve gene models.</p> <p>Results</p> <p>The statistical analysis of the results of more than 500 hybridized samples distributed among 12 organs provides an experimental validation for 465 novel genes. The hybridization evidence was confirmed by RT-PCR approaches for 88% of the 465 novel genes. Comparisons with the current annotation show that these novel genes often encode small proteins, with an average size of 137 aa. Our approach has also led to the improvement of pre-existing gene models through both the extension of 16 CDS and the identification of 13 gene models erroneously constituted of two merged CDS.</p> <p>Conclusion</p> <p>This work is a noticeable step forward in the improvement of the Arabidopsis genome annotation. We increased the number of Arabidopsis validated genes by 465 novel transcribed genes to which we associated several functional annotations such as expression profiles, sequence conservation in plants, cognate transcripts and protein motifs.</p

Sélection de variables pour la classification par mélanges gaussiens pour prédire la fonction des gènes orphelins

Biologists are interested in predicting the gene functions of sequenced genome organisms according to microarray transcriptome data. The microarray technology development allows one to study the whole genome in different experimental conditions. The information abundance may seem to be an advantage for the gene clustering. However, the structure of interest can often be contained in a subset of the available variables. The currently available variable selection procedures in model-based clustering assume that the irrelevant clustering variables are all independent or are all linked with the relevant clustering variables. A more versatile variable selection model is proposed, taking into account three possible roles for each variable: The relevant clustering variables, the redundant variables and the independent variables. A model selection criterion and a variable selection algorithm are derived for this new variable role modelling. The interest of this new modelling for discovering the function of orphan genes is highlighted on a transcriptome dataset for the arabidopsis thaliana plant.Les biologistes s’attachent actuellement à prédire la fonction des gènes d’organismes de génome séquence à partir de données transcriptomes, issues de l’utilisation des puces à ADN. Le d´développement de cette technologie permet de tester l’expression de l’ensemble du génome dans de nombreuses conditions expérimentales. Cette quantité d’information peut alors sembler être un atout pour la classification des gènes. Pourtant il est courant que seul un sous-ensemble contienne l’information pertinente pour la classification. Les procédures de sélection des variables en classification non supervisée par mélanges gaussiens supposent généralement que les variables non informatives pour la classification sont soit toutes indépendantes, soit liées à des variables informatives. Nous proposons une nouvelle modélisation du rôle des variables plus polyvalente : les variables sont soit informatives pour la classification, soit redondantes, soit totalement indépendantes. Nous proposons un critère de sélection des variables et un algorithme pour cette nouvelle modélisation. L’intérêt de cette nouvelle modélisation pour la prédiction de la fonction des gènes orphelins est illustrée sur un ensemble de données transcriptomes obtenues chez Arabidopsis thaliana

GeneFarm, structural and functional annotation of Arabidopsis gene and protein families by a network of experts

Genomic projects heavily depend on genome annotations and are limited by the current deficiencies in the published predictions of gene structure and function. It follows that, improved annotation will allow better data mining of genomes, and more secure planning and design of experiments. The purpose of the GeneFarm project is to obtain homogeneous, reliable, documented and traceable annotations for Arabidopsis nuclear genes and gene products, and to enter them into an added-value database. This re-annotation project is being performed exhaustively on every member of each gene family. Performing a family-wide annotation makes the task easier and more efficient than a gene-by-gene approach since many features obtained for one gene can be extrapolated to some or all the other genes of a family. A complete annotation procedure based on the most efficient prediction tools available is being used by 16 partner laboratories, each contributing annotated families from its field of expertise. A database, named GeneFarm, and an associated user-friendly interface to query the annotations have been developed. More than 3000 genes distributed over 300 families have been annotated and are available at http://genoplante-info.infobiogen.fr/Genefarm/. Furthermore, collaboration with the Swiss Institute of Bioinformatics is underway to integrate the GeneFarm data into the protein knowledgebase Swiss-Prot

GeneFarm, structural and functional annotation of Arabidopsis gene and protein families by a network of experts

Genomic projects heavily depend on genome annotations and are limited by the current deficiencies in the published predictions of gene structure and function. It follows that, improved annotation will allow better data mining of genomes, and more secure planning and design of experiments. The purpose of the GeneFarm project is to obtain homogeneous, reliable, documented and traceable annotations for Arabidopsis nuclear genes and gene products, and to enter them into an added-value database. This re-annotation project is being performed exhaustively on every member of each gene family. Performing a family-wide annotation makes the task easier and more efficient than a gene-by-gene approach since many features obtained for one gene can be extrapolated to some or all the other genes of a family. A complete annotation procedure based on the most efficient prediction tools available is being used by 16 partner laboratories, each contributing annotated families from its field of expertise. A database, named GeneFarm, and an associated user-friendly interface to query the annotations have been developed. More than 3000 genes distributed over 300 families have been annotated and are available at http://genoplante-info.infobiogen.fr/Genefarm/. Furthermore, collaboration with the Swiss Institute of Bioinformatics is underway to integrate the GeneFarm data into the protein knowledgebase Swiss-Pro

The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the extended Baryon Oscillation Spectroscopic Survey and from the second phase of the Apache Point Observatory Galactic Evolution Experiment

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since July 2014. This paper describes the second data release from this phase, and the fourteenth from SDSS overall (making this, Data Release Fourteen or DR14). This release makes public data taken by SDSS-IV in its first two years of operation (July 2014-2016). Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey (eBOSS); the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data driven machine learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS website (www.sdss.org) has been updated for this release, and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020, and will be followed by SDSS-V.Comment: SDSS-IV collaboration alphabetical author data release paper. DR14 happened on 31st July 2017. 19 pages, 5 figures. Accepted by ApJS on 28th Nov 2017 (this is the "post-print" and "post-proofs" version; minor corrections only from v1, and most of errors found in proofs corrected

The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the Extended Baryon Oscillation Spectroscopic Survey and from the Second Phase of the Apache Point Observatory Galactic Evolution Experiment

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since 2014 July. This paper describes the second data release from this phase, and the 14th from SDSS overall (making this Data Release Fourteen or DR14). This release makes the data taken by SDSS-IV in its first two years of operation (2014–2016 July) public. Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey; the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data-driven machine-learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from the SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS web site (www.sdss.org) has been updated for this release and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020 and will be followed by SDSS-V

Rubin-Euclid Derived Data Products:Initial Recommendations

This report is the result of a joint discussion between the Rubin and Euclid scientific communities. The work presented in this report was focused on designing and recommending an initial set of Derived Data products (DDPs) that could realize the science goals enabled by joint processing. All interested Rubin and Euclid data rights holders were invited to contribute via an online discussion forum and a series of virtual meetings. Strong interest in enhancing science with joint DDPs emerged from across a wide range of astrophysical domains: Solar System, the Galaxy, the Local Volume, from the nearby to the primaeval Universe, and cosmology

La proteine kinase C et le metabolisme des phosphates d'inositol peuvent intervenir dans la secretion de base mais pas dans la secretion stimulee des caseines dans la cellule epitheliale mammaire de lapines en lactation

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