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      Comparison of the Transcriptional Profiles of Melanocytes from Dark and Light Skinned Individuals under Basal Conditions and Following Ultraviolet-B Irradiation

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          Abstract

          We analysed the whole-genome transcriptional profile of 6 cell lines of dark melanocytes (DM) and 6 of light melanocytes (LM) at basal conditions and after ultraviolet-B (UVB) radiation at different time points to investigate the mechanisms by which melanocytes protect human skin from the damaging effects of UVB. Further, we assessed the effect of different keratinocyte-conditioned media (KCM+ and KCM-) on melanocytes. Our results suggest that an interaction between ribosomal proteins and the P53 signaling pathway may occur in response to UVB in both DM and LM. We also observed that DM and LM show differentially expressed genes after irradiation, in particular at the first 6h after UVB. These are mainly associated with inflammatory reactions, cell survival or melanoma. Furthermore, the culture with KCM+ compared with KCM- had a noticeable effect on LM. This effect includes the activation of various signaling pathways such as the mTOR pathway, involved in the regulation of cell metabolism, growth, proliferation and survival. Finally, the comparison of the transcriptional profiles between LM and DM under basal conditions, and the application of natural selection tests in human populations allowed us to support the significant evolutionary role of MIF and ATP6V0B in the pigmentary phenotype.

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          DnaSP v5: a software for comprehensive analysis of DNA polymorphism data.

          P Librado, J Rozas (2009)
          DnaSP is a software package for a comprehensive analysis of DNA polymorphism data. Version 5 implements a number of new features and analytical methods allowing extensive DNA polymorphism analyses on large datasets. Among other features, the newly implemented methods allow for: (i) analyses on multiple data files; (ii) haplotype phasing; (iii) analyses on insertion/deletion polymorphism data; (iv) visualizing sliding window results integrated with available genome annotations in the UCSC browser. Freely available to academic users from: (http://www.ub.edu/dnasp).
          Article 0 comments Cited 1375 times – based on 0 reviews     Review now
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            A comparison of normalization methods for high density oligonucleotide array data based on variance and bias.

            B.M. Bolstad, R.A Irizarry, M Astrand … (2003)
            When running experiments that involve multiple high density oligonucleotide arrays, it is important to remove sources of variation between arrays of non-biological origin. Normalization is a process for reducing this variation. It is common to see non-linear relations between arrays and the standard normalization provided by Affymetrix does not perform well in these situations. We present three methods of performing normalization at the probe intensity level. These methods are called complete data methods because they make use of data from all arrays in an experiment to form the normalizing relation. These algorithms are compared to two methods that make use of a baseline array: a one number scaling based algorithm and a method that uses a non-linear normalizing relation by comparing the variability and bias of an expression measure. Two publicly available datasets are used to carry out the comparisons. The simplest and quickest complete data method is found to perform favorably. Software implementing all three of the complete data normalization methods is available as part of the R package Affy, which is a part of the Bioconductor project http://www.bioconductor.org. Additional figures may be found at http://www.stat.berkeley.edu/~bolstad/normalize/index.html
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              Significance analysis of microarrays applied to the ionizing radiation response.

              V Tusher, R Tibshirani, G. Chu (2001)
              Microarrays can measure the expression of thousands of genes to identify changes in expression between different biological states. Methods are needed to determine the significance of these changes while accounting for the enormous number of genes. We describe a method, Significance Analysis of Microarrays (SAM), that assigns a score to each gene on the basis of change in gene expression relative to the standard deviation of repeated measurements. For genes with scores greater than an adjustable threshold, SAM uses permutations of the repeated measurements to estimate the percentage of genes identified by chance, the false discovery rate (FDR). When the transcriptional response of human cells to ionizing radiation was measured by microarrays, SAM identified 34 genes that changed at least 1.5-fold with an estimated FDR of 12%, compared with FDRs of 60 and 84% by using conventional methods of analysis. Of the 34 genes, 19 were involved in cell cycle regulation and 3 in apoptosis. Surprisingly, four nucleotide excision repair genes were induced, suggesting that this repair pathway for UV-damaged DNA might play a previously unrecognized role in repairing DNA damaged by ionizing radiation.
              Article 0 comments Cited 509 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Thomas G Hofmann: Role: Editor
                Journal
                Journal ID (nlm-ta): PLoS One
                Journal ID (iso-abbrev): PLoS ONE
                Journal ID (publisher-id): plos
                Journal ID (pmc): plosone
                Title: PLoS ONE
                Publisher: Public Library of Science (San Francisco, CA USA )
                ISSN (Electronic): 1932-6203
                Publication date (Electronic): 5 August 2015
                Publication date Collection: 2015
                Volume: 10
                Issue: 8
                Electronic Location Identifier: e0134911
                Affiliations
                [1 ]Department of Genetics, Physical Anthropology and Animal Physiology. University of the Basque Country UPV/EHU, Leioa, Bizkaia, Spain
                [2 ]Department of Zoology and Animal Cell Biology, University of the Basque Country UPV/EHU, Leioa, Bizkaia, Spain
                [3 ]Department of Cell Biology and Histology. University of the Basque Country UPV/EHU, Leioa, Bizkaia, Spain
                [4 ]BioCruces Health Research Institute, Cruces University Hospital, Cruces-Barakaldo, Bizkaia, Spain
                [5 ]Forensic Genetics Laboratory, Forensic Science Unit, Ertaintza-Basque Country Police, Erandio, Bizkaia, Spain
                [6 ]Dermatology Service, BioCruces Health Research Institute, Cruces University Hospital, Cruces-Barakaldo, Bizkaia, Spain
                [7 ]Department of Medicine, Jaume I University of Castellón, Castellón, Spain
                German Cancer Research Center, GERMANY
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: SL ISZ SA. Performed the experiments: SL ISZ AGG SA. Analyzed the data: SL ISZ SA. Contributed reagents/materials/analysis tools: MDB OG JG CMC NI CR AGG. Wrote the paper: SL ISZ SA.

                [¤]

                Current address: University College London Genetics Institute (UGI). University College London, London, United Kingdom

                Article
                Publisher ID: PONE-D-15-23927
                DOI: 10.1371/journal.pone.0134911
                PMC ID: 4526690
                PubMed ID: 26244334
                SO-VID: 3b190e6f-8933-408b-97ff-53d01d0354e8
                Copyright statement: Copyright @ 2015
                License:

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

                History
                Date received : 2 June 2015
                Date accepted : 16 July 2015
                Page count
                Figures: 4, Tables: 8, Pages: 24
                Funding
                This work was supported by the former Spanish Ministerio de Ciencia e Innovación, project CGL2008-04066/BOS to S.A.; by the Dept. Educación, Universidades e Investigación of the Basque Government, project IT542-10 to C.R.; the University of the Basque Country program UFI11/09; a predoctoral fellowship from the Dept. Educación, Universidades e Investigación of the Basque Government to S.L. (BFI09.248). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Subject: Research Article
                Custom metadata
                Data Availability All microarray data are available from the Gene Expression Omnibus database (Accession Number GSE70280).

                ScienceOpen disciplines: Uncategorized
                Data availability:
                ScienceOpen disciplines: Uncategorized

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