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      What microRNAs could tell us about the human X chromosome

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          Abstract

          MicroRNAs (miRNA) are small-non coding RNAs endowed with great regulatory power, thus playing key roles not only in almost all physiological pathways, but also in the pathogenesis of several diseases. Surprisingly, genomic distribution analysis revealed the highest density of miRNA sequences on the X chromosome; this evolutionary conserved mammalian feature equips females with a larger miRNA machinery than males. However, miRNAs contribution to some X-related conditions, properties or functions is still poorly explored. With the aim to support and focus research in the field, this review analyzes the literature and databases about X-linked miRNAs, trying to understand how miRNAs could contribute to emerging gender-biased functions and pathological mechanisms, such as immunity and cancer. A fine map of miRNA sequences on the X chromosome is reported, and their known functions are discussed; in addition, bioinformatics functional analyses of the whole X-linked miRNA targetome (predicted and validated) were performed. The emerging scenario points to different gaps in the knowledge that should be filled with future experimental investigations, also in terms of possible implications and pathological perspectives for X chromosome aneuploidy syndromes, such as Turner and Klinefelter syndromes.

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          The online version of this article (10.1007/s00018-020-03526-7) contains supplementary material, which is available to authorized users.

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          Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources.

          DAVID bioinformatics resources consists of an integrated biological knowledgebase and analytic tools aimed at systematically extracting biological meaning from large gene/protein lists. This protocol explains how to use DAVID, a high-throughput and integrated data-mining environment, to analyze gene lists derived from high-throughput genomic experiments. The procedure first requires uploading a gene list containing any number of common gene identifiers followed by analysis using one or more text and pathway-mining tools such as gene functional classification, functional annotation chart or clustering and functional annotation table. By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.
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            MicroRNAs: genomics, biogenesis, mechanism, and function.

            MicroRNAs (miRNAs) are endogenous approximately 22 nt RNAs that can play important regulatory roles in animals and plants by targeting mRNAs for cleavage or translational repression. Although they escaped notice until relatively recently, miRNAs comprise one of the more abundant classes of gene regulatory molecules in multicellular organisms and likely influence the output of many protein-coding genes.
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              Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists

              Functional analysis of large gene lists, derived in most cases from emerging high-throughput genomic, proteomic and bioinformatics scanning approaches, is still a challenging and daunting task. The gene-annotation enrichment analysis is a promising high-throughput strategy that increases the likelihood for investigators to identify biological processes most pertinent to their study. Approximately 68 bioinformatics enrichment tools that are currently available in the community are collected in this survey. Tools are uniquely categorized into three major classes, according to their underlying enrichment algorithms. The comprehensive collections, unique tool classifications and associated questions/issues will provide a more comprehensive and up-to-date view regarding the advantages, pitfalls and recent trends in a simpler tool-class level rather than by a tool-by-tool approach. Thus, the survey will help tool designers/developers and experienced end users understand the underlying algorithms and pertinent details of particular tool categories/tools, enabling them to make the best choices for their particular research interests.
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                Author and article information

                Contributors
                nicoletta.potenza@unicampania.it
                Journal
                Cell Mol Life Sci
                Cell Mol Life Sci
                Cellular and Molecular Life Sciences
                Springer International Publishing (Cham )
                1420-682X
                1420-9071
                30 April 2020
                30 April 2020
                2020
                : 77
                : 20
                : 4069-4080
                Affiliations
                [1 ]GRID grid.9841.4, ISNI 0000 0001 2200 8888, Department of Environmental, Biological and Pharmaceutical Sciences and Technologies, , University of Campania “Luigi Vanvitelli”, ; Caserta, Italy
                [2 ]GRID grid.4691.a, ISNI 0000 0001 0790 385X, Pediatric Endocrine Unit, Department of Translational Medical Sciences, , University of Naples Federico II, ; Naples, Italy
                [3 ]GRID grid.154185.c, ISNI 0000 0004 0512 597X, Department of Endocrinology and Internal Medicine, , Aarhus University Hospital, ; Aarhus, Denmark
                [4 ]GRID grid.154185.c, ISNI 0000 0004 0512 597X, Department of Molecular Medicine, , Aarhus University Hospital, ; Aarhus, Denmark
                Author information
                http://orcid.org/0000-0001-5421-3552
                http://orcid.org/0000-0003-1310-3300
                http://orcid.org/0000-0001-5924-1720
                http://orcid.org/0000-0002-9736-792X
                Article
                3526
                10.1007/s00018-020-03526-7
                7854456
                32356180
                34c4f72d-b73b-4a71-bda4-48fae6655cb1
                © The Author(s) 2020, corrected publication 2021

                Open AccessThis 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/.

                History
                : 19 December 2019
                : 18 March 2020
                : 13 April 2020
                Categories
                Review
                Custom metadata
                © Springer Nature Switzerland AG 2020

                Molecular biology
                microrna,x chromosome,turner syndrome,klinefelter syndrome
                Molecular biology
                microrna, x chromosome, turner syndrome, klinefelter syndrome

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