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      The Baboon Kidney Transcriptome: Analysis of Transcript Sequence, Splice Variants, and Abundance

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          Abstract

          The baboon is an invaluable model for the study of human health and disease, including many complex diseases of the kidney. Although scientists have made great progress in developing this animal as a model for numerous areas of biomedical research, genomic resources for the baboon, such as a quality annotated genome, are still lacking. To this end, we characterized the baboon kidney transcriptome using high-throughput cDNA sequencing (RNA-Seq) to identify genes, gene variants, single nucleotide polymorphisms (SNPs), insertion-deletion polymorphisms (InDels), cellular functions, and key pathways in the baboon kidney to provide a genomic resource for the baboon. Analysis of our sequencing data revealed 45,499 high-confidence SNPs and 29,813 InDels comparing baboon cDNA sequences with the human hg18 reference assembly and identified 35,900 cDNAs in the baboon kidney, including 35,150 transcripts representing 15,369 genic genes that are novel for the baboon. Gene ontology analysis of our sequencing dataset also identified numerous biological functions and canonical pathways that were significant in the baboon kidney, including a large number of metabolic pathways that support known functions of the kidney. The results presented in this study catalogues the transcribed mRNAs, noncoding RNAs, and hypothetical proteins in the baboon kidney and establishes a genomic resource for scientists using the baboon as an experimental model.

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          Quantitative monitoring of gene expression patterns with a complementary DNA microarray.

          A high-capacity system was developed to monitor the expression of many genes in parallel. Microarrays prepared by high-speed robotic printing of complementary DNAs on glass were used for quantitative expression measurements of the corresponding genes. Because of the small format and high density of the arrays, hybridization volumes of 2 microliters could be used that enabled detection of rare transcripts in probe mixtures derived from 2 micrograms of total cellular messenger RNA. Differential expression measurements of 45 Arabidopsis genes were made by means of simultaneous, two-color fluorescence hybridization.
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            Identification of novel transcripts in annotated genomes using RNA-Seq.

            We describe a new 'reference annotation based transcript assembly' problem for RNA-Seq data that involves assembling novel transcripts in the context of an existing annotation. This problem arises in the analysis of expression in model organisms, where it is desirable to leverage existing annotations for discovering novel transcripts. We present an algorithm for reference annotation-based transcript assembly and show how it can be used to rapidly investigate novel transcripts revealed by RNA-Seq in comparison with a reference annotation. The methods described in this article are implemented in the Cufflinks suite of software for RNA-Seq, freely available from http://bio.math.berkeley.edu/cufflinks. The software is released under the BOOST license. cole@broadinstitute.org; lpachter@math.berkeley.edu Supplementary data are available at Bioinformatics online.
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              Computational methods for transcriptome annotation and quantification using RNA-seq.

              High-throughput RNA sequencing (RNA-seq) promises a comprehensive picture of the transcriptome, allowing for the complete annotation and quantification of all genes and their isoforms across samples. Realizing this promise requires increasingly complex computational methods. These computational challenges fall into three main categories: (i) read mapping, (ii) transcriptome reconstruction and (iii) expression quantification. Here we explain the major conceptual and practical challenges, and the general classes of solutions for each category. Finally, we highlight the interdependence between these categories and discuss the benefits for different biological applications.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2013
                23 April 2013
                : 8
                : 4
                : e57563
                Affiliations
                [1 ]Department of Genetics, Texas Biomedical Research Institute, San Antonio, Texas, United States of America
                [2 ]Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, Texas, United States of America
                University of California, Los Angeles, United States of America
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: LAC RES. Performed the experiments: JPG RG. Analyzed the data: KDS JPG LAC. Contributed reagents/materials/analysis tools: RES. Wrote the paper: KDS LAC.

                Article
                PONE-D-12-22718
                10.1371/journal.pone.0057563
                3634053
                23637735
                f027a60a-93f7-408c-83cf-e2a1292fa236
                Copyright @ 2013

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 26 July 2012
                : 24 January 2013
                Page count
                Pages: 15
                Funding
                This study was supported by research grants HL028972 and HD021350 from the National Institutes of Health (NIH) and was conducted in facilities constructed with support from Research Facilities Improvement Program grant C06 RR013556 from the National Center for Research Resources (NCRR) of the NIH. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology
                Computational Biology
                Genomics
                Genome Analysis Tools
                Transcriptomes
                Genome Expression Analysis
                Molecular Genetics
                Gene Identification and Analysis
                Gene Expression
                Sequence Analysis
                Genetics
                Gene Expression
                DNA transcription
                Molecular Genetics
                Gene Identification and Analysis
                Gene Networks
                Genomics
                Genome Analysis Tools
                Gene Ontologies
                Genetic Networks
                Sequence Assembly Tools
                Transcriptomes
                Genome Databases
                Sequence Databases
                Genome Expression Analysis
                Model Organisms
                Animal Models
                Molecular Cell Biology
                Gene Expression
                DNA transcription
                Nucleic Acids
                RNA

                Uncategorized
                Uncategorized

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