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      An Arabidopsis pre-RNA processing8a (prp8a) missense allele restores splicing of a subset of mis-spliced mRNAs

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          Abstract

          Eukaryotic precursor mRNAs often harbor noncoding introns that must be removed prior to translation. Accurate splicing of precursor messenger RNA depends on placement and assembly of small nuclear ribonucleoprotein (snRNP) sub-complexes of the spliceosome. Yeast ( Saccharomyces cerevisiae) studies established a role in splice-site selection for PRE-RNA PROCESSING8 (PRP8), a conserved spliceosome scaffolding protein of the U5 snRNP. However, analogous splice-site selection studies in multicellular eukaryotes are lacking. Such studies are crucial for a comprehensive understanding of alternative splicing, which is extensive in plants and animals but limited in yeast. In this work, we describe an Arabidopsis ( Arabidopsis thaliana) prp8a mutant that modulates splice-site selection. We isolated prp8a-14 from a screen for suppressors of pex14-6, which carries a splice-site mutation in the PEROXIN14 ( PEX14) peroxisome biogenesis gene. To elucidate Arabidopsis PRP8A function in spliceosome fidelity, we combined prp8a-14 with various pex14 splice-site mutations and monitored the double mutants for physiological and molecular consequences of dysfunctional and functional peroxisomes that correspond to impaired and recovered splicing, respectively. prp8a-14 restored splicing and PEX14 function to alleles with mutations in the exonic guanine of the 5′-splice site but did not restore splicing or function to alleles with mutations in the intronic guanine of 5′- or 3′-splice sites. We used RNA-seq to reveal the systemic impact of prp8a-14 and found hundreds of differentially spliced transcripts and thousands of transcripts with significantly altered levels. Among differentially spliced transcripts, prp8a-14 significantly altered 5′- and 3′-splice-site utilization to favor sites resulting in shorter introns. This study provides a genetic platform for probing splicing in plants and hints at a role for plant PRP8 in splice-site selection.

          Abstract

          An Arabidopsis suppression screen identifies a missense allele of a conserved and essential splicing factor that modifies splice-site selection.

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          Most cited references78

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          The Sequence Alignment/Map format and SAMtools

          Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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            HTSeq—a Python framework to work with high-throughput sequencing data

            Motivation: A large choice of tools exists for many standard tasks in the analysis of high-throughput sequencing (HTS) data. However, once a project deviates from standard workflows, custom scripts are needed. Results: We present HTSeq, a Python library to facilitate the rapid development of such scripts. HTSeq offers parsers for many common data formats in HTS projects, as well as classes to represent data, such as genomic coordinates, sequences, sequencing reads, alignments, gene model information and variant calls, and provides data structures that allow for querying via genomic coordinates. We also present htseq-count, a tool developed with HTSeq that preprocesses RNA-Seq data for differential expression analysis by counting the overlap of reads with genes. Availability and implementation: HTSeq is released as an open-source software under the GNU General Public Licence and available from http://www-huber.embl.de/HTSeq or from the Python Package Index at https://pypi.python.org/pypi/HTSeq. Contact: sanders@fs.tum.de
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              Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype

              Rapid advances in next-generation sequencing technologies have dramatically changed our ability to perform genome-scale analyses. The human reference genome used for most genomic analyses represents only a small number of individuals, limiting its usefulness for genotyping. We designed a novel method, HISAT2, for representing and searching an expanded model of the human reference genome, in which a large catalogue of known genomic variants and haplotypes is incorporated into the data structure used for searching and alignment. This strategy for representing a population of genomes, along with a fast and memory-efficient search algorithm, enables more detailed and accurate variant analyses than previous methods. We demonstrate two initial applications of HISAT2: HLA typing, a critical need in human organ transplantation, and DNA fingerprinting, widely used in forensics. These applications are part of HISAT-genotype, with performance not only surpassing earlier computational methods, but matching or exceeding the accuracy of laboratory-based assays.
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                Author and article information

                Contributors
                Journal
                Plant Physiol
                Plant Physiol
                plphys
                Plant Physiology
                Oxford University Press
                0032-0889
                1532-2548
                August 2022
                24 May 2022
                24 May 2022
                : 189
                : 4
                : 2175-2192
                Affiliations
                Department of Biosciences, Rice University , Houston, Texas 77005, USA
                Department of Biosciences, Rice University , Houston, Texas 77005, USA
                Department of Plant Pathology and Microbiology, Iowa State University , Ames, Iowa 50011, USA
                Department of Biosciences, Rice University , Houston, Texas 77005, USA
                Department of Biosciences, Rice University , Houston, Texas 77005, USA
                Author notes
                Author for correspondence: bartel@ 123456rice.edu

                Present address for Jia Qi Xiong: Baylor College of Medicine, Houston, Texas 77030, USA

                Senior author

                Author information
                https://orcid.org/0000-0002-6479-5426
                https://orcid.org/0000-0001-5176-2038
                https://orcid.org/0000-0003-0988-321X
                https://orcid.org/0000-0003-3846-9149
                https://orcid.org/0000-0002-6367-346X
                Article
                kiac221
                10.1093/plphys/kiac221
                9342983
                35608297
                73af02fb-3e53-4cd5-8f20-a0ca57d6e4f1
                © The Author(s) 2022. Published by Oxford University Press on behalf of American Society of Plant Biologists.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence ( https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                : 19 April 2022
                : 19 November 2021
                : 26 May 2022
                Page count
                Pages: 18
                Funding
                Funded by: National Institutes of Health, DOI 10.13039/100000002;
                Funded by: NIH, DOI 10.13039/100000002;
                Award ID: R35GM130338
                Funded by: Robert A. Welch Foundation, DOI 10.13039/100000928;
                Award ID: C-1309
                Funded by: NIH, DOI 10.13039/100000002;
                Award ID: F31GM125367
                Funded by: United States Department of Agriculture-National Institute of Food and Agriculture;
                Funded by: USDA-NIFA;
                Funded by: Postdoctoral Research Fellowship;
                Award ID: 2019-67012-29712
                Funded by: The Genome Technology Access Center;
                Funded by: National Cancer Institute Cancer Center Support;
                Award ID: P30CA91842
                Funded by: National Center for Research Resources, DOI 10.13039/100000097;
                Award ID: UL1TR002345
                Categories
                Research Articles
                Genes, Development and Evolution
                AcademicSubjects/SCI02286
                AcademicSubjects/SCI02287
                AcademicSubjects/SCI01270
                AcademicSubjects/SCI01280
                AcademicSubjects/SCI02288

                Plant science & Botany
                Plant science & Botany

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