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      POSTAR2: deciphering the post-transcriptional regulatory logics

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          Abstract

          Post-transcriptional regulation of RNAs is critical to the diverse range of cellular processes. The volume of functional genomic data focusing on post-transcriptional regulation logics continues to grow in recent years. In the current database version, POSTAR2 ( http://lulab.life.tsinghua.edu.cn/postar), we included the following new features and data: updated ∼500 CLIP-seq datasets (∼1200 CLIP-seq datasets in total) from six species, including human, mouse, fly, worm, Arabidopsis and yeast; added a new module ‘Translatome’, which is derived from Ribo-seq datasets and contains ∼36 million open reading frames (ORFs) in the genomes from the six species; updated and unified post-transcriptional regulation and variation data. Finally, we improved web interfaces for searching and visualizing protein–RNA interactions with multi-layer information. Meanwhile, we also merged our CLIPdb database into POSTAR2. POSTAR2 will help researchers investigate the post-transcriptional regulatory logics coordinated by RNA-binding proteins and translational landscape of cellular RNAs.

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          Most cited references17

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          Scalable Open Science Approach for Mutation Calling of Tumor Exomes Using Multiple Genomic Pipelines

          The Cancer Genome Atlas (TCGA) cancer genomics dataset includes over ten-thousand tumor-normal exome pairs across 33 different cancer types, in total >400 TB of raw data files requiring analysis. Here we describe the Multi-Center Mutation Calling in Multiple Cancers (MC3) project, our effort to generate a comprehensive encyclopedia of somatic mutation calls for the TCGA data to enable robust cross-tumor-type analyses. Our approach accounts for variance and batch effects introduced by the rapid advancement of DNA extraction, hybridization-capture, sequencing, and analysis methods over time. We present best practices for applying an ensemble of seven mutation-calling algorithms with scoring and artifact filtering. The dataset created by this analysis includes 3.5 million somatic variants and forms the basis for PanCan Atlas papers. The results have been made available to the research community along with the methods used to generate them. This project is the result of collaboration from a number of institutes and demonstrates how team science drives extremely large genomics projects. The MC3 project is a variant calling of over 10,000 cancer exome samples from 33 cancer types. Over 3 million somatic variants were detected using 7 different methods developed from institutions across the United States. These variants formed the basis for the PanCan Atlas papers.
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            The Arabidopsis Information Resource (TAIR): a model organism database providing a centralized, curated gateway to Arabidopsis biology, research materials and community.

            Arabidopsis thaliana is the most widely-studied plant today. The concerted efforts of over 11 000 researchers and 4000 organizations around the world are generating a rich diversity and quantity of information and materials. This information is made available through a comprehensive on-line resource called the Arabidopsis Information Resource (TAIR) (http://arabidopsis.org), which is accessible via commonly used web browsers and can be searched and downloaded in a number of ways. In the last two years, efforts have been focused on increasing data content and diversity, functionally annotating genes and gene products with controlled vocabularies, and improving data retrieval, analysis and visualization tools. New information include sequence polymorphisms including alleles, germplasms and phenotypes, Gene Ontology annotations, gene families, protein information, metabolic pathways, gene expression data from microarray experiments and seed and DNA stocks. New data visualization and analysis tools include SeqViewer, which interactively displays the genome from the whole chromosome down to 10 kb of nucleotide sequence and AraCyc, a metabolic pathway database and map tool that allows overlaying expression data onto the pathway diagrams. Finally, we have recently incorporated seed and DNA stock information from the Arabidopsis Biological Resource Center (ABRC) and implemented a shopping-cart style on-line ordering system.
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              Identification of small ORFs in vertebrates using ribosome footprinting and evolutionary conservation.

              Identification of the coding elements in the genome is a fundamental step to understanding the building blocks of living systems. Short peptides (< 100 aa) have emerged as important regulators of development and physiology, but their identification has been limited by their size. We have leveraged the periodicity of ribosome movement on the mRNA to define actively translated ORFs by ribosome footprinting. This approach identifies several hundred translated small ORFs in zebrafish and human. Computational prediction of small ORFs from codon conservation patterns corroborates and extends these findings and identifies conserved sequences in zebrafish and human, suggesting functional peptide products (micropeptides). These results identify micropeptide-encoding genes in vertebrates, providing an entry point to define their function in vivo.
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                08 January 2019
                17 September 2018
                17 September 2018
                : 47
                : Database issue , Database issue
                : D203-D211
                Affiliations
                [1 ]MOE Key Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing 100084, China
                [2 ]Division of General Surgery, Peking University First Hospital, Beijing 100034, China
                [3 ]Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
                Author notes
                To whom correspondence should be addressed. Tel: +86 10 62789217; Fax: +86 10 62789217; Email: zhilu@ 123456tsinghua.edu.cn . Correspondence may also be addressed to Pengyuan Wang. Tel: +86 10 83575653; Fax: +86 10 66551027; Email: pengyuan_wang@ 123456bjmu.edu.cn

                The authors wish it to be known that, in their opinion, the first three authors should be regarded as joint First Authors.

                Article
                gky830
                10.1093/nar/gky830
                6323971
                30239819
                e953bb80-d40f-4e43-8fcf-dbc3149a5a0b
                © The Author(s) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 08 September 2018
                : 25 August 2018
                : 26 July 2018
                Page count
                Pages: 9
                Funding
                Funded by: National Key Research and Development Plan of China
                Award ID: 2016YFA0500803
                Funded by: National Natural Science Foundation of China 10.13039/501100001809
                Award ID: 31522030
                Award ID: 31771461
                Categories
                Database Issue

                Genetics
                Genetics

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