Arakelyan, Arsen

Binder, Hans

English

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genesG C A TT A C GG C A TEditorialSpecial Issue “Disentangling Mechanisms ofGenomic Regulation of Cell Functions at theGene Level”Hans Binder 1,* and Arsen Arakelyan 21 IZBI, Interdisciplinary Centre for Bioinformatics, Universität Leipzig, Härtelstr. 16–18,04107 Leipzig, Germany2 Research Group of Bioinformatics, Institute of Molecular Biology NAS RA, 7 Hasratyan st,Yerevan 0014, Armenia; aarakelyan@sci.am* Correspondence: binder@izbi.uni-leipzig.de; Tel.: +49-341-9716671; Fax: +49-341-16679Received: 4 December 2020; Accepted: 5 December 2020; Published: 7 December 2020The term “gene” was introduced more than a hundred years ago to define a “fundamental physicaland functional unit of heredity” [1]. Its use refers back to Mendel’s idea about discrete hereditableunits, and it also serves as a reminiscence of Darwin’s pangenesis theory. Watson and Crick’sdouble helix discovery in 1962, which rationalized the molecular basis of replication and Crick’scentral dogma, claiming the one-directional information flow from DNA to proteins via RNA,conceptually represent milestones linking heredity with traits, and thus, genes with cellular function.From a practical perspective, after first determination of a gene sequence (coding bacteriophage MS2coat protein, 1972), discoveries of Sanger sequencing (1977) and polymerase chain reaction (1983)mark technological milestones that enabled the decoding of the human genome until the end ofthe 20th century and, with the advent of expression microarray technology, the deciphering of thehuman transcriptome during the following decade (ENCODE project). Instead of solving the basicmysteries of life, these discoveries probably raised more questions about gene functioning than theyanswered. RNA appeared as a complex information flow machinery with highly specific nucleotideinteractions fulfilling a large variety of functions in fine-tuning gene activity beyond transcription andtranslation. Moreover, DNA appeared not only as a one-dimensional textbook of the genetic code asthought previously. Instead, it was found to represent a highly complex three-dimensional polymer,where genetic information is managed via a multitude of conformations, interactions, and molecularcomponents. Information management includes many tasks, such as reading, writing, erasing,repairing, transferring, and translating, where each of these steps must act in a proper way in space andtime to ensure the functioning of life on cellular and organismal levels. Now, the central dogma appearsless dogmatic because of the multidirectional nature of these interactions including feedback loopsfrom the transcribed and translated parts towards their information source. Biological informationmanagement involves epigenetic mechanisms forming another feedback loop linking the phenotypeand environmental factors back to genetics. Presently, diverse variants of next-generation sequencingtechnologies that have now reached single-cell resolution together with advanced metabolomicsand proteomics methods provide an immensely powerful toolbox to discover mechanisms of genefunctioning on the cellular level with increasing practical impact in healthcare and biotechnology.The latest cutting-edge examples from these areas are immuno-therapy against cancer (Nobel Price inMedicine 2019), CRISPR/Cas9 gene scissor (Nobel Price in Medicine 2020), and the mRNA vaccinationtechnique just now becoming a sword against COVID-19.This Special Issue collects seven publications addressing different topics around genomic regulationof cell functions at the gene level as examples illustrating various aspects of this field of discovery.Two original research publications deal with temporal aspects stored in the genome on completelyGenes 2020, 11, 1463; doi:10.3390/genes11121463 www.mdpi.com/journal/genesGenes 2020, 11, 1463 2 of 3different timescales; one on the scale of thousands of years and the other on the scale of minutesto hours [2,3]. Both works make use of similarity relations, with one considering the genomes ofvine accessions [2] and the other considering the transcriptomes of single cells extracted from theflatworm [3]. The vine genome reveals “slow” mutational modifications, which enable reconstructingpaths of distribution of wine agriculture and usage from the Middle East towards Western Europe on along time-scale over many centuries. The single-cell transcriptome of the flatworm, on the other hand,reflects relatively “fast” changes of cellular programs upon differentiation of tissues proceeding ona much shorter time scale. Both applications illustrate the impact of another methodical ingredient,namely bioinformatics (also called computational biology), in order to process huge amounts of datagenerated by the novel high-throughput technologies and to “translate” them into useful (systems)biological information. Algorithmic developments, data science, and computational pipelines foreffective practical use are inevitable parts of realizing “from-gene-to-cell-function” discoveries. Due tothe size, and most importantly, the complex, often unknown intrinsic relations between the data,machine learning is an adequate approach to extract hidden information from the data. Both papersapply self-organizing map machine learning as a so-called “molecular portrayal” approach becausedata are reduced into handy dimensions and visualized in terms of easy-to-interpret images on an“individual” basis, e.g., for each measured unit (vine accession or worm single cell, respectively),making it an interesting approach for personalized medicine as well.A topic with a medical impact has been presented in the paper of Filipenko et al. [4], who reportedthat the protective properties of a peptide drug (Semax) against ischemic stroke are associated withthe compensation of mRNA expression patterns that are disrupted during ischaemic conditions.Leitao et al. [5] reviewed the geographic distribution of genetic variants of the CYP2D6 gene which areassociated with different metabolization profiles, with a focus on Amerindian populations. This studyunderlines the impact of genomic variability on lifestyle factors and disease incidence in differentethnicities. In their in silico study, Chetta et al. [6] addressed mechanisms of the small noncoding RNAlevel of genomic regulation, a field that has risen in importance only in the last 15 years. Short sequencemotifs of micro- and pi-RNA transcribed from non- (protein) coding regions of the DNA modifyactivity via binding to mRNA and transposons, and in this way, form intricate molecular networksbetween the different RNA-species and transcription factors with high impact for genomic regulation.Khokhlova et al. [7] reviewed DNA repair mechanisms in the early stages of mammalian embryonicdevelopment. In general, DNA repair links cell activity back to the genome because improper functioncauses errors in the genetic code to accumulate and result in the appearance of diseases and/or geneticdrifts. Mutations that occur in somatic cells lead to dysfunction in certain tissues or organs, while aviolation of genomic integrity during the embryonic period often leads to death. A mammalianembryo’s ability to respond to damaged DNA and repair it, as well as its sensitivity to specific lesions,is not well understood. In their review, Lesne et al. [8] addressed a supramolecular aspect of genomicregulation, particularly the formation of nuclear bodies, membraneless organelles with crucial impactin regulating genome functions by promoting efficient interactions between distant genomic regions ofthe same or different chromosomes.Overall, this collection of four original research papers and three reviews covers a series ofmechanisms of genomic regulation and bioinformatics methods for their analysis; it provides examplesand applications ranging from biotechnology to developmental biology to healthcare which willbe of interest to researchers in different fields of molecular biology and medicine, agriculture,and computational biology.Funding: This research received no external funding.Conflicts of Interest: The authors declare no conflict of interest.Genes 2020, 11, 1463 3 of 3References1. Noble, D. Genes and causation. Philos. Trans. R. Soc. A Math. Phys. Eng. Sci. 2008, 366, 3001–3015.[CrossRef] [PubMed]2. Nikoghosyan, M.; Schmidt, M.; Margaryan, K.; Loeffler-Wirth, H.; Arakelyan, A.; Binder, H. SOMmelier—IntuitiveVisualization of the Topology of Grapevine Genome Landscapes Using Artificial Neural Networks. Genes 2020,11, 817. [CrossRef] [PubMed]3. Schmidt, M.; Loeffler-Wirth, H.; Binder, H. Developmental scRNAseq Trajectories in Gene- and Cell-StateSpace—The Flatworm Example. Genes 2020, 11, 1214. [CrossRef] [PubMed]4. Filippenkov, I.B.; Stavchansky, V.V.; Denisova, A.E.; Yuzhakov, V.V.; Sevan’kaeva, L.E.; Sudarkina, O.Y.;Dmitrieva, V.G.; Gubsky, L.V.; Myasoedov, N.F.; Limborska, S.A.; et al. Novel Insights into theProtective Properties of ACTH(4-7)PGP (Semax) Peptide at the Transcriptome Level Following CerebralIschaemia–Reperfusion in Rats. Genes 2020, 11, 681. [CrossRef] [PubMed]5. Leitão, L.P.C.; Souza, T.P.; Rodrigues, J.C.G.; Fernandes, M.R.; Santos, S.; Santos, N.P.C. The MetabolizationProfile of the CYP2D6 Gene in Amerindian Populations: A Review. Genes 2020, 11, 262. [CrossRef] [PubMed]6. Chetta, M.; Di Pietro, L.; Bukvic, N.; Lattanzi, W. Rising Roles of Small Noncoding RNAs in CotranscriptionalRegulation: In Silico Study of miRNA and piRNA Regulatory Network in Humans. Genes 2020, 11, 482.[CrossRef] [PubMed]7. Khokhlova, E.V.; Fesenko, Z.S.; Sopova, J.V.; Leonova, E.I. Features of DNA Repair in the Early Stages ofMammalian Embryonic Development. Genes 2020, 11, 1138. [CrossRef] [PubMed]8. Lesne, A.; Baudement, M.-O.; Rebouissou, C.; Forné, T. Exploring Mammalian Genome within Phase-SeparatedNuclear Bodies: Experimental Methods and Implications for Gene Expression. Genes 2019, 10, 1049.[CrossRef] [PubMed]Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutionalaffiliations.© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open accessarticle distributed under the terms and conditions of the Creative Commons Attribution(CC BY) license (http://creativecommons.org/licenses/by/4.0/).

Special Issue “Disentangling Mechanisms of Genomic Regulation of Cell Functions at the Gene Level”

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Special Issue “Disentangling Mechanisms of Genomic Regulation of Cell Functions at the Gene Level”

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