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Jones EF, Haldar A, Oza VH, Lasseigne BN. Quantifying transcriptome diversity: a review. Brief Funct Genomics 2024; 23:83-94. [PMID: 37225889 DOI: 10.1093/bfgp/elad019] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 04/14/2023] [Accepted: 05/05/2023] [Indexed: 05/26/2023] Open
Abstract
Following the central dogma of molecular biology, gene expression heterogeneity can aid in predicting and explaining the wide variety of protein products, functions and, ultimately, heterogeneity in phenotypes. There is currently overlapping terminology used to describe the types of diversity in gene expression profiles, and overlooking these nuances can misrepresent important biological information. Here, we describe transcriptome diversity as a measure of the heterogeneity in (1) the expression of all genes within a sample or a single gene across samples in a population (gene-level diversity) or (2) the isoform-specific expression of a given gene (isoform-level diversity). We first overview modulators and quantification of transcriptome diversity at the gene level. Then, we discuss the role alternative splicing plays in driving transcript isoform-level diversity and how it can be quantified. Additionally, we overview computational resources for calculating gene-level and isoform-level diversity for high-throughput sequencing data. Finally, we discuss future applications of transcriptome diversity. This review provides a comprehensive overview of how gene expression diversity arises, and how measuring it determines a more complete picture of heterogeneity across proteins, cells, tissues, organisms and species.
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Affiliation(s)
- Emma F Jones
- The Department of Cell, Developmental and Integrative Biology, Heersink School of Medicine, The University of Alabama at Birmingham, Birmingham, AL, USA
| | - Anisha Haldar
- The Department of Cell, Developmental and Integrative Biology, Heersink School of Medicine, The University of Alabama at Birmingham, Birmingham, AL, USA
| | - Vishal H Oza
- The Department of Cell, Developmental and Integrative Biology, Heersink School of Medicine, The University of Alabama at Birmingham, Birmingham, AL, USA
| | - Brittany N Lasseigne
- The Department of Cell, Developmental and Integrative Biology, Heersink School of Medicine, The University of Alabama at Birmingham, Birmingham, AL, USA
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O’Connor LM, O’Connor BA, Zeng J, Lo CH. Data Mining of Microarray Datasets in Translational Neuroscience. Brain Sci 2023; 13:1318. [PMID: 37759919 PMCID: PMC10527016 DOI: 10.3390/brainsci13091318] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 09/04/2023] [Accepted: 09/10/2023] [Indexed: 09/29/2023] Open
Abstract
Data mining involves the computational analysis of a plethora of publicly available datasets to generate new hypotheses that can be further validated by experiments for the improved understanding of the pathogenesis of neurodegenerative diseases. Although the number of sequencing datasets is on the rise, microarray analysis conducted on diverse biological samples represent a large collection of datasets with multiple web-based programs that enable efficient and convenient data analysis. In this review, we first discuss the selection of biological samples associated with neurological disorders, and the possibility of a combination of datasets, from various types of samples, to conduct an integrated analysis in order to achieve a holistic understanding of the alterations in the examined biological system. We then summarize key approaches and studies that have made use of the data mining of microarray datasets to obtain insights into translational neuroscience applications, including biomarker discovery, therapeutic development, and the elucidation of the pathogenic mechanisms of neurodegenerative diseases. We further discuss the gap to be bridged between microarray and sequencing studies to improve the utilization and combination of different types of datasets, together with experimental validation, for more comprehensive analyses. We conclude by providing future perspectives on integrating multi-omics, to advance precision phenotyping and personalized medicine for neurodegenerative diseases.
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Affiliation(s)
- Lance M. O’Connor
- College of Biological Sciences, University of Minnesota, Minneapolis, MN 55455, USA;
| | - Blake A. O’Connor
- School of Pharmacy, University of Wisconsin, Madison, WI 53705, USA;
| | - Jialiu Zeng
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 308232, Singapore;
| | - Chih Hung Lo
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 308232, Singapore;
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Costa C, de Jesus J, Nikula C, Murta T, Grime GW, Palitsin V, Webb R, Goodwin RJA, Bunch J, Bailey MJ. Exploring New Methods to Study and Moderate Proton Beam Damage for Multimodal Imaging on a Single Tissue Section. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2022; 33:2263-2272. [PMID: 36398943 PMCID: PMC9732869 DOI: 10.1021/jasms.2c00226] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 11/01/2022] [Accepted: 11/07/2022] [Indexed: 06/16/2023]
Abstract
Characterizing proton beam damage in biological materials is of interest to enable the integration of proton microprobe elemental mapping techniques with other imaging modalities. It is also of relevance to obtain a deeper understanding of mechanical damage to lipids in tissues during proton beam cancer therapy. We have developed a novel strategy to characterize proton beam damage to lipids in biological tissues based on mass spectrometry imaging. This methodology is applied to characterize changes to lipids in tissues ex vivo, irradiated under different conditions designed to mitigate beam damage. This work shows that performing proton beam irradiation at ambient pressure, as well as including the application of an organic matrix prior to irradiation, can reduce damage to lipids in tissues. We also discovered that, irrespective of proton beam irradiation, placing a sample in a vacuum prior to desorption electrospray ionization imaging can enhance lipid signals, a conclusion that may be of future benefit to the mass spectrometry imaging community.
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Affiliation(s)
- Catia Costa
- University
of Surrey Ion Beam Centre, Guildford, Surrey GU2 7XH, U.K.
| | - Janella de Jesus
- Department
of Chemistry, University of Surrey, Guildford, Surrey GU2 7XH, U.K.
- The
National Physical Laboratory, Teddington, Middlesex TW11 0LW, U.K.
| | - Chelsea Nikula
- The
National Physical Laboratory, Teddington, Middlesex TW11 0LW, U.K.
| | - Teresa Murta
- The
National Physical Laboratory, Teddington, Middlesex TW11 0LW, U.K.
| | - Geoffrey W. Grime
- University
of Surrey Ion Beam Centre, Guildford, Surrey GU2 7XH, U.K.
| | - Vladimir Palitsin
- University
of Surrey Ion Beam Centre, Guildford, Surrey GU2 7XH, U.K.
| | - Roger Webb
- University
of Surrey Ion Beam Centre, Guildford, Surrey GU2 7XH, U.K.
| | - Richard J. A. Goodwin
- Imaging
and Data Analytics, Clinical Pharmacology and Safety Science, R&D, AstraZeneca, Cambridge CB4 0WG, U.K.
- Institute
of Infection, Immunity and Inflammation, College of Medical, Veterinary
and Life Sciences, University of Glasgow, Glasgow G61 1QH, U.K.
| | - Josephine Bunch
- The
National Physical Laboratory, Teddington, Middlesex TW11 0LW, U.K.
| | - Melanie Jane Bailey
- University
of Surrey Ion Beam Centre, Guildford, Surrey GU2 7XH, U.K.
- Department
of Chemistry, University of Surrey, Guildford, Surrey GU2 7XH, U.K.
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From single-omics to interactomics: How can ligand-induced perturbations modulate single-cell phenotypes? ADVANCES IN PROTEIN CHEMISTRY AND STRUCTURAL BIOLOGY 2022; 131:45-83. [PMID: 35871896 DOI: 10.1016/bs.apcsb.2022.05.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
Cells suffer from perturbations by different stimuli, which, consequently, rise to individual alterations in their profile and function that may end up affecting the tissue as a whole. This is no different if we consider the effect of a therapeutic agent on a biological system. As cells are exposed to external ligands their profile can change at different single-omics levels. Detecting how these changes take place through different sequencing technologies is key to a better understanding of the effects of therapeutic agents. Single-cell RNA-sequencing stands out as one of the most common approaches for cell profiling and perturbation analysis. As a result, single-cell transcriptomics data can be integrated with other omics data sources, such as proteomics and epigenomics data, to clarify the perturbation effects and mechanism at the cell level. Appropriate computational tools are key to process and integrate the available information. This chapter focuses on the recent advances on ligand-induced perturbation and single-cell omics computational tools and algorithms, their current limitations, and how the deluge of data can be used to improve the current process of drug research and development.
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Recent Developments in Clinical Plasma Proteomics—Applied to Cardiovascular Research. Biomedicines 2022; 10:biomedicines10010162. [PMID: 35052841 PMCID: PMC8773619 DOI: 10.3390/biomedicines10010162] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Revised: 01/05/2022] [Accepted: 01/12/2022] [Indexed: 01/27/2023] Open
Abstract
The human plasma proteome mirrors the physiological state of the cardiovascular system, a fact that has been used to analyze plasma biomarkers in routine analysis for the diagnosis and monitoring of cardiovascular diseases for decades. These biomarkers address, however, only a very limited subset of cardiovascular diseases, such as acute myocardial infarct or acute deep vein thrombosis, and clinical plasma biomarkers for the diagnosis and stratification cardiovascular diseases that are growing in incidence, such as heart failure and abdominal aortic aneurysm, do not exist and are urgently needed. The discovery of novel biomarkers in plasma has been hindered by the complexity of the human plasma proteome that again transforms into an extreme analytical complexity when it comes to the discovery of novel plasma biomarkers. This complexity is, however, addressed by recent achievements in technologies for analyzing the human plasma proteome, thereby facilitating the possibility for novel biomarker discoveries. The aims of this article is to provide an overview of the recent achievements in technologies for proteomic analysis of the human plasma proteome and their applications in cardiovascular medicine.
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Peng S, Petersen JL, Bellone RR, Kalbfleisch T, Kingsley NB, Barber AM, Cappelletti E, Giulotto E, Finno CJ. Decoding the Equine Genome: Lessons from ENCODE. Genes (Basel) 2021; 12:genes12111707. [PMID: 34828313 PMCID: PMC8625040 DOI: 10.3390/genes12111707] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 10/24/2021] [Accepted: 10/26/2021] [Indexed: 12/23/2022] Open
Abstract
The horse reference genome assemblies, EquCab2.0 and EquCab3.0, have enabled great advancements in the equine genomics field, from tools to novel discoveries. However, significant gaps of knowledge regarding genome function remain, hindering the study of complex traits in horses. In an effort to address these gaps and with inspiration from the Encyclopedia of DNA Elements (ENCODE) project, the equine Functional Annotation of Animal Genome (FAANG) initiative was proposed to bridge the gap between genome and gene expression, providing further insights into functional regulation within the horse genome. Three years after launching the initiative, the equine FAANG group has generated data from more than 400 experiments using over 50 tissues, targeting a variety of regulatory features of the equine genome. In this review, we examine how valuable lessons learned from the ENCODE project informed our decisions in the equine FAANG project. We report the current state of the equine FAANG project and discuss how FAANG can serve as a template for future expansion of functional annotation in the equine genome and be used as a reference for studies of complex traits in horse. A well-annotated reference functional atlas will also help advance equine genetics in the pan-genome and precision medicine era.
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Affiliation(s)
- Sichong Peng
- Department of Population Health and Reproduction, School of Veterinary Medicine, University of California-Davis, Davis, CA 95616, USA; (S.P.); (R.R.B.); (N.B.K.)
| | - Jessica L. Petersen
- Department of Animal Science, University of Nebraska, Lincoln, NE 68583-0908, USA; (J.L.P.); (A.M.B.)
| | - Rebecca R. Bellone
- Department of Population Health and Reproduction, School of Veterinary Medicine, University of California-Davis, Davis, CA 95616, USA; (S.P.); (R.R.B.); (N.B.K.)
- Veterinary Genetics Laboratory, School of Veterinary Medicine, University of California, Davis, CA 95616, USA
| | - Ted Kalbfleisch
- Department of Veterinary Science, Gluck Equine Research Center, University of Kentucky, Lexington, KY 40503, USA;
| | - N. B. Kingsley
- Department of Population Health and Reproduction, School of Veterinary Medicine, University of California-Davis, Davis, CA 95616, USA; (S.P.); (R.R.B.); (N.B.K.)
- Veterinary Genetics Laboratory, School of Veterinary Medicine, University of California, Davis, CA 95616, USA
| | - Alexa M. Barber
- Department of Animal Science, University of Nebraska, Lincoln, NE 68583-0908, USA; (J.L.P.); (A.M.B.)
| | - Eleonora Cappelletti
- Department of Biology and Biotechnology “L. Spallanzani”, University of Pavia, 27100 Pavia, Italy; (E.C.); (E.G.)
| | - Elena Giulotto
- Department of Biology and Biotechnology “L. Spallanzani”, University of Pavia, 27100 Pavia, Italy; (E.C.); (E.G.)
| | - Carrie J. Finno
- Department of Population Health and Reproduction, School of Veterinary Medicine, University of California-Davis, Davis, CA 95616, USA; (S.P.); (R.R.B.); (N.B.K.)
- Correspondence:
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