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Gustavsson EK, Sethi S, Gao Y, Brenton JW, García-Ruiz S, Zhang D, Garza R, Reynolds RH, Evans JR, Chen Z, Grant-Peters M, Macpherson H, Montgomery K, Dore R, Wernick AI, Arber C, Wray S, Gandhi S, Esselborn J, Blauwendraat C, Douse CH, Adami A, Atacho DAM, Kouli A, Quaegebeur A, Barker RA, Englund E, Platt F, Jakobsson J, Wood NW, Houlden H, Saini H, Bento CF, Hardy J, Ryten M. The annotation of GBA1 has been concealed by its protein-coding pseudogene GBAP1. SCIENCE ADVANCES 2024; 10:eadk1296. [PMID: 38924406 PMCID: PMC11204300 DOI: 10.1126/sciadv.adk1296] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Accepted: 05/17/2024] [Indexed: 06/28/2024]
Abstract
Mutations in GBA1 cause Gaucher disease and are the most important genetic risk factor for Parkinson's disease. However, analysis of transcription at this locus is complicated by its highly homologous pseudogene, GBAP1. We show that >50% of short RNA-sequencing reads mapping to GBA1 also map to GBAP1. Thus, we used long-read RNA sequencing in the human brain, which allowed us to accurately quantify expression from both GBA1 and GBAP1. We discovered significant differences in expression compared to short-read data and identify currently unannotated transcripts of both GBA1 and GBAP1. These included protein-coding transcripts from both genes that were translated in human brain, but without the known lysosomal function-yet accounting for almost a third of transcription. Analyzing brain-specific cell types using long-read and single-nucleus RNA sequencing revealed region-specific variations in transcript expression. Overall, these findings suggest nonlysosomal roles for GBA1 and GBAP1 with implications for our understanding of the role of GBA1 in health and disease.
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Affiliation(s)
- Emil K. Gustavsson
- Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London, UK
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
| | - Siddharth Sethi
- Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London, UK
- Astex Pharmaceuticals, 436 Cambridge Science Park, Cambridge, UK
| | - Yujing Gao
- Astex Pharmaceuticals, 436 Cambridge Science Park, Cambridge, UK
| | - Jonathan W. Brenton
- Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London, UK
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
| | - Sonia García-Ruiz
- Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London, UK
- NIHR Great Ormond Street Hospital Biomedical Research Centre, University College London, London, UK
| | - David Zhang
- Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London, UK
| | - Raquel Garza
- Laboratory of Molecular Neurogenetics, Department of Experimental Medical Science, Wallenberg Neuroscience Center and Lund Stem Cell Center, Lund, Sweden
| | - Regina H. Reynolds
- Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London, UK
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
| | - James R. Evans
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, London, UK
- The Francis Crick Institute, London, UK
| | - Zhongbo Chen
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Melissa Grant-Peters
- Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London, UK
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
| | - Hannah Macpherson
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Kylie Montgomery
- Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London, UK
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Rhys Dore
- Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London, UK
| | - Anna I. Wernick
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, London, UK
- The Francis Crick Institute, London, UK
| | - Charles Arber
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Selina Wray
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Sonia Gandhi
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, London, UK
- The Francis Crick Institute, London, UK
| | - Julian Esselborn
- Astex Pharmaceuticals, 436 Cambridge Science Park, Cambridge, UK
| | - Cornelis Blauwendraat
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA
| | - Christopher H. Douse
- Laboratory of Epigenetics and Chromatin Dynamics, Department of Experimental Medical Science, Lund Stem Cell Center, Lund University, Lund, Sweden
| | - Anita Adami
- Laboratory of Molecular Neurogenetics, Department of Experimental Medical Science, Wallenberg Neuroscience Center and Lund Stem Cell Center, Lund, Sweden
| | - Diahann A. M. Atacho
- Laboratory of Molecular Neurogenetics, Department of Experimental Medical Science, Wallenberg Neuroscience Center and Lund Stem Cell Center, Lund, Sweden
| | - Antonina Kouli
- Wellcome-MRC Cambridge Stem Cell Institute and John Van Geest Centre for Brain Repair, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Annelies Quaegebeur
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
- Department of Clinical Neurosciences, University of Cambridge, Clifford Albutt Building, Cambridge, UK
| | - Roger A. Barker
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
- Wellcome-MRC Cambridge Stem Cell Institute and John Van Geest Centre for Brain Repair, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | | | - Frances Platt
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
- Department of Pharmacology, University of Oxford, Oxford, UK
| | - Johan Jakobsson
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
- Laboratory of Molecular Neurogenetics, Department of Experimental Medical Science, Wallenberg Neuroscience Center and Lund Stem Cell Center, Lund, Sweden
| | - Nicholas W. Wood
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Henry Houlden
- Department of Neuromuscular Disease, UCL Queen Square Institute of Neurology, UCL, London, UK
| | - Harpreet Saini
- Astex Pharmaceuticals, 436 Cambridge Science Park, Cambridge, UK
| | - Carla F. Bento
- Astex Pharmaceuticals, 436 Cambridge Science Park, Cambridge, UK
| | - John Hardy
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
- Reta Lila Weston Institute, UCL Queen Square Institute of Neurology, UCL, London, UK
- UK Dementia Research Institute at UCL, UCL Queen Square Institute of Neurology, UCL, London, UK
- NIHR University College London Hospitals Biomedical Research Centre, London, UK
- Institute for Advanced Study, The Hong Kong University of Science and Technology, Hong Kong SAR, China
| | - Mina Ryten
- Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London, UK
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
- NIHR Great Ormond Street Hospital Biomedical Research Centre, University College London, London, UK
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2
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Wan L, Su S, Liu J, Zou B, Jiang Y, Jiao B, Tang S, Zhang Y, Deng C, Xiao W. The Spatio-Temporal Expression Profiles of Silkworm Pseudogenes Provide Valuable Insights into Their Biological Roles. Evol Bioinform Online 2024; 20:11769343241261814. [PMID: 38883803 PMCID: PMC11179516 DOI: 10.1177/11769343241261814] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Accepted: 05/28/2024] [Indexed: 06/18/2024] Open
Abstract
Background Pseudogenes are sequences that have lost the ability to transcribe RNA molecules or encode truncated but possibly functional proteins. While they were once considered to be meaningless remnants of evolution, recent researches have shown that pseudogenes play important roles in various biological processes. However, the studies of pseudogenes in the silkworm, an important model organism, are limited and have focused on single or only a few specific genes. Objective To fill these gaps, we present a systematic genome-wide studies of pseudogenes in the silkworm. Methods We identified the pseudogenes in the silkworm using the silkworm genome assemblies, transcriptome, protein sequences from silkworm and its related species. Then we used transcriptome datasets from 832 RNA-seq analyses to construct spatio-temporal expression profiles for these pseudogenes. Additionally, we identified tissue-specifically expressed and differentially expressed pseudogenes to further understand their characteristics. Finally, the functional roles of pseudogenes as lncRNAs were systematically analyzed. Results We identified a total of 4410 pseudogenes, which were grouped into 4 groups, including duplications (DUPs), unitary pseudogenes (Unitary), processed pseudogenes (retropseudogenes, RETs), and fragments (FRAGs). The most of pseudogenes in the domestic silkworm were generated before the divergence of wild and domestic silkworm, however, the domestication may also involve in the accumulation of pseudogenes. These pseudogenes were clearly divided into 2 cluster, a highly expressed and a lowly expressed, and the posterior silk gland was the tissue with the most tissue-specific pseudogenes (199), implying these pseudogenes may be involved in the development and function of silkgland. We identified 3299 lncRNAs in these pseudogenes, and the target genes of these lncRNAs in silkworm pseudogenes were enriched in the egg formation and olfactory function. Conclusions This study replenishes the genome annotations for silkworm, provide valuable insights into the biological roles of pseudogenes. It will also contribute to our understanding of the complex gene regulatory networks in the silkworm and will potentially have implications for other organisms as well.
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Affiliation(s)
- Linrong Wan
- Sericultural Research Institute, Sichuan Academy of Agricultural Sciences, Nanchong, Sichuan, China
- State Key Laboratory of Resource Insects, Southwest University, Chongqing, China
| | - Siyuan Su
- Sericultural Research Institute, Sichuan Academy of Agricultural Sciences, Nanchong, Sichuan, China
| | - Jinyun Liu
- Research and Development Center, LyuKang, Chengdu, China
- Department of Bioinformatics, DNA Stories Bioinformatics Center, Chengdu, China
| | - Bangxing Zou
- Sericultural Research Institute, Sichuan Academy of Agricultural Sciences, Nanchong, Sichuan, China
| | - Yaming Jiang
- Sericultural Research Institute, Sichuan Academy of Agricultural Sciences, Nanchong, Sichuan, China
| | - Beibei Jiao
- Research and Development Center, LyuKang, Chengdu, China
- Department of Bioinformatics, DNA Stories Bioinformatics Center, Chengdu, China
| | - Shaokuan Tang
- Research and Development Center, LyuKang, Chengdu, China
- Department of Bioinformatics, DNA Stories Bioinformatics Center, Chengdu, China
| | - Youhong Zhang
- Sericultural Research Institute, Sichuan Academy of Agricultural Sciences, Nanchong, Sichuan, China
| | - Cao Deng
- Research and Development Center, LyuKang, Chengdu, China
- Department of Bioinformatics, DNA Stories Bioinformatics Center, Chengdu, China
| | - Wenfu Xiao
- Sericultural Research Institute, Sichuan Academy of Agricultural Sciences, Nanchong, Sichuan, China
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3
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Jaafari H, Bueno C, Schafer NP, Martin J, Morcos F, Wolynes PG. The physical and evolutionary energy landscapes of devolved protein sequences corresponding to pseudogenes. Proc Natl Acad Sci U S A 2024; 121:e2322428121. [PMID: 38739795 PMCID: PMC11127006 DOI: 10.1073/pnas.2322428121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Accepted: 03/26/2024] [Indexed: 05/16/2024] Open
Abstract
Protein evolution is guided by structural, functional, and dynamical constraints ensuring organismal viability. Pseudogenes are genomic sequences identified in many eukaryotes that lack translational activity due to sequence degradation and thus over time have undergone "devolution." Previously pseudogenized genes sometimes regain their protein-coding function, suggesting they may still encode robust folding energy landscapes despite multiple mutations. We study both the physical folding landscapes of protein sequences corresponding to human pseudogenes using the Associative Memory, Water Mediated, Structure and Energy Model, and the evolutionary energy landscapes obtained using direct coupling analysis (DCA) on their parent protein families. We found that generally mutations that have occurred in pseudogene sequences have disrupted their native global network of stabilizing residue interactions, making it harder for them to fold if they were translated. In some cases, however, energetic frustration has apparently decreased when the functional constraints were removed. We analyzed this unexpected situation for Cyclophilin A, Profilin-1, and Small Ubiquitin-like Modifier 2 Protein. Our analysis reveals that when such mutations in the pseudogene ultimately stabilize folding, at the same time, they likely alter the pseudogenes' former biological activity, as estimated by DCA. We localize most of these stabilizing mutations generally to normally frustrated regions required for binding to other partners.
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Affiliation(s)
- Hana Jaafari
- Center for Theoretical Biophysics, Rice University, Houston, TX77005
- Applied Physics Graduate Program, Smalley-Curl Institute, Rice University, Houston, TX77005
- Department of Chemistry, Rice University, Houston, TX77005
| | - Carlos Bueno
- Center for Theoretical Biophysics, Rice University, Houston, TX77005
| | | | - Jonathan Martin
- Department of Biological Sciences, University of Texas at Dallas, Richardson, TX75080
| | - Faruck Morcos
- Department of Biological Sciences, University of Texas at Dallas, Richardson, TX75080
- Department of Bioengineering, University of Texas at Dallas, Richardson, TX75080
- Center for Systems Biology, University of Texas at Dallas, Richardson, TX75080
| | - Peter G. Wolynes
- Center for Theoretical Biophysics, Rice University, Houston, TX77005
- Department of Chemistry, Rice University, Houston, TX77005
- Department of Physics and Astronomy, Rice University, Houston, TX77005
- Department of Biochemistry and Cell Biology, Rice University, Houston, TX77005
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4
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Porter HL, Ansere VA, Undi RB, Hoolehan W, Giles CB, Brown CA, Stanford D, Huycke MM, Freeman WM, Wren JD. Methylation Array Signals are Predictive of Chronological Age Without Bisulfite Conversion. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.20.572465. [PMID: 38187520 PMCID: PMC10769286 DOI: 10.1101/2023.12.20.572465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
DNA methylation data has been used to make "epigenetic clocks" which attempt to measure chronological and biological aging. These models rely on data derived from bisulfite-based measurements, which exploit a semi-selective deamination and a genomic reference to determine methylation states. Here, we demonstrate how another hallmark of aging, genomic instability, influences methylation measurements in both bisulfite sequencing and methylation arrays. We found that non-methylation factors lead to "pseudomethylation" signals that are both confounding of epigenetic clocks and uniquely age predictive. Quantifying these covariates in aging studies will be critical to building better clocks and designing appropriate studies of epigenetic aging.
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Affiliation(s)
- Hunter L Porter
- Oklahoma Medical Research Foundation
- University of Oklahoma Health Sciences Center
- Oklahoma Nathan Shock Center
| | - Victor A Ansere
- Oklahoma Medical Research Foundation
- University of Oklahoma Health Sciences Center
| | | | - Walker Hoolehan
- Oklahoma Medical Research Foundation
- University of Oklahoma Health Sciences Center
| | | | - Chase A Brown
- Oklahoma Medical Research Foundation
- University of Oklahoma Health Sciences Center
| | | | | | - Willard M Freeman
- Oklahoma Medical Research Foundation
- University of Oklahoma Health Sciences Center
- Oklahoma Nathan Shock Center
| | - Jonathan D Wren
- Oklahoma Medical Research Foundation
- University of Oklahoma Health Sciences Center
- Oklahoma Nathan Shock Center
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5
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Klarić TS, Gudelj I, Santpere G, Novokmet M, Vučković F, Ma S, Doll HM, Risgaard R, Bathla S, Karger A, Nairn AC, Luria V, Bečeheli I, Sherwood CC, Ely JJ, Hof PR, Sousa AM, Josić D, Lauc G, Sestan N. Human-specific features and developmental dynamics of the brain N-glycome. SCIENCE ADVANCES 2023; 9:eadg2615. [PMID: 38055821 PMCID: PMC10699788 DOI: 10.1126/sciadv.adg2615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 11/07/2023] [Indexed: 12/08/2023]
Abstract
Comparative "omics" studies have revealed unique aspects of human neurobiology, yet an evolutionary perspective of the brain N-glycome is lacking. We performed multiregional characterization of rat, macaque, chimpanzee, and human brain N-glycomes using chromatography and mass spectrometry and then integrated these data with complementary glycotranscriptomic data. We found that, in primates, the brain N-glycome has diverged more rapidly than the underlying transcriptomic framework, providing a means for rapidly generating additional interspecies diversity. Our data suggest that brain N-glycome evolution in hominids has been characterized by an overall increase in complexity coupled with a shift toward increased usage of α(2-6)-linked N-acetylneuraminic acid. Moreover, interspecies differences in the cell type expression pattern of key glycogenes were identified, including some human-specific differences, which may underpin this evolutionary divergence. Last, by comparing the prenatal and adult human brain N-glycomes, we uncovered region-specific neurodevelopmental pathways that lead to distinct spatial N-glycosylation profiles in the mature brain.
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Affiliation(s)
- Thomas S. Klarić
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA
- Genos Glycoscience Research Laboratory, Zagreb, Croatia
| | - Ivan Gudelj
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA
- Genos Glycoscience Research Laboratory, Zagreb, Croatia
- Department of Biotechnology, University of Rijeka, Rijeka, Croatia
| | - Gabriel Santpere
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA
- Hospital del Mar Research Institute, Barcelona, Catalonia, Spain
| | | | | | - Shaojie Ma
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA
| | - Hannah M. Doll
- Waisman Center and Department of Neuroscience, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
- Department of Neuroscience, University of Wisconsin-Madison, Madison, WI, USA
| | - Ryan Risgaard
- Waisman Center and Department of Neuroscience, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
- Department of Neuroscience, University of Wisconsin-Madison, Madison, WI, USA
| | - Shveta Bathla
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Amir Karger
- IT Research Computing, Harvard Medical School, Boston, MA, USA
| | - Angus C. Nairn
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Victor Luria
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA
- Division of Genetics and Genomics, Boston Children’s Hospital, Harvard Medical School, Boston, USA
| | | | - Chet C. Sherwood
- Department of Anthropology, The George Washington University, Washington, DC, USA
| | - John J. Ely
- Center for the Advanced Study of Human Paleobiology, The George Washington University, Washington, DC, USA
- MAEBIOS, Alamogordo, NM, USA
| | - Patrick R. Hof
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - André M. M. Sousa
- Waisman Center and Department of Neuroscience, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
- Department of Neuroscience, University of Wisconsin-Madison, Madison, WI, USA
| | - Djuro Josić
- Department of Biotechnology, University of Rijeka, Rijeka, Croatia
- Warren Alpert Medical School, Brown University, Providence, RI, USA
| | - Gordan Lauc
- Genos Glycoscience Research Laboratory, Zagreb, Croatia
- University of Zagreb Faculty of Pharmacy and Biochemistry, Zagreb, Croatia
| | - Nenad Sestan
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Departments of Genetics and Comparative Medicine, Kavli Institute for Neuroscience, Program in Cellular Neuroscience, Neurodegeneration and Repair, and Yale Child Study Center, Yale School of Medicine, New Haven, CT, USA
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6
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Yan Y, Tian Y, Wu Z, Zhang K, Yang R. Interchromosomal Colocalization with Parental Genes Is Linked to the Function and Evolution of Mammalian Retrocopies. Mol Biol Evol 2023; 40:msad265. [PMID: 38060983 PMCID: PMC10733166 DOI: 10.1093/molbev/msad265] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 10/25/2023] [Accepted: 11/29/2023] [Indexed: 12/22/2023] Open
Abstract
Retrocopies are gene duplicates arising from reverse transcription of mature mRNA transcripts and their insertion back into the genome. While long being regarded as processed pseudogenes, more and more functional retrocopies have been discovered. How the stripped-down retrocopies recover expression capability and become functional paralogs continually intrigues evolutionary biologists. Here, we investigated the function and evolution of retrocopies in the context of 3D genome organization. By mapping retrocopy-parent pairs onto sequencing-based and imaging-based chromatin contact maps in human and mouse cell lines and onto Hi-C interaction maps in 5 other mammals, we found that retrocopies and their parental genes show a higher-than-expected interchromosomal colocalization frequency. The spatial interactions between retrocopies and parental genes occur frequently at loci in active subcompartments and near nuclear speckles. Accordingly, colocalized retrocopies are more actively transcribed and translated and are more evolutionarily conserved than noncolocalized ones. The active transcription of colocalized retrocopies may result from their permissive epigenetic environment and shared regulatory elements with parental genes. Population genetic analysis of retroposed gene copy number variants in human populations revealed that retrocopy insertions are not entirely random in regard to interchromosomal interactions and that colocalized retroposed gene copy number variants are more likely to reach high frequencies, suggesting that both insertion bias and natural selection contribute to the colocalization of retrocopy-parent pairs. Further dissection implies that reduced selection efficacy, rather than positive selection, contributes to the elevated allele frequency of colocalized retroposed gene copy number variants. Overall, our results hint a role of interchromosomal colocalization in the "resurrection" of initially neutral retrocopies.
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Affiliation(s)
- Yubin Yan
- College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, China
| | - Yuhan Tian
- College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, China
| | - Zefeng Wu
- College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, China
| | - Kunling Zhang
- College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, China
| | - Ruolin Yang
- College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, China
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7
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Leblanc S, Brunet MA, Jacques JF, Lekehal AM, Duclos A, Tremblay A, Bruggeman-Gascon A, Samandi S, Brunelle M, Cohen AA, Scott MS, Roucou X. Newfound Coding Potential of Transcripts Unveils Missing Members of Human Protein Communities. GENOMICS, PROTEOMICS & BIOINFORMATICS 2023; 21:515-534. [PMID: 36183975 PMCID: PMC10787177 DOI: 10.1016/j.gpb.2022.09.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 08/10/2022] [Accepted: 09/26/2022] [Indexed: 06/16/2023]
Abstract
Recent proteogenomic approaches have led to the discovery that regions of the transcriptome previously annotated as non-coding regions [i.e., untranslated regions (UTRs), open reading frames overlapping annotated coding sequences in a different reading frame, and non-coding RNAs] frequently encode proteins, termed alternative proteins (altProts). This suggests that previously identified protein-protein interaction (PPI) networks are partially incomplete because altProts are not present in conventional protein databases. Here, we used the proteogenomic resource OpenProt and a combined spectrum- and peptide-centric analysis for the re-analysis of a high-throughput human network proteomics dataset, thereby revealing the presence of 261 altProts in the network. We found 19 genes encoding both an annotated (reference) and an alternative protein interacting with each other. Of the 117 altProts encoded by pseudogenes, 38 are direct interactors of reference proteins encoded by their respective parental genes. Finally, we experimentally validate several interactions involving altProts. These data improve the blueprints of the human PPI network and suggest functional roles for hundreds of altProts.
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Affiliation(s)
- Sébastien Leblanc
- Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC J1E 4K8, Canada; PROTEO, Quebec Network for Research on Protein Function, Structure, and Engineering, Quebec City, QC G1V 0A6, Canada
| | - Marie A Brunet
- Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC J1E 4K8, Canada; PROTEO, Quebec Network for Research on Protein Function, Structure, and Engineering, Quebec City, QC G1V 0A6, Canada
| | - Jean-François Jacques
- Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC J1E 4K8, Canada; PROTEO, Quebec Network for Research on Protein Function, Structure, and Engineering, Quebec City, QC G1V 0A6, Canada
| | - Amina M Lekehal
- Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC J1E 4K8, Canada; PROTEO, Quebec Network for Research on Protein Function, Structure, and Engineering, Quebec City, QC G1V 0A6, Canada
| | - Andréa Duclos
- Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC J1E 4K8, Canada
| | - Alexia Tremblay
- Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC J1E 4K8, Canada
| | - Alexis Bruggeman-Gascon
- Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC J1E 4K8, Canada
| | - Sondos Samandi
- Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC J1E 4K8, Canada; PROTEO, Quebec Network for Research on Protein Function, Structure, and Engineering, Quebec City, QC G1V 0A6, Canada
| | - Mylène Brunelle
- Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC J1E 4K8, Canada; PROTEO, Quebec Network for Research on Protein Function, Structure, and Engineering, Quebec City, QC G1V 0A6, Canada
| | - Alan A Cohen
- Department of Family Medicine, Université de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada
| | - Michelle S Scott
- Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC J1E 4K8, Canada
| | - Xavier Roucou
- Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC J1E 4K8, Canada; PROTEO, Quebec Network for Research on Protein Function, Structure, and Engineering, Quebec City, QC G1V 0A6, Canada.
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8
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Qian SH, Chen L, Xiong YL, Chen ZX. Evolution and function of developmentally dynamic pseudogenes in mammals. Genome Biol 2022; 23:235. [PMID: 36348461 PMCID: PMC9641868 DOI: 10.1186/s13059-022-02802-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Accepted: 10/23/2022] [Indexed: 11/11/2022] Open
Abstract
BACKGROUND Pseudogenes are excellent markers for genome evolution, which are emerging as crucial regulators of development and disease, especially cancer. However, systematic functional characterization and evolution of pseudogenes remain largely unexplored. RESULTS To systematically characterize pseudogenes, we date the origin of human and mouse pseudogenes across vertebrates and observe a burst of pseudogene gain in these two lineages. Based on a hybrid sequencing dataset combining full-length PacBio sequencing, sample-matched Illumina sequencing, and public time-course transcriptome data, we observe that abundant mammalian pseudogenes could be transcribed, which contribute to the establishment of organ identity. Our analyses reveal that developmentally dynamic pseudogenes are evolutionarily conserved and show an increasing weight during development. Besides, they are involved in complex transcriptional and post-transcriptional modulation, exhibiting the signatures of functional enrichment. Coding potential evaluation suggests that 19% of human pseudogenes could be translated, thus serving as a new way for protein innovation. Moreover, pseudogenes carry disease-associated SNPs and conduce to cancer transcriptome perturbation. CONCLUSIONS Our discovery reveals an unexpectedly high abundance of mammalian pseudogenes that can be transcribed and translated, and these pseudogenes represent a novel regulatory layer. Our study also prioritizes developmentally dynamic pseudogenes with signatures of functional enrichment and provides a hybrid sequencing dataset for further unraveling their biological mechanisms in organ development and carcinogenesis in the future.
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Affiliation(s)
- Sheng Hu Qian
- grid.35155.370000 0004 1790 4137Hubei Hongshan Laboratory, College of Biomedicine and Health, Huazhong Agricultural University, Wuhan, 430070 PR China ,grid.35155.370000 0004 1790 4137Hubei Key Laboratory of Agricultural Bioinformatics, College of Life Science and Technology, Huazhong Agricultural University, Wuhan, 430070 PR China
| | - Lu Chen
- grid.35155.370000 0004 1790 4137Hubei Hongshan Laboratory, College of Biomedicine and Health, Huazhong Agricultural University, Wuhan, 430070 PR China ,grid.35155.370000 0004 1790 4137Hubei Key Laboratory of Agricultural Bioinformatics, College of Life Science and Technology, Huazhong Agricultural University, Wuhan, 430070 PR China
| | - Yu-Li Xiong
- grid.35155.370000 0004 1790 4137Hubei Hongshan Laboratory, College of Biomedicine and Health, Huazhong Agricultural University, Wuhan, 430070 PR China ,grid.35155.370000 0004 1790 4137Hubei Key Laboratory of Agricultural Bioinformatics, College of Life Science and Technology, Huazhong Agricultural University, Wuhan, 430070 PR China
| | - Zhen-Xia Chen
- grid.35155.370000 0004 1790 4137Hubei Hongshan Laboratory, College of Biomedicine and Health, Huazhong Agricultural University, Wuhan, 430070 PR China ,grid.35155.370000 0004 1790 4137Hubei Key Laboratory of Agricultural Bioinformatics, College of Life Science and Technology, Huazhong Agricultural University, Wuhan, 430070 PR China ,grid.35155.370000 0004 1790 4137Interdisciplinary Sciences Institute, Huazhong Agricultural University, Wuhan, 430070 PR China ,grid.35155.370000 0004 1790 4137Shenzhen Institute of Nutrition and Health, Huazhong Agricultural University, Shenzhen, 518124 PR China ,grid.488316.00000 0004 4912 1102Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124 PR China
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9
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Structural and developmental dynamics of Matrix associated regions in Drosophila melanogaster genome. BMC Genomics 2022; 23:725. [PMID: 36284304 PMCID: PMC9597980 DOI: 10.1186/s12864-022-08944-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Accepted: 10/10/2022] [Indexed: 11/18/2022] Open
Abstract
Background Eukaryotic genome is compartmentalized into structural and functional domains. One of the concepts of higher order organization of chromatin posits that the DNA is organized in constrained loops that behave as independent functional domains. Nuclear Matrix (NuMat), a ribo-proteinaceous nucleoskeleton, provides the structural basis for this organization. DNA sequences located at base of the loops are known as the Matrix Attachment Regions (MARs). NuMat relates to multiple nuclear processes and is partly cell type specific in composition. It is a biochemically defined structure and several protocols have been used to isolate the NuMat where some of the steps have been critically evaluated. These sequences play an important role in genomic organization it is imperative to know their dynamics during development and differentiation. Results Here we look into the dynamics of MARs when the preparation process is varied and during embryonic development of D. melanogaster. A subset of MARs termed as “Core-MARs” present abundantly in pericentromeric heterochromatin, are constant unalterable anchor points as they associate with NuMat through embryonic development and are independent of the isolation procedure. Euchromatic MARs are dynamic and reflect the transcriptomic profile of the cell. New MARs are generated by nuclear stabilization, and during development, mostly at paused RNA polymerase II promoters. Paused Pol II MARs depend on RNA transcripts for NuMat association. Conclusions Our data reveals the role of MARs in functionally dynamic nucleus and contributes to the current understanding of nuclear architecture in genomic context. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-022-08944-4.
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10
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Zhang J, Chi X, Zhong J, Fernie A, Alseekh S, Huang L, Qian D. Extensive nrDNA ITS polymorphism in Lycium: Non-concerted evolution and the identification of pseudogenes. FRONTIERS IN PLANT SCIENCE 2022; 13:984579. [PMID: 36092433 PMCID: PMC9453804 DOI: 10.3389/fpls.2022.984579] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/02/2022] [Accepted: 08/01/2022] [Indexed: 06/01/2023]
Abstract
The internal transcribed spacer (ITS) is one of the most extensively sequenced molecular markers in plant systematics due to its generally concerted evolution. While non-concerted evolution has been found in some plant taxa, such information is missing in Lycium. Molecular studies of six species and two variants of the genus Lycium revealed high levels of intra- and inter-individual polymorphism in the ITS, indicating non-concerted evolution. All genomic DNA ITS paralogues were identified as putative pseudogenes or functional paralogues through a series of comparisons of sequence features, including length and substitution variation, GC content, secondary structure stability, and the presence of conserved motifs in the 5.8S gene, and the rate of evolution. Approximately, 60% of ITS pseudogenes could be easily detected. Based on phylogenetic analysis, all pseudogenes were highly distinct from their corresponding functional copies, tended to evolve neutrally, and clustered randomly together in the evolutionary tree. The results probably suggest that this ITS non-concerted evolution is related to the recent divergence between tandem repeats within the Lycium genome and hybridization between species. Our study complements those of pseudogenes in plant taxa and provides a theoretical basis for the phylogeny and genetic origin of the genus Lycium while having important implications for the use of ITS molecular markers for phylogenetic reconstruction.
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Affiliation(s)
- Jiao Zhang
- Beijing Key Laboratory of Research of Chinese Medicine on Prevention and Treatment for Major Diseases, Experimental Research Center, China Academy of Chinese Medical Sciences, Beijing, China
| | - Xiulian Chi
- State Key Laboratory Breeding Base of Dao-di Herbs, National Resource Center for Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, China
| | - Juying Zhong
- Beijing Key Laboratory of Research of Chinese Medicine on Prevention and Treatment for Major Diseases, Experimental Research Center, China Academy of Chinese Medical Sciences, Beijing, China
| | - Alisdair Fernie
- Max Planck Institute of Molecular Plant Physiology, Potsdam, Germany
| | - Saleh Alseekh
- Max Planck Institute of Molecular Plant Physiology, Potsdam, Germany
| | - Luqi Huang
- State Key Laboratory Breeding Base of Dao-di Herbs, National Resource Center for Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, China
| | - Dan Qian
- Beijing Key Laboratory of Research of Chinese Medicine on Prevention and Treatment for Major Diseases, Experimental Research Center, China Academy of Chinese Medical Sciences, Beijing, China
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11
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Meller A, Boisvert FM. Mining Proteomics Datasets to Uncover Functional Pseudogenes. Methods Mol Biol 2022; 2456:241-251. [PMID: 35612746 DOI: 10.1007/978-1-0716-2124-0_16] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Analysis of the proteome, combined with the human genome sequence, improved gene annotation and confirmed that some genes are actually expressed as proteins, including pseudogenes, alternative reading frames, and additional protein isoforms. Although sequencing a genome is a challenge in itself, the annotation of all genes encoding proteins is a bigger one. Here, we describe an in silico approach to identify evidence of pseudogene expression, as well as an experimental approach for the validation of the protein encoded by pseudogenes, including the steps necessary to quantify these proteins. This technique enables a comprehensive analysis for the expression of genes into proteins that were not suspected of existing.
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Affiliation(s)
- Anna Meller
- Department of Immunology and Cell Biology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Québec, QC, Canada
| | - François-Michel Boisvert
- Department of Immunology and Cell Biology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Québec, QC, Canada.
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12
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Shaw BC, Estus S. Pseudogene-Mediated Gene Conversion After CRISPR-Cas9 Editing Demonstrated by Partial CD33 Conversion with SIGLEC22P. CRISPR J 2021; 4:699-709. [PMID: 34558988 DOI: 10.1089/crispr.2021.0052] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Although gene editing workflows typically consider the possibility of off-target editing, pseudogene-directed homology repair has not, to our knowledge, been reported previously. Here, we employed a CRISPR-Cas9 strategy for targeted excision of exon 2 in CD33 in U937 human monocyte cell line. Candidate clonal cell lines were screened by using a clinically relevant antibody known to label the IgV domain encoded by exon 2 (P67.6, gemtuzumab). In addition to the anticipated deletion of exon 2, we also found unexpected P67.6-negative cell lines, which had apparently retained CD33 exon 2. Sequencing revealed that these lines underwent gene conversion from the nearby SIGLEC22P pseudogene during homology repair that resulted in three missense mutations relative to CD33. Ectopic expression studies confirmed that the P67.6 epitope is dependent upon these amino acids. In summation, we report that pseudogene-directed homology repair can lead to aberrant CRISPR gene editing.
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Affiliation(s)
- Benjamin C Shaw
- Department of Physiology and Sanders-Brown Center on Aging, University of Kentucky, Lexington, USA
| | - Steven Estus
- Department of Physiology and Sanders-Brown Center on Aging, University of Kentucky, Lexington, USA
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13
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Sun M, Wang Y, Zheng C, Wei Y, Hou J, Zhang P, He W, Lv X, Ding Y, Liang H, Hon CC, Chen X, Xu H, Chen Y. Systematic functional interrogation of human pseudogenes using CRISPRi. Genome Biol 2021; 22:240. [PMID: 34425866 PMCID: PMC8381491 DOI: 10.1186/s13059-021-02464-2] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2020] [Accepted: 08/06/2021] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND The human genome encodes over 14,000 pseudogenes that are evolutionary relics of protein-coding genes and commonly considered as nonfunctional. Emerging evidence suggests that some pseudogenes may exert important functions. However, to what extent human pseudogenes are functionally relevant remains unclear. There has been no large-scale characterization of pseudogene function because of technical challenges, including high sequence similarity between pseudogene and parent genes, and poor annotation of transcription start sites. RESULTS To overcome these technical obstacles, we develop an integrated computational pipeline to design the first genome-wide library of CRISPR interference (CRISPRi) single-guide RNAs (sgRNAs) that target human pseudogene promoter-proximal regions. We perform the first pseudogene-focused CRISPRi screen in luminal A breast cancer cells and reveal approximately 70 pseudogenes that affect breast cancer cell fitness. Among the top hits, we identify a cancer-testis unitary pseudogene, MGAT4EP, that is predominantly localized in the nucleus and interacts with FOXA1, a key regulator in luminal A breast cancer. By enhancing the promoter binding of FOXA1, MGAT4EP upregulates the expression of oncogenic transcription factor FOXM1. Integrative analyses of multi-omic data from the Cancer Genome Atlas (TCGA) reveal many unitary pseudogenes whose expressions are significantly dysregulated and/or associated with overall/relapse-free survival of patients in diverse cancer types. CONCLUSIONS Our study represents the first large-scale study characterizing pseudogene function. Our findings suggest the importance of nuclear function of unitary pseudogenes and underscore their underappreciated roles in human diseases. The functional genomic resources developed here will greatly facilitate the study of human pseudogene function.
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Affiliation(s)
- Ming Sun
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
- Present affiliation: Department of Oncology Center, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Baita west road #16, Suzhou, 215001, China
| | - Yunfei Wang
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
- Present affiliation: Clinical Science Lab, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, 33612, USA
| | - Caishang Zheng
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Yanjun Wei
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Jiakai Hou
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
- Present affiliation: Department of Biology and Biochemistry, University of Houston, Houston, TX, USA
| | - Peng Zhang
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
- Present affiliation: Key Laboratory of RNA Biology, Center for Big Data Research in Health, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China
| | - Wei He
- Department of Epigenetics and Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
- Genetics and Epigenetics Program, MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX, 77030, USA
- Quantitative Sciences Program, MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX, 77030, USA
| | - Xiangdong Lv
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, 77030, USA
- Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX, 77030, USA
- Dan L. Duncan Cancer Center, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Yao Ding
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, 77030, USA
- Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX, 77030, USA
- Dan L. Duncan Cancer Center, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Han Liang
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
- Quantitative Sciences Program, MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX, 77030, USA
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Chung-Chau Hon
- Center for Integrative Medical Sciences, RIKEN, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan
| | - Xi Chen
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, 77030, USA
- Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX, 77030, USA
- Dan L. Duncan Cancer Center, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Han Xu
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
- Department of Epigenetics and Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
- Genetics and Epigenetics Program, MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX, 77030, USA.
- Quantitative Sciences Program, MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX, 77030, USA.
| | - Yiwen Chen
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
- Quantitative Sciences Program, MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX, 77030, USA.
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14
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Pseudogenes: Four Decades of Discovery. Methods Mol Biol 2021. [PMID: 34165705 DOI: 10.1007/978-1-0716-1503-4_1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/10/2023]
Abstract
A pseudogene is defined as a genomic DNA sequence that looks like a mutated or truncated version of a known functional gene. Nearly four decades since their first discovery it has been estimated that between ~12,000 and ~20,000 pseudogenes exist in the human genome. Early efforts to characterize functions for pseudogenes were unsuccessful, thus they were considered functionless relics of evolutionary selection, junk DNA or genetic fossils. Remarkably, an increasing number of pseudogenes have been reported to be expressed as RNA transcripts above and beyond levels considered accidental or spurious transcription. There is emerging evidence that some expressed pseudogene transcripts have biological functions and should be defined as a subclass of functional long noncoding RNAs (lncRNA). In this introductory chapter, I briefly summarize the history and the current knowledge of pseudogenes, and highlight the emerging functions of some pseudogenes in human biology and disease. This second iteration of Pseudogenes in Methods in Molecular Biology highlights new methodological approaches to investigate this intriguing family of lncRNAs and the extent of their biological function.
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15
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Rowley PA, Ellahi A, Han K, Patel JS, Van Leuven JT, Sawyer SL. Nuku, a family of primate retrocopies derived from KU70. G3 GENES|GENOMES|GENETICS 2021; 11:6283581. [PMID: 34849803 PMCID: PMC8496227 DOI: 10.1093/g3journal/jkab163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Accepted: 04/30/2021] [Indexed: 11/16/2022]
Abstract
The gene encoding the ubiquitous DNA repair protein, Ku70p, has undergone extensive copy number expansion during primate evolution. Gene duplications of KU70 have the hallmark of long interspersed element-1 mediated retrotransposition with evidence of target-site duplications, the poly-A tails, and the absence of introns. Evolutionary analysis of this expanded family of KU70-derived “NUKU” retrocopies reveals that these genes are both ancient and also actively being created in extant primate species. NUKU retrocopies show evidence of functional divergence away from KU70, as evinced by their altered pattern of tissue expression and possible tissue-specific translation. Molecular modeling predicted that amino acid changes in Nuku2p at the interaction interface with Ku80p would prevent the assembly of the Ku heterodimer. The lack of Nuku2p-Ku80p interaction was confirmed by yeast two-hybrid assay, which contrasts the robust interaction of Ku70p-Ku80p. While several NUKU retrocopies appear to have been degraded by mutation, NUKU2 shows evidence of positive natural selection, suggesting that this retrocopy is undergoing neofunctionalization. Although Nuku proteins do not appear to antagonize retrovirus transduction in cell culture, the observed expansion and rapid evolution of NUKUs could be being driven by alternative selective pressures related to infectious disease or an undefined role in primate physiology.
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Affiliation(s)
- Paul A Rowley
- Department of Biological Sciences, University of Idaho, Moscow, ID 83844, USA
| | - Aisha Ellahi
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX 78751, USA
| | - Kyudong Han
- Department of Microbiology, College of Science & Technology, Dankook University, Cheonan 31116, Republic of Korea
- Center for Bio- Medical Engineering Core Facility, Dankook University, Cheonan 31116, Republic of Korea
| | - Jagdish Suresh Patel
- Center for Modeling Complex Interactions, University of Idaho, Moscow, ID 83844, USA and
| | - James T Van Leuven
- Center for Modeling Complex Interactions, University of Idaho, Moscow, ID 83844, USA and
| | - Sara L Sawyer
- Department of Molecular, Cellular, and Developmental Biology, University of Colorado Boulder, Boulder, CO 80302, USA
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16
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Khan AA, Ali MS, Babar F, Fatima A, Shafqat MA, Asghar B, Ilyas N, Fatima M, Liaqat A, Gondal MA. Lack of CpG islands in human unitary pseudogenes and its implication. Mamm Genome 2021; 32:443-447. [PMID: 34272576 DOI: 10.1007/s00335-021-09893-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Accepted: 07/07/2021] [Indexed: 11/24/2022]
Abstract
CpG islands (CGIs) are aggregation of CpG dinucleotides in the promoters of mammalian genes. These CGIs are present in almost all the housekeeping genes and some tissue-specific genes in the mammalian genome. Extensive research has been done on the prevalence and role of CGIs in protein-coding genes. However, little is known about CGIs in pseudogenes. In the current research project, we focused on CGIs in three main classes of pseudogenes e.g., duplicated pseudogenes (DPGs), processed pseudogenes (PPGs), and unitary pseudogenes (UPGs). We discovered a predominant absence of CGIs in the promoters of all three pseudogenes. We also compared the CGI profile of these pseudogenes with their parent genes and found that unitary pseudogenes (UPGs) differ from the DPGs and PPGs in the sense that in the latter, lack of CGIs is a consequential event while in UPGs, this lack of CGIs in their promoters is not a result of pseudogenization process. We also discussed the implication of the results obtained from this comparison. To our knowledge, this is the first-ever study highlighting this aspect of UPGs throwing new insights into the evolution of genome in general and especially in the context of pseudogenes.
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Affiliation(s)
- Ammad Aslam Khan
- Department of Bioinformatics and Computational Biology, Virtual University, Lahore, 547 92, Pakistan.
| | - Muhammad Shahryar Ali
- Department of Bioinformatics and Computational Biology, Virtual University, Lahore, 547 92, Pakistan
| | - Farah Babar
- Department of Bioinformatics and Computational Biology, Virtual University, Lahore, 547 92, Pakistan
| | - Anees Fatima
- Department of Bioinformatics and Computational Biology, Virtual University, Lahore, 547 92, Pakistan
| | - Muhammad Awais Shafqat
- Department of Bioinformatics and Computational Biology, Virtual University, Lahore, 547 92, Pakistan
| | - Bisma Asghar
- Department of Bioinformatics and Computational Biology, Virtual University, Lahore, 547 92, Pakistan
| | - Nimra Ilyas
- Department of Bioinformatics and Computational Biology, Virtual University, Lahore, 547 92, Pakistan
| | - Maheen Fatima
- Department of Bioinformatics and Computational Biology, Virtual University, Lahore, 547 92, Pakistan
| | - Ayesha Liaqat
- Department of Bioinformatics and Computational Biology, Virtual University, Lahore, 547 92, Pakistan
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Tan L, Cheng W, Liu F, Wang DO, Wu L, Cao N, Wang J. Positive natural selection of N6-methyladenosine on the RNAs of processed pseudogenes. Genome Biol 2021; 22:180. [PMID: 34120636 PMCID: PMC8201931 DOI: 10.1186/s13059-021-02402-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Accepted: 06/04/2021] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND Canonical nonsense-mediated decay (NMD) is an important splicing-dependent process for mRNA surveillance in mammals. However, processed pseudogenes are not able to trigger NMD due to their lack of introns. It is largely unknown whether they have evolved other surveillance mechanisms. RESULTS Here, we find that the RNAs of pseudogenes, especially processed pseudogenes, have dramatically higher m6A levels than their cognate protein-coding genes, associated with de novo m6A peaks and motifs in human cells. Furthermore, pseudogenes have rapidly accumulated m6A motifs during evolution. The m6A sites of pseudogenes are evolutionarily younger than neutral sites and their m6A levels are increasing, supporting the idea that m6A on the RNAs of pseudogenes is under positive selection. We then find that the m6A RNA modification of processed, rather than unprocessed, pseudogenes promotes cytosolic RNA degradation and attenuates interference with the RNAs of their cognate protein-coding genes. We experimentally validate the m6A RNA modification of two processed pseudogenes, DSTNP2 and NAP1L4P1, which promotes the RNA degradation of both pseudogenes and their cognate protein-coding genes DSTN and NAP1L4. In addition, the m6A of DSTNP2 regulation of DSTN is partially dependent on the miRNA miR-362-5p. CONCLUSIONS Our discovery reveals a novel evolutionary role of m6A RNA modification in cleaning up the unnecessary processed pseudogene transcripts to attenuate their interference with the regulatory network of protein-coding genes.
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Affiliation(s)
- Liqiang Tan
- Department of Medical Informatics, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou, 510080, China
| | - Weisheng Cheng
- Department of Medical Informatics, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou, 510080, China
| | - Fang Liu
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou, 510080, China
| | - Dan Ohtan Wang
- Center for Biosystems Dynamics Research, RIKEN, 2-2-3 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo, 650-0047, Japan
- Wuya College of Innovation, Shenyang Pharmaceutical University, Shenyang, 110016, China
| | - Linwei Wu
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou, 510080, China
| | - Nan Cao
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou, 510080, China
| | - Jinkai Wang
- Department of Medical Informatics, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou, 510080, China.
- RNA Biomedical Institute, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, China.
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18
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Tian R, Geng Y, Guo H, Yang C, Seim I, Yang G. Comparative analysis of the superoxide dismutase gene family in Cetartiodactyla. J Evol Biol 2021; 34:1046-1060. [PMID: 33896059 DOI: 10.1111/jeb.13792] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Revised: 03/29/2021] [Accepted: 04/16/2021] [Indexed: 12/18/2022]
Abstract
Cetacea, whales, dolphins and porpoises form an order of mammals adapted to aquatic life. Their transition to an aquatic habitat resulted in exceptional protection against cellular insults, including oxidative and osmotic stress. Here, we considered the structure and molecular evolution of the superoxide dismutase (SOD) gene family, which encodes essential enzymes in the mammalian antioxidant system, in the superorder Cetartiodactyla. To this end, we juxtaposed cetaceans and their closest extant relatives (order Artiodactyla). We identified 94 genes in 23 species, of which 70 are bona fide intact genes. Although the SOD gene family is conserved in Cetartiodactyla, lineage-specific gene duplications and deletions were observed. Phylogenetic analyses show that the SOD2 subfamily diverged from a clade containing SOD1 and SOD3, suggesting that cytoplasmic, extracellular and mitochondrial SODs have started down independent evolutionary paths. Specific-amino acid changes (e.g. K130N in SOD2) that may enhance ROS elimination were identified in cetaceans. In silico analysis suggests that the core transcription factor repertoire of cetartiodactyl SOD genes may include Sp1, NF-κB, Nrf2 and AHR. Putative transcription factors binding sites responding to hypoxia were (e.g. Suppressor of Hairless; Su(H)) found in the cetacean SOD1 gene. We found significant evidence for positive selection in cetaceans using codon models. Cetaceans with different diving abilities also show divergent evolution of SOD1 and SOD2. Our genome-wide analysis of SOD genes helps clarify their relationship and evolutionary trajectory and identify putative functional changes in cetaceans.
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Affiliation(s)
- Ran Tian
- Integrative Biology Laboratory, College of Life Sciences, Nanjing Normal University, Nanjing, China.,Jiangsu Key Laboratory for Biodiversity and Biotechnology, College of Life Sciences, Nanjing Normal University, Nanjing, China
| | - Yuepan Geng
- Integrative Biology Laboratory, College of Life Sciences, Nanjing Normal University, Nanjing, China
| | - Han Guo
- Integrative Biology Laboratory, College of Life Sciences, Nanjing Normal University, Nanjing, China
| | - Chen Yang
- Integrative Biology Laboratory, College of Life Sciences, Nanjing Normal University, Nanjing, China
| | - Inge Seim
- Integrative Biology Laboratory, College of Life Sciences, Nanjing Normal University, Nanjing, China.,School of Biology and Environmental Science, Queensland University of Technology, Brisbane, QLD, Australia
| | - Guang Yang
- Jiangsu Key Laboratory for Biodiversity and Biotechnology, College of Life Sciences, Nanjing Normal University, Nanjing, China
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19
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Host Genome-Wide Association Study of Infant Susceptibility to Shigella-Associated Diarrhea. Infect Immun 2021; 89:IAI.00012-21. [PMID: 33649051 PMCID: PMC8316060 DOI: 10.1128/iai.00012-21] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Accepted: 02/22/2021] [Indexed: 12/15/2022] Open
Abstract
Shigella is a leading cause of moderate-to-severe diarrhea globally and the causative agent of shigellosis and bacillary dysentery. Associated with 80 to 165 million cases of diarrhea and >13% of diarrheal deaths, in many regions, Shigella exposure is ubiquitous while infection is heterogenous. To characterize host-genetic susceptibility to Shigella-associated diarrhea, we performed two independent genome-wide association studies (GWAS) including Bangladeshi infants from the PROVIDE and CBC birth cohorts in Dhaka, Bangladesh. Cases were infants with Shigella-associated diarrhea (n = 143) and controls were infants with no Shigella-associated diarrhea in the first 13 months of life (n = 446). Shigella-associated diarrhea was identified via quantitative PCR (qPCR) threshold cycle (CT ) distributions for the ipaH gene, carried by all four Shigella species and enteroinvasive Escherichia coli Host GWAS were performed under an additive genetic model. A joint analysis identified protective loci on chromosomes 11 (rs582240, within the KRT18P59 pseudogene; P = 6.40 × 10-8; odds ratio [OR], 0.43) and 8 (rs12550437, within the lincRNA RP11-115J16.1; P = 1.49 × 10-7; OR, 0.48). Conditional analyses identified two previously suggestive loci, a protective locus on chromosome 7 (rs10266841, within the 3' untranslated region [UTR] of CYTH3; P conditional = 1.48 × 10-7; OR, 0.44) and a risk-associated locus on chromosome 10 (rs2801847, an intronic variant within MPP7; P conditional = 8.37 × 10-8; OR, 5.51). These loci have all been indirectly linked to bacterial type 3 secretion system (T3SS) activity, its components, and bacterial effectors delivered into host cells. Host genetic factors that may affect bacterial T3SS activity and are associated with the host response to Shigella-associated diarrhea may provide insight into vaccine and drug development efforts for Shigella-associated diarrheal disease.
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20
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Mascagni F, Usai G, Cavallini A, Porceddu A. Structural characterization and duplication modes of pseudogenes in plants. Sci Rep 2021; 11:5292. [PMID: 33674668 PMCID: PMC7935947 DOI: 10.1038/s41598-021-84778-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2020] [Accepted: 02/19/2021] [Indexed: 11/24/2022] Open
Abstract
We identified and characterized the pseudogene complements of five plant species: four dicots (Arabidopsis thaliana, Vitis vinifera, Populus trichocarpa and Phaseolus vulgaris) and one monocot (Oryza sativa). Retroposition was considered of modest importance for pseudogene formation in all investigated species except V. vinifera, which showed an unusually high number of retro-pseudogenes in non coding genic regions. By using a pipeline for the classification of sequence duplicates in plant genomes, we compared the relative importance of whole genome, tandem, proximal, transposed and dispersed duplication modes in the pseudo and functional gene complements. Pseudogenes showed higher tendencies than functional genes to genomic dispersion. Dispersed pseudogenes were prevalently fragmented and showed high sequence divergence at flanking regions. On the contrary, those deriving from whole genome duplication were proportionally less than expected based on observations on functional loci and showed higher levels of flanking sequence conservation than dispersed pseudogenes. Pseudogenes deriving from tandem and proximal duplications were in excess compared to functional loci, probably reflecting the high evolutionary rate associated with these duplication modes in plant genomes. These data are compatible with high rates of sequence turnover at neutral sites and double strand break repairs mediated duplication mechanisms.
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Affiliation(s)
- Flavia Mascagni
- Department of Agricultural, Food, and Environment, University of Pisa, Via del Borghetto 80, 56124, Pisa, Italy
| | - Gabriele Usai
- Department of Agricultural, Food, and Environment, University of Pisa, Via del Borghetto 80, 56124, Pisa, Italy
| | - Andrea Cavallini
- Department of Agricultural, Food, and Environment, University of Pisa, Via del Borghetto 80, 56124, Pisa, Italy
| | - Andrea Porceddu
- Dipartimento di Agraria, Università degli studi di Sassari, Via Enrico de Nicola 1, 07100, Sassari, Italy.
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21
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Simoneau J, Gosselin R, Scott MS. Factorial study of the RNA-seq computational workflow identifies biases as technical gene signatures. NAR Genom Bioinform 2021; 2:lqaa043. [PMID: 33575596 PMCID: PMC7671328 DOI: 10.1093/nargab/lqaa043] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2020] [Revised: 05/15/2020] [Accepted: 06/05/2020] [Indexed: 12/12/2022] Open
Abstract
RNA-seq is a modular experimental and computational approach aiming in identifying and quantifying RNA molecules. The modularity of the RNA-seq technology enables adaptation of the protocol to develop new ways to explore RNA biology, but this modularity also brings forth the importance of methodological thoroughness. Liberty of approach comes with the responsibility of choices, and such choices must be informed. Here, we present an approach that identifies gene group-specific quantification biases in current RNA-seq software and references by processing datasets using diverse RNA-seq computational pipelines, and by decomposing these expression datasets with an independent component analysis matrix factorization method. By exploring the RNA-seq pipeline using this systemic approach, we identify genome annotations as a design choice that affects to the same extent quantification results as does the choice of aligners and quantifiers. We also show that the different choices in RNA-seq methodology are not independent, identifying interactions between genome annotations and quantification software. Genes were mainly affected by differences in their sequence, by overlapping genes and genes with similar sequence. Our approach offers an explanation for the observed biases by identifying the common features used differently by the software and references, therefore providing leads for the betterment of RNA-seq methodology.
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Affiliation(s)
- Joël Simoneau
- Department of Biochemistry and Functional Genomics, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Québec, J1K 2R1, Canada
| | - Ryan Gosselin
- Department of Chemical & Biotechnological Engineering, Faculty of Engineering, Université de Sherbrooke, Sherbrooke, Québec, J1K 2R1, Canada
| | - Michelle S Scott
- Department of Biochemistry and Functional Genomics, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, Québec, J1K 2R1, Canada
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22
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Abstract
Pseudogenes are commonly labeled as "junk DNA" given their perceived nonfunctional status. However, the advent of large-scale genomics projects prompted a revisit of pseudogene biology, highlighting their key functional and regulatory roles in numerous diseases, including cancers. Integrative analyses of cancer data have shown that pseudogenes can be transcribed and even translated, and that pseudogenic DNA, RNA, and proteins can interfere with the activity and function of key protein coding genes, acting as regulators of oncogenes and tumor suppressors. Capitalizing on the available clinical research, we are able to get an insight into the spread and variety of pseudogene biomarker and therapeutic potential. In this chapter, we describe pseudogenes that fulfill their role as diagnostic or prognostic biomarkers, both as unique elements and in collaboration with other genes or pseudogenes. We also report that the majority of prognostic pseudogenes are overexpressed and exert an oncogenic role in colorectal, liver, lung, and gastric cancers. Finally, we highlight a number of pseudogenes that can establish future therapeutic avenues.
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23
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Di Sanzo M, Quaresima B, Biamonte F, Palmieri C, Faniello MC. FTH1 Pseudogenes in Cancer and Cell Metabolism. Cells 2020; 9:E2554. [PMID: 33260500 PMCID: PMC7760355 DOI: 10.3390/cells9122554] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Revised: 11/24/2020] [Accepted: 11/24/2020] [Indexed: 12/15/2022] Open
Abstract
Ferritin, the principal intracellular iron-storage protein localized in the cytoplasm, nucleus, and mitochondria, plays a major role in iron metabolism. The encoding ferritin genes are members of a multigene family that includes some pseudogenes. Even though pseudogenes have been initially considered as relics of ancient genes or junk DNA devoid of function, their role in controlling gene expression in normal and transformed cells has recently been re-evaluated. Numerous studies have revealed that some pseudogenes compete with their parental gene for binding to the microRNAs (miRNAs), while others generate small interference RNAs (siRNAs) to decrease functional gene expression, and still others encode functional mutated proteins. Consequently, pseudogenes can be considered as actual master regulators of numerous biological processes. Here, we provide a detailed classification and description of the structural features of the ferritin pseudogenes known to date and review the recent evidence on their mutual interrelation within the complex regulatory network of the ferritin gene family.
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Affiliation(s)
- Maddalena Di Sanzo
- Department of Experimental and Clinical Medicine, “Magna Graecia” University of Catanzaro, 88100 Catanzaro, Italy; (M.D.S.); (B.Q.); (F.B.)
| | - Barbara Quaresima
- Department of Experimental and Clinical Medicine, “Magna Graecia” University of Catanzaro, 88100 Catanzaro, Italy; (M.D.S.); (B.Q.); (F.B.)
| | - Flavia Biamonte
- Department of Experimental and Clinical Medicine, “Magna Graecia” University of Catanzaro, 88100 Catanzaro, Italy; (M.D.S.); (B.Q.); (F.B.)
| | - Camillo Palmieri
- Department of Experimental and Clinical Medicine, “Magna Graecia” University of Catanzaro, 88100 Catanzaro, Italy; (M.D.S.); (B.Q.); (F.B.)
| | - Maria Concetta Faniello
- Department of Experimental and Clinical Medicine, “Magna Graecia” University of Catanzaro, 88100 Catanzaro, Italy; (M.D.S.); (B.Q.); (F.B.)
- Research Center of Biochemistry and Advanced Molecular Biology, Department of Experimental and Clinical Medicine, “Magna Graecia” University of Catanzaro, 88100 Catanzaro, Italy
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24
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Lau LY, Nguyen LT, Reverter A, Moore SS, Lynn A, McBride‐Kelly L, Phillips‐Rose L, Plath M, Macfarlane R, Vasudivan V, Morton L, Ardley R, Ye Y, Fortes MRS. Gene regulation could be attributed to TCF3 and other key transcription factors in the muscle of pubertal heifers. Vet Med Sci 2020; 6:695-710. [PMID: 32432381 PMCID: PMC7738712 DOI: 10.1002/vms3.278] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2019] [Revised: 03/13/2020] [Accepted: 04/09/2020] [Indexed: 01/17/2023] Open
Abstract
Puberty is a whole-body event, driven by the hypothalamic integration of peripheral signals such as leptin or IGF-1. In the process of puberty, reproductive development is simultaneous to growth, including muscle growth. To enhance our understanding of muscle function related to puberty, we performed transcriptome analyses of muscle samples from six pre- and six post-pubertal Brahman heifers (Bos indicus). Our aims were to perform differential expression analyses and co-expression analyses to derive a regulatory gene network associate with puberty. As a result, we identified 431 differentially expressed (DEx) transcripts (genes and non-coding RNAs) when comparing pre- to post-pubertal average gene expression. The DEx transcripts were compared with all expressed transcripts in our samples (over 14,000 transcripts) for functional enrichment analyses. The DEx transcripts were associated with "extracellular region," "inflammatory response" and "hormone activity" (adjusted p < .05). Inflammatory response for muscle regeneration is a necessary aspect of muscle growth, which is accelerated during puberty. The term "hormone activity" may signal genes that respond to progesterone signalling in the muscle, as the presence of this hormone is an important difference between pre- and post-pubertal heifers in our experimental design. The DEx transcript with the highest average expression difference was a mitochondrial gene, ENSBTAG00000043574 that might be another important link between energy metabolism and puberty. In the derived co-expression gene network, we identified six hub genes: CDC5L, MYC, TCF3, RUNX2, ATF2 and CREB1. In the same network, 48 key regulators of DEx transcripts were identified, using a regulatory impact factor metric. The hub gene TCF3 was also a key regulator. The majority of the key regulators (22 genes) are members of the zinc finger family, which has been implicated in bovine puberty in other tissues. In conclusion, we described how puberty may affect muscle gene expression in cattle.
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Affiliation(s)
- Li Yieng Lau
- School of Chemistry and Molecular BiologyThe University of QueenslandBrisbaneQLDAustralia
| | - Loan T. Nguyen
- Queensland Alliance for Agriculture and Food InnovationThe University of QueenslandBrisbaneQLDAustralia
| | - Antonio Reverter
- CSIRO Agriculture and FoodQueensland Biosciences PrecinctBrisbaneQLDAustralia
| | - Stephen S. Moore
- Queensland Alliance for Agriculture and Food InnovationThe University of QueenslandBrisbaneQLDAustralia
| | - Aaron Lynn
- School of Chemistry and Molecular BiologyThe University of QueenslandBrisbaneQLDAustralia
| | - Liam McBride‐Kelly
- School of Chemistry and Molecular BiologyThe University of QueenslandBrisbaneQLDAustralia
| | - Louis Phillips‐Rose
- School of Chemistry and Molecular BiologyThe University of QueenslandBrisbaneQLDAustralia
| | - Mackenzie Plath
- School of Chemistry and Molecular BiologyThe University of QueenslandBrisbaneQLDAustralia
| | - Rhys Macfarlane
- School of Chemistry and Molecular BiologyThe University of QueenslandBrisbaneQLDAustralia
| | - Vanisha Vasudivan
- School of Chemistry and Molecular BiologyThe University of QueenslandBrisbaneQLDAustralia
| | - Lachlan Morton
- School of Chemistry and Molecular BiologyThe University of QueenslandBrisbaneQLDAustralia
| | - Ryan Ardley
- School of Chemistry and Molecular BiologyThe University of QueenslandBrisbaneQLDAustralia
| | - Yunan Ye
- School of Chemistry and Molecular BiologyThe University of QueenslandBrisbaneQLDAustralia
| | - Marina R. S. Fortes
- School of Chemistry and Molecular BiologyThe University of QueenslandBrisbaneQLDAustralia
- Queensland Alliance for Agriculture and Food InnovationThe University of QueenslandBrisbaneQLDAustralia
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25
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Guo XL, Zheng HY, Price M, Zhou SD, He XJ. Phylogeny and Comparative Analysis of Chinese Chamaesium Species Revealed by the Complete Plastid Genome. PLANTS 2020; 9:plants9080965. [PMID: 32751647 PMCID: PMC7464574 DOI: 10.3390/plants9080965] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 07/27/2020] [Accepted: 07/28/2020] [Indexed: 12/20/2022]
Abstract
Chamaesium H. Wolff (Apiaceae, Apioideae) is a small genus mainly distributed in the Hengduan Mountains and the Himalayas. Ten species of Chamaesium have been described and nine species are distributed in China. Recent advances in molecular phylogenetics have revolutionized our understanding of Chinese Chamaesium taxonomy and evolution. However, an accurate phylogenetic relationship in Chamaesium based on the second-generation sequencing technology remains poorly understood. Here, we newly assembled nine plastid genomes from the nine Chinese Chamaesium species and combined these genomes with eight other species from five genera to perform a phylogenic analysis by maximum likelihood (ML) using the complete plastid genome and analyzed genome structure, GC content, species pairwise Ka/Ks ratios and the simple sequence repeat (SSR) component. We found that the nine species’ plastid genomes ranged from 152,703 bp (C. thalictrifolium) to 155,712 bp (C. mallaeanum), and contained 133 genes, 34 SSR types and 585 SSR loci. We also found 20,953–21,115 codons from 53 coding sequence (CDS) regions, 38.4–38.7% GC content of the total genome and low Ka/Ks (0.27–0.43) ratios of 53 aligned CDS. These results will facilitate our further understanding of the evolution of the genus Chamaesium.
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Affiliation(s)
- Xian-Lin Guo
- Key Laboratory of Bio-Resources and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu 610065, China; (X.-L.G.); (H.-Y.Z.)
| | - Hong-Yi Zheng
- Key Laboratory of Bio-Resources and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu 610065, China; (X.-L.G.); (H.-Y.Z.)
| | - Megan Price
- Sichuan Key Laboratory of Conservation Biology on Endangered Wildlife, College of Life Sciences, Sichuan University, Chengdu 610065, China;
| | - Song-Dong Zhou
- Key Laboratory of Bio-Resources and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu 610065, China; (X.-L.G.); (H.-Y.Z.)
- Correspondence: (S.-D.Z.); (X.-J.H.)
| | - Xing-Jin He
- Key Laboratory of Bio-Resources and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu 610065, China; (X.-L.G.); (H.-Y.Z.)
- Correspondence: (S.-D.Z.); (X.-J.H.)
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26
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Transcriptional activity and strain-specific history of mouse pseudogenes. Nat Commun 2020; 11:3695. [PMID: 32728065 PMCID: PMC7392758 DOI: 10.1038/s41467-020-17157-w] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2018] [Accepted: 06/08/2020] [Indexed: 01/07/2023] Open
Abstract
Pseudogenes are ideal markers of genome remodelling. In turn, the mouse is an ideal platform for studying them, particularly with the recent availability of strain-sequencing and transcriptional data. Here, combining both manual curation and automatic pipelines, we present a genome-wide annotation of the pseudogenes in the mouse reference genome and 18 inbred mouse strains (available via the mouse.pseudogene.org resource). We also annotate 165 unitary pseudogenes in mouse, and 303, in human. The overall pseudogene repertoire in mouse is similar to that in human in terms of size, biotype distribution, and family composition (e.g. with GAPDH and ribosomal proteins being the largest families). Notable differences arise in the pseudogene age distribution, with multiple retro-transpositional bursts in mouse evolutionary history and only one in human. Furthermore, in each strain about a fifth of all pseudogenes are unique, reflecting strain-specific evolution. Finally, we find that ~15% of the mouse pseudogenes are transcribed, and that highly transcribed parent genes tend to give rise to many processed pseudogenes.
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27
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Meuleman W, Muratov A, Rynes E, Halow J, Lee K, Bates D, Diegel M, Dunn D, Neri F, Teodosiadis A, Reynolds A, Haugen E, Nelson J, Johnson A, Frerker M, Buckley M, Sandstrom R, Vierstra J, Kaul R, Stamatoyannopoulos J. Index and biological spectrum of human DNase I hypersensitive sites. Nature 2020; 584:244-251. [PMID: 32728217 PMCID: PMC7422677 DOI: 10.1038/s41586-020-2559-3] [Citation(s) in RCA: 155] [Impact Index Per Article: 38.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2019] [Accepted: 07/01/2020] [Indexed: 01/08/2023]
Abstract
DNase I hypersensitive sites (DHSs) are generic markers of regulatory DNA1–5 and contain genetic variations associated with diseases and phenotypic traits6–8. We created high-resolution maps of DHSs from 733 human biosamples encompassing 438 cell and tissue types and states, and integrated these to delineate and numerically index approximately 3.6 million DHSs within the human genome sequence, providing a common coordinate system for regulatory DNA. Here we show that these maps highly resolve the cis-regulatory compartment of the human genome, which encodes unexpectedly diverse cell- and tissue-selective regulatory programs at very high density. These programs can be captured comprehensively by a simple vocabulary that enables the assignment to each DHS of a regulatory barcode that encapsulates its tissue manifestations, and global annotation of protein-coding and non-coding RNA genes in a manner orthogonal to gene expression. Finally, we show that sharply resolved DHSs markedly enhance the genetic association and heritability signals of diseases and traits. Rather than being confined to a small number of distal elements or promoters, we find that genetic signals converge on congruently regulated sets of DHSs that decorate entire gene bodies. Together, our results create a universal, extensible coordinate system and vocabulary for human regulatory DNA marked by DHSs, and provide a new global perspective on the architecture of human gene regulation. High-resolution maps of DNase I hypersensitive sites from 733 human biosamples are used to identify and index regulatory DNA within the human genome.
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Affiliation(s)
| | | | - Eric Rynes
- Altius Institute for Biomedical Sciences, Seattle, WA, USA
| | - Jessica Halow
- Altius Institute for Biomedical Sciences, Seattle, WA, USA
| | - Kristen Lee
- Altius Institute for Biomedical Sciences, Seattle, WA, USA
| | - Daniel Bates
- Altius Institute for Biomedical Sciences, Seattle, WA, USA
| | - Morgan Diegel
- Altius Institute for Biomedical Sciences, Seattle, WA, USA
| | - Douglas Dunn
- Altius Institute for Biomedical Sciences, Seattle, WA, USA
| | - Fidencio Neri
- Altius Institute for Biomedical Sciences, Seattle, WA, USA
| | | | - Alex Reynolds
- Altius Institute for Biomedical Sciences, Seattle, WA, USA
| | - Eric Haugen
- Altius Institute for Biomedical Sciences, Seattle, WA, USA
| | - Jemma Nelson
- Altius Institute for Biomedical Sciences, Seattle, WA, USA
| | - Audra Johnson
- Altius Institute for Biomedical Sciences, Seattle, WA, USA
| | - Mark Frerker
- Altius Institute for Biomedical Sciences, Seattle, WA, USA
| | | | | | - Jeff Vierstra
- Altius Institute for Biomedical Sciences, Seattle, WA, USA
| | - Rajinder Kaul
- Altius Institute for Biomedical Sciences, Seattle, WA, USA
| | - John Stamatoyannopoulos
- Altius Institute for Biomedical Sciences, Seattle, WA, USA. .,Department of Genome Sciences, University of Washington, Seattle, WA, USA. .,Division of Oncology, Department of Medicine, University of Washington, Seattle, WA, USA.
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28
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Shuffling type of biological evolution based on horizontal gene transfer and the biosphere gene pool hypothesis. Biosystems 2020; 193-194:104131. [DOI: 10.1016/j.biosystems.2020.104131] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Revised: 03/12/2020] [Accepted: 03/12/2020] [Indexed: 02/08/2023]
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29
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A bioinformatics workflow for the evaluation of RT-qPCR primer specificity: Application for the assessment of gene expression data reliability in toxicological studies. Regul Toxicol Pharmacol 2020; 111:104575. [PMID: 31945455 DOI: 10.1016/j.yrtph.2020.104575] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2019] [Accepted: 01/02/2020] [Indexed: 12/11/2022]
Abstract
The reliability of Reverse Transcription quantitative real-time PCR (RT-qPCR) gene expression data depends on proper primer design and RNA quality controls. Despite freely available genomic databases and bioinformatics tools, primer design deficiencies can be found across life science publications. In order to assess the prevalence of such deficiencies in the toxicological literature, 504 primer sets extracted from a random selection of 70 recent rat toxicological studies were evaluated. The specificity of each primer set was systematically analysed using a bioinformatics workflow developed from publicly available resources (NCBI Primer BLAST, in silico PCR in UCSC genome browser, Ensembl DNA database). Potential mismatches (9%), cross-matches (13.5%), co-amplification of multiple gene splice variants (9%) and sub-optimal amplicon sizes (25%) were identified for a significant proportion of the primer sets assessed in silico. Quality controls for gDNA contamination of RNA samples were infrequently reported in the surveyed manuscripts. Hence, the impacts of gDNA contamination on RT-qPCR data were further investigated, revealing that lowly expressed genes presented higher susceptibility to contaminating gDNA. In addition to the retrospective identification of potential primer design issues presented in this study, the described bioinformatics workflow can also be used prospectively to select candidate primer sets for experimental validation.
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30
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Johnson TS, Li S, Franz E, Huang Z, Dan Li S, Campbell MJ, Huang K, Zhang Y. PseudoFuN: Deriving functional potentials of pseudogenes from integrative relationships with genes and microRNAs across 32 cancers. Gigascience 2019; 8:5480571. [PMID: 31029062 PMCID: PMC6486473 DOI: 10.1093/gigascience/giz046] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2018] [Revised: 12/13/2018] [Accepted: 03/29/2019] [Indexed: 12/14/2022] Open
Abstract
Background Long thought “relics” of evolution, not until recently have pseudogenes been of medical interest regarding regulation in cancer. Often, these regulatory roles are a direct by-product of their close sequence homology to protein-coding genes. Novel pseudogene-gene (PGG) functional associations can be identified through the integration of biomedical data, such as sequence homology, functional pathways, gene expression, pseudogene expression, and microRNA expression. However, not all of the information has been integrated, and almost all previous pseudogene studies relied on 1:1 pseudogene–parent gene relationships without leveraging other homologous genes/pseudogenes. Results We produce PGG families that expand beyond the current 1:1 paradigm. First, we construct expansive PGG databases by (i) CUDAlign graphics processing unit (GPU) accelerated local alignment of all pseudogenes to gene families (totaling 1.6 billion individual local alignments and >40,000 GPU hours) and (ii) BLAST-based assignment of pseudogenes to gene families. Second, we create an open-source web application (PseudoFuN [Pseudogene Functional Networks]) to search for integrative functional relationships of sequence homology, microRNA expression, gene expression, pseudogene expression, and gene ontology. We produce four “flavors” of CUDAlign-based databases (>462,000,000 PGG pairwise alignments and 133,770 PGG families) that can be queried and downloaded using PseudoFuN. These databases are consistent with previous 1:1 PGG annotation and also are much more powerful including millions of de novo PGG associations. For example, we find multiple known (e.g., miR-20a-PTEN-PTENP1) and novel (e.g., miR-375-SOX15-PPP4R1L) microRNA-gene-pseudogene associations in prostate cancer. PseudoFuN provides a “one stop shop” for identifying and visualizing thousands of potential regulatory relationships related to pseudogenes in The Cancer Genome Atlas cancers. Conclusions Thousands of new PGG associations can be explored in the context of microRNA-gene-pseudogene co-expression and differential expression with a simple-to-use online tool by bioinformaticians and oncologists alike.
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Affiliation(s)
- Travis S Johnson
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, 1800 Cannon Drive, Columbus, OH 43210, USA.,Department of Medicine, Indiana University School of Medicine, 545 Barnhill Drive, Indianapolis, IN 46202, USA
| | - Sihong Li
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, 1800 Cannon Drive, Columbus, OH 43210, USA
| | - Eric Franz
- Ohio Supercomputer Center, 1224 Kinnear Road, Columbus, OH 43212, USA
| | - Zhi Huang
- School of Electrical and Computer Engineering, Purdue University, 465 Northwestern Avenue, West Lafayette, IN 47907, USA.,Department of Medicine, Indiana University School of Medicine, 545 Barnhill Drive, Indianapolis, IN 46202, USA
| | - Shuyu Dan Li
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
| | - Moray J Campbell
- Division of Pharmaceutics and Pharmaceutical Chemistry, College of Pharmacy, The Ohio State University, 500 West 12 th Avenue, Columbus, OH 43210, USA
| | - Kun Huang
- Department of Medicine, Indiana University School of Medicine, 545 Barnhill Drive, Indianapolis, IN 46202, USA.,Regenstrief Institute, Indiana University, 1101 West 10 th Street, Indianapolis, IN 46262, USA
| | - Yan Zhang
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, 1800 Cannon Drive, Columbus, OH 43210, USA.,The Ohio State University Comprehensive Cancer Center (OSUCCC - James), 460 West 10 th Avenue, Columbus, OH 43210, USA
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31
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Overcoming challenges and dogmas to understand the functions of pseudogenes. Nat Rev Genet 2019; 21:191-201. [DOI: 10.1038/s41576-019-0196-1] [Citation(s) in RCA: 92] [Impact Index Per Article: 18.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/05/2019] [Indexed: 01/08/2023]
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Mudge JM, Jungreis I, Hunt T, Gonzalez JM, Wright JC, Kay M, Davidson C, Fitzgerald S, Seal R, Tweedie S, He L, Waterhouse RM, Li Y, Bruford E, Choudhary JS, Frankish A, Kellis M. Discovery of high-confidence human protein-coding genes and exons by whole-genome PhyloCSF helps elucidate 118 GWAS loci. Genome Res 2019; 29:2073-2087. [PMID: 31537640 PMCID: PMC6886504 DOI: 10.1101/gr.246462.118] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2018] [Accepted: 09/09/2019] [Indexed: 12/15/2022]
Abstract
The most widely appreciated role of DNA is to encode protein, yet the exact portion of the human genome that is translated remains to be ascertained. We previously developed PhyloCSF, a widely used tool to identify evolutionary signatures of protein-coding regions using multispecies genome alignments. Here, we present the first whole-genome PhyloCSF prediction tracks for human, mouse, chicken, fly, worm, and mosquito. We develop a workflow that uses machine learning to predict novel conserved protein-coding regions and efficiently guide their manual curation. We analyze more than 1000 high-scoring human PhyloCSF regions and confidently add 144 conserved protein-coding genes to the GENCODE gene set, as well as additional coding regions within 236 previously annotated protein-coding genes, and 169 pseudogenes, most of them disabled after primates diverged. The majority of these represent new discoveries, including 70 previously undetected protein-coding genes. The novel coding genes are additionally supported by single-nucleotide variant evidence indicative of continued purifying selection in the human lineage, coding-exon splicing evidence from new GENCODE transcripts using next-generation transcriptomic data sets, and mass spectrometry evidence of translation for several new genes. Our discoveries required simultaneous comparative annotation of other vertebrate genomes, which we show is essential to remove spurious ORFs and to distinguish coding from pseudogene regions. Our new coding regions help elucidate disease-associated regions by revealing that 118 GWAS variants previously thought to be noncoding are in fact protein altering. Altogether, our PhyloCSF data sets and algorithms will help researchers seeking to interpret these genomes, while our new annotations present exciting loci for further experimental characterization.
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Affiliation(s)
- Jonathan M Mudge
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Irwin Jungreis
- MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, Massachusetts 02139, USA.,Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
| | - Toby Hunt
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Jose Manuel Gonzalez
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - James C Wright
- Functional Proteomics, Division of Cancer Biology, Institute of Cancer Research, London SW7 3RP, United Kingdom
| | - Mike Kay
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Claire Davidson
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Stephen Fitzgerald
- Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, United Kingdom
| | - Ruth Seal
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom.,Department of Haematology, University of Cambridge, Cambridge CB2 0PT, United Kingdom
| | - Susan Tweedie
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Liang He
- MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, Massachusetts 02139, USA.,Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
| | - Robert M Waterhouse
- Department of Ecology and Evolution, University of Lausanne, Lausanne 1015, Switzerland.,Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
| | - Yue Li
- MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, Massachusetts 02139, USA.,Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
| | - Elspeth Bruford
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom.,Department of Haematology, University of Cambridge, Cambridge CB2 0PT, United Kingdom
| | - Jyoti S Choudhary
- Functional Proteomics, Division of Cancer Biology, Institute of Cancer Research, London SW7 3RP, United Kingdom
| | - Adam Frankish
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Manolis Kellis
- MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, Massachusetts 02139, USA.,Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
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Kim CY, Na K, Park S, Jeong SK, Cho JY, Shin H, Lee MJ, Han G, Paik YK. FusionPro, a Versatile Proteogenomic Tool for Identification of Novel Fusion Transcripts and Their Potential Translation Products in Cancer Cells. Mol Cell Proteomics 2019; 18:1651-1668. [PMID: 31208993 PMCID: PMC6683003 DOI: 10.1074/mcp.ra119.001456] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2019] [Revised: 05/23/2019] [Indexed: 01/21/2023] Open
Abstract
Fusion proteoforms are translation products derived from gene fusion. Although very rare, the fusion proteoforms play important roles in biomedical science. For example, fusion proteoforms influence the development of tumors by serving as cancer markers or cell cycle regulators. Although numerous studies have reported bioinformatics tools that can predict fusion transcripts, few proteogenomic tools are available that can predict and identify proteoforms. In this study, we develop a versatile proteogenomic tool "FusionPro," which facilitates the identification of fusion transcripts and their potential translatable peptides. FusionPro provides an independent gene fusion prediction module and can build sequence databases for annotated fusion proteoforms. FusionPro shows greater sensitivity than the available fusion finders when analyzing simulated or real RNA sequencing data sets. We use FusionPro to identify 18 fusion junction peptides and three potential fusion-derived peptides by MS/MS-based analysis of leukemia cell lines (Jurkat and K562) and ovarian cancer tissues from the Clinical Proteomic Tumor Analysis Consortium. Among the identified fusion proteins, we molecularly validate two fusion junction isoforms and a translation product of FAM133B:CDK6. Moreover, sequence analysis suggests that the fusion protein participates in the cell cycle progression. In addition, our prediction results indicate that fusion transcripts often have multiple fusion junctions and that these fusion junctions tend to be distributed in a nonrandom pattern at both the chromosome and gene levels. Thus, FusionPro allows users to detect various types of fusion translation products using a transcriptome-informed approach and to gain a comprehensive understanding of the formation and biological roles of fusion proteoforms.
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Affiliation(s)
- Chae-Yeon Kim
- ‡Interdisciplinary Program of Integrated OMICS for Biomedical Science, The Graduate School, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea; §Yonsei Proteome Research Center, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea
| | - Keun Na
- §Yonsei Proteome Research Center, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea
| | - Saeram Park
- §Yonsei Proteome Research Center, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea
| | - Seul-Ki Jeong
- §Yonsei Proteome Research Center, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea
| | - Jin-Young Cho
- §Yonsei Proteome Research Center, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea
| | - Heon Shin
- §Yonsei Proteome Research Center, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea
| | - Min Jung Lee
- §Yonsei Proteome Research Center, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea
| | - Gyoonhee Han
- ¶Department of Pharmacy, College of Pharmacy, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea
| | - Young-Ki Paik
- §Yonsei Proteome Research Center, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea.
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Gebert D, Zischler H, Rosenkranz D. Primate piRNA Cluster Evolution Suggests Limited Relevance of Pseudogenes in piRNA-Mediated Gene Regulation. Genome Biol Evol 2019; 11:1088-1104. [PMID: 30888404 PMCID: PMC6461890 DOI: 10.1093/gbe/evz060] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/16/2019] [Indexed: 12/11/2022] Open
Abstract
PIWI proteins and their guiding Piwi-interacting (pi-) RNAs direct the silencing of target nucleic acids in the animal germline and soma. Although in mammal testes fetal piRNAs are involved in extensive silencing of transposons, pachytene piRNAs have additionally been shown to act in post-transcriptional gene regulation. The bulk of pachytene piRNAs is produced from large genomic loci, named piRNA clusters. Recently, the presence of reversed pseudogenes within piRNA clusters prompted the idea that piRNAs derived from such sequences might direct regulation of their parent genes. Here, we examine primate piRNA clusters and integrated pseudogenes in a comparative approach to gain a deeper understanding about mammalian piRNA cluster evolution and the presumed gene-regulatory role of pseudogene-derived piRNAs. Initially, we provide a broad analysis of the evolutionary relationships of piRNA clusters and their differential activity among six primate species. Subsequently, we show that pseudogenes in reserve orientation relative to piRNA cluster transcription direction generally do not exhibit signs of selection pressure and cause weakly conserved targeting of homologous genes among species, suggesting a lack of functional constraints and thus only a minor significance for gene regulation in most cases. Finally, we report that piRNA-producing loci generally tend to be located in active genomic regions with elevated gene and pseudogene density. Thus, we conclude that the presence of most pseudogenes in piRNA clusters might be regarded as a byproduct of piRNA cluster generation, whereas this does not exclude that some pseudogenes nevertheless play critical roles in individual cases.
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Affiliation(s)
- Daniel Gebert
- Institute of Organismic and Molecular Evolution, Anthropology, Johannes Gutenberg University, Mainz, Germany
| | - Hans Zischler
- Institute of Organismic and Molecular Evolution, Anthropology, Johannes Gutenberg University, Mainz, Germany
| | - David Rosenkranz
- Institute of Organismic and Molecular Evolution, Anthropology, Johannes Gutenberg University, Mainz, Germany
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35
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Xie J, Li Y, Liu X, Zhao Y, Li B, Ingvarsson PK, Zhang D. Evolutionary Origins of Pseudogenes and Their Association with Regulatory Sequences in Plants. THE PLANT CELL 2019; 31:563-578. [PMID: 30760562 PMCID: PMC6482637 DOI: 10.1105/tpc.18.00601] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2018] [Revised: 12/03/2018] [Accepted: 02/12/2019] [Indexed: 05/06/2023]
Abstract
Pseudogenes (Ψs), nonfunctional relatives of functional genes, form by duplication or retrotransposition, and loss of gene function by disabling mutations. Evolutionary analysis provides clues to Ψ origins and effects on gene regulation. However, few systematic studies of plant Ψs have been conducted, hampering comparative analyses. Here, we examined the origin, evolution, and expression patterns of Ψs and their relationships with noncoding sequences in seven angiosperm plants. We identified ∼250,000 Ψs, most of which are more lineage specific than protein-coding genes. The distribution of Ψs on the chromosome indicates that genome recombination may contribute to Ψ elimination. Most Ψs evolve rapidly in terms of sequence and expression levels, showing tissue- or stage-specific expression patterns. We found that a surprisingly large fraction of nontransposable element regulatory noncoding RNAs (microRNAs and long noncoding RNAs) originate from transcription of Ψ proximal upstream regions. We also found that transcription factor binding sites preferentially occur in putative Ψ proximal upstream regions compared with random intergenic regions, suggesting that Ψs have conditioned genome evolution by providing transcription factor binding sites that serve as promoters and enhancers. We therefore propose that rapid rewiring of Ψ transcriptional regulatory regions is a major mechanism driving the origin of novel regulatory modules.
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Affiliation(s)
- Jianbo Xie
- Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, No. 35, Qinghua East Road, Beijing 100083, People's Republic of China
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing 100083, People's Republic of China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing 100083, People's Republic of China
| | - Ying Li
- Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, No. 35, Qinghua East Road, Beijing 100083, People's Republic of China
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing 100083, People's Republic of China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing 100083, People's Republic of China
| | - Xiaomin Liu
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing 100083, People's Republic of China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing 100083, People's Republic of China
| | - Yiyang Zhao
- Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, No. 35, Qinghua East Road, Beijing 100083, People's Republic of China
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing 100083, People's Republic of China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing 100083, People's Republic of China
| | - Bailian Li
- Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, No. 35, Qinghua East Road, Beijing 100083, People's Republic of China
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing 100083, People's Republic of China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing 100083, People's Republic of China
- Department of Forestry, North Carolina State University, Raleigh, North Carolina 27695-8203
| | - Pär K Ingvarsson
- Linnean Center for Plant Biology, Department of Plant Biology, Swedish University of Agricultural Sciences, Box 7080, SE-750 07 Uppsala, Sweden
| | - Deqiang Zhang
- Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, No. 35, Qinghua East Road, Beijing 100083, People's Republic of China
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing 100083, People's Republic of China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing 100083, People's Republic of China
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36
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Krasnov GS, Kudryavtseva AV, Snezhkina AV, Lakunina VA, Beniaminov AD, Melnikova NV, Dmitriev AA. Pan-Cancer Analysis of TCGA Data Revealed Promising Reference Genes for qPCR Normalization. Front Genet 2019; 10:97. [PMID: 30881377 PMCID: PMC6406071 DOI: 10.3389/fgene.2019.00097] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2018] [Accepted: 01/29/2019] [Indexed: 11/20/2022] Open
Abstract
Quantitative PCR (qPCR) remains the most widely used technique for gene expression evaluation. Obtaining reliable data using this method requires reference genes (RGs) with stable mRNA level under experimental conditions. This issue is especially crucial in cancer studies because each tumor has a unique molecular portrait. The Cancer Genome Atlas (TCGA) project provides RNA-Seq data for thousands of samples corresponding to dozens of cancers and presents the basis for assessment of the suitability of genes as reference ones for qPCR data normalization. Using TCGA RNA-Seq data and previously developed CrossHub tool, we evaluated mRNA level of 32 traditionally used RGs in 12 cancer types, including those of lung, breast, prostate, kidney, and colon. We developed an 11-component scoring system for the assessment of gene expression stability. Among the 32 genes, PUM1 was one of the most stably expressed in the majority of examined cancers, whereas GAPDH, which is widely used as a RG, showed significant mRNA level alterations in more than a half of cases. For each of 12 cancer types, we suggested a pair of genes that are the most suitable for use as reference ones. These genes are characterized by high expression stability and absence of correlation between their mRNA levels. Next, the scoring system was expanded with several features of a gene: mutation rate, number of transcript isoforms and pseudogenes, participation in cancer-related processes on the basis of Gene Ontology, and mentions in PubMed-indexed articles. All the genes covered by RNA-Seq data in TCGA were analyzed using the expanded scoring system that allowed us to reveal novel promising RGs for each examined cancer type and identify several "universal" pan-cancer RG candidates, including SF3A1, CIAO1, and SFRS4. The choice of RGs is the basis for precise gene expression evaluation by qPCR. Here, we suggested optimal pairs of traditionally used RGs for 12 cancer types and identified novel promising RGs that demonstrate high expression stability and other features of reliable and convenient RGs (high expression level, low mutation rate, non-involvement in cancer-related processes, single transcript isoform, and absence of pseudogenes).
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Affiliation(s)
- George S. Krasnov
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Russia
| | | | | | | | | | | | - Alexey A. Dmitriev
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Russia
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37
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Nagasawa T, Kawaguchi M, Yano T, Isoyama S, Yasumasu S, Okabe M. Translocation of promoter-conserved hatching enzyme genes with intron-loss provides a new insight in the role of retrocopy during teleostean evolution. Sci Rep 2019; 9:2448. [PMID: 30792427 PMCID: PMC6385490 DOI: 10.1038/s41598-019-38693-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2018] [Accepted: 12/17/2018] [Indexed: 11/12/2022] Open
Abstract
The hatcing enzyme gene (HE) encodes a protease that is indispensable for the hatching process and is conserved during vertebrate evolution. During teleostean evolution, it is known that HE experienced a drastic transfiguration of gene structure, namely, losing all of its introns. However, these facts are contradiction with each other, since intron-less genes typically lose their original promoter because of duplication via mature mRNA, called retrocopy. Here, using a comparative genomic assay, we showed that HEs have changed their genomic location several times, with the evolutionary timings of these translocations being identical to those of intron-loss. We further showed that HEs maintain the promoter sequence upstream of them after translocation. Therefore, teleostean HEs are unique genes which have changed intra- (exon-intron) and extra-genomic structure (genomic loci) several times, although their indispensability for the reproductive process of hatching implies that HE genes are translocated by retrocopy with their promoter sequence.
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Affiliation(s)
- Tatsuki Nagasawa
- Department of Anatomy, The Jikei University School of Medicine, 3-25-8 Nishishimbashi, Minato-ku, Tokyo, 105-8461, Japan.,Research Fellow of the Japan Society for the Promotion of Science (JSPS), Tokyo, 102-0083, Japan.,Department of Materials and Life Sciences, Faculty of Science and Technology, Sophia University, 7-1 Kioi-cho, Chiyoda-ku, Tokyo, 102-8554, Japan
| | - Mari Kawaguchi
- Department of Materials and Life Sciences, Faculty of Science and Technology, Sophia University, 7-1 Kioi-cho, Chiyoda-ku, Tokyo, 102-8554, Japan
| | - Tohru Yano
- Department of Anatomy, The Jikei University School of Medicine, 3-25-8 Nishishimbashi, Minato-ku, Tokyo, 105-8461, Japan
| | - Sho Isoyama
- Department of Materials and Life Sciences, Faculty of Science and Technology, Sophia University, 7-1 Kioi-cho, Chiyoda-ku, Tokyo, 102-8554, Japan
| | - Shigeki Yasumasu
- Department of Materials and Life Sciences, Faculty of Science and Technology, Sophia University, 7-1 Kioi-cho, Chiyoda-ku, Tokyo, 102-8554, Japan.
| | - Masataka Okabe
- Department of Anatomy, The Jikei University School of Medicine, 3-25-8 Nishishimbashi, Minato-ku, Tokyo, 105-8461, Japan
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38
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Xie J, Chen S, Xu W, Zhao Y, Zhang D. Origination and Function of Plant Pseudogenes. PLANT SIGNALING & BEHAVIOR 2019; 14:1625698. [PMID: 31161861 PMCID: PMC6619919 DOI: 10.1080/15592324.2019.1625698] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/07/2023]
Abstract
Pseudogenes, nonfunctional genomic sequences derived from functional protein-coding genes, form by duplication or retrotransposition, and loss of gene function by disabling mutations. Studies on the evolution and functional aspects of plant pseudogenes are limited, despite their abundance in the plant genome. To date, most researches on pseudogenes focus on mammals. Here, we summarized current knowledge on pseudogenes including the historical and recent progress, analyzes their essential roles in gene regulation in hope of further stimulating researches in plant species for understanding gene regulation and evolution.
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Affiliation(s)
- Jianbo Xie
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
| | - Sisi Chen
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
| | - Weijie Xu
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
| | - Yiyang Zhao
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
| | - Deqiang Zhang
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- CONTACT Deqiang Zhang National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing 100083, P. R. China
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39
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Silar P, Dauget JM, Gautier V, Grognet P, Chablat M, Hermann-Le Denmat S, Couloux A, Wincker P, Debuchy R. A gene graveyard in the genome of the fungus Podospora comata. Mol Genet Genomics 2018; 294:177-190. [PMID: 30288581 DOI: 10.1007/s00438-018-1497-3] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2018] [Accepted: 09/28/2018] [Indexed: 02/07/2023]
Abstract
Mechanisms involved in fine adaptation of fungi to their environment include differential gene regulation associated with single nucleotide polymorphisms and indels (including transposons), horizontal gene transfer, gene copy amplification, as well as pseudogenization and gene loss. The two Podospora genome sequences examined here emphasize the role of pseudogenization and gene loss, which have rarely been documented in fungi. Podospora comata is a species closely related to Podospora anserina, a fungus used as model in several laboratories. Comparison of the genome of P. comata with that of P. anserina, whose genome is available for over 10 years, should yield interesting data related to the modalities of genome evolution between these two closely related fungal species that thrive in the same types of biotopes, i.e., herbivore dung. Here, we present the genome sequence of the mat + isolate of the P. comata reference strain T. Comparison with the genome of the mat + isolate of P. anserina strain S confirms that P. anserina and P. comata are likely two different species that rarely interbreed in nature. Despite having a 94-99% of nucleotide identity in the syntenic regions of their genomes, the two species differ by nearly 10% of their gene contents. Comparison of the species-specific gene sets uncovered genes that could be responsible for the known physiological differences between the two species. Finally, we identified 428 and 811 pseudogenes (3.8 and 7.2% of the genes) in P. anserina and P. comata, respectively. Presence of high numbers of pseudogenes supports the notion that difference in gene contents is due to gene loss rather than horizontal gene transfers. We propose that the high frequency of pseudogenization leading to gene loss in P. anserina and P. comata accompanies specialization of these two fungi. Gene loss may be more prevalent during the evolution of other fungi than usually thought.
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Affiliation(s)
- Philippe Silar
- Univ Paris Diderot, Sorbonne Paris Cité, Laboratoire Interdisciplinaire des Energies de Demain, 75205, Paris Cedex 13, France.
| | - Jean-Marc Dauget
- Univ Paris Diderot, Sorbonne Paris Cité, Laboratoire Interdisciplinaire des Energies de Demain, 75205, Paris Cedex 13, France
| | - Valérie Gautier
- Univ Paris Diderot, Sorbonne Paris Cité, Laboratoire Interdisciplinaire des Energies de Demain, 75205, Paris Cedex 13, France
| | - Pierre Grognet
- Institute for Integrative Biology of the Cell (I2BC), CEA, CNRS, Univ. Paris-Sud, Université Paris-Saclay, 91198, Gif-sur-Yvette cedex, France
| | - Michelle Chablat
- Institute for Integrative Biology of the Cell (I2BC), CEA, CNRS, Univ. Paris-Sud, Université Paris-Saclay, 91198, Gif-sur-Yvette cedex, France
| | - Sylvie Hermann-Le Denmat
- Institute for Integrative Biology of the Cell (I2BC), CEA, CNRS, Univ. Paris-Sud, Université Paris-Saclay, 91198, Gif-sur-Yvette cedex, France.,Ecole Normale Supérieure, 75005, Paris, France
| | - Arnaud Couloux
- CEA, Genoscope, Institut de biologie François Jacob, CP 5706, Evry, France
| | - Patrick Wincker
- CEA, Genoscope, Institut de biologie François Jacob, CP 5706, Evry, France.,CNRS UMR 8030, Evry, France.,Univ. Evry, Université Paris-Saclay, Evry, France
| | - Robert Debuchy
- Institute for Integrative Biology of the Cell (I2BC), CEA, CNRS, Univ. Paris-Sud, Université Paris-Saclay, 91198, Gif-sur-Yvette cedex, France.
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40
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Lokits AD, Indrischek H, Meiler J, Hamm HE, Stadler PF. Tracing the evolution of the heterotrimeric G protein α subunit in Metazoa. BMC Evol Biol 2018; 18:51. [PMID: 29642851 PMCID: PMC5896119 DOI: 10.1186/s12862-018-1147-8] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2017] [Accepted: 03/06/2018] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND Heterotrimeric G proteins are fundamental signaling proteins composed of three subunits, Gα and a Gβγ dimer. The role of Gα as a molecular switch is critical for transmitting and amplifying intracellular signaling cascades initiated by an activated G protein Coupled Receptor (GPCR). Despite their biochemical and therapeutic importance, the study of G protein evolution has been limited to the scope of a few model organisms. Furthermore, of the five primary Gα subfamilies, the underlying gene structure of only two families has been thoroughly investigated outside of Mammalia evolution. Therefore our understanding of Gα emergence and evolution across phylogeny remains incomplete. RESULTS We have computationally identified the presence and absence of every Gα gene (GNA-) across all major branches of Deuterostomia and evaluated the conservation of the underlying exon-intron structures across these phylogenetic groups. We provide evidence of mutually exclusive exon inclusion through alternative splicing in specific lineages. Variations of splice site conservation and isoforms were found for several paralogs which coincide with conserved, putative motifs of DNA-/RNA-binding proteins. In addition to our curated gene annotations, within Primates, we identified 15 retrotranspositions, many of which have undergone pseudogenization. Most importantly, we find numerous deviations from previous findings regarding the presence and absence of individual GNA- genes, nuanced differences in phyla-specific gene copy numbers, novel paralog duplications and subsequent intron gain and loss events. CONCLUSIONS Our curated annotations allow us to draw more accurate inferences regarding the emergence of all Gα family members across Metazoa and to present a new, updated theory of Gα evolution. Leveraging this, our results are critical for gaining new insights into the co-evolution of the Gα subunit and its many protein binding partners, especially therapeutically relevant G protein - GPCR signaling pathways which radiated in Vertebrata evolution.
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Affiliation(s)
- A. D. Lokits
- 0000 0001 2264 7217grid.152326.1Neuroscience Program, Vanderbilt University, Nashville, TN USA ,0000 0001 2264 7217grid.152326.1Center for Structural Biology, Vanderbilt University, Nashville, TN USA
| | - H. Indrischek
- 0000 0001 2230 9752grid.9647.cBioinformatics Group, Department of Computer Science, Leipzig University, Leipzig, Germany ,0000 0001 2230 9752grid.9647.cComputational EvoDevo Group, Bioinformatics Department, Leipzig University, Leipzig, Germany
| | - J. Meiler
- 0000 0001 2264 7217grid.152326.1Center for Structural Biology, Vanderbilt University, Nashville, TN USA ,0000 0001 2264 7217grid.152326.1Chemistry Department, Vanderbilt University, Nashville, TN USA
| | - H. E. Hamm
- 0000 0004 1936 9916grid.412807.8Pharmacology Department, Vanderbilt University Medical Center, Nashville, TN USA
| | - P. F. Stadler
- 0000 0001 2230 9752grid.9647.cBioinformatics Group, Department of Computer Science, Leipzig University, Leipzig, Germany ,0000 0001 0674 042Xgrid.5254.6Center for non-coding RNA in Technology and Health, University of Copenhagen, Frederiksberg C, Denmark ,0000 0001 2286 1424grid.10420.37Institute for Theoretical Chemistry, University of Vienna, Wien, Austria ,0000 0001 2230 9752grid.9647.cIZBI-Interdisciplinary Center for Bioinformatics and LIFE-Leipzig Research Center for Civilization Diseases and Competence Center for Scalable Data Services and Solutions, University Leipzig, Leipzig, Germany ,grid.419532.8Max Planck Institute for Mathematics in the Sciences, Leipzig, Germany ,0000 0001 1941 1940grid.209665.eSanta Fe Institute, Santa Fe, NM USA
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Thybert D, Roller M, Navarro FCP, Fiddes I, Streeter I, Feig C, Martin-Galvez D, Kolmogorov M, Janoušek V, Akanni W, Aken B, Aldridge S, Chakrapani V, Chow W, Clarke L, Cummins C, Doran A, Dunn M, Goodstadt L, Howe K, Howell M, Josselin AA, Karn RC, Laukaitis CM, Jingtao L, Martin F, Muffato M, Nachtweide S, Quail MA, Sisu C, Stanke M, Stefflova K, Van Oosterhout C, Veyrunes F, Ward B, Yang F, Yazdanifar G, Zadissa A, Adams DJ, Brazma A, Gerstein M, Paten B, Pham S, Keane TM, Odom DT, Flicek P. Repeat associated mechanisms of genome evolution and function revealed by the Mus caroli and Mus pahari genomes. Genome Res 2018; 28:448-459. [PMID: 29563166 PMCID: PMC5880236 DOI: 10.1101/gr.234096.117] [Citation(s) in RCA: 75] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2017] [Accepted: 03/05/2018] [Indexed: 12/31/2022]
Abstract
Understanding the mechanisms driving lineage-specific evolution in both primates and rodents has been hindered by the lack of sister clades with a similar phylogenetic structure having high-quality genome assemblies. Here, we have created chromosome-level assemblies of the Mus caroli and Mus pahari genomes. Together with the Mus musculus and Rattus norvegicus genomes, this set of rodent genomes is similar in divergence times to the Hominidae (human-chimpanzee-gorilla-orangutan). By comparing the evolutionary dynamics between the Muridae and Hominidae, we identified punctate events of chromosome reshuffling that shaped the ancestral karyotype of Mus musculus and Mus caroli between 3 and 6 million yr ago, but that are absent in the Hominidae. Hominidae show between four- and sevenfold lower rates of nucleotide change and feature turnover in both neutral and functional sequences, suggesting an underlying coherence to the Muridae acceleration. Our system of matched, high-quality genome assemblies revealed how specific classes of repeats can play lineage-specific roles in related species. Recent LINE activity has remodeled protein-coding loci to a greater extent across the Muridae than the Hominidae, with functional consequences at the species level such as reproductive isolation. Furthermore, we charted a Muridae-specific retrotransposon expansion at unprecedented resolution, revealing how a single nucleotide mutation transformed a specific SINE element into an active CTCF binding site carrier specifically in Mus caroli, which resulted in thousands of novel, species-specific CTCF binding sites. Our results show that the comparison of matched phylogenetic sets of genomes will be an increasingly powerful strategy for understanding mammalian biology.
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Affiliation(s)
- David Thybert
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
- Earlham Institute, Norwich Research Park, Norwich NR4 7UH, United Kingdom
| | - Maša Roller
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Fábio C P Navarro
- Yale University Medical School, Computational Biology and Bioinformatics Program, New Haven, Connecticut 06520, USA
| | - Ian Fiddes
- Department of Biomolecular Engineering, University of California, Santa Cruz, California 95064, USA
| | - Ian Streeter
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Christine Feig
- University of Cambridge, Cancer Research UK Cambridge Institute, Robinson Way, Cambridge CB2 0RE, United Kingdom
| | - David Martin-Galvez
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Mikhail Kolmogorov
- Department of Computer Science and Engineering, University of California, San Diego, La Jolla, California 92092, USA
| | - Václav Janoušek
- Department of Zoology, Faculty of Science, Charles University in Prague, 128 44 Prague, Czech Republic
| | - Wasiu Akanni
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Bronwen Aken
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Sarah Aldridge
- University of Cambridge, Cancer Research UK Cambridge Institute, Robinson Way, Cambridge CB2 0RE, United Kingdom
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SA, United Kingdom
| | - Varshith Chakrapani
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - William Chow
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SA, United Kingdom
| | - Laura Clarke
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Carla Cummins
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Anthony Doran
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SA, United Kingdom
| | - Matthew Dunn
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SA, United Kingdom
| | - Leo Goodstadt
- Wellcome Trust Centre for Human Genetics, Oxford OX3 7BN, United Kingdom
| | - Kerstin Howe
- Yale University Medical School, Computational Biology and Bioinformatics Program, New Haven, Connecticut 06520, USA
| | - Matthew Howell
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Ambre-Aurore Josselin
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Robert C Karn
- Department of Medicine, College of Medicine, University of Arizona, Tuscon, Arizona 85724, USA
| | - Christina M Laukaitis
- Department of Medicine, College of Medicine, University of Arizona, Tuscon, Arizona 85724, USA
| | - Lilue Jingtao
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SA, United Kingdom
| | - Fergal Martin
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Matthieu Muffato
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Stefanie Nachtweide
- Institute of Mathematics and Computer Science, University of Greifswald, Greifswald 17487, Germany
| | - Michael A Quail
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SA, United Kingdom
| | - Cristina Sisu
- Yale University Medical School, Computational Biology and Bioinformatics Program, New Haven, Connecticut 06520, USA
| | - Mario Stanke
- Institute of Mathematics and Computer Science, University of Greifswald, Greifswald 17487, Germany
| | - Klara Stefflova
- University of Cambridge, Cancer Research UK Cambridge Institute, Robinson Way, Cambridge CB2 0RE, United Kingdom
| | - Cock Van Oosterhout
- School of Environmental Sciences, University of East Anglia, Norwich Research Park, Norwich NR4 7TJ, United Kingdom
| | - Frederic Veyrunes
- Institut des Sciences de l'Evolution de Montpellier, Université Montpellier/CNRS, 34095 Montpellier, France
| | - Ben Ward
- Earlham Institute, Norwich Research Park, Norwich NR4 7UH, United Kingdom
| | - Fengtang Yang
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SA, United Kingdom
| | - Golbahar Yazdanifar
- Department of Medicine, College of Medicine, University of Arizona, Tuscon, Arizona 85724, USA
| | - Amonida Zadissa
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - David J Adams
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SA, United Kingdom
| | - Alvis Brazma
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Mark Gerstein
- Yale University Medical School, Computational Biology and Bioinformatics Program, New Haven, Connecticut 06520, USA
| | - Benedict Paten
- Department of Biomolecular Engineering, University of California, Santa Cruz, California 95064, USA
| | - Son Pham
- Bioturing Inc, San Diego, California 92121, USA
| | - Thomas M Keane
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SA, United Kingdom
| | - Duncan T Odom
- University of Cambridge, Cancer Research UK Cambridge Institute, Robinson Way, Cambridge CB2 0RE, United Kingdom
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SA, United Kingdom
| | - Paul Flicek
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SA, United Kingdom
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42
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A genomics approach reveals insights into the importance of gene losses for mammalian adaptations. Nat Commun 2018; 9:1215. [PMID: 29572503 PMCID: PMC5865188 DOI: 10.1038/s41467-018-03667-1] [Citation(s) in RCA: 126] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2017] [Accepted: 03/02/2018] [Indexed: 11/08/2022] Open
Abstract
Identifying the genomic changes that underlie phenotypic adaptations is a key challenge in evolutionary biology and genomics. Loss of protein-coding genes is one type of genomic change with the potential to affect phenotypic evolution. Here, we develop a genomics approach to accurately detect gene losses and investigate their importance for adaptive evolution in mammals. We discover a number of gene losses that likely contributed to morphological, physiological, and metabolic adaptations in aquatic and flying mammals. These gene losses shed light on possible molecular and cellular mechanisms that underlie these adaptive phenotypes. In addition, we show that gene loss events that occur as a consequence of relaxed selection following adaptation provide novel insights into species' biology. Our results suggest that gene loss is an evolutionary mechanism for adaptation that may be more widespread than previously anticipated. Hence, investigating gene losses has great potential to reveal the genomic basis underlying macroevolutionary changes.
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43
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Prade VM, Gundlach H, Twardziok S, Chapman B, Tan C, Langridge P, Schulman AH, Stein N, Waugh R, Zhang G, Platzer M, Li C, Spannagl M, Mayer KFX. The pseudogenes of barley. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2018; 93:502-514. [PMID: 29205595 DOI: 10.1111/tpj.13794] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/22/2017] [Revised: 11/16/2017] [Accepted: 11/24/2017] [Indexed: 06/07/2023]
Abstract
Pseudogenes have a reputation of being 'evolutionary relics' or 'junk DNA'. While they are well characterized in mammals, studies in more complex plant genomes have so far been hampered by the absence of reference genome sequences. Barley is one of the economically most important cereals and has a genome size of 5.1 Gb. With the first high-quality genome reference assembly available for a Triticeae crop, we conducted a whole-genome assessment of pseudogenes on the barley genome. We identified, characterized and classified 89 440 gene fragments and pseudogenes scattered along the chromosomes, with occasional hotspots and higher densities at the chromosome ends. Full-length pseudogenes (11 015) have preferentially retained their exon-intron structure. Retrotransposition of processed mRNAs only plays a marginal role in their creation. However, the distribution of retroposed pseudogenes reflects the Rabl configuration of barley chromosomes and thus hints at founding mechanisms. While parent genes related to the defense-response were found to be under-represented in cultivated barley, we detected several defense-related pseudogenes in wild barley accessions. The percentage of transcriptionally active pseudogenes is 7.2%, and these may potentially adopt new regulatory roles.The barley genome is rich in pseudogenes and small gene fragments mainly located towards chromosome tips or as tandemly repeated units. Our results indicate non-random duplication and pseudogenization preferences and improve our understanding of the dynamics of gene birth and death in large plant genomes and the mechanisms that lead to evolutionary innovations.
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Affiliation(s)
- Verena M Prade
- Plant Genome and Systems Biology, Helmholtz Center Munich - German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
| | - Heidrun Gundlach
- Plant Genome and Systems Biology, Helmholtz Center Munich - German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
| | - Sven Twardziok
- Plant Genome and Systems Biology, Helmholtz Center Munich - German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
| | - Brett Chapman
- Centre for Comparative Genomics, Murdoch University, 90 South Street, WA6150, Murdoch, Australia
| | - Cong Tan
- School of Veterinary and Life Sciences, Murdoch University, 90 South Street, WA6150, Murdoch, Australia
| | - Peter Langridge
- School of Agriculture, University of Adelaide, Waite Campus, SA5064, Urrbrae, Australia
| | - Alan H Schulman
- Green Technology, Natural Resources Institute (Luke), Viikki Plant Science Centre, Institute of Biotechnology, University of Helsinki, 00014, Helsinki, Finland
| | - Nils Stein
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, 06466, Seeland, Germany
- School of Plant Biology, University of Western Australia, Crawley, WA6009, Australia
| | - Robbie Waugh
- The James Hutton Institute, Dundee, DD2 5DA, UK
- School of Life Sciences, University of Dundee, Dundee, DD2 5DA, UK
| | - Guoping Zhang
- College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, 310058, China
| | - Matthias Platzer
- Leibniz Institute on Aging - Fritz Lipmann Institute (FLI), 07745, Jena, Germany
| | - Chengdao Li
- School of Veterinary and Life Sciences, Murdoch University, 90 South Street, WA6150, Murdoch, Australia
- Department of Agriculture and Food, Government of Western Australia, South Perth, WA, 6151, Australia
| | - Manuel Spannagl
- Plant Genome and Systems Biology, Helmholtz Center Munich - German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
| | - Klaus F X Mayer
- Plant Genome and Systems Biology, Helmholtz Center Munich - German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
- TUM School of Life Sciences Weihenstephan, Technical University of Munich, Alte Akademie 8, 85354, Freising, Germany
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Khan S, Fagerholm R, Kadalayil L, Tapper W, Aittomäki K, Liu J, Blomqvist C, Eccles D, Nevanlinna H. Meta-analysis of three genome-wide association studies identifies two loci that predict survival and treatment outcome in breast cancer. Oncotarget 2018; 9:4249-4257. [PMID: 29423119 PMCID: PMC5790536 DOI: 10.18632/oncotarget.22747] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2017] [Accepted: 11/09/2017] [Indexed: 11/25/2022] Open
Abstract
The majority of breast cancers are driven by the female hormone oestrogen via oestrogen receptor (ER) alpha. ER-positive patients are commonly treated with adjuvant endocrine therapy, however, resistance is a common occurrence and aside from ER-status, no unequivocal predictive biomarkers are currently in clinical use. In this study, we aimed to identify constitutional genetic variants influencing breast cancer survival among ER-positive patients and specifically, among endocrine-treated patients. We conducted a meta-analysis of three genome-wide association studies comprising in total 3,136 patients with ER-positive breast cancer of which 2,751 had received adjuvant endocrine therapy. We identified a novel locus (rs992531 at 8p21.2) associated with reduced survival among the patients with ER-positive breast cancer (P = 3.77 × 10-8). Another locus (rs7701292 at 5q21.3) was associated with reduced survival among the endocrine-treated patients (P = 2.13 × 10-8). Interaction analysis indicated that the survival association of rs7701292 is treatment-specific and independent of conventional prognostic markers. In silico functional studies suggest plausible biological mechanisms for the observed survival associations and a functional link between the putative target genes of the rs992531 and rs7701292 (RHOBTB2 and RAB9P1, respectively). We further explored the genetic interaction between rs992531 and rs7701292 and found a significant, treatment-specific interactive effect on survival among ER-positive, endocrine-treated patients (hazard ratio = 6.97; 95% confidence interval, 1.79-27.08, Pinteraction= 0.036). This is the first study to identify a genetic interaction that specifically predicts treatment outcome. These findings may provide predictive biomarkers based on germ line genotype informing more personalized treatment selection.
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Affiliation(s)
- Sofia Khan
- Department of Obstetrics and Gynaecology, University of Helsinki and Helsinki University Hospital, Biomedicum, Helsinki, Finland
| | - Rainer Fagerholm
- Department of Obstetrics and Gynaecology, University of Helsinki and Helsinki University Hospital, Biomedicum, Helsinki, Finland
| | - Latha Kadalayil
- Faculty of Medicine, University of Southampton, University Hospital Southampton, Southampton, UK
- Faculty of Natural and Environmental Sciences, University of Southampton, Southampton, UK
| | - William Tapper
- Faculty of Medicine, University of Southampton, University Hospital Southampton, Southampton, UK
| | - Kristiina Aittomäki
- Department of Clinical Genetics, Helsinki University Hospital and Genome Scale Biology Research Program, University of Helsinki, Helsinki, Finland
| | - Jianjun Liu
- Human Genetics, Genome Institute of Singapore, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Carl Blomqvist
- Department of Oncology, Helsinki University Hospital, Helsinki, Finland
- Department of Oncology, University of Örebro, Örebro, Sweden
| | - Diana Eccles
- Faculty of Medicine, University of Southampton, University Hospital Southampton, Southampton, UK
| | - Heli Nevanlinna
- Department of Obstetrics and Gynaecology, University of Helsinki and Helsinki University Hospital, Biomedicum, Helsinki, Finland
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Muir VS, Gasch AP, Anderson P. The Substrates of Nonsense-Mediated mRNA Decay in Caenorhabditis elegans. G3 (BETHESDA, MD.) 2018; 8:195-205. [PMID: 29122854 PMCID: PMC5765348 DOI: 10.1534/g3.117.300254] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/08/2017] [Accepted: 11/07/2017] [Indexed: 12/27/2022]
Abstract
Nonsense-mediated mRNA decay (NMD) is a conserved pathway that strongly influences eukaryotic gene expression. Inactivating or inhibiting NMD affects the abundance of a substantial fraction of the transcriptome in numerous species. Transcripts whose abundance is altered in NMD-deficient cells may represent either direct substrates of NMD or indirect effects of inhibiting NMD. We present a genome-wide investigation of the direct substrates of NMD in Caenorhabditis elegans Our goals were (i) to identify mRNA substrates of NMD and (ii) to distinguish those mRNAs from others whose abundance is indirectly influenced by the absence of NMD. We previously demonstrated that Upf1p/SMG-2, the central effector of NMD in all studied eukaryotes, preferentially associates with mRNAs that contain premature translation termination codons. We used this preferential association to distinguish direct from indirect effects by coupling immunopurification of Upf1/SMG-2 with high-throughput mRNA sequencing of NMD-deficient mutants and NMD-proficient controls. We identify 680 substrates of NMD, 171 of which contain novel spliced forms that (i) include sequences of annotated introns and (ii) have not been previously documented in the C. elegans transcriptome. NMD degrades unproductively spliced mRNAs with sufficient efficiency in NMD-proficient strains that such mRNAs were not previously known. Two classes of genes are enriched among the identified NMD substrates: (i) mRNAs of expressed pseudogenes and (ii) mRNAs of gene families whose gene number has recently expanded in the C. elegans genome. Our results identify novel NMD substrates and provide a context for understanding NMD's role in normal gene expression and genome evolution.
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Affiliation(s)
- Virginia S Muir
- Laboratory of Genetics, University of Wisconsin-Madison, Wisconsin 53706
| | - Audrey P Gasch
- Laboratory of Genetics, University of Wisconsin-Madison, Wisconsin 53706
| | - Philip Anderson
- Laboratory of Genetics, University of Wisconsin-Madison, Wisconsin 53706
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Johnson TS, Li S, Kho JR, Huang K, Zhang Y. Network analysis of pseudogene-gene relationships: from pseudogene evolution to their functional potentials. PACIFIC SYMPOSIUM ON BIOCOMPUTING. PACIFIC SYMPOSIUM ON BIOCOMPUTING 2018; 23:536-547. [PMID: 29218912 PMCID: PMC5744670] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Pseudogenes are fossil relatives of genes. Pseudogenes have long been thought of as "junk DNAs", since they do not code proteins in normal tissues. Although most of the human pseudogenes do not have noticeable functions, ∼20% of them exhibit transcriptional activity. There has been evidence showing that some pseudogenes adopted functions as lncRNAs and work as regulators of gene expression. Furthermore, pseudogenes can even be "reactivated" in some conditions, such as cancer initiation. Some pseudogenes are transcribed in specific cancer types, and some are even translated into proteins as observed in several cancer cell lines. All the above have shown that pseudogenes could have functional roles or potentials in the genome. Evaluating the relationships between pseudogenes and their gene counterparts could help us reveal the evolutionary path of pseudogenes and associate pseudogenes with functional potentials. It also provides an insight into the regulatory networks involving pseudogenes with transcriptional and even translational activities.In this study, we develop a novel approach integrating graph analysis, sequence alignment and functional analysis to evaluate pseudogene-gene relationships, and apply it to human gene homologs and pseudogenes. We generated a comprehensive set of 445 pseudogene-gene (PGG) families from the original 3,281 gene families (13.56%). Of these 438 (98.4% PGG, 13.3% total) were non-trivial (containing more than one pseudogene). Each PGG family contains multiple genes and pseudogenes with high sequence similarity. For each family, we generate a sequence alignment network and phylogenetic trees recapitulating the evolutionary paths. We find evidence supporting the evolution history of olfactory family (both genes and pseudogenes) in human, which also supports the validity of our analysis method. Next, we evaluate these networks in respect to the gene ontology from which we identify functions enriched in these pseudogene-gene families and infer functional impact of pseudogenes involved in the networks. This demonstrates the application of our PGG network database in the study of pseudogene function in disease context.
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Affiliation(s)
- Travis S Johnson
- Dept. Biomedical Informatics, Ohio State University, 5000 HITS, 410 W. 10th St. Indianapolis, Indiana, 46202, USA,
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Ritchie H, Jamieson AJ, Piertney SB. Genome size variation in deep-sea amphipods. ROYAL SOCIETY OPEN SCIENCE 2017; 4:170862. [PMID: 28989783 PMCID: PMC5627123 DOI: 10.1098/rsos.170862] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/07/2017] [Accepted: 08/16/2017] [Indexed: 06/07/2023]
Abstract
Genome size varies considerably across taxa, and extensive research effort has gone into understanding whether variation can be explained by differences in key ecological and life-history traits among species. The extreme environmental conditions that characterize the deep sea have been hypothesized to promote large genome sizes in eukaryotes. Here we test this supposition by examining genome sizes among 13 species of deep-sea amphipods from the Mariana, Kermadec and New Hebrides trenches. Genome sizes were estimated using flow cytometry and found to vary nine-fold, ranging from 4.06 pg (4.04 Gb) in Paralicella caperesca to 34.79 pg (34.02 Gb) in Alicella gigantea. Phylogenetic independent contrast analysis identified a relationship between genome size and maximum body size, though this was largely driven by those species that display size gigantism. There was a distinct shift in the genome size trait diversification rate in the supergiant amphipod A. gigantea relative to the rest of the group. The variation in genome size observed is striking and argues against genome size being driven by a common evolutionary history, ecological niche and life-history strategy in deep-sea amphipods.
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Affiliation(s)
- H. Ritchie
- Institute of Biological and Environmental Sciences, University of Aberdeen, Zoology Building, Aberdeen AB24 2TZ, UK
| | - A. J. Jamieson
- Oceanlab, University of Aberdeen, Newburgh, Aberdeenshire AB41 6AA, UK
| | - S. B. Piertney
- Institute of Biological and Environmental Sciences, University of Aberdeen, Zoology Building, Aberdeen AB24 2TZ, UK
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Zhang Y, Li S, Abyzov A, Gerstein MB. Landscape and variation of novel retroduplications in 26 human populations. PLoS Comput Biol 2017; 13:e1005567. [PMID: 28662076 PMCID: PMC5510864 DOI: 10.1371/journal.pcbi.1005567] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2016] [Revised: 07/14/2017] [Accepted: 05/12/2017] [Indexed: 01/10/2023] Open
Abstract
Retroduplications come from reverse transcription of mRNAs and their insertion back into the genome. Here, we performed comprehensive discovery and analysis of retroduplications in a large cohort of 2,535 individuals from 26 human populations, as part of 1000 Genomes Phase 3. We developed an integrated approach to discover novel retroduplications combining high-coverage exome and low-coverage whole-genome sequencing data, utilizing information from both exon-exon junctions and discordant paired-end reads. We found 503 parent genes having novel retroduplications absent from the reference genome. Based solely on retroduplication variation, we built phylogenetic trees of human populations; these represent superpopulation structure well and indicate that variable retroduplications are effective population markers. We further identified 43 retroduplication parent genes differentiating superpopulations. This group contains several interesting insertion events, including a SLMO2 retroduplication and insertion into CAV3, which has a potential disease association. We also found retroduplications to be associated with a variety of genomic features: (1) Insertion sites were correlated with regular nucleosome positioning. (2) They, predictably, tend to avoid conserved functional regions, such as exons, but, somewhat surprisingly, also avoid introns. (3) Retroduplications tend to be co-inserted with young L1 elements, indicating recent retrotranspositional activity, and (4) they have a weak tendency to originate from highly expressed parent genes. Our investigation provides insight into the functional impact and association with genomic elements of retroduplications. We anticipate our approach and analytical methodology to have application in a more clinical context, where exome sequencing data is abundant and the discovery of retroduplications can potentially improve the accuracy of SNP calling.
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Affiliation(s)
- Yan Zhang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, United States of America
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut, United States of America
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, Ohio, United States of America
| | - Shantao Li
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, United States of America
| | - Alexej Abyzov
- Department of Health Sciences Research, Center for Individualized Medicine, Mayo Clinic, Rochester, Minnesota, United States of America
| | - Mark B. Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, United States of America
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut, United States of America
- Department of Computer Science, Yale University, New Haven, Connecticut, United States of America
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49
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Abstract
A genome sequence is worthless if it cannot be deciphered; therefore, efforts to describe - or 'annotate' - genes began as soon as DNA sequences became available. Whereas early work focused on individual protein-coding genes, the modern genomic ocean is a complex maelstrom of alternative splicing, non-coding transcription and pseudogenes. Scientists - from clinicians to evolutionary biologists - need to navigate these waters, and this has led to the design of high-throughput, computationally driven annotation projects. The catalogues that are being produced are key resources for genome exploration, especially as they become integrated with expression, epigenomic and variation data sets. Their creation, however, remains challenging.
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Affiliation(s)
- Jonathan M Mudge
- Department of Computational Genomics, Wellcome Trust Sanger Institute, Hinxton CB10 1SA, UK
| | - Jennifer Harrow
- Department of Computational Genomics, Wellcome Trust Sanger Institute, Hinxton CB10 1SA, UK.,Illumina Cambridge Ltd, Chesterford Research Park, Little Chesterford, Saffron Walden CB10 1 XL, UK
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50
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Tan TK, Tan KY, Hari R, Mohamed Yusoff A, Wong GJ, Siow CC, Mutha NVR, Rayko M, Komissarov A, Dobrynin P, Krasheninnikova K, Tamazian G, Paterson IC, Warren WC, Johnson WE, O'Brien SJ, Choo SW. PGD: a pangolin genome hub for the research community. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2016; 2016:baw063. [PMID: 27616775 PMCID: PMC5018392 DOI: 10.1093/database/baw063] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/24/2015] [Accepted: 04/11/2016] [Indexed: 01/01/2023]
Abstract
Pangolins (order Pholidota) are the only mammals covered by scales. We have recently sequenced and analyzed the genomes of two critically endangered Asian pangolin species, namely the Malayan pangolin (Manis javanica) and the Chinese pangolin (Manis pentadactyla). These complete genome sequences will serve as reference sequences for future research to address issues of species conservation and to advance knowledge in mammalian biology and evolution. To further facilitate the global research effort in pangolin biology, we developed the Pangolin Genome Database (PGD), as a future hub for hosting pangolin genomic and transcriptomic data and annotations, and with useful analysis tools for the research community. Currently, the PGD provides the reference pangolin genome and transcriptome data, gene sequences and functional information, expressed transcripts, pseudogenes, genomic variations, organ-specific expression data and other useful annotations. We anticipate that the PGD will be an invaluable platform for researchers who are interested in pangolin and mammalian research. We will continue updating this hub by including more data, annotation and analysis tools particularly from our research consortium.Database URL: http://pangolin-genome.um.edu.my.
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Affiliation(s)
- Tze King Tan
- Genome Informatics Research Laboratory, Centre for Research in Biotechnology for Agriculture (CEBAR), High Impact Research Building, University of Malaya, 50603 Kuala Lumpur, Malaysia Department of Oral and Craniofacial Sciences, Faculty of Dentistry, University of Malaya, 50603 Kuala Lumpur, Malaysia
| | - Ka Yun Tan
- Genome Informatics Research Laboratory, Centre for Research in Biotechnology for Agriculture (CEBAR), High Impact Research Building, University of Malaya, 50603 Kuala Lumpur, Malaysia Institute of Biology Sciences, Faculty of Science, University of Malaya, 50603 Kuala Lumpur Malaysia
| | - Ranjeev Hari
- Genome Informatics Research Laboratory, Centre for Research in Biotechnology for Agriculture (CEBAR), High Impact Research Building, University of Malaya, 50603 Kuala Lumpur, Malaysia Department of Oral and Craniofacial Sciences, Faculty of Dentistry, University of Malaya, 50603 Kuala Lumpur, Malaysia
| | - Aini Mohamed Yusoff
- Genome Informatics Research Laboratory, Centre for Research in Biotechnology for Agriculture (CEBAR), High Impact Research Building, University of Malaya, 50603 Kuala Lumpur, Malaysia Department of Oral and Craniofacial Sciences, Faculty of Dentistry, University of Malaya, 50603 Kuala Lumpur, Malaysia
| | - Guat Jah Wong
- Genome Informatics Research Laboratory, Centre for Research in Biotechnology for Agriculture (CEBAR), High Impact Research Building, University of Malaya, 50603 Kuala Lumpur, Malaysia
| | - Cheuk Chuen Siow
- Genome Informatics Research Laboratory, Centre for Research in Biotechnology for Agriculture (CEBAR), High Impact Research Building, University of Malaya, 50603 Kuala Lumpur, Malaysia
| | - Naresh V R Mutha
- Genome Informatics Research Laboratory, Centre for Research in Biotechnology for Agriculture (CEBAR), High Impact Research Building, University of Malaya, 50603 Kuala Lumpur, Malaysia
| | - Mike Rayko
- Theodosius Dobzhansky Center for Genome Bioinformatics, Saint Petersburg State University, St. Petersburg 199004, Russia
| | - Aleksey Komissarov
- Theodosius Dobzhansky Center for Genome Bioinformatics, Saint Petersburg State University, St. Petersburg 199004, Russia
| | - Pavel Dobrynin
- Theodosius Dobzhansky Center for Genome Bioinformatics, Saint Petersburg State University, St. Petersburg 199004, Russia
| | - Ksenia Krasheninnikova
- Theodosius Dobzhansky Center for Genome Bioinformatics, Saint Petersburg State University, St. Petersburg 199004, Russia
| | - Gaik Tamazian
- Theodosius Dobzhansky Center for Genome Bioinformatics, Saint Petersburg State University, St. Petersburg 199004, Russia
| | - Ian C Paterson
- Department of Oral and Craniofacial Sciences, Faculty of Dentistry, University of Malaya, 50603 Kuala Lumpur, Malaysia Oral Cancer Research and Coordinating Centre, Faculty of Dentistry, University of Malaya, 50603 Kuala Lumpur, Malaysia
| | - Wesley C Warren
- McDonnell Genome Institute, Washington University, St Louis, MO 63108, USA
| | - Warren E Johnson
- Smithsonian Conservation Biology Institute, Front Royal, Virginia 22630, USA
| | - Stephen J O'Brien
- Theodosius Dobzhansky Center for Genome Bioinformatics, Saint Petersburg State University, St. Petersburg 199004, Russia Oceanographic Center, Nova Southeastern University, Ft Lauderdale, FL, 33004, USA
| | - Siew Woh Choo
- Genome Informatics Research Laboratory, Centre for Research in Biotechnology for Agriculture (CEBAR), High Impact Research Building, University of Malaya, 50603 Kuala Lumpur, Malaysia Department of Oral and Craniofacial Sciences, Faculty of Dentistry, University of Malaya, 50603 Kuala Lumpur, Malaysia Genome Solutions Sdn Bhd, Suite 8, Innovation Incubator UM, Level 5, Research Management & Innovation Complex, University of Malaya, 50603 Kuala Lumpur, Malaysia
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