DOCSLIB.ORG

(HCC) Using RNA-Seq Datasets and Machine Learning

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
(HCC) Using RNA-Seq Datasets and Machine Learning Gupta et al. BMC Cancer (2021) 21:962 https://doi.org/10.1186/s12885-021-08704-9 RESEARCH Open Access Identifying novel transcript biomarkers for hepatocellular carcinoma (HCC) using RNA- Seq datasets and machine learning Rajinder Gupta, Jos Kleinjans and Florian Caiment* Abstract Background: Hepatocellular carcinoma (HCC) is one of the leading causes of cancer death in the world owing to limitations in its prognosis. The current prognosis approaches include radiological examination and detection of serum biomarkers, however, both have limited efficiency and are ineffective in early prognosis. Due to such limitations, we propose to use RNA-Seq data for evaluating putative higher accuracy biomarkers at the transcript level that could help in early prognosis. Methods: To identify such potential transcript biomarkers, RNA-Seq data for healthy liver and various HCC cell models were subjected to five different machine learning algorithms: random forest, K-nearest neighbor, Naïve Bayes, support vector machine, and neural networks. Various metrics, namely sensitivity, specificity, MCC, informedness, and AUC-ROC (except for support vector machine) were evaluated. The algorithms that produced the highest values for all metrics were chosen to extract the top features that were subjected to recursive feature elimination. Through recursive feature elimination, the least number of features were obtained to differentiate between the healthy and HCC cell models. Results: From the metrics used, it is demonstrated that the efficiency of the known protein biomarkers for HCC is comparatively lower than complete transcriptomics data. Among the different machine learning algorithms, random forest and support vector machine demonstrated the best performance. Using recursive feature elimination on top features of random forest and support vector machine three transcripts were selected that had an accuracy of 0.97 and kappa of 0.93. Of the three transcripts, two were protein coding (PARP2–202 and SPON2–203) and one was a non-coding transcript (CYREN-211). Lastly, we demonstrated that these three selected transcripts outperformed randomly taken three transcripts (15,000 combinations), hence were not chance findings, and could then be an interesting candidate for new HCC biomarker development. Conclusion: Using RNA-Seq data combined with machine learning approaches can aid in finding novel transcript biomarkers. The three biomarkers identified: PARP2–202, SPON2–203, and CYREN-211, presented the highest accuracy among all other transcripts in differentiating the healthy and HCC cell models. The machine learning pipeline developed in this study can be used for any RNA-Seq dataset to find novel transcript biomarkers. Code: www.github.com/rajinder4489/ML_biomarkers Keywords: Hepatocellular carcinoma, Machine learning, Biomarkers, RNA-Seq, Transcript expression * Correspondence: [email protected] Department of Toxicogenomics, School of Oncology and Developmental Biology (GROW), Maastricht University, Maastricht, The Netherlands © The Author(s). 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Gupta et al. BMC Cancer (2021) 21:962 Page 2 of 15 Introduction transcriptomics data is available for HCC tissue/cell The liver, one of the largest organ in the body, performs vari- models (c.f. Methods) and hence, we concentrated on ous important functions, such as filtering harmful substances such data to find novel HCC biomarkers. from the blood to be then excreted from the body, producing Using RNA-Sequencing (RNA-Seq), the whole tran- bile to help in the digestion of fats from food, or storing scriptome can be quantified. Moreover, different types of glycogen (sugar) that will be used for energy. Due to its con- transcripts (protein coding and non-coding) can also be tinuous exposure to harmful substances, it is prone to the identified. Most transcriptomics analyses focus on gene amplitude of diseases that can eventually cause liver failure expression by aggregating the expression of all tran- and/or liver cancer. Cirrhosis, long-term infection with hepa- scripts for the given gene. However, in this study, we will titis B virus, and hepatitis C virus, alcoholic liver disease, and focus on the transcripts because alternative-splicing de- nonalcoholic fatty liver disease (NAFLD) are leading risk fac- fects in cancer are well documented [33–35] and dysreg- tors for primary liver cancer [1]. Moreover, cancer can de- ulation of splicing variants’ expression has recently velop in the liver at any stage in the progression of various emerged as a novel cancer hallmark [35]. Moreover, liver diseases. As published in independent reports by World using the RNA-Seq data at the transcript level will also Health Organization (WHO) [2] and the US Center for Dis- allow us to investigate the potency of non-coding tran- ease Control and Prevention (CDC) [3], liver cancer is scripts to be used as biomarkers. among the top causes for cancer death worldwide, of which Machine learning (ML) is a multidisciplinary field that hepatocellular carcinoma (HCC) is the most common type makes use of computer science, artificial intelligence, of primary liver cancer, accounting for ~ 80% liver cancers. computational statistics, and information theory to build Reducing the global burden of HCC is, therefore, a pri- algorithms that learn from existing data and make predic- mary concern and it can be achieved by improving early tions on new data [36]. It has found application in diverse detection and management [4]. Currently, the employed domains of biomedicine, including, but not limited to, prognosis for HCC includes radiological examinations and image analysis [37], cancer prediction from heterogeneous assessment of serum markers. Radiological examinations data [38], robust phenotyping [39], gene discovery [40], are limited for early diagnosis as the performance of the differential network analysis [41], biomarker discovery imaging techniques begins to degrade substantially below [42], and transcriptional regulated genes [43]. The appli- a lesion size of 2 cm and have only modest accuracy below cation of machine learning for the biomarker discov- a lesion size of 1 cm [5]. In the case of biomarkers, cur- ery from the RNA-Seq data is mainly focused on rently, there are ~ 20 biomarkers (Table 1)inresearch, genes, however, recent studies have demonstrated that and out of these only α-fetoprotein (alpha-fetoprotein or transcript-based analyses outperformed gene-based AFP) has a clinical application; even though it is ineffect- analyses using ML [44, 45]. To assess if transcript ive for detecting early lesions [1, 24–26]. Of the other biomarkers have better prediction accuracy, we ana- markers used in research, none have reached the standard lyzed various HCC cell models and healthy liver level of clinical practice so far [24, 27]. However, in vari- RNA-Seq data. Several HCC cell models were taken ous studies, it has also been demonstrated that a combin- for this study (Table 2) to ascertain that their bio- ation of different biomarkers provides higher accuracy in logical heterogeneity is accounted for while building predicting HCC [6, 11, 20–23]. theMLmodels.VariousMLalgorithms,namelyran- Though the combinations of various biomarkers are dom forest (RF), K-nearest neighbors (KNN), support better predictors than the individual biomarkers, sensi- vector machines (SVM), Naïve Bayes (NB), and tivity or specificity is still low for all biomarker combina- Neural networks (NNET), which are extensively used tions [6, 11, 20–23]. While proteins are the major in the field of biomedicine, were applied to build the functional element, the corresponding transcripts can be models and identify novel putative transcript bio- an easier surrogate to detect and quantify. The cancer- markers for HCC. specific mRNAs can leak into the serum as a result of From the transcriptomics data, three datasets were as- passive processes (such as necrosis) and active processes sembled: all transcripts, protein coding only, and non- (such as tumor cell apoptosis and active release in coding only. The goal of making these three datasets microvesicles by tumor cells) [28–31]. Though non- was to see if one of them provides a better prediction. invasive, the lack of transcriptomics data for circulating Consecutively, the efficiency of the known protein bio- cell-free mRNAs for HCC poses a limitation in under- markers (Table 1) was also assessed by taking the taking a comprehensive in silico study to find novel
Load more

Recommended publications
  • DNA Damage Response
    biomolecules Editorial DNA Damage Response Valentyn Oksenych 1,2,3,4,* and Denis E. Kainov 1,5,* 1 Department for Cancer Research and Molecular Medicine (IKOM), Norwegian University of Science and Technology, 7491 Trondheim, Norway 2 Department of Biosciences and Nutrition (BioNuT), Karolinska Institutet, 14183 Huddinge, Sweden 3 KG Jebsen Centre for B Cell Malignancies, Institute of Clinical Medicine, University of Oslo, 0316 Oslo, Norway 4 Institute of Clinical Medicine, University of Oslo, 0318 Oslo, Norway 5 Institute of Technology, University of Tartu, 50090 Tartu, Estonia * Correspondence: [email protected] (V.O.); [email protected] (D.E.K.) DNA in our cells is constantly modified by internal and external factors. For exam- ple, metabolic byproducts, ionizing radiation (IR), ultraviolet (UV) light, and medicines can induce spontaneous DNA lesions [1–3]. However, DNA modifications can also be programmed. In particular, the recombination activating gene (RAG) can induce breaks generated during the V(D)J recombination in developing B and T lymphocytes [1,2]. In addition, activation-induced cytidine deaminase (AID) makes DNA break during the class-switch recombination (CSR) and somatic hypermutation (SHM) in B cells [1,2]. One focus of this Special Issue is on the non-homologous end-joining (NHEJ) DNA repair pathway and DNA repair and DNA damage response (DDR) factors. Oksenych et al. and others found the functional redundancy of these factors in mammalian cells. In particu- lar, a genetic interaction was found between the X-ray repair cross-complementing protein 4 (XRCC4)-like factor (XLF, also known as Cernunnos) and the DNA-dependent protein kinase catalytic subunit (DNA-PKcs) [4,5], the paralog of XRCC4 and XLF (PAXX) [6–9], and the modulator of retrovirus infection (MRI, also known as Cyren) [10].
    [Show full text]
  • Generation of a Mouse Model Lacking the Non-Homologous End-Joining Factor Mri/Cyren
    biomolecules Article Generation of a Mouse Model Lacking the Non-Homologous End-Joining Factor Mri/Cyren 1,2, 1,2, 1,2, 1,2 Sergio Castañeda-Zegarra y , Camilla Huse y, Øystein Røsand y, Antonio Sarno , Mengtan Xing 1,2, Raquel Gago-Fuentes 1,2, Qindong Zhang 1,2, Amin Alirezaylavasani 1,2, Julia Werner 1,2,3, Ping Ji 1, Nina-Beate Liabakk 1, Wei Wang 1, Magnar Bjørås 1,2 and Valentyn Oksenych 1,2,4,* 1 Department of Clinical and Molecular Medicine (IKOM), Norwegian University of Science and Technology, 7491 Trondheim, Norway; [email protected] (S.C.-Z.); [email protected] (C.H.); [email protected] (Ø.R.); [email protected] (A.S.); [email protected] (M.X.); [email protected] (R.G.-F.); [email protected] (Q.Z.); [email protected] (A.A.); [email protected] (J.W.); [email protected] (P.J.); [email protected] (N.-B.L.); [email protected] (W.W.); [email protected] (M.B.) 2 St. Olavs Hospital, Trondheim University Hospital, Clinic of Medicine, Postboks 3250, Sluppen, 7006 Trondheim, Norway 3 Molecular Biotechnology MS programme, Heidelberg University, 69120 Heidelberg, Germany 4 Department of Biosciences and Nutrition (BioNut), Karolinska Institutet, 14183 Huddinge, Sweden * Correspondence: [email protected]; Tel.: +47-913-43-084 These authors contributed equally to this work. y Received: 7 November 2019; Accepted: 26 November 2019; Published: 28 November 2019 Abstract: Classical non-homologous end joining (NHEJ) is a molecular pathway that detects, processes, and ligates DNA double-strand breaks (DSBs) throughout the cell cycle.
    [Show full text]
  • The Response to DNA Damage at Telomeric Repeats and Its Consequences for Telomere Function
    Review The Response to DNA Damage at Telomeric Repeats and Its Consequences for Telomere Function Ylli Doksani IFOM, The FIRC Institute of Molecular Oncology, via Adamello 16, 20139 Milan, Italy; [email protected]; Tel.: +39-02-574303258 Received: 26 March 2019; Accepted: 18 April 2019; Published: 24 April 2019 Abstract: Telomeric repeats, coated by the shelterin complex, prevent inappropriate activation of the DNA damage response at the ends of linear chromosomes. Shelterin has evolved distinct solutions to protect telomeres from different aspects of the DNA damage response. These solutions include formation of t-loops, which can sequester the chromosome terminus from DNA-end sensors and inhibition of key steps in the DNA damage response. While blocking the DNA damage response at chromosome ends, telomeres make wide use of many of its players to deal with exogenous damage and replication stress. This review focuses on the interplay between the end-protection functions and the response to DNA damage occurring inside the telomeric repeats, as well as on the consequences that telomere damage has on telomere structure and function. Keywords: telomere maintenance; shelterin complex; end-protection problem; telomere damage; telomeric double strand breaks; telomere replication; alternative lengthening of telomeres 1. Telomere Structure and End-Protection Functions Mammalian telomeres are made of tandem TTAGGG repeats that extend several kilobases and terminate with a 3′ single-stranded overhang about 50–400 nucleotides long. Telomeric repeats are coated in a sequence-specific fashion by a 6-protein complex named shelterin that prevents the activation of the Double Strand Break (DSB) response at chromosome ends [1-3].
    [Show full text]
  • UC San Diego UC San Diego Electronic Theses and Dissertations
    UC San Diego UC San Diego Electronic Theses and Dissertations Title Methods and Characterization of smORF-Encoded Microproteins Permalink https://escholarship.org/uc/item/25k5d8z0 Author Rathore, Annie Publication Date 2018 Peer reviewed|Thesis/dissertation eScholarship.org Powered by the California Digital Library University of California UNIVERSITY OF CALIFORNIA SAN DIEGO Methods and Characterization of smORF-Encoded Microproteins A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Biology by Annie Rathore Committee in charge: Professor Alan Saghatelian, Chair Professor Christopher Benner Professor Christopher Glass Professor Randolph Hampton Professor Martin Hetzer Professor Jens Lykke-Anderson 2018 © Annie Rathore, 2018 All rights reserved. The Dissertation of Annie Rathore is approved, and is acceptable in quality and form for publication on microfilm and electronically: Chair University of California San Diego 2018 iii TABLE OF CONTENTS Signature Page .......................................................................................................................... iii Table of Contents ....................................................................................................................... iv List of Figures ............................................................................................................................ vi Acknowledgements .................................................................................................................
    [Show full text]
  • Structural Mechanism of DNA-End Synapsis in the Non- Homologous End Joining Pathway for Repairing Double-Strand Breaks: Bridge Over Troubled Ends
    This is a repository copy of Structural mechanism of DNA-end synapsis in the non- homologous end joining pathway for repairing double-strand breaks: bridge over troubled ends. White Rose Research Online URL for this paper: http://eprints.whiterose.ac.uk/154931/ Version: Accepted Version Article: Wu, Q orcid.org/0000-0002-6948-7043 (2019) Structural mechanism of DNA-end synapsis in the non-homologous end joining pathway for repairing double-strand breaks: bridge over troubled ends. Biochemical Society Transactions, 47 (6). pp. 1609-1619. ISSN 0300-5127 https://doi.org/10.1042/bst20180518 © 2019 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society. This is an author produced version of a paper published in Biochemical Society Transactions. Uploaded in accordance with the publisher's self-archiving policy. Reuse Items deposited in White Rose Research Online are protected by copyright, with all rights reserved unless indicated otherwise. They may be downloaded and/or printed for private study, or other acts as permitted by national copyright laws. The publisher or other rights holders may allow further reproduction and re-use of the full text version. This is indicated by the licence information on the White Rose Research Online record for the item. Takedown If you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing [email protected] including the URL of the record and the reason for the withdrawal request. [email protected] https://eprints.whiterose.ac.uk/
    [Show full text]
  • Beyond Gene Expression
    Beyond gene expression Citation for published version (APA): Gupta, R. (2021). Beyond gene expression: novel methods and applications of transcript expression analyses in RNA-Seq. Maastricht University. https://doi.org/10.26481/dis.20210304rg Document status and date: Published: 01/01/2021 DOI: 10.26481/dis.20210304rg Document Version: Publisher's PDF, also known as Version of record Please check the document version of this publication: • A submitted manuscript is the version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal.
    [Show full text]
  • Approaches to Identify and Characterize Microproteins and Their Potential Uses in Biotechnology
    Cellular and Molecular Life Sciences (2018) 75:2529–2536 https://doi.org/10.1007/s00018-018-2818-8 Cellular andMolecular Life Sciences REVIEW Approaches to identify and characterize microProteins and their potential uses in biotechnology Kaushal Kumar Bhati1,2 · Anko Blaakmeer1,2 · Esther Botterweg Paredes1,2 · Ulla Dolde1,2 · Tenai Eguen1,2 · Shin‑Young Hong1,2 · Vandasue Rodrigues1,2 · Daniel Straub1,2 · Bin Sun1,2 · Stephan Wenkel1,2 Received: 27 November 2017 / Revised: 5 March 2018 / Accepted: 13 April 2018 / Published online: 18 April 2018 © The Author(s) 2018 Abstract MicroProteins are small proteins that contain a single protein domain and are related to larger, often multi-domain proteins. At the molecular level, microProteins act by interfering with the formation of higher order protein complexes. In the past years, several microProteins have been identifed in plants and animals that strongly infuence biological processes. Due to their ability to act as dominant regulators in a targeted manner, microProteins have a high potential for biotechnological use. In this review, we present diferent ways in which microProteins are generated and we elaborate on techniques used to identify and characterize them. Finally, we give an outlook on possible applications in biotechnology. Keywords MicroProtein · Small proteins · Targets · Complex · MiPFinder · Inhibition · Protein–protein interaction Introduction BINDING (Id) in animals. The Id protein is a 16 kDa small protein consisting of only a helix–loop–helix (HLH) domain. MicroProteins are small proteins that contain only a single Id can disrupt functional basic helix–loop–helix (bHLH) protein domain, often a protein–protein interaction (PPI) homodimers by forming bHLH/HLH heterodimers.
    [Show full text]
  • Plugged Into the Ku-DNA Hub: the NHEJ Network Philippe Frit, Virginie Ropars, Mauro Modesti, Jean-Baptiste Charbonnier, Patrick Calsou
    Plugged into the Ku-DNA hub: The NHEJ network Philippe Frit, Virginie Ropars, Mauro Modesti, Jean-Baptiste Charbonnier, Patrick Calsou To cite this version: Philippe Frit, Virginie Ropars, Mauro Modesti, Jean-Baptiste Charbonnier, Patrick Calsou. Plugged into the Ku-DNA hub: The NHEJ network. Progress in Biophysics and Molecular Biology, Elsevier, 2019, 10.1016/j.pbiomolbio.2019.03.001. hal-02144114 HAL Id: hal-02144114 https://hal.archives-ouvertes.fr/hal-02144114 Submitted on 29 May 2019 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Progress in Biophysics and Molecular Biology xxx (xxxx) xxx Contents lists available at ScienceDirect Progress in Biophysics and Molecular Biology journal homepage: www.elsevier.com/locate/pbiomolbio Plugged into the Ku-DNA hub: The NHEJ network * Philippe Frit a, b, Virginie Ropars c, Mauro Modesti d, e, Jean Baptiste Charbonnier c, , ** Patrick Calsou a, b, a Institut de Pharmacologie et Biologie Structurale, IPBS, Universite de Toulouse, CNRS, UPS, Toulouse, France b Equipe Labellisee Ligue Contre le Cancer, Toulouse,
    [Show full text]
  • Prediction of Novel Bioactive Micropeptides in the Immune System
    Prediction of novel bioactive micropeptides in the immune system Fengyuan Hu The Babraham Institute St Edmund’s College, University of Cambridge June 2020 Submitted for the degree of Doctor of Philosophy at the University of Cambridge Declaration of Originality This thesis is the result of my own work and includes nothing which is the outcome of work done in collaboration except as declared in the Preface and specified in the text. It is not substantially the same as any that I have submitted, or, is being concurrently submitted for a degree or diploma or other qualification at the University of Cambridge or any other University or similar institution except as declared in the Preface and specified in the text. I further state that no substantial part of my dissertation has already been submitted, or, is being concurrently submitted for any such degree, diploma or other qualification at the University of Cambridge or any other University or similar institution except as declared in the Preface and specified in the text. It does not exceed the prescribed word limit for the relevant Degree Committee. Fengyuan Hu 1 Table of Contents Acknowledgements ……...……………………………………………………………………...06 Abstract……...…………………………………………………………………………………..08 Abbreviation……………………………………………………………………………………..09 1 Introduction……………………...…………..10 1.1 Roles of bioactive peptides and small proteins in the immune system ....................................... 111 1.2 Small open reading frames (smORFs) and micropeptides ............................................................
    [Show full text]
  • ERIBA Annual Report 2017
    European Research Institute for the Biology of Ageing Annual Report 2017 Annual Report 2017 Table of Contents Foreword 6 Ageing Research at ERIBA 8 2017: A Closer Look 12 Facts and Figures 18 Table of Contents Scientific Publications 20 Table of Contents 4 www.eriba.umcg.nl 5 Funding/Grants 26 Coordination: Gerald de Haan and Helena Rico Secretarial Support: Invited Speakers 28 Sylvia Hoks, Nina Kool and Annet Vos-Hassing Design and Illustrations: G2K Creative Agency People 32 Printing: Zalsman Grafische Bedrijven, Groningen 400 issues Education 36 Outreach and Dissemination 38 Scientific Advisory Board 41 Sponsors 42 In 2017 ERIBA scientists secured a Foreword VIDI award and multiple grants from the Dutch Cancer Society. A former 2017 in review PhD student has been honoured with a Rubicon Fellowship, which we are very proud of. I am very pleased to share with you the 2017 We invite you to revisit the 2012-2016 Report which contains a comprehensive Annual Report of the European Research Institute description of ERIBA’s research avenues and an extensive compilation of ongoing projects (see link below). for the Biology of Ageing. It has now been five Foreword The current Report provides a summary of the 2017 activities we want to draw years since our doors opened in 2012, and I am special attention to. A lot of good news: more excellent papers, more happy and proud to say that it has been a employees, more PhD students, more interns. Foreword tremendous journey. 6 Furthermore, we successfully organized for the second time the Molecular 7 Biology of Ageing Meeting, with the participation of a large number of well We built an Institute from scratch.
    [Show full text]
  • Methods Favoring Homology-Directed Repair Choice in Response to CRISPR/Cas9 Induced-Double Strand Breaks
    International Journal of Molecular Sciences Review Methods Favoring Homology-Directed Repair Choice in Response to CRISPR/Cas9 Induced-Double Strand Breaks Han Yang y, Shuling Ren y, Siyuan Yu, Haifeng Pan, Tingdong Li *, Shengxiang Ge *, Jun Zhang and Ningshao Xia State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Disease, Collaborative Innovation Centers of Biological Products, School of Public Health, Xiamen University, Xiamen 361102, China; [email protected] (H.Y.); [email protected] (S.R.); [email protected] (S.Y.); [email protected] (H.P.); [email protected] (J.Z.); [email protected] (N.X.) * Correspondence: [email protected] (T.L.); [email protected] (S.G.); Tel.: +86-0592-2183111 (T.L. & S.G.) These authors contributed equally to this work. y Received: 30 July 2020; Accepted: 1 September 2020; Published: 4 September 2020 Abstract: Precise gene editing is—or will soon be—in clinical use for several diseases, and more applications are under development. The programmable nuclease Cas9, directed by a single-guide RNA (sgRNA), can introduce double-strand breaks (DSBs) in target sites of genomic DNA, which constitutes the initial step of gene editing using this novel technology. In mammals, two pathways dominate the repair of the DSBs—nonhomologous end joining (NHEJ) and homology-directed repair (HDR)—and the outcome of gene editing mainly depends on the choice between these two repair pathways. Although HDR is attractive for its high fidelity, the choice of repair pathway is biased in a biological context.
    [Show full text]
  • How Many Human Proteoforms Are There?
    HHS Public Access Author manuscript Author ManuscriptAuthor Manuscript Author Nat Chem Manuscript Author Biol. Author Manuscript Author manuscript; available in PMC 2019 February 14. Published in final edited form as: Nat Chem Biol. 2018 February 14; 14(3): 206–214. doi:10.1038/nchembio.2576. How many human proteoforms are there? A full list of authors and affiliations appears at the end of the article. Abstract Despite decades of accumulated knowledge about proteins and their post-translational modifications (PTMs), numerous questions remain regarding their molecular composition and biological function. One of the most fundamental queries is the extent to which the combinations of DNA-, RNA- and PTM-level variations explode the complexity of the human proteome. Here, we outline what we know from current databases and measurement strategies including mass spectrometry–based proteomics. In doing so, we examine prevailing notions about the number of modifications displayed on human proteins and how they combine to generate the protein diversity underlying health and disease. We frame central issues regarding determination of protein-level variation and PTMs, including some paradoxes present in the field today. We use this framework to assess existing data and to ask the question, “How many distinct primary structures of proteins (proteoforms) are created from the 20,300 human genes?” We also explore prospects for improving measurements to better regularize protein-level biology and efficiently associate PTMs to function and phenotype. Proteins come in all shapes, sizes and forms. They are deeply involved in the major processes of life and comprise a large and enigmatic space between human genetics and diverse phenotypes of both wellness and disease.
    [Show full text]