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      Evolution, structure and emerging roles of C1ORF112 in DNA replication, DNA damage responses, and cancer

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          Abstract

          The C1ORF112 gene initially drew attention when it was found to be strongly co‐expressed with several genes previously associated with cancer and implicated in DNA repair and cell cycle regulation, such as RAD51 and the BRCA genes. The molecular functions of C1ORF112 remain poorly understood, yet several studies have uncovered clues as to its potential functions. Here, we review the current knowledge on C1ORF112 biology, its evolutionary history, possible functions, and its potential relevance to cancer. C1ORF112 is conserved throughout eukaryotes, from plants to humans, and is very highly conserved in primates. Protein models suggest that C1ORF112 is an alpha-helical protein. Interestingly, homozygous knockout mice are not viable, suggesting an essential role for C1ORF112 in mammalian development. Gene expression data show that, among human tissues, C1ORF112 is highly expressed in the testes and overexpressed in various cancers when compared to healthy tissues. C1ORF112 has also been shown to have altered levels of expression in some tumours with mutant TP53. Recent screens associate C1ORF112 with DNA replication and reveal possible links to DNA damage repair pathways, including the Fanconi anaemia pathway and homologous recombination. These insights provide important avenues for future research in our efforts to understand the functions and potential disease relevance of C1ORF112.

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          MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability

          We report a major update of the MAFFT multiple sequence alignment program. This version has several new features, including options for adding unaligned sequences into an existing alignment, adjustment of direction in nucleotide alignment, constrained alignment and parallel processing, which were implemented after the previous major update. This report shows actual examples to explain how these features work, alone and in combination. Some examples incorrectly aligned by MAFFT are also shown to clarify its limitations. We discuss how to avoid misalignments, and our ongoing efforts to overcome such limitations.
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            Basic local alignment search tool.

            A new approach to rapid sequence comparison, basic local alignment search tool (BLAST), directly approximates alignments that optimize a measure of local similarity, the maximal segment pair (MSP) score. Recent mathematical results on the stochastic properties of MSP scores allow an analysis of the performance of this method as well as the statistical significance of alignments it generates. The basic algorithm is simple and robust; it can be implemented in a number of ways and applied in a variety of contexts including straightforward DNA and protein sequence database searches, motif searches, gene identification searches, and in the analysis of multiple regions of similarity in long DNA sequences. In addition to its flexibility and tractability to mathematical analysis, BLAST is an order of magnitude faster than existing sequence comparison tools of comparable sensitivity.
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              IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies

              Large phylogenomics data sets require fast tree inference methods, especially for maximum-likelihood (ML) phylogenies. Fast programs exist, but due to inherent heuristics to find optimal trees, it is not clear whether the best tree is found. Thus, there is need for additional approaches that employ different search strategies to find ML trees and that are at the same time as fast as currently available ML programs. We show that a combination of hill-climbing approaches and a stochastic perturbation method can be time-efficiently implemented. If we allow the same CPU time as RAxML and PhyML, then our software IQ-TREE found higher likelihoods between 62.2% and 87.1% of the studied alignments, thus efficiently exploring the tree-space. If we use the IQ-TREE stopping rule, RAxML and PhyML are faster in 75.7% and 47.1% of the DNA alignments and 42.2% and 100% of the protein alignments, respectively. However, the range of obtaining higher likelihoods with IQ-TREE improves to 73.3-97.1%.
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                Author and article information

                Contributors
                jp@senescence.info
                Journal
                Cell Mol Life Sci
                Cell Mol Life Sci
                Cellular and Molecular Life Sciences
                Springer International Publishing (Cham )
                1420-682X
                1420-9071
                24 February 2021
                24 February 2021
                2021
                : 78
                : 9
                : 4365-4376
                Affiliations
                [1 ]GRID grid.10025.36, ISNI 0000 0004 1936 8470, Integrative Genomics of Ageing Group, Institute of Ageing and Chronic Disease, , University of Liverpool, ; Liverpool, L7 8TX UK
                [2 ]GRID grid.7119.e, ISNI 0000 0004 0487 459X, Programa de Doctorado en Ciencias mención Ecología Y Evolución, Facultad de Ciencias, , Instituto de Ciencias Ambientales Y Evolutivas, Universidad Austral de Chile, ; Valdivia, 5090000 Chile
                [3 ]GRID grid.265008.9, ISNI 0000 0001 2166 5843, Department of Biochemistry and Molecular Biology, , Thomas Jefferson University, ; Philadelphia, PA 19107 USA
                [4 ]GRID grid.10025.36, ISNI 0000 0004 1936 8470, Institute of Systems, Molecular and Integrative Biology, , University of Liverpool, ; Liverpool, L69 7ZB UK
                [5 ]GRID grid.410595.c, ISNI 0000 0001 2230 9154, Institute of Aging Research, School of Medicine, , Hangzhou Normal University, ; Hangzhou, China
                [6 ]GRID grid.4494.d, ISNI 0000 0000 9558 4598, Department of Endocrinology, , University of Groningen, University Medical Center Groningen, ; Hanzeplein 1, 9713 GZ Groningen, The Netherlands
                [7 ]Ancora Health, Herestraat 106, 9711 LM Groningen, The Netherlands
                [8 ]GRID grid.9613.d, ISNI 0000 0001 1939 2794, Faculty of Biological Sciences, , Friedrich Schiller University, ; Jena, Germany
                Author information
                http://orcid.org/0000-0002-4778-5955
                http://orcid.org/0000-0002-6363-2465
                Article
                3789
                10.1007/s00018-021-03789-8
                8164572
                33625522
                856fbf36-63a0-4a5e-b7e8-6b36e2e8226c
                © The Author(s) 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
                : 28 September 2020
                : 28 January 2021
                : 9 February 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100004440, Wellcome Trust;
                Award ID: 208375/Z/17/Z
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000268, Biotechnology and Biological Sciences Research Council;
                Award ID: BB/R014949/1
                Award Recipient :
                Categories
                Review
                Custom metadata
                © Springer Nature Switzerland AG 2021

                Molecular biology
                bc055324,dna repair,oncogene,tumour,fanconi anaemia
                Molecular biology
                bc055324, dna repair, oncogene, tumour, fanconi anaemia

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