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Perini F, Cendron F, Lasagna E, Cassandro M, Penasa M. Genomic insights into shank and eggshell color in Italian local chickens. Poult Sci 2024; 103:103677. [PMID: 38593544 PMCID: PMC11004871 DOI: 10.1016/j.psj.2024.103677] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Revised: 03/12/2024] [Accepted: 03/14/2024] [Indexed: 04/11/2024] Open
Abstract
Eggshell and shank color in poultry is an intriguing topic of research due to the roles in selection, breed recognition, and environmental adaptation. This study delves into the genomics foundations of shank and eggshell pigmentation in Italian local chickens through genome-wide association studies analysis to uncover the mechanisms governing these phenotypes. To this purpose, 483 animals from 20 local breeds (n = 466) and 2 commercial lines (n = 17) were considered and evaluated for shank and eggshell color. All animals were genotyped using the Affymetrix Axiom 600 K Chicken Genotyping Array. As regards shank color, the most interesting locus was detected on chromosome Z, close to the TYRP1 gene, known to play a key role in avian pigmentation. Additionally, several novel loci and genes associated with shank pigmentation, skin pigmentation, UV protection, and melanocyte regulation were identified (e.g., MTAP, CDKN2A, CDKN2B). In eggshell, fewer significant loci were identified, including SLC7A11 and MITF on chromosomes 4 and 12, respectively, associated with melanocyte processes and pigment synthesis. This comprehensive study shed light on the genetic architecture underlying shank and eggshell color in Italian native chicken breeds, contributing to a better understanding of this phenomenon which plays a role in breed identification and conservation, and has ecological and economic implications.
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Affiliation(s)
- Francesco Perini
- Department of Agronomy, Food, Natural resources, Animals and Environment, University of Padova, Legnaro, Padua 35020, Italy
| | - Filippo Cendron
- Department of Agronomy, Food, Natural resources, Animals and Environment, University of Padova, Legnaro, Padua 35020, Italy.
| | - Emiliano Lasagna
- Department of Agricultural, Food and Environmental Sciences, University of Perugia, Perugia 06121, Italy
| | - Martino Cassandro
- Department of Agronomy, Food, Natural resources, Animals and Environment, University of Padova, Legnaro, Padua 35020, Italy
| | - Mauro Penasa
- Department of Agronomy, Food, Natural resources, Animals and Environment, University of Padova, Legnaro, Padua 35020, Italy
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Becher D, Jmel H, Kheriji N, Sarno S, Kefi R. Genetic landscape of forensic DNA phenotyping markers among Mediterranean populations. Forensic Sci Int 2024; 354:111906. [PMID: 38128201 DOI: 10.1016/j.forsciint.2023.111906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Accepted: 12/02/2023] [Indexed: 12/23/2023]
Abstract
Forensic DNA Phenotyping can reveal the appearance of an unknown individual by predicting the External Visible Characteristics (EVC) from DNA obtained at the crime scene. Our aim is to characterize the genetic landscape of Human identification markers responsible for EVC among Mediterranean populations compared to other worldwide groups. We conducted an exhaustive search for genes involved in EVC variation. Then, variants located on these genes were extracted from public genotypic data of Mediterranean, American, African and East Asiatic populations. The genetic landscape of these Human identification markers, their allelic distribution and admixture analyses, were determined using plink, R and ADMIXTURE softwares. Our results showed that the Mediterranean populations appear close to the Mexican populations and distinguished from sub Saharan African populations living in the USA and from East Asiatic populations. We highlighted a total of 103454 common variants shared between the studied populations and among them, 25 common variants associated with EVC. Interestingly, genotype frequencies results showed that the rs17646946, rs13016869, rs977588, rs1805008 and rs2240751 variants located respectively in the TCHH, PRKCE, OCA2, MC1R and MFSD12 genes are significantly different between the Mediterranean and Asiatic populations. The genotype frequencies of the variants rs977589 and rs7179994 located in the OCA2 gene, and of rs12913832 and rs2240751 located respectively in HERC2 and MFSD12 genes are significantly different between the Mediterranean and American populations. Our work generates a large number of EVC variants that could be a valuable resource for future studies in the forensic field.
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Affiliation(s)
- Dorra Becher
- Laboratory of Biomedical Genomics and Oncogenetics, Institut Pasteur de Tunis, BP 74, 13 Place Pasteur, Tunis 1002, Tunisia; Directorate of Technical and Scientific Police, Sub-Directorate of Forensic and Scientific Laboratories, Tunis,Tunisia; University of Carthage, National Institute of Applied Science and Technology, Tunis, Tunisia
| | - Haifa Jmel
- Laboratory of Biomedical Genomics and Oncogenetics, Institut Pasteur de Tunis, BP 74, 13 Place Pasteur, Tunis 1002, Tunisia; Genetic Typing Service, Institut Pasteur de Tunis, BP 74, 13 Place Pasteur, Tunis 1002, Tunisia; University of Tunis El Manar, 2092 El Manar I, Tunis, Tunisia
| | - Nadia Kheriji
- Laboratory of Biomedical Genomics and Oncogenetics, Institut Pasteur de Tunis, BP 74, 13 Place Pasteur, Tunis 1002, Tunisia; University of Tunis El Manar, 2092 El Manar I, Tunis, Tunisia
| | - Stefania Sarno
- Laboratory of Molecular Anthropology and Centre for Genome Biology, Department of Biological, Geological and Environmental Sciences, University of Bologna, Bologna, Italy
| | - Rym Kefi
- Laboratory of Biomedical Genomics and Oncogenetics, Institut Pasteur de Tunis, BP 74, 13 Place Pasteur, Tunis 1002, Tunisia; Genetic Typing Service, Institut Pasteur de Tunis, BP 74, 13 Place Pasteur, Tunis 1002, Tunisia; University of Tunis El Manar, 2092 El Manar I, Tunis, Tunisia.
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Luo L, Molthoff J, Li Q, Liu Y, Luo S, Li N, Xuan S, Wang Y, Shen S, Bovy AG, Zhao J, Chen X. Identification of candidate genes associated with less-photosensitive anthocyanin phenotype using an EMS mutant ( pind) in eggplant ( Solanum melongena L.). FRONTIERS IN PLANT SCIENCE 2023; 14:1282661. [PMID: 38169942 PMCID: PMC10758619 DOI: 10.3389/fpls.2023.1282661] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Accepted: 11/24/2023] [Indexed: 01/05/2024]
Abstract
Eggplant (Solanum melongena L.) is a highly nutritious and economically important vegetable crop. However, the fruit peel of eggplant often shows poor coloration owing to low-light intensity during cultivation, especially in the winter. The less-photosensitive varieties produce anthocyanin in low light or even dark conditions, making them valuable breeding materials. Nevertheless, genes responsible for anthocyanin biosynthesis in less-photosensitive eggplant varieties are not characterized. In this study, an EMS mutant, named purple in the dark (pind), was used to identify the key genes responsible for less-photosensitive coloration. Under natural conditions, the peel color and anthocyanin content in pind fruits were similar to that of wildtype '14-345'. The bagged pind fruits were light purple, whereas those of '14-345' were white; and the anthocyanin content in the pind fruit peel was significantly higher than that in '14-345'. Genetic analysis revealed that the less-photosensitive trait was controlled by a single dominant gene. The candidate gene was mapped on chromosome 10 in the region 7.72 Mb to 11.71 Mb. Thirty-five differentially expressed genes, including 12 structural genes, such as CHS, CHI, F3H, DFR, ANS, and UFGT, and three transcription factors MYB113, GL3, and TTG2, were identified in pind using RNA-seq. Four candidate genes EGP21875 (myb domain protein 113), EGP21950 (unknown protein), EGP21953 (CAAX amino-terminal protease family protein), and EGP21961 (CAAX amino-terminal protease family protein) were identified as putative genes associated with less-photosensitive anthocyanin biosynthesis in pind. These findings may clarify the molecular mechanisms underlying less-photosensitive anthocyanin biosynthesis in eggplant.
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Affiliation(s)
- Lei Luo
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory of Vegetable Germplasm Innovation and Utilization of Hebei, Collaborative Innovation Center of Vegetable Industry in Hebei, International Joint R & D Center of Hebei Province in Modern Agricultural Biotechnology, College of Horticulture, Hebei Agricultural University, Baoding, China
| | - Jos Molthoff
- Plant Breeding, Wageningen University and Research, Wageningen, Netherlands
| | - Qiang Li
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory of Vegetable Germplasm Innovation and Utilization of Hebei, Collaborative Innovation Center of Vegetable Industry in Hebei, International Joint R & D Center of Hebei Province in Modern Agricultural Biotechnology, College of Horticulture, Hebei Agricultural University, Baoding, China
| | - Ying Liu
- Horticulture and Product Physiology, Wageningen University and Research, Wageningen, Netherlands
| | - Shuangxia Luo
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory of Vegetable Germplasm Innovation and Utilization of Hebei, Collaborative Innovation Center of Vegetable Industry in Hebei, International Joint R & D Center of Hebei Province in Modern Agricultural Biotechnology, College of Horticulture, Hebei Agricultural University, Baoding, China
| | - Na Li
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory of Vegetable Germplasm Innovation and Utilization of Hebei, Collaborative Innovation Center of Vegetable Industry in Hebei, International Joint R & D Center of Hebei Province in Modern Agricultural Biotechnology, College of Horticulture, Hebei Agricultural University, Baoding, China
| | - Shuxin Xuan
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory of Vegetable Germplasm Innovation and Utilization of Hebei, Collaborative Innovation Center of Vegetable Industry in Hebei, International Joint R & D Center of Hebei Province in Modern Agricultural Biotechnology, College of Horticulture, Hebei Agricultural University, Baoding, China
| | - Yanhua Wang
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory of Vegetable Germplasm Innovation and Utilization of Hebei, Collaborative Innovation Center of Vegetable Industry in Hebei, International Joint R & D Center of Hebei Province in Modern Agricultural Biotechnology, College of Horticulture, Hebei Agricultural University, Baoding, China
| | - Shuxing Shen
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory of Vegetable Germplasm Innovation and Utilization of Hebei, Collaborative Innovation Center of Vegetable Industry in Hebei, International Joint R & D Center of Hebei Province in Modern Agricultural Biotechnology, College of Horticulture, Hebei Agricultural University, Baoding, China
| | - Arnaud G. Bovy
- Plant Breeding, Wageningen University and Research, Wageningen, Netherlands
| | - Jianjun Zhao
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory of Vegetable Germplasm Innovation and Utilization of Hebei, Collaborative Innovation Center of Vegetable Industry in Hebei, International Joint R & D Center of Hebei Province in Modern Agricultural Biotechnology, College of Horticulture, Hebei Agricultural University, Baoding, China
| | - Xueping Chen
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory of Vegetable Germplasm Innovation and Utilization of Hebei, Collaborative Innovation Center of Vegetable Industry in Hebei, International Joint R & D Center of Hebei Province in Modern Agricultural Biotechnology, College of Horticulture, Hebei Agricultural University, Baoding, China
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Zhang W, Jin M, Lu Z, Li T, Wang H, Yuan Z, Wei C. Whole Genome Resequencing Reveals Selection Signals Related to Wool Color in Sheep. Animals (Basel) 2023; 13:3265. [PMID: 37893989 PMCID: PMC10603731 DOI: 10.3390/ani13203265] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 10/10/2023] [Accepted: 10/17/2023] [Indexed: 10/29/2023] Open
Abstract
Wool color is controlled by a variety of genes. Although the gene regulation of some wool colors has been studied in relative depth, there may still be unknown genetic variants and control genes for some colors or different breeds of wool that need to be identified and recognized by whole genome resequencing. Therefore, we used whole genome resequencing data to compare and analyze sheep populations of different breeds by population differentiation index and nucleotide diversity ratios (Fst and θπ ratio) as well as extended haplotype purity between populations (XP-EHH) to reveal selection signals related to wool coloration in sheep. Screening in the non-white wool color group (G1 vs. G2) yielded 365 candidate genes, among which PDE4B, GMDS, GATA1, RCOR1, MAPK4, SLC36A1, and PPP3CA were associated with the formation of non-white wool; an enrichment analysis of the candidate genes yielded 21 significant GO terms and 49 significant KEGG pathways (p < 0.05), among which 17 GO terms and 21 KEGG pathways were associated with the formation of non-white wool. Screening in the white wool color group (G2 vs. G1) yielded 214 candidate genes, including ABCD4, VSX2, ITCH, NNT, POLA1, IGF1R, HOXA10, and DAO, which were associated with the formation of white wool; an enrichment analysis of the candidate genes revealed 9 significant GO-enriched pathways and 19 significant KEGG pathways (p < 0.05), including 5 GO terms and 12 KEGG pathways associated with the formation of white wool. In addition to furthering our understanding of wool color genetics, this research is important for breeding purposes.
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Affiliation(s)
- Wentao Zhang
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100193, China; (W.Z.); (M.J.); (T.L.); (H.W.)
| | - Meilin Jin
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100193, China; (W.Z.); (M.J.); (T.L.); (H.W.)
| | - Zengkui Lu
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China;
| | - Taotao Li
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100193, China; (W.Z.); (M.J.); (T.L.); (H.W.)
| | - Huihua Wang
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100193, China; (W.Z.); (M.J.); (T.L.); (H.W.)
| | - Zehu Yuan
- Joint International Research Laboratory of Agriculture and Agri-Product Safety of Ministry of Education of China, Yangzhou University, Yangzhou 225009, China;
| | - Caihong Wei
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100193, China; (W.Z.); (M.J.); (T.L.); (H.W.)
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5
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Orang A, Dredge BK, Liu CY, Bracken JM, Chen CH, Sourdin L, Whitfield HJ, Lumb R, Boyle ST, Davis MJ, Samuel MS, Gregory PA, Khew-Goodall Y, Goodall GJ, Pillman KA, Bracken CP. Basonuclin-2 regulates extracellular matrix production and degradation. Life Sci Alliance 2023; 6:e202301984. [PMID: 37536977 PMCID: PMC10400885 DOI: 10.26508/lsa.202301984] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 07/16/2023] [Accepted: 07/20/2023] [Indexed: 08/05/2023] Open
Abstract
Epithelial-mesenchymal transition is essential for tissue patterning and organization. It involves both regulation of cell motility and alterations in the composition and organization of the ECM-a complex environment of proteoglycans and fibrous proteins essential for tissue homeostasis, signaling in response to chemical and biomechanical stimuli, and is often dysregulated under conditions such as cancer, fibrosis, and chronic wounds. Here, we demonstrate that basonuclin-2 (BNC2), a mesenchymal-expressed gene, that is, strongly associated with cancer and developmental defects across genome-wide association studies, is a novel regulator of ECM composition and degradation. We find that at endogenous levels, BNC2 controls the expression of specific collagens, matrix metalloproteases, and other matrisomal components in breast cancer cells, and in fibroblasts that are primarily responsible for the production and processing of the ECM within the tumour microenvironment. In so doing, BNC2 modulates the motile and invasive properties of cancers, which likely explains the association of high BNC2 expression with increasing cancer grade and poor patient prognosis.
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Affiliation(s)
- Ayla Orang
- Centre for Cancer Biology, An Alliance of SA Pathology and University of South Australia, Adelaide, Australia
| | - B Kate Dredge
- Centre for Cancer Biology, An Alliance of SA Pathology and University of South Australia, Adelaide, Australia
| | - Chi Yau Liu
- Centre for Cancer Biology, An Alliance of SA Pathology and University of South Australia, Adelaide, Australia
| | - Julie M Bracken
- Centre for Cancer Biology, An Alliance of SA Pathology and University of South Australia, Adelaide, Australia
| | - Chun-Hsien Chen
- Centre for Cancer Biology, An Alliance of SA Pathology and University of South Australia, Adelaide, Australia
| | - Laura Sourdin
- Centre for Cancer Biology, An Alliance of SA Pathology and University of South Australia, Adelaide, Australia
| | - Holly J Whitfield
- Division of Bioinformatics, Walter and Eliza Hall Institute of Medical Research, Parkville, Australia
- Department of Medical Biology, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, Australia
| | - Rachael Lumb
- Centre for Cancer Biology, An Alliance of SA Pathology and University of South Australia, Adelaide, Australia
| | - Sarah T Boyle
- Centre for Cancer Biology, An Alliance of SA Pathology and University of South Australia, Adelaide, Australia
| | - Melissa J Davis
- South Australian ImmunogGENomics Cancer Institute, Faculty of Health and Medical Sciences, University of Adelaide, Adelaide, Australia
- Division of Bioinformatics, Walter and Eliza Hall Institute of Medical Research, Parkville, Australia
- Department of Medical Biology, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, Australia
- Department of Clinical Pathology, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, Australia
- Fraser Institute, University of Queensland, Wooloongabba, Australia
| | - Michael S Samuel
- Centre for Cancer Biology, An Alliance of SA Pathology and University of South Australia, Adelaide, Australia
- Adelaide Medical School, Faculty of Health and Medical Sciences, University of Adelaide, Adelaide, Australia
| | - Philip A Gregory
- Centre for Cancer Biology, An Alliance of SA Pathology and University of South Australia, Adelaide, Australia
- Department of Medicine and School of Biological Sciences, University of Adelaide, Adelaide, Australia
| | - Yeesim Khew-Goodall
- Centre for Cancer Biology, An Alliance of SA Pathology and University of South Australia, Adelaide, Australia
- Department of Medicine and School of Biological Sciences, University of Adelaide, Adelaide, Australia
| | - Gregory J Goodall
- Centre for Cancer Biology, An Alliance of SA Pathology and University of South Australia, Adelaide, Australia
- Department of Medicine and School of Biological Sciences, University of Adelaide, Adelaide, Australia
| | - Katherine A Pillman
- Centre for Cancer Biology, An Alliance of SA Pathology and University of South Australia, Adelaide, Australia
- Department of Medicine and School of Biological Sciences, University of Adelaide, Adelaide, Australia
| | - Cameron P Bracken
- Centre for Cancer Biology, An Alliance of SA Pathology and University of South Australia, Adelaide, Australia
- Department of Medicine and School of Biological Sciences, University of Adelaide, Adelaide, Australia
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6
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Aman AJ, Saunders LM, Carr AA, Srivatasan S, Eberhard C, Carrington B, Watkins-Chow D, Pavan WJ, Trapnell C, Parichy DM. Transcriptomic profiling of tissue environments critical for post-embryonic patterning and morphogenesis of zebrafish skin. eLife 2023; 12:RP86670. [PMID: 37695017 PMCID: PMC10495112 DOI: 10.7554/elife.86670] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/12/2023] Open
Abstract
Pigment patterns and skin appendages are prominent features of vertebrate skin. In zebrafish, regularly patterned pigment stripes and an array of calcified scales form simultaneously in the skin during post-embryonic development. Understanding the mechanisms that regulate stripe patterning and scale morphogenesis may lead to the discovery of fundamental mechanisms that govern the development of animal form. To learn about cell types and signaling interactions that govern skin patterning and morphogenesis, we generated and analyzed single-cell transcriptomes of skin from wild-type fish as well as fish having genetic or transgenically induced defects in squamation or pigmentation. These data reveal a previously undescribed population of epidermal cells that express transcripts encoding enamel matrix proteins, suggest hormonal control of epithelial-mesenchymal signaling, clarify the signaling network that governs scale papillae development, and identify a critical role for the hypodermis in supporting pigment cell development. Additionally, these comprehensive single-cell transcriptomic data representing skin phenotypes of biomedical relevance should provide a useful resource for accelerating the discovery of mechanisms that govern skin development and homeostasis.
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Affiliation(s)
- Andrew J Aman
- Department of Biology, University of VirginiaCharlottesvilleUnited States
| | - Lauren M Saunders
- Department of Genome Sciences, University of WashingtonSeattleUnited States
| | - August A Carr
- Department of Biology, University of VirginiaCharlottesvilleUnited States
| | - Sanjay Srivatasan
- Department of Genome Sciences, University of WashingtonSeattleUnited States
| | - Colten Eberhard
- National Human Genome Research Institute, National Institutes of HealthBethesdaUnited States
| | - Blake Carrington
- National Human Genome Research Institute, National Institutes of HealthBethesdaUnited States
| | - Dawn Watkins-Chow
- National Human Genome Research Institute, National Institutes of HealthBethesdaUnited States
| | - William J Pavan
- National Human Genome Research Institute, National Institutes of HealthBethesdaUnited States
| | - Cole Trapnell
- Department of Genome Sciences, University of WashingtonSeattleUnited States
| | - David M Parichy
- Department of Biology, University of VirginiaCharlottesvilleUnited States
- Department of Cell Biology, University of VirginiaCharlottesvilleUnited States
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Farré X, Blay N, Cortés B, Carreras A, Iraola-Guzmán S, de Cid R. Skin Phototype and Disease: A Comprehensive Genetic Approach to Pigmentary Traits Pleiotropy Using PRS in the GCAT Cohort. Genes (Basel) 2023; 14:149. [PMID: 36672889 PMCID: PMC9859115 DOI: 10.3390/genes14010149] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 12/22/2022] [Accepted: 12/26/2022] [Indexed: 01/09/2023] Open
Abstract
Human pigmentation has largely been associated with different disease prevalence among populations, but most of these studies are observational and inconclusive. Known to be genetically determined, pigmentary traits have largely been studied by Genome-Wide Association Study (GWAS), mostly in Caucasian ancestry cohorts from North Europe, identifying robustly, several loci involved in many of the pigmentary traits. Here, we conduct a detailed analysis by GWAS and Polygenic Risk Score (PRS) of 13 pigmentary-related traits in a South European cohort of Caucasian ancestry (n = 20,000). We observed fair phototype strongly associated with non-melanoma skin cancer and other dermatoses and confirmed by PRS-approach the shared genetic basis with skin and eye diseases, such as melanoma (OR = 0.95), non-melanoma skin cancer (OR = 0.93), basal cell carcinoma (OR = 0.97) and darker phototype with vitiligo (OR = 1.02), cataracts (OR = 1.04). Detailed genetic analyses revealed 37 risk loci associated with 10 out of 13 analyzed traits, and 16 genes significantly associated with at least two pigmentary traits. Some of them have been widely reported, such as MC1R, HERC2, OCA2, TYR, TYRP1, SLC45A2, and some novel candidate genes C1QTNF3, LINC02876, and C1QTNF3-AMACR have not been reported in the GWAS Catalog, with regulatory potential. These results highlight the importance of the assess phototype as a genetic proxy of skin functionality and disease when evaluating open mixed populations.
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Affiliation(s)
| | | | | | | | | | - Rafael de Cid
- Genomes for Life-GCAT Lab, Germans Trias i Pujol Research Institute (IGTP), 08916 Badalona, Spain
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8
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Markiewicz E, Idowu OC. Evaluation of Personalized Skincare Through in-silico Gene Interactive Networks and Cellular Responses to UVR and Oxidative Stress. Clin Cosmet Investig Dermatol 2022; 15:2221-2243. [PMID: 36284733 PMCID: PMC9588296 DOI: 10.2147/ccid.s383790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Accepted: 10/13/2022] [Indexed: 11/07/2022]
Abstract
Purpose Personalized approaches in dermatology are designed to match the specific requirements based on the individual genetic makeup. One major factor accounting for the differences in skin phenotypes is single nucleotide polymorphism (SNP) within several genes with diverse roles that extend beyond skin tone and pigmentation. Therefore, the cellular sensitivities to the environmental stress and damage linked to extrinsic aging could also underlie the individual characteristics of the skin and dictate the unique skin care requirements. This study aimed to identify the likely biomarkers and molecular signatures expressed in skin cells of different ethnic backgrounds, which could aid further the design of personalized skin products based on specific demands. Methods Using data mining and in-silico modeling, the association of SNP-affected genes with three major skin types of European, Asian and African origin was analyzed and compared within the structure-function gene interaction networks. Cultured dermal fibroblasts were subsequently subjected to ultraviolet radiation and oxidative stress and analyzed for DNA damage and senescent markers. The protective applications of two cosmetic ingredients, Resveratrol and Quercetin, were validated in both cellular and in-silico models. Results Each skin type was characterized by the presence of SNPs in the genes controlling facultative and constitutive pigmentation, which could also underlie the major differences in responses to photodamage, such as oxidative stress, inflammation, and barrier homeostasis. Skin-type-specific dermal fibroblasts cultured in-vitro demonstrated distinctive sensitivities to ultraviolet radiation and oxidative stress, which could be modulated further by the bioactive compounds with the predicted capacities to interact with some of the genes in the in-silico models. Conclusion Evaluation of the SNP-affected gene networks and likely sensitivities of skin cells, defined as low threshold levels to extrinsic stress factors, can provide a valuable tool for the design and formulation of personalized skin products that match more accurately diverse ethnic backgrounds.
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Affiliation(s)
- Ewa Markiewicz
- Hexis Lab, The Catalyst, Newcastle Helix, Newcastle upon Tyne, UK
| | - Olusola C Idowu
- Hexis Lab, The Catalyst, Newcastle Helix, Newcastle upon Tyne, UK,Correspondence: Olusola C Idowu, HexisLab Limited, The Catalyst, Newcastle Helix, Newcastle upon Tyne, NE4 5TG, UK, Tel +44 1394 825487, Email
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9
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Zhu X, Ni P, Sturrock M, Wang Y, Ding J, Chang Y, Hu J, Bao Z. Fine-mapping and association analysis of candidate genes for papilla number in sea cucumber, Apostichopus japonicus. MARINE LIFE SCIENCE & TECHNOLOGY 2022; 4:343-355. [PMID: 37073167 PMCID: PMC10077181 DOI: 10.1007/s42995-022-00139-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Accepted: 06/03/2022] [Indexed: 05/03/2023]
Abstract
The papilla number is one of the most economically important traits of sea cucumber in the China marketing trade. However, the genetic basis for papilla number diversity in holothurians is still scarce. In the present study, we conducted genome-wide association studies (GWAS) for the trait papilla number of sea cucumbers utilizing a set of 400,186 high-quality SNPs derived from 200 sea cucumbers. Two significant trait-associated SNPs that passed Bonferroni correction (P < 1.25E-7) were located in the intergenic region near PATS1 and the genic region of EIF4G, which were reported to play a pivotal role in cell growth and proliferation. The fine-mapping regions around the top two lead SNPs provided precise causative loci/genes related to papilla formation and cellular activity, including PPP2R3C, GBP1, and BCAS3. Potential SNPs with P < 1E-4 were acquired for the following GO and KEGG enrichment analysis. Moreover, the two lead SNPs were verified in another population of sea cucumber, and the expressive detection of three potential candidate genes PATS1, PPP2R3C, and EIF4G that near or cover the two lead SNPs was conducted in papilla tissue of TG (Top papilla number group) and BG (Bottom papilla number group) by qRT-PCR. We found the significantly higher expression profile of PATS1 (3.34-fold), PPP2R3C (4.90-fold), and EIF4G (4.23-fold) in TG, implying their potential function in papilla polymorphism. The present results provide valuable information to decipher the phenotype differences of the papilla trait and will provide a scientific basis for selective breeding in sea cucumbers. Supplementary Information The online version contains supplementary material available at 10.1007/s42995-022-00139-w.
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Affiliation(s)
- Xinghai Zhu
- Ministry of Education Key Laboratory of Marine Genetics and Breeding, College of Marine Life Sciences, Ocean University of China, Qingdao, 266003 China
| | - Ping Ni
- Ministry of Education Key Laboratory of Marine Genetics and Breeding, College of Marine Life Sciences, Ocean University of China, Qingdao, 266003 China
| | - Marc Sturrock
- Department of Physiology and Medical Physics, Royal College of Surgeons in Ireland, Dublin, D02 YN77 Ireland
| | - Yangfan Wang
- Ministry of Education Key Laboratory of Marine Genetics and Breeding, College of Marine Life Sciences, Ocean University of China, Qingdao, 266003 China
| | - Jun Ding
- College of Fisheries and Life Science, Dalian Ocean University, Dalian, 116023 China
| | - Yaqing Chang
- College of Fisheries and Life Science, Dalian Ocean University, Dalian, 116023 China
| | - Jingjie Hu
- Laboratory of Tropical Marine Germplasm Resources and Breeding Engineering, Sanya Oceanographic Institution, Ocean University of China, Sanya, 572000 China
| | - Zhenmin Bao
- Ministry of Education Key Laboratory of Marine Genetics and Breeding, College of Marine Life Sciences, Ocean University of China, Qingdao, 266003 China
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10
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Kim Y, Yin J, Huang H, Jorgenson E, Choquet H, Asgari MM. Genome-wide association study of actinic keratosis identifies new susceptibility loci implicated in pigmentation and immune regulation pathways. Commun Biol 2022; 5:386. [PMID: 35449187 PMCID: PMC9023580 DOI: 10.1038/s42003-022-03301-3] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Accepted: 03/18/2022] [Indexed: 01/07/2023] Open
Abstract
Actinic keratosis (AK) is a common precancerous cutaneous neoplasm that arises on chronically sun-exposed skin. AK susceptibility has a moderate genetic component, and although a few susceptibility loci have been identified, including IRF4, TYR, and MC1R, additional loci have yet to be discovered. We conducted a genome-wide association study of AK in non-Hispanic white participants of the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort (n = 63,110, discovery cohort), with validation in the Mass-General Brigham (MGB) Biobank cohort (n = 29,130). We identified eleven loci (P < 5 × 10-8), including seven novel loci, of which four novel loci were validated. In a meta-analysis (GERA + MGB), one additional novel locus, TRPS1, was identified. Genes within the identified loci are implicated in pigmentation (SLC45A2, IRF4, BNC2, TYR, DEF8, RALY, HERC2, and TRPS1), immune regulation (FOXP1 and HLA-DQA1), and cell signaling and tissue remodeling (MMP24) pathways. Our findings provide novel insight into the genetics and pathogenesis of AK susceptibility.
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Affiliation(s)
- Yuhree Kim
- Department of Dermatology, Massachusetts General Hospital, Boston, MA, USA
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
| | - Jie Yin
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Hailiang Huang
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | | | - Hélène Choquet
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA.
| | - Maryam M Asgari
- Department of Dermatology, Massachusetts General Hospital, Boston, MA, USA.
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA.
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11
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Huang X, Wang S, Jin L, He Y. Dissecting dynamics and differences of selective pressures in the evolution of human pigmentation. Biol Open 2021; 10:bio056523. [PMID: 33495209 PMCID: PMC7888712 DOI: 10.1242/bio.056523] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2020] [Accepted: 12/21/2020] [Indexed: 01/05/2023] Open
Abstract
Human pigmentation is a highly diverse and complex trait among populations and has drawn particular attention from both academic and non-academic investigators for thousands of years. Previous studies detected selection signals in several human pigmentation genes, but few studies have integrated contribution from multiple genes to the evolution of human pigmentation. Moreover, none has quantified selective pressures on human pigmentation over epochs and between populations. Here, we dissect dynamics and differences of selective pressures during different periods and between distinct populations with new approaches. We use genotype data of 19 genes associated with human pigmentation from 17 publicly available datasets and obtain data for 2346 individuals of six representative population groups from across the world. Our results quantify the strength of natural selection on light pigmentation not only in modern Europeans (0.0259/generation) but also in proto-Eurasians (0.00650/generation). Our results also suggest that several derived alleles associated with human dark pigmentation may be under positive directional selection in some African populations. Our study provides the first attempt to quantitatively investigate the dynamics of selective pressures during different time periods in the evolution of human pigmentation.This article has an associated First Person interview with the first author of the article.
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Affiliation(s)
- Xin Huang
- Chinese Academy of Sciences Key Laboratory of Computational Biology, Chinese Academy of Sciences-Max Planck Society Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Sijia Wang
- Chinese Academy of Sciences Key Laboratory of Computational Biology, Chinese Academy of Sciences-Max Planck Society Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
- State Key Laboratory of Genetic Engineering and Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 200433, China
| | - Li Jin
- Chinese Academy of Sciences Key Laboratory of Computational Biology, Chinese Academy of Sciences-Max Planck Society Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
- State Key Laboratory of Genetic Engineering and Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 200433, China
| | - Yungang He
- Key Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China
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12
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Missaggia BO, Reales G, Cybis GB, Hünemeier T, Bortolini MC. Adaptation and co-adaptation of skin pigmentation and vitamin D genes in native Americans. AMERICAN JOURNAL OF MEDICAL GENETICS PART C-SEMINARS IN MEDICAL GENETICS 2020; 184:1060-1077. [PMID: 33325159 DOI: 10.1002/ajmg.c.31873] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Revised: 11/23/2020] [Accepted: 12/02/2020] [Indexed: 11/06/2022]
Abstract
We carried out an exhaustive review regarding human skin color variation and how much it may be related to vitamin D metabolism and other photosensitive molecules. We discuss evolutionary contexts that modulate this variability and hypotheses postulated to explain them; for example, a small amount of melanin in the skin facilitates vitamin D production, making it advantageous to have fair skin in an environment with little radiation incidence. In contrast, more melanin protects folate from degradation in an environment with a high incidence of radiation. Some Native American populations have a skin color at odds with what would be expected for the amount of radiation in the environment in which they live, a finding challenging the so-called "vitamin D-folate hypothesis." Since food is also a source of vitamin D, dietary habits should also be considered. Here we argue that a gene network approach provides tools to explain this phenomenon since it indicates potential alleles co-evolving in a compensatory way. We identified alleles of the vitamin D metabolism and pigmentation pathways segregated together, but in different proportions, in agriculturalists and hunter-gatherers. Finally, we highlight how an evolutionary approach can be useful to understand current topics of medical interest.
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Affiliation(s)
- Bruna Oliveira Missaggia
- Genetics Departament, Biosciences Institute, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - Guillermo Reales
- Genetics Departament, Biosciences Institute, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - Gabriela B Cybis
- Statistics Department, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - Tábita Hünemeier
- Department of Genetics and Evolutionary Biology, Biosciences Institute, Universidade de São Paulo, São Paulo, SP, Brazil
| | - Maria Cátira Bortolini
- Genetics Departament, Biosciences Institute, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
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13
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Walsh S, Pagani L, Xue Y, Laayouni H, Tyler-Smith C, Bertranpetit J. Positive selection in admixed populations from Ethiopia. BMC Genet 2020; 21:108. [PMID: 33092534 PMCID: PMC7580818 DOI: 10.1186/s12863-020-00908-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Accepted: 08/27/2020] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND In the process of adaptation of humans to their environment, positive or adaptive selection has played a main role. Positive selection has, however, been under-studied in African populations, despite their diversity and importance for understanding human history. RESULTS Here, we have used 119 available whole-genome sequences from five Ethiopian populations (Amhara, Oromo, Somali, Wolayta and Gumuz) to investigate the modes and targets of positive selection in this part of the world. The site frequency spectrum-based test SFselect was applied to idfentify a wide range of events of selection (old and recent), and the haplotype-based statistic integrated haplotype score to detect more recent events, in each case with evaluation of the significance of candidate signals by extensive simulations. Additional insights were provided by considering admixture proportions and functional categories of genes. We identified both individual loci that are likely targets of classic sweeps and groups of genes that may have experienced polygenic adaptation. We found population-specific as well as shared signals of selection, with folate metabolism and the related ultraviolet response and skin pigmentation standing out as a shared pathway, perhaps as a response to the high levels of ultraviolet irradiation, and in addition strong signals in genes such as IFNA, MRC1, immunoglobulins and T-cell receptors which contribute to defend against pathogens. CONCLUSIONS Signals of positive selection were detected in Ethiopian populations revealing novel adaptations in East Africa, and abundant targets for functional follow-up.
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Affiliation(s)
- Sandra Walsh
- Institut de Biologia Evolutiva (UPF-CSIC), Universitat Pompeu Fabra, Dr. Aiguader, 88 08003, Barcelona, Catalonia, Spain
| | - Luca Pagani
- Estonian Biocentre, Institute of Genomics, University of Tartu, 51010, Tartu, Estonia
- Department of Biology, University of Padova, 35131, Padova, Italy
| | - Yali Xue
- The Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SA, UK
| | - Hafid Laayouni
- Institut de Biologia Evolutiva (UPF-CSIC), Universitat Pompeu Fabra, Dr. Aiguader, 88 08003, Barcelona, Catalonia, Spain
- Bioinformatics Studies, ESCI-UPF, Barcelona, Catalonia, Spain
| | - Chris Tyler-Smith
- The Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SA, UK.
| | - Jaume Bertranpetit
- Institut de Biologia Evolutiva (UPF-CSIC), Universitat Pompeu Fabra, Dr. Aiguader, 88 08003, Barcelona, Catalonia, Spain.
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Mughal MR, Koch H, Huang J, Chiaromonte F, DeGiorgio M. Learning the properties of adaptive regions with functional data analysis. PLoS Genet 2020; 16:e1008896. [PMID: 32853200 PMCID: PMC7480868 DOI: 10.1371/journal.pgen.1008896] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Revised: 09/09/2020] [Accepted: 05/29/2020] [Indexed: 12/12/2022] Open
Abstract
Identifying regions of positive selection in genomic data remains a challenge in population genetics. Most current approaches rely on comparing values of summary statistics calculated in windows. We present an approach termed SURFDAWave, which translates measures of genetic diversity calculated in genomic windows to functional data. By transforming our discrete data points to be outputs of continuous functions defined over genomic space, we are able to learn the features of these functions that signify selection. This enables us to confidently identify complex modes of natural selection, including adaptive introgression. We are also able to predict important selection parameters that are responsible for shaping the inferred selection events. By applying our model to human population-genomic data, we recapitulate previously identified regions of selective sweeps, such as OCA2 in Europeans, and predict that its beneficial mutation reached a frequency of 0.02 before it swept 1,802 generations ago, a time when humans were relatively new to Europe. In addition, we identify BNC2 in Europeans as a target of adaptive introgression, and predict that it harbors a beneficial mutation that arose in an archaic human population that split from modern humans within the hypothesized modern human-Neanderthal divergence range.
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Affiliation(s)
- Mehreen R. Mughal
- Bioinformatics and Genomics at the Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania, United States of America
| | - Hillary Koch
- Department of Statistics, Pennsylvania State University, University Park, Pennsylvania, United States of America
| | - Jinguo Huang
- Bioinformatics and Genomics at the Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania, United States of America
| | - Francesca Chiaromonte
- Department of Statistics, Pennsylvania State University, University Park, Pennsylvania, United States of America
| | - Michael DeGiorgio
- Department of Computer and Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, Florida, United States of America
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15
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Andersen JD, Meyer OS, Simão F, Jannuzzi J, Carvalho E, Andersen MM, Pereira V, Børsting C, Morling N, Gusmão L. Skin pigmentation and genetic variants in an admixed Brazilian population of primarily European ancestry. Int J Legal Med 2020; 134:1569-1579. [PMID: 32385594 DOI: 10.1007/s00414-020-02307-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2019] [Accepted: 04/22/2020] [Indexed: 01/16/2023]
Abstract
Although many genes have been shown to be associated with human pigmentary traits and forensic prediction assays exist (e.g. HIrisPlex-S), the genetic knowledge about skin colour remains incomplete. The highly admixed Brazilian population is an interesting study population for investigation of the complex genotype-phenotype architecture of human skin colour because of its large variation. Here, we compared variants in 22 pigmentary genes with quantitative skin pigmentation levels on the buttock, arm, and forehead areas of 266 genetically admixed Brazilian individuals. The genetic ancestry of each individual was estimated by typing 46 AIM-InDels. The mean proportion of genetic ancestry was 68.8% European, 20.8% Sub-Saharan African, and 10.4% Native American. A high correlation (adjusted R2 = 0.65, p < 0.05) was observed between nine SNPs and quantitative skin pigmentation using multiple linear regression analysis. The correlations were notably smaller between skin pigmentation and biogeographic ancestry (adjusted R2 = 0.45, p < 0.05), or markers in the leading forensic skin colour prediction system, the HIrisPlex-S (adjusted R2 = 0.54, p < 0.05). Four of the nine SNPs, OCA2 rs1448484 (rank 2), APBA2 rs4424881 (rank 4), MFSD12 rs10424065 (rank 8), and TYRP1 1408799 (rank 9) were not investigated as part of the HIrisPlex-S selection process, and therefore not included in the HIrisPlex-S model. Our results indicate that these SNPs account for a substantial part of the skin colour variation in individuals of admixed ancestry. Hence, we suggest that these SNPs are considered when developing future skin colour prediction models.
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Affiliation(s)
- Jeppe D Andersen
- Section of Forensic Genetics, Department of Forensic Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, DK-2100, Copenhagen, Denmark.
| | - Olivia S Meyer
- Section of Forensic Genetics, Department of Forensic Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, DK-2100, Copenhagen, Denmark
| | - Filipa Simão
- DNA Diagnostic Laboratory (LDD), Institute of Biology, State University of Rio de Janeiro (UERJ), Rio de Janeiro, Brazil
| | - Juliana Jannuzzi
- DNA Diagnostic Laboratory (LDD), Institute of Biology, State University of Rio de Janeiro (UERJ), Rio de Janeiro, Brazil
| | - Elizeu Carvalho
- DNA Diagnostic Laboratory (LDD), Institute of Biology, State University of Rio de Janeiro (UERJ), Rio de Janeiro, Brazil
| | - Mikkel M Andersen
- Department of Mathematical Sciences, Aalborg University, DK-9000, Aalborg, Denmark
| | - Vania Pereira
- Section of Forensic Genetics, Department of Forensic Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, DK-2100, Copenhagen, Denmark
| | - Claus Børsting
- Section of Forensic Genetics, Department of Forensic Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, DK-2100, Copenhagen, Denmark
| | - Niels Morling
- Section of Forensic Genetics, Department of Forensic Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, DK-2100, Copenhagen, Denmark
| | - Leonor Gusmão
- DNA Diagnostic Laboratory (LDD), Institute of Biology, State University of Rio de Janeiro (UERJ), Rio de Janeiro, Brazil
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16
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Li C, Cai W, Liu S, Zhou C, Cao M, Yin H, Sun D, Zhang S, Loor JJ. Association of UDP-galactose-4-epimerase with milk protein concentration in the Chinese Holstein population. ASIAN-AUSTRALASIAN JOURNAL OF ANIMAL SCIENCES 2020; 33:1725-1731. [PMID: 32106650 PMCID: PMC7649079 DOI: 10.5713/ajas.19.0549] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/08/2019] [Accepted: 02/14/2020] [Indexed: 01/20/2023]
Abstract
Objective An initial RNA-Sequencing study revealed that UDP-galactose-4-epimerase (GALE) was one of the most promising candidates for milk protein concentration in Chinese Holstein cattle. This enzyme catalyzes the interconversion of UDP-galactose and UDP-glucose, an important step in galactose catabolism. To further validate the genetic effect of GALE on milk protein traits, genetic variations were identified, and genotypes-phenotypes associations were performed. Methods The entire coding region and the 5′-regulatory region (5′-UTR) of GALE were re-sequenced using pooled DNA of 17 unrelated sires. Association studies for five milk production traits were performed using a mixed linear animal model with a population encompassing 1,027 Chinese Holstein cows. Results A total of three variants in GALE were identified, including two novel variants (g.2114 A>G and g.2037 G>A) in the 5′-UTR and one previously reported variant (g.3836 G>C) in an intron. All three single nucleotide polymorphisms (SNPs) were associated with milk yield (p<0.0001), fat yield (p = 0.0006 to <0.0001), protein yield (p = 0.0232 to <0.0001) and protein percentage (p<0.0001), while no significant associations were detected between the SNPs and fat percentage. A strong linkage disequilibrium (D’ = 0.96 to 1.00) was observed among all three SNPs, and a 5 Kb haplotype block involving three main haplotypes with GAG, AGC, and AGG was formed. The results of haplotype association analyses were consistent with the results of single locus association analysis (p<0.0001). The phenotypic variance ratio above 3.00% was observed for milk protein yield that was explained by SNP-g.3836G >C. Conclusion Overall, our findings provided new insights into the polymorphic variations in bovine GALE gene and their associations with milk protein concentration. The data indicate their potential uses for marker-assisted breeding or genetic selection schemes.
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Affiliation(s)
- Cong Li
- Shaanxi Key Laboratory of Molecular Biology for Agriculture, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Wentao Cai
- College of Animal Science and Technology, Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory for Animal Breeding, China Agricultural University, Beijing 100193, China
| | - Shuli Liu
- College of Animal Science and Technology, Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory for Animal Breeding, China Agricultural University, Beijing 100193, China
| | - Chenghao Zhou
- College of Animal Science and Technology, Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory for Animal Breeding, China Agricultural University, Beijing 100193, China
| | - Mingyue Cao
- College of Animal Science and Technology, Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory for Animal Breeding, China Agricultural University, Beijing 100193, China
| | - Hongwei Yin
- College of Animal Science and Technology, Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory for Animal Breeding, China Agricultural University, Beijing 100193, China
| | - Dongxiao Sun
- College of Animal Science and Technology, Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory for Animal Breeding, China Agricultural University, Beijing 100193, China
| | - Shengli Zhang
- College of Animal Science and Technology, Key Laboratory of Animal Genetics and Breeding of Ministry of Agriculture, National Engineering Laboratory for Animal Breeding, China Agricultural University, Beijing 100193, China
| | - Juan J Loor
- Mammalian NutriPhysioGenomics, Department of Animal Sciences and Division of Nutritional Sciences, University of Illinois, Urbana, IL 61801, USA
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17
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Women with fair phenotypes seem to confer a survival advantage in a low UV milieu. A nested matched case control study. PLoS One 2020; 15:e0228582. [PMID: 31999788 PMCID: PMC6992199 DOI: 10.1371/journal.pone.0228582] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2019] [Accepted: 01/18/2020] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Sun exposure in combination with skin pigmentation is the main determinant for vitamin D status. Human skin color seems to be adapted and optimized for regional sun ultraviolet (UV) intensity. However, we do not know if fair, UV-sensitive skin is a survival advantage in regions with low UV radiation. METHODS A population-based nested case-control study of 29,518 Caucasian women, ages 25 to 64 years from Southern Sweden who responded to a questionnaire regarding risk-factors for malignant melanoma in 1990 and followed for 25 years. For each fair woman, defined as having red hair or freckles (n = 11,993), a control was randomly selected from all non-fair women from within the cohort of similar age, smoking habits, education, marital status, income, and comorbidity, i.e., 11,993 pairs. The main outcome was the difference in all-cause mortality between fair and non-fair women in a low UV milieu, defined as living in Sweden and having low-to-moderate sun exposure habits. Secondary outcomes were mortality by sun exposure, and among those non-overweight. RESULTS In a low UV milieu, fair women were at a significantly lower all-cause mortality risk as compared to non-fair women (log rank test p = 0.04) with an 8% lower all-cause mortality rate (hazard ratio [HR] = 0.92, 95% CI 0.84‒1.0), including a 59% greater risk of dying from skin cancer among fair women (HR 1.59, 95% CI 1.26‒2.0). Thus, it seem that the beneficial health effect from low skin coloration outweigh the risk of skin cancer at high latitudes. CONCLUSION In a region with low UV milieu, evolution seems to improve all-cause survival by selecting a fair skin phenotype, i.e., comprising fair women with a survival advantage.
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18
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Xiong Z, Dankova G, Howe LJ, Lee MK, Hysi PG, de Jong MA, Zhu G, Adhikari K, Li D, Li Y, Pan B, Feingold E, Marazita ML, Shaffer JR, McAloney K, Xu SH, Jin L, Wang S, de Vrij FMS, Lendemeijer B, Richmond S, Zhurov A, Lewis S, Sharp GC, Paternoster L, Thompson H, Gonzalez-Jose R, Bortolini MC, Canizales-Quinteros S, Gallo C, Poletti G, Bedoya G, Rothhammer F, Uitterlinden AG, Ikram MA, Wolvius E, Kushner SA, Nijsten TEC, Palstra RJTS, Boehringer S, Medland SE, Tang K, Ruiz-Linares A, Martin NG, Spector TD, Stergiakouli E, Weinberg SM, Liu F, Kayser M. Novel genetic loci affecting facial shape variation in humans. eLife 2019; 8:e49898. [PMID: 31763980 PMCID: PMC6905649 DOI: 10.7554/elife.49898] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Accepted: 11/22/2019] [Indexed: 12/14/2022] Open
Abstract
The human face represents a combined set of highly heritable phenotypes, but knowledge on its genetic architecture remains limited, despite the relevance for various fields. A series of genome-wide association studies on 78 facial shape phenotypes quantified from 3-dimensional facial images of 10,115 Europeans identified 24 genetic loci reaching study-wide suggestive association (p < 5 × 10-8), among which 17 were previously unreported. A follow-up multi-ethnic study in additional 7917 individuals confirmed 10 loci including six unreported ones (padjusted < 2.1 × 10-3). A global map of derived polygenic face scores assembled facial features in major continental groups consistent with anthropological knowledge. Analyses of epigenomic datasets from cranial neural crest cells revealed abundant cis-regulatory activities at the face-associated genetic loci. Luciferase reporter assays in neural crest progenitor cells highlighted enhancer activities of several face-associated DNA variants. These results substantially advance our understanding of the genetic basis underlying human facial variation and provide candidates for future in-vivo functional studies.
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Affiliation(s)
- Ziyi Xiong
- Department of Genetic IdentificationErasmus MC University Medical Center RotterdamRotterdamNetherlands
- Department of EpidemiologyErasmus MC University Medical Center RotterdamRotterdamNetherlands
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of GenomicsUniversity of Chinese Academy of Sciences (CAS)BeijingChina
| | - Gabriela Dankova
- Department of Genetic IdentificationErasmus MC University Medical Center RotterdamRotterdamNetherlands
| | - Laurence J Howe
- Medical Research Council Integrative Epidemiology Unit, Population Health SciencesUniversity of BristolBristolUnited Kingdom
| | - Myoung Keun Lee
- Center for Craniofacial and Dental Genetics, Department of Oral BiologyUniversity of PittsburghPittsburghUnited States
| | - Pirro G Hysi
- Department of Twin Research and Genetic EpidemiologyKing’s College LondonLondonUnited Kingdom
| | - Markus A de Jong
- Department of Genetic IdentificationErasmus MC University Medical Center RotterdamRotterdamNetherlands
- Department of Oral & Maxillofacial Surgery, Special Dental Care, and OrthodonticsErasmus MC University Medical Center RotterdamRotterdamNetherlands
- Department of Biomedical Data SciencesLeiden University Medical CenterLeidenNetherlands
| | - Gu Zhu
- QIMR Berghofer Medical Research InstituteBrisbaneAustralia
| | - Kaustubh Adhikari
- Department of Genetics, Evolution, and EnvironmentUniversity College LondonLondonUnited Kingdom
| | - Dan Li
- CAS Key Laboratory of Computational BiologyChinese Academy of Sciences (CAS)ShanghaiChina
- CAS-MPG Partner Institute for Computational Biology (PICB)Chinese Academy of Sciences (CAS)ShanghaiChina
- Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological SciencesChinese Academy of Sciences (CAS)ShanghaiChina
| | - Yi Li
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of GenomicsUniversity of Chinese Academy of Sciences (CAS)BeijingChina
| | - Bo Pan
- Department of Auricular ReconstructionPlastic Surgery HospitalBeijingChina
| | - Eleanor Feingold
- Center for Craniofacial and Dental Genetics, Department of Oral BiologyUniversity of PittsburghPittsburghUnited States
| | - Mary L Marazita
- Center for Craniofacial and Dental Genetics, Department of Oral BiologyUniversity of PittsburghPittsburghUnited States
- Department of Human GeneticsUniversity of PittsburghPittsburghUnited States
| | - John R Shaffer
- Center for Craniofacial and Dental Genetics, Department of Oral BiologyUniversity of PittsburghPittsburghUnited States
- Department of Human GeneticsUniversity of PittsburghPittsburghUnited States
| | | | - Shu-Hua Xu
- CAS Key Laboratory of Computational BiologyChinese Academy of Sciences (CAS)ShanghaiChina
- CAS-MPG Partner Institute for Computational Biology (PICB)Chinese Academy of Sciences (CAS)ShanghaiChina
- Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological SciencesChinese Academy of Sciences (CAS)ShanghaiChina
- School of Life Science and TechnologyShanghaiTech UniversityShanghaiChina
- Center for Excellence in Animal Evolution and GeneticsChinese Academy of SciencesKunmingChina
| | - Li Jin
- CAS Key Laboratory of Computational BiologyChinese Academy of Sciences (CAS)ShanghaiChina
- CAS-MPG Partner Institute for Computational Biology (PICB)Chinese Academy of Sciences (CAS)ShanghaiChina
- Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological SciencesChinese Academy of Sciences (CAS)ShanghaiChina
- State Key Laboratory of Genetic Engineering, School of Life SciencesFudan UniversityShanghaiChina
- Ministry of Education Key Laboratory of Contemporary Anthropology, School of Life SciencesFudan UniversityShanghaiChina
| | - Sijia Wang
- CAS Key Laboratory of Computational BiologyChinese Academy of Sciences (CAS)ShanghaiChina
- CAS-MPG Partner Institute for Computational Biology (PICB)Chinese Academy of Sciences (CAS)ShanghaiChina
- Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological SciencesChinese Academy of Sciences (CAS)ShanghaiChina
- Center for Excellence in Animal Evolution and GeneticsChinese Academy of SciencesKunmingChina
| | - Femke MS de Vrij
- Department of PsychiatryErasmus MC University Medical Center RotterdamRotterdamNetherlands
| | - Bas Lendemeijer
- Department of PsychiatryErasmus MC University Medical Center RotterdamRotterdamNetherlands
| | - Stephen Richmond
- Applied Clinical Research and Public Health, University Dental SchoolCardiff UniversityCardiffUnited Kingdom
| | - Alexei Zhurov
- Applied Clinical Research and Public Health, University Dental SchoolCardiff UniversityCardiffUnited Kingdom
| | - Sarah Lewis
- Medical Research Council Integrative Epidemiology Unit, Population Health SciencesUniversity of BristolBristolUnited Kingdom
| | - Gemma C Sharp
- Medical Research Council Integrative Epidemiology Unit, Population Health SciencesUniversity of BristolBristolUnited Kingdom
- School of Oral and Dental SciencesUniversity of BristolBristolUnited Kingdom
| | - Lavinia Paternoster
- Medical Research Council Integrative Epidemiology Unit, Population Health SciencesUniversity of BristolBristolUnited Kingdom
| | - Holly Thompson
- Medical Research Council Integrative Epidemiology Unit, Population Health SciencesUniversity of BristolBristolUnited Kingdom
| | - Rolando Gonzalez-Jose
- Instituto Patagonico de Ciencias Sociales y Humanas, CENPAT-CONICETPuerto MadrynArgentina
| | | | - Samuel Canizales-Quinteros
- UNAM-Instituto Nacional de Medicina Genomica, Facultad de QuımicaUnidad de Genomica de Poblaciones Aplicada a la SaludMexico CityMexico
| | - Carla Gallo
- Laboratorios de Investigacion y Desarrollo, Facultad de Ciencias y FilosofıaUniversidad Peruana Cayetano HerediaLimaPeru
| | - Giovanni Poletti
- Laboratorios de Investigacion y Desarrollo, Facultad de Ciencias y FilosofıaUniversidad Peruana Cayetano HerediaLimaPeru
| | - Gabriel Bedoya
- GENMOL (Genetica Molecular)Universidad de AntioquiaMedellınColombia
| | | | - André G Uitterlinden
- Department of EpidemiologyErasmus MC University Medical Center RotterdamRotterdamNetherlands
- Department of Internal MedicineErasmus MC University Medical Center RotterdamRotterdamNetherlands
| | - M Arfan Ikram
- Department of EpidemiologyErasmus MC University Medical Center RotterdamRotterdamNetherlands
| | - Eppo Wolvius
- Department of Oral & Maxillofacial Surgery, Special Dental Care, and OrthodonticsErasmus MC University Medical Center RotterdamRotterdamNetherlands
| | - Steven A Kushner
- Department of PsychiatryErasmus MC University Medical Center RotterdamRotterdamNetherlands
| | - Tamar EC Nijsten
- Department of DermatologyErasmus MC University Medical Center RotterdamRotterdamNetherlands
| | - Robert-Jan TS Palstra
- Department of BiochemistryErasmus MC University Medical Center RotterdamRotterdamNetherlands
| | - Stefan Boehringer
- Department of Biomedical Data SciencesLeiden University Medical CenterLeidenNetherlands
| | | | - Kun Tang
- CAS Key Laboratory of Computational BiologyChinese Academy of Sciences (CAS)ShanghaiChina
- CAS-MPG Partner Institute for Computational Biology (PICB)Chinese Academy of Sciences (CAS)ShanghaiChina
- Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological SciencesChinese Academy of Sciences (CAS)ShanghaiChina
| | - Andres Ruiz-Linares
- State Key Laboratory of Genetic Engineering, School of Life SciencesFudan UniversityShanghaiChina
- Ministry of Education Key Laboratory of Contemporary Anthropology, School of Life SciencesFudan UniversityShanghaiChina
- Aix-Marseille Université, CNRS, EFS, ADESMarseilleFrance
| | | | - Timothy D Spector
- Department of Twin Research and Genetic EpidemiologyKing’s College LondonLondonUnited Kingdom
| | - Evie Stergiakouli
- Medical Research Council Integrative Epidemiology Unit, Population Health SciencesUniversity of BristolBristolUnited Kingdom
- School of Oral and Dental SciencesUniversity of BristolBristolUnited Kingdom
| | - Seth M Weinberg
- Center for Craniofacial and Dental Genetics, Department of Oral BiologyUniversity of PittsburghPittsburghUnited States
- Department of Human GeneticsUniversity of PittsburghPittsburghUnited States
- Department of AnthropologyUniversity of PittsburghPittsburghUnited States
| | - Fan Liu
- Department of Genetic IdentificationErasmus MC University Medical Center RotterdamRotterdamNetherlands
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of GenomicsUniversity of Chinese Academy of Sciences (CAS)BeijingChina
| | - Manfred Kayser
- Department of Genetic IdentificationErasmus MC University Medical Center RotterdamRotterdamNetherlands
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19
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Yang F, Chen F, Li L, Yan L, Badri T, Lv C, Yu D, Zhang M, Jang X, Li J, Yuan L, Wang G, Li H, Li J, Cai Y. Three Novel Players: PTK2B, SYK, and TNFRSF21 Were Identified to Be Involved in the Regulation of Bovine Mastitis Susceptibility via GWAS and Post-transcriptional Analysis. Front Immunol 2019; 10:1579. [PMID: 31447828 PMCID: PMC6691815 DOI: 10.3389/fimmu.2019.01579] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2019] [Accepted: 06/24/2019] [Indexed: 12/25/2022] Open
Abstract
Bovine mastitis is a common inflammatory disease caused by multiple factors in early lactation or dry period. Genome wide association studies (GWAS) can provide a convenient and effective strategy for understanding the biological basis of mastitis and better prevention. 2b-RADseq is a high-throughput sequencing technique that offers a powerful method for genome-wide genetic marker development and genotyping. In this study, single nucleotide polymorphisms (SNPs) of the immune-regulated gene correlative with mastitis were screened and identified by two stage association analysis via GWAS-2b-RADseq in Chinese Holstein cows. We have screened 10,058 high quality SNPs from 7,957,920 tags and calculated their allele frequencies. Twenty-seven significant SNPs were co-labeled in two GWAS analysis models [Bayesian (P < 0.001) and Logistic regression (P < 0.01)], and only three SNPs (rs75762330, C > T, PIC = 0.2999; rs88640083, A > G, PIC = 0.1676; rs20438858, G > A, PIC = 0.3366) were annotated to immune-regulated genes (PTK2B, SYK, and TNFRSF21). Identified three SNPs are located in non-coding regions with low or moderate genetic polymorphisms. However, independent sample population validation (Case-control study) data showed that three important SNPs (rs75762330, P < 0.025, OR > 1; rs88640083, P < 0.005, OR > 1; rs20438858, P < 0.001, OR < 1) were significantly associated with clinical mastitis trait. Importantly, PTK2B and SYK expression was down-regulated in both peripheral blood leukocytes (PBLs) of clinical mastitis cows and in vitro LPS (E. coli)-stimulated bovine mammary epithelial cells, while TNFRSF21 was up-regulated. Under the same conditions, expression of Toll-like receptor 4 (TLR4), AKT1, and pro-inflammatory factors (IL-1β and IL-8) were also up-regulated. Interestingly, network analysis indicated that PTK2B and SYK are co-expressed in innate immune signaling pathway of Chinese Holstein. Taken together, these results provided strong evidence for the study of SNPs in bovine mastitis, and revealed the role of SYK, PTK2B, and TNFRSF21 in bovine mastitis susceptibility/tolerance.
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Affiliation(s)
- Fan Yang
- Anhui Provincial Key Lab of the Conservation and Exploitation of Biological Resources, College of Life Sciences, Anhui Normal University, Wuhu, China
- College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, China
| | - Fanghui Chen
- College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, China
| | - Lili Li
- National Animal Husbandry Station, Beijing, China
| | - Li Yan
- Department of Radiation Oncology, Linyi People Hospital, Linyi, China
| | - Tarig Badri
- College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, China
| | - Chenglong Lv
- College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, China
| | - Daolun Yu
- Anhui Provincial Key Lab of the Conservation and Exploitation of Biological Resources, College of Life Sciences, Anhui Normal University, Wuhu, China
| | - Manling Zhang
- Anhui Provincial Key Lab of the Conservation and Exploitation of Biological Resources, College of Life Sciences, Anhui Normal University, Wuhu, China
| | - Xiaojun Jang
- Anhui Provincial Key Lab of the Conservation and Exploitation of Biological Resources, College of Life Sciences, Anhui Normal University, Wuhu, China
| | - Jie Li
- Anhui Provincial Key Lab of the Conservation and Exploitation of Biological Resources, College of Life Sciences, Anhui Normal University, Wuhu, China
| | - Lu Yuan
- Anhui Provincial Key Lab of the Conservation and Exploitation of Biological Resources, College of Life Sciences, Anhui Normal University, Wuhu, China
| | - Genlin Wang
- College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, China
| | - Honglin Li
- Department of Biochemistry and Molecular Biology, Medical College of Georgia, Augusta University, Augusta, GA, United States
| | - Jun Li
- Anhui Provincial Key Lab of the Conservation and Exploitation of Biological Resources, College of Life Sciences, Anhui Normal University, Wuhu, China
| | - Yafei Cai
- College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, China
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20
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The Evolutionary History of Human Skin Pigmentation. J Mol Evol 2019; 88:77-87. [PMID: 31363820 DOI: 10.1007/s00239-019-09902-7] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2019] [Accepted: 07/16/2019] [Indexed: 02/07/2023]
Abstract
Skin pigmentation is a complex, conspicuous, highly variable human trait that exhibits a remarkable correlation with latitude. The evolutionary history and genetic basis of skin color variation has been the subject of intense research in the last years. This article reviews the major hypotheses explaining skin color diversity and explores the implications of recent findings about the genes associated with skin pigmentation for understanding the evolutionary forces that have shaped the current patterns of skin color variation. A major aspect of these findings is that the genetic basis of skin color is less simple than previously thought and that geographic variation in skin pigmentation was influenced by the concerted action of different types of natural selection, rather than just by selective sweeps in a few key genes.
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21
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Szpak M, Xue Y, Ayub Q, Tyler‐Smith C. How well do we understand the basis of classic selective sweeps in humans? FEBS Lett 2019; 593:1431-1448. [DOI: 10.1002/1873-3468.13447] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2019] [Revised: 04/29/2019] [Accepted: 05/17/2019] [Indexed: 12/14/2022]
Affiliation(s)
| | - Yali Xue
- The Wellcome Sanger Institute Hinxton UK
| | - Qasim Ayub
- School of Science Monash University Malaysia Bandar Sunway Malaysia
- Tropical Medicine and Biology Multidisciplinary Platform Monash University Malaysia Genomics Facility Bandar Sunway Malaysia
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22
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Abstract
Human skin and hair color are visible traits that can vary dramatically within and across ethnic populations. The genetic makeup of these traits-including polymorphisms in the enzymes and signaling proteins involved in melanogenesis, and the vital role of ion transport mechanisms operating during the maturation and distribution of the melanosome-has provided new insights into the regulation of pigmentation. A large number of novel loci involved in the process have been recently discovered through four large-scale genome-wide association studies in Europeans, two large genetic studies of skin color in Africans, one study in Latin Americans, and functional testing in animal models. The responsible polymorphisms within these pigmentation genes appear at different population frequencies, can be used as ancestry-informative markers, and provide insight into the evolutionary selective forces that have acted to create this human diversity.
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Affiliation(s)
- William J Pavan
- Genetic Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland 20892, USA;
| | - Richard A Sturm
- Dermatology Research Centre, The University of Queensland Diamantina Institute, The University of Queensland, Brisbane, Queensland 4102, Australia;
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23
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Tam I, Dzierżęga-Lęcznar A, Stępień K. Differential expression of inflammatory cytokines and chemokines in lipopolysaccharide-stimulated melanocytes from lightly and darkly pigmented skin. Exp Dermatol 2019; 28:551-560. [PMID: 30801846 DOI: 10.1111/exd.13908] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2018] [Accepted: 02/11/2019] [Indexed: 01/02/2023]
Abstract
Increasing evidence suggests that human epidermal melanocytes play an important role in the skin immune system; however, a role of their pigmentation in immune and inflammatory responses is poorly examined. In the study, the expression of Toll-like receptor 4 (TLR4) and inflammatory cytokines and chemokines by cultured normal melanocytes derived from lightly and darkly pigmented skin was investigated after cell stimulation with lipopolysaccharide (LPS). The basal TLR4 mRNA level in heavily pigmented cells was higher as compared to their lightly pigmented counterparts. Melanocyte exposure to LPS upregulated the expression of TLR4 mRNA and enhanced the DNA-binding activity of NF-κB p50 and p65. We found substantial differences in the LPS-stimulated expression of numerous genes encoding inflammatory cytokines and chemokines between the cells with various melanin contents. In lightly pigmented melanocytes, the most significantly upregulated genes were nicotinamide phosphoribosyltransferase (NAMPT/visfatin), the chemokines CCL2 and CCL20, and IL6, while the genes for CXCL12, IL-16 and the chemokine receptor CCR4 were the most significantly upregulated in heavily pigmented cells. Moreover, the lightly pigmented melanocytes secreted much more NAMPT, CCL2 and IL-6. The results of our study suggest modulatory effect of melanogenesis on the immune properties of normal epidermal melanocytes.
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Affiliation(s)
- Irena Tam
- Department of Instrumental Analysis, School of Pharmacy with the Division of Laboratory Medicine, Medical University of Silesia in Katowice, Sosnowiec, Poland
| | - Anna Dzierżęga-Lęcznar
- Department of Instrumental Analysis, School of Pharmacy with the Division of Laboratory Medicine, Medical University of Silesia in Katowice, Sosnowiec, Poland
| | - Krystyna Stępień
- Department of Instrumental Analysis, School of Pharmacy with the Division of Laboratory Medicine, Medical University of Silesia in Katowice, Sosnowiec, Poland
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24
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Buckley MA, Woods NT, Tyrer JP, Mendoza-Fandiño G, Lawrenson K, Hazelett DJ, Najafabadi HS, Gjyshi A, Carvalho RS, Lyra PC, Coetzee SG, Shen HC, Yang AW, Earp MA, Yoder SJ, Risch H, Chenevix-Trench G, Ramus SJ, Phelan CM, Coetzee GA, Noushmehr H, Hughes TR, Sellers TA, Goode EL, Pharoah PD, Gayther SA, Monteiro ANA. Functional Analysis and Fine Mapping of the 9p22.2 Ovarian Cancer Susceptibility Locus. Cancer Res 2019; 79:467-481. [PMID: 30487138 PMCID: PMC6359979 DOI: 10.1158/0008-5472.can-17-3864] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2017] [Revised: 04/11/2018] [Accepted: 11/16/2018] [Indexed: 01/15/2023]
Abstract
Genome-wide association studies have identified 40 ovarian cancer risk loci. However, the mechanisms underlying these associations remain elusive. In this study, we conducted a two-pronged approach to identify candidate causal SNPs and assess underlying biological mechanisms at chromosome 9p22.2, the first and most statistically significant associated locus for ovarian cancer susceptibility. Three transcriptional regulatory elements with allele-specific effects and a scaffold/matrix attachment region were characterized and, through physical DNA interactions, BNC2 was established as the most likely target gene. We determined the consensus binding sequence for BNC2 in vitro, verified its enrichment in BNC2 ChIP-seq regions, and validated a set of its downstream target genes. Fine-mapping by dense regional genotyping in over 15,000 ovarian cancer cases and 30,000 controls identified SNPs in the scaffold/matrix attachment region as among the most likely causal variants. This study reveals a comprehensive regulatory landscape at 9p22.2 and proposes a likely mechanism of susceptibility to ovarian cancer. SIGNIFICANCE: Mapping the 9p22.2 ovarian cancer risk locus identifies BNC2 as an ovarian cancer risk gene.See related commentary by Choi and Brown, p. 439.
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Affiliation(s)
- Melissa A Buckley
- Cancer Epidemiology Program, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida
- University of South Florida Cancer Biology PhD Program, Tampa, Florida
| | - Nicholas T Woods
- Cancer Epidemiology Program, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida
- Department of Oncological Sciences, Morsani College of Medicine, University of South Florida, Tampa, Florida
| | - Jonathan P Tyrer
- The Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Gustavo Mendoza-Fandiño
- Cancer Epidemiology Program, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida
| | - Kate Lawrenson
- Women's Cancer Program at the Samuel Oschin Comprehensive, Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California
| | - Dennis J Hazelett
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California Norris Comprehensive Cancer Center, Los Angeles, California
- Department of Urology, University of Southern California Norris Comprehensive Cancer Center, Los Angeles, California
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California
| | - Hamed S Najafabadi
- Donnelly Centre, University of Toronto, Toronto, Ontario, Canada
- Department of Human Genetics, McGill University, Montreal, Quebec, Canada
| | - Anxhela Gjyshi
- Cancer Epidemiology Program, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida
- University of South Florida Cancer Biology PhD Program, Tampa, Florida
| | - Renato S Carvalho
- Cancer Epidemiology Program, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida
| | - Paulo C Lyra
- Cancer Epidemiology Program, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida
| | - Simon G Coetzee
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California
| | - Howard C Shen
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California Norris Comprehensive Cancer Center, Los Angeles, California
| | - Ally W Yang
- Donnelly Centre, University of Toronto, Toronto, Ontario, Canada
| | - Madalene A Earp
- Division of Biomedical Statistics and Informatics, Department of Health Science Research, Mayo Clinic, Rochester, Minnesota
| | - Sean J Yoder
- Molecular Genomics Core, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida
| | - Harvey Risch
- Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, Connecticut
| | | | - Susan J Ramus
- School of Women's and Children's Health, University of New South Wales, Sydney, Australia
- The Kinghorn Cancer Center, Garvan Institute of Medical Research, Darlinghurst, Australia
| | - Catherine M Phelan
- Cancer Epidemiology Program, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida
| | - Gerhard A Coetzee
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California Norris Comprehensive Cancer Center, Los Angeles, California
- Van Andel Institute, Grand Rapids, Michigan
| | - Houtan Noushmehr
- Department of Neurosurgery, Henry Ford Health System, Detroit, Michigan
| | - Timothy R Hughes
- Donnelly Centre, University of Toronto, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
- Canadian Institutes for Advanced Research, Toronto, Ontario, Canada
| | - Thomas A Sellers
- Cancer Epidemiology Program, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida
| | - Ellen L Goode
- Division of Biomedical Statistics and Informatics, Department of Health Science Research, Mayo Clinic, Rochester, Minnesota
| | - Paul D Pharoah
- The Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Simon A Gayther
- Women's Cancer Program at the Samuel Oschin Comprehensive, Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California
- Center for Bioinformatics and Functional Genomics, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California
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25
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PINES: phenotype-informed tissue weighting improves prediction of pathogenic noncoding variants. Genome Biol 2018; 19:173. [PMID: 30359302 PMCID: PMC6203199 DOI: 10.1186/s13059-018-1546-6] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2017] [Accepted: 09/19/2018] [Indexed: 12/17/2022] Open
Abstract
Functional characterization of the noncoding genome is essential for biological understanding of gene regulation and disease. Here, we introduce the computational framework PINES (Phenotype-Informed Noncoding Element Scoring), which predicts the functional impact of noncoding variants by integrating epigenetic annotations in a phenotype-dependent manner. PINES enables analyses to be customized towards genomic annotations from cell types of the highest relevance given the phenotype of interest. We illustrate that PINES identifies functional noncoding variation more accurately than methods that do not use phenotype-weighted knowledge, while at the same time being flexible and easy to use via a dedicated web portal.
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26
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El Rouby N, McDonough CW, Gong Y, McClure LA, Mitchell BD, Horenstein RB, Talbert RL, Crawford DC, Gitzendanner MA, Takahashi A, Tanaka T, Kubo M, Pepine CJ, Cooper-DeHoff RM, Benavente OR, Shuldiner AR, Johnson JA. Genome-wide association analysis of common genetic variants of resistant hypertension. THE PHARMACOGENOMICS JOURNAL 2018; 19:295-304. [PMID: 30237584 DOI: 10.1038/s41397-018-0049-x] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/11/2017] [Revised: 08/02/2018] [Accepted: 08/10/2018] [Indexed: 12/24/2022]
Abstract
Resistant hypertension (RHTN), defined as uncontrolled blood pressure (BP) ≥ 140/90 using three or more drugs or controlled BP (<140/90) using four or more drugs, is associated with adverse outcomes, including decline in kidney function. We conducted a genome-wide association analysis in 1194 White and Hispanic participants with hypertension and coronary artery disease from the INternational VErapamil-SR Trandolapril STudy-GENEtic Substudy (INVEST-GENES). Top variants associated with RHTN at p < 10-4 were tested for replication in 585 White and Hispanic participants with hypertension and subcortical strokes from the Secondary Prevention of Subcortical Strokes GENEtic Substudy (SPS3-GENES). A genetic risk score for RHTN was created by summing the risk alleles of replicated RHTN signals. rs11749255 in MSX2 was associated with RHTN in INVEST (odds ratio (OR) (95% CI) = 1.50 (1.2-1.8), p = 7.3 × 10-5) and replicated in SPS3 (OR = 2.0 (1.4-2.8), p = 4.3 × 10-5), with genome-wide significance in meta-analysis (OR = 1.60 (1.3-1.9), p = 3.8 × 10-8). Other replicated signals were in IFLTD1 and PTPRD. IFLTD1 rs6487504 was associated with RHTN in INVEST (OR = 1.90 (1.4-2.5), p = 1.1 × 10-5) and SPS3 (OR = 1.70 (1.2-2.5), p = 4 × 10-3). PTPRD rs324498, a previously reported RHTN signal, was among the top signals in INVEST (OR = 1.60 (1.3-2.0), p = 3.4 × 10-5) and replicated in SPS3 (OR = 1.60 (1.1-2.4), one-sided p = 0.005). Participants with the highest number of risk alleles were at increased risk of RHTN compared to participants with a lower number (p-trend = 1.8 × 10-15). Overall, we identified and replicated associations with RHTN in the MSX2, IFLTD1, and PTPRD regions, and combined these associations to create a genetic risk score.
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Affiliation(s)
- Nihal El Rouby
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, College of Pharmacy, University of Florida, Gainesville, FL, USA
| | - Caitrin W McDonough
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, College of Pharmacy, University of Florida, Gainesville, FL, USA
| | - Yan Gong
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, College of Pharmacy, University of Florida, Gainesville, FL, USA
| | - Leslie A McClure
- Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA, USA
| | - Braxton D Mitchell
- Division of Endocrinology, Diabetes and Nutrition, University of Maryland School of Medicine, Baltimore, MD, USA.,Geriatric Research and Education Clinical Center, Veterans Administration Medical Center, Baltimore, MD, USA
| | - Richard B Horenstein
- Division of Endocrinology, Diabetes and Nutrition, University of Maryland School of Medicine, Baltimore, MD, USA.,Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Robert L Talbert
- College of Pharmacy, University of Texas at Austin, Austin, TX, USA
| | - Dana C Crawford
- Epidemiology and Biostatistics, Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA
| | | | | | | | | | - Michiaki Kubo
- RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Carl J Pepine
- Division of Cardiovascular Medicine, Department of Medicine, University of Florida, Gainesville, FL, USA
| | - Rhonda M Cooper-DeHoff
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, College of Pharmacy, University of Florida, Gainesville, FL, USA.,Division of Cardiovascular Medicine, Department of Medicine, University of Florida, Gainesville, FL, USA
| | - Oscar R Benavente
- Department of Neurology, University of British Columbia, Vancouver, BC, Canada
| | - Alan R Shuldiner
- Division of Endocrinology, Diabetes and Nutrition, University of Maryland School of Medicine, Baltimore, MD, USA.,Geriatric Research and Education Clinical Center, Veterans Administration Medical Center, Baltimore, MD, USA.,Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Julie A Johnson
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, College of Pharmacy, University of Florida, Gainesville, FL, USA. .,Division of Cardiovascular Medicine, Department of Medicine, University of Florida, Gainesville, FL, USA.
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27
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Del Bino S, Duval C, Bernerd F. Clinical and Biological Characterization of Skin Pigmentation Diversity and Its Consequences on UV Impact. Int J Mol Sci 2018; 19:ijms19092668. [PMID: 30205563 PMCID: PMC6163216 DOI: 10.3390/ijms19092668] [Citation(s) in RCA: 132] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2018] [Revised: 07/24/2018] [Accepted: 07/27/2018] [Indexed: 12/27/2022] Open
Abstract
Skin color diversity is the most variable and noticeable phenotypic trait in humans resulting from constitutive pigmentation variability. This paper will review the characterization of skin pigmentation diversity with a focus on the most recent data on the genetic basis of skin pigmentation, and the various methodologies for skin color assessment. Then, melanocyte activity and amount, type and distribution of melanins, which are the main drivers for skin pigmentation, are described. Paracrine regulators of melanocyte microenvironment are also discussed. Skin response to sun exposure is also highly dependent on color diversity. Thus, sensitivity to solar wavelengths is examined in terms of acute effects such as sunburn/erythema or induced-pigmentation but also long-term consequences such as skin cancers, photoageing and pigmentary disorders. More pronounced sun-sensitivity in lighter or darker skin types depending on the detrimental effects and involved wavelengths is reviewed.
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Affiliation(s)
- Sandra Del Bino
- L'Oréal Research and Innovation, 1 avenue Eugène Schueller, 93601 Aulnay-sous-Bois, France.
| | - Christine Duval
- L'Oréal Research and Innovation, 1 avenue Eugène Schueller, 93601 Aulnay-sous-Bois, France.
| | - Françoise Bernerd
- L'Oréal Research and Innovation, 1 avenue Eugène Schueller, 93601 Aulnay-sous-Bois, France.
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28
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Endo C, Johnson TA, Morino R, Nakazono K, Kamitsuji S, Akita M, Kawajiri M, Yamasaki T, Kami A, Hoshi Y, Tada A, Ishikawa K, Hine M, Kobayashi M, Kurume N, Tsunemi Y, Kamatani N, Kawashima M. Genome-wide association study in Japanese females identifies fifteen novel skin-related trait associations. Sci Rep 2018; 8:8974. [PMID: 29895819 PMCID: PMC5997657 DOI: 10.1038/s41598-018-27145-2] [Citation(s) in RCA: 46] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2017] [Accepted: 05/25/2018] [Indexed: 12/27/2022] Open
Abstract
Skin trait variation impacts quality-of-life, especially for females from the viewpoint of beauty. To investigate genetic variation related to these traits, we conducted a GWAS of various skin phenotypes in 11,311 Japanese women and identified associations for age-spots, freckles, double eyelids, straight/curly hair, eyebrow thickness, hairiness, and sweating. In silico annotation with RoadMap Epigenomics epigenetic state maps and colocalization analysis of GWAS and GTEx Project eQTL signals provided information about tissue specificity, candidate causal variants, and functional target genes. Novel signals for skin-spot traits neighboured AKAP1/MSI2 (rs17833789; P = 2.2 × 10-9), BNC2 (rs10810635; P = 2.1 × 10-22), HSPA12A (rs12259842; P = 7.1 × 10-11), PPARGC1B (rs251468; P = 1.3 × 10-21), and RAB11FIP2 (rs10444039; P = 5.6 × 10-21). HSPA12A SNPs were the only protein-coding gene eQTLs identified across skin-spot loci. Double edged eyelid analysis identified that a signal around EMX2 (rs12570134; P = 8.2 × 10-15) was also associated with expression of EMX2 and the antisense-RNA gene EMX2OS in brain putamen basal ganglia tissue. A known hair morphology signal in EDAR was associated with both eyebrow thickness (rs3827760; P = 1.7 × 10-9) and straight/curly hair (rs260643; P = 1.6 × 10-103). Excessive hairiness signals' top SNPs were also eQTLs for TBX15 (rs984225; P = 1.6 × 10-8), BCL2 (rs7226979; P = 7.3 × 10-11), and GCC2 and LIMS1 (rs6542772; P = 2.2 × 10-9). For excessive sweating, top variants in two signals in chr2:28.82-29.05 Mb (rs56089836; P = 1.7 × 10-11) were eQTLs for either PPP1CB or PLB1, while a top chr16:48.26-48.45 Mb locus SNP was a known ABCC11 missense variant (rs6500380; P = 6.8 × 10-10). In total, we identified twelve loci containing sixteen association signals, of which fifteen were novel. These findings will help dermatologic researchers better understand the genetic underpinnings of skin-related phenotypic variation in human populations.
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Affiliation(s)
- Chihiro Endo
- Department of Dermatology, School of Medicine, Tokyo Women's Medical University, Shinjuku, Tokyo, 162-8666, Japan
| | | | - Ryoko Morino
- EverGene Ltd., Shinjuku-ku, Tokyo, 163-1435, Japan
| | | | | | | | | | - Tatsuya Yamasaki
- Life Science Group, Healthcare Division, Department of Healthcare Business, MTI Ltd., Shinjuku-ku, Tokyo, 163-1435, Japan
| | - Azusa Kami
- EverGene Ltd., Shinjuku-ku, Tokyo, 163-1435, Japan
| | - Yuria Hoshi
- Life Science Group, Healthcare Division, Department of Healthcare Business, MTI Ltd., Shinjuku-ku, Tokyo, 163-1435, Japan
| | - Asami Tada
- EverGene Ltd., Shinjuku-ku, Tokyo, 163-1435, Japan
| | | | - Maaya Hine
- LunaLuna Division, Department of Healthcare Business, MTI Ltd., Shinjuku-ku, Tokyo, 163-1435, Japan
| | - Miki Kobayashi
- LunaLuna Division, Department of Healthcare Business, MTI Ltd., Shinjuku-ku, Tokyo, 163-1435, Japan
| | - Nami Kurume
- LunaLuna Division, Department of Healthcare Business, MTI Ltd., Shinjuku-ku, Tokyo, 163-1435, Japan
| | - Yuichiro Tsunemi
- Department of Dermatology, School of Medicine, Tokyo Women's Medical University, Shinjuku, Tokyo, 162-8666, Japan
| | | | - Makoto Kawashima
- Department of Dermatology, School of Medicine, Tokyo Women's Medical University, Shinjuku, Tokyo, 162-8666, Japan
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Backenroth D, He Z, Kiryluk K, Boeva V, Pethukova L, Khurana E, Christiano A, Buxbaum JD, Ionita-Laza I. FUN-LDA: A Latent Dirichlet Allocation Model for Predicting Tissue-Specific Functional Effects of Noncoding Variation: Methods and Applications. Am J Hum Genet 2018; 102:920-942. [PMID: 29727691 PMCID: PMC5986983 DOI: 10.1016/j.ajhg.2018.03.026] [Citation(s) in RCA: 44] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2017] [Accepted: 03/21/2018] [Indexed: 10/17/2022] Open
Abstract
We describe a method based on a latent Dirichlet allocation model for predicting functional effects of noncoding genetic variants in a cell-type- and/or tissue-specific way (FUN-LDA). Using this unsupervised approach, we predict tissue-specific functional effects for every position in the human genome in 127 different tissues and cell types. We demonstrate the usefulness of our predictions by using several validation experiments. Using eQTL data from several sources, including the GTEx project, Geuvadis project, and TwinsUK cohort, we show that eQTLs in specific tissues tend to be most enriched among the predicted functional variants in relevant tissues in Roadmap. We further show how these integrated functional scores can be used for (1) deriving the most likely cell or tissue type causally implicated for a complex trait by using summary statistics from genome-wide association studies and (2) estimating a tissue-based correlation matrix of various complex traits. We found large enrichment of heritability in functional components of relevant tissues for various complex traits, and FUN-LDA yielded higher enrichment estimates than existing methods. Finally, using experimentally validated functional variants from the literature and variants possibly implicated in disease by previous studies, we rigorously compare FUN-LDA with state-of-the-art functional annotation methods and show that FUN-LDA has better prediction accuracy and higher resolution than these methods. In particular, our results suggest that tissue- and cell-type-specific functional prediction methods tend to have substantially better prediction accuracy than organism-level prediction methods. Scores for each position in the human genome and for each ENCODE and Roadmap tissue are available online (see Web Resources).
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Affiliation(s)
- Daniel Backenroth
- Department of Biostatistics, Columbia University, New York, NY 10032, USA
| | - Zihuai He
- Department of Biostatistics, Columbia University, New York, NY 10032, USA
| | - Krzysztof Kiryluk
- Department of Medicine, Columbia University, New York, NY 10032, USA
| | - Valentina Boeva
- INSERM, U900, 75005 Paris, France; Institut Curie, Mines ParisTech, PSL Research University, 75005 Paris, France
| | - Lynn Pethukova
- Department of Epidemiology, Columbia University, New York, NY 10032, USA; Department of Dermatology, Columbia University, New York, NY 10032, USA
| | - Ekta Khurana
- Department of Physiology and Biophysics, Weill Medical College, Cornell University, New York, NY 10021, USA
| | - Angela Christiano
- Department of Dermatology, Columbia University, New York, NY 10032, USA; Department of Genetics and Development, Columbia University, New York, NY 10032, USA
| | - Joseph D Buxbaum
- Departments of Psychiatry, Neuroscience, and Genetics and Genomic Sciences, Icahn School of Medicine at Mount SInai, New York, NY 10029, USA; Friedman Brain Institute and Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
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30
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Markiewicz E, Idowu OC. Personalized skincare: from molecular basis to clinical and commercial applications. Clin Cosmet Investig Dermatol 2018; 11:161-171. [PMID: 29692619 PMCID: PMC5903487 DOI: 10.2147/ccid.s163799] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Individual responses of human skin to the environmental stress are determined by differences in the anatomy and physiology that are closely linked to the genetic characteristics such as pigmentation. Ethnic skin phenotypes can be distinguished based on defined genotypic traits, structural organization and compartmentalized sensitivity to distinct extrinsic aging factors. These differences are not only responsible for the variation in skin performance after exposure to damaging conditions, but can also affect the mechanisms of drug absorption, sensitization and other longer term effects. The unique characteristics of the individual skin function and, particularly, of the ethnic skin type are currently considered to shape the future of clinical and pharmacologic interventions as a basis for personalized skincare. Individual approaches to skincare render a novel and actively growing area with a range of biomedical and commercial applications within cosmetics industry. In this review, we summarize the aspects of the molecular and clinical manifestations of the environmental stress on human skin and proposed protective mechanisms that are linked to ethnic differences and pathophysiology of extrinsic skin aging. We subsequently discuss the possible applications and translation of this knowledge into personalized skincare.
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Affiliation(s)
- Ewa Markiewicz
- Research & Development, Hexis Lab, Science Central, The Core, Bath Lane, Newcastle upon Tyne, UK
| | - Olusola Clement Idowu
- Research & Development, Hexis Lab, Science Central, The Core, Bath Lane, Newcastle upon Tyne, UK
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31
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Szpak M, Mezzavilla M, Ayub Q, Chen Y, Xue Y, Tyler-Smith C. FineMAV: prioritizing candidate genetic variants driving local adaptations in human populations. Genome Biol 2018; 19:5. [PMID: 29343290 PMCID: PMC5771147 DOI: 10.1186/s13059-017-1380-2] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2017] [Accepted: 12/12/2017] [Indexed: 12/30/2022] Open
Abstract
We present a new method, Fine-Mapping of Adaptive Variation (FineMAV), which combines population differentiation, derived allele frequency, and molecular functionality to prioritize positively selected candidate variants for functional follow-up. We calibrate and test FineMAV using eight experimentally validated "gold standard" positively selected variants and simulations. FineMAV has good sensitivity and a low false discovery rate. Applying FineMAV to the 1000 Genomes Project Phase 3 SNP dataset, we report many novel selected variants, including ones in TGM3 and PRSS53 associated with hair phenotypes that we validate using available independent data. FineMAV is widely applicable to sequence data from both human and other species.
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Affiliation(s)
- Michał Szpak
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, CB10 1SA UK
| | - Massimo Mezzavilla
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, CB10 1SA UK
- Division of Experimental Genetics, Sidra Medical and Research Center, Doha, Qatar
| | - Qasim Ayub
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, CB10 1SA UK
- Present Address: Genomics Facility, School of Science, Monash University Malaysia, Bandar Sunway, Selangor, Darul Ehsan Malaysia
| | - Yuan Chen
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, CB10 1SA UK
| | - Yali Xue
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, CB10 1SA UK
| | - Chris Tyler-Smith
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, CB10 1SA UK
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32
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Zhong K, Zhu G, Jing X, Hendriks AEJ, Drop SLS, Ikram MA, Gordon S, Zeng C, Uitterlinden AG, Martin NG, Liu F, Kayser M. Genome-wide compound heterozygote analysis highlights alleles associated with adult height in Europeans. Hum Genet 2017; 136:1407-1417. [PMID: 28921393 PMCID: PMC5702380 DOI: 10.1007/s00439-017-1842-3] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2017] [Accepted: 08/26/2017] [Indexed: 01/08/2023]
Abstract
Adult height is the most widely genetically studied common trait in humans; however, the trait variance explainable by currently known height-associated single nucleotide polymorphisms (SNPs) identified from the previous genome-wide association studies (GWAS) is yet far from complete given the high heritability of this complex trait. To exam if compound heterozygotes (CH) may explain extra height variance, we conducted a genome-wide analysis to screen for CH in association with adult height in 10,631 Dutch Europeans enriched with extremely tall people, using our recently developed method implemented in the software package CollapsABEL. The analysis identified six regions (3q23, 5q35.1, 6p21.31, 6p21.33, 7q21.2, and 9p24.3), where multiple pairs of SNPs as CH showed genome-wide significant association with height (P < 1.67 × 10−10). Of those, 9p24.3 represents a novel region influencing adult height, whereas the others have been highlighted in the previous GWAS on height based on analysis of individual SNPs. A replication analysis in 4080 Australians of European ancestry confirmed the significant CH-like association at 9p24.3 (P < 0.05). Together, the collapsed genotypes at these six loci explained 2.51% of the height variance (after adjusting for sex and age), compared with 3.23% explained by the 14 top-associated SNPs at 14 loci identified by traditional GWAS in the same data set (P < 5 × 10−8). Overall, our study empirically demonstrates that CH plays an important role in adult height and may explain a proportion of its “missing heritability”. Moreover, our findings raise promising expectations for other highly polygenic complex traits to explain missing heritability identifiable through CH-like associations.
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Affiliation(s)
- Kaiyin Zhong
- Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Gu Zhu
- Queensland Institute of Medical Research, Brisbane, 4029, Australia
| | - Xiaoxi Jing
- Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China.,University of Chinese Academy of Sciences, Beijing, China
| | - A Emile J Hendriks
- Division of Endocrinology, Department of Pediatrics, Sophia Children's Hospital, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands.,Department of Pediatrics, University of Cambridge, Cambridge, UK
| | - Sten L S Drop
- Division of Endocrinology, Department of Pediatrics, Sophia Children's Hospital, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - M Arfan Ikram
- Department of Internal Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Scott Gordon
- Queensland Institute of Medical Research, Brisbane, 4029, Australia
| | - Changqing Zeng
- Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Andre G Uitterlinden
- Department of Internal Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands.,Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | | | - Fan Liu
- Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands. .,Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China. .,University of Chinese Academy of Sciences, Beijing, China.
| | - Manfred Kayser
- Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands.
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33
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Walsh S, Chaitanya L, Breslin K, Muralidharan C, Bronikowska A, Pospiech E, Koller J, Kovatsi L, Wollstein A, Branicki W, Liu F, Kayser M. Global skin colour prediction from DNA. Hum Genet 2017; 136:847-863. [PMID: 28500464 PMCID: PMC5487854 DOI: 10.1007/s00439-017-1808-5] [Citation(s) in RCA: 73] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2017] [Accepted: 05/03/2017] [Indexed: 12/14/2022]
Abstract
Human skin colour is highly heritable and externally visible with relevance in medical, forensic, and anthropological genetics. Although eye and hair colour can already be predicted with high accuracies from small sets of carefully selected DNA markers, knowledge about the genetic predictability of skin colour is limited. Here, we investigate the skin colour predictive value of 77 single-nucleotide polymorphisms (SNPs) from 37 genetic loci previously associated with human pigmentation using 2025 individuals from 31 global populations. We identified a minimal set of 36 highly informative skin colour predictive SNPs and developed a statistical prediction model capable of skin colour prediction on a global scale. Average cross-validated prediction accuracies expressed as area under the receiver-operating characteristic curve (AUC) ± standard deviation were 0.97 ± 0.02 for Light, 0.83 ± 0.11 for Dark, and 0.96 ± 0.03 for Dark-Black. When using a 5-category, this resulted in 0.74 ± 0.05 for Very Pale, 0.72 ± 0.03 for Pale, 0.73 ± 0.03 for Intermediate, 0.87±0.1 for Dark, and 0.97 ± 0.03 for Dark-Black. A comparative analysis in 194 independent samples from 17 populations demonstrated that our model outperformed a previously proposed 10-SNP-classifier approach with AUCs rising from 0.79 to 0.82 for White, comparable at the intermediate level of 0.63 and 0.62, respectively, and a large increase from 0.64 to 0.92 for Black. Overall, this study demonstrates that the chosen DNA markers and prediction model, particularly the 5-category level; allow skin colour predictions within and between continental regions for the first time, which will serve as a valuable resource for future applications in forensic and anthropologic genetics.
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Affiliation(s)
- Susan Walsh
- Department of Biology, Indiana University Purdue University Indianapolis (IUPUI), Indianapolis, IN, USA.
| | - Lakshmi Chaitanya
- Department of Genetic Identification, Erasmus MC University Medical Centre Rotterdam, Rotterdam, The Netherlands
| | - Krystal Breslin
- Department of Biology, Indiana University Purdue University Indianapolis (IUPUI), Indianapolis, IN, USA
| | - Charanya Muralidharan
- Department of Biology, Indiana University Purdue University Indianapolis (IUPUI), Indianapolis, IN, USA
| | - Agnieszka Bronikowska
- Department of Dermatology, Collegium Medicum of the Jagiellonian University, Kraków, Poland
| | - Ewelina Pospiech
- Faculty of Biology and Earth Sciences, Institute of Zoology, Jagiellonian University, Kraków, Poland
- Malopolska Centre of Biotechnology, Jagiellonian University, Kraków, Poland
| | - Julia Koller
- Department of Genetic Identification, Erasmus MC University Medical Centre Rotterdam, Rotterdam, The Netherlands
| | - Leda Kovatsi
- Laboratory of Forensic Medicine and Toxicology, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Andreas Wollstein
- Section of Evolutionary Biology, Department of Biology II, University of Munich LMU, Planegg-Martinsried, Germany
| | - Wojciech Branicki
- Malopolska Centre of Biotechnology, Jagiellonian University, Kraków, Poland
- Central Forensic Laboratory of the Police, Warsaw, Poland
| | - Fan Liu
- Department of Genetic Identification, Erasmus MC University Medical Centre Rotterdam, Rotterdam, The Netherlands
- Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Manfred Kayser
- Department of Genetic Identification, Erasmus MC University Medical Centre Rotterdam, Rotterdam, The Netherlands.
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34
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Zhong K, Verkouteren JA, Jacobs LC, Uitterlinden AG, Hofman A, Liu F, Nijsten T, Kayser M. Pigmentation-Independent Susceptibility Loci for Actinic Keratosis Highlighted by Compound Heterozygosity Analysis. J Invest Dermatol 2017; 137:77-84. [DOI: 10.1016/j.jid.2016.09.007] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2016] [Revised: 08/29/2016] [Accepted: 09/02/2016] [Indexed: 10/21/2022]
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35
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Namazi H, Akrami A, Hussaini J, Silva ON, Wong A, Kulish VV. The fractal based analysis of human face and DNA variations during aging. Biosci Trends 2016; 10:477-481. [PMID: 27795483 DOI: 10.5582/bst.2016.01182] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Human DNA is the main unit that shapes human characteristics and features such as behavior. Thus, it is expected that changes in DNA (DNA mutation) influence human characteristics and features. Face is one of the human features which is unique and also dependent on his gen. In this paper, for the first time we analyze the variations of human DNA and face simultaneously. We do this job by analyzing the fractal dimension of DNA walk and face during human aging. The results of this study show the human DNA and face get more complex by aging. These complexities are mapped on fractal exponents of DNA walk and human face. The method discussed in this paper can be further developed in order to investigate the direct influence of DNA mutation on the face variations during aging, and accordingly making a model between human face fractality and the complexity of DNA walk.
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Affiliation(s)
- Hamidreza Namazi
- School of Mechanical and Aerospace Engineering, Nanyang Technological University
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36
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Chahal HS, Wu W, Ransohoff KJ, Yang L, Hedlin H, Desai M, Lin Y, Dai HJ, Qureshi AA, Li WQ, Kraft P, Hinds DA, Tang JY, Han J, Sarin KY. Genome-wide association study identifies 14 novel risk alleles associated with basal cell carcinoma. Nat Commun 2016; 7:12510. [PMID: 27539887 PMCID: PMC4992160 DOI: 10.1038/ncomms12510] [Citation(s) in RCA: 71] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2016] [Accepted: 07/08/2016] [Indexed: 12/18/2022] Open
Abstract
Basal cell carcinoma (BCC) is the most common cancer worldwide with an annual incidence of 2.8 million cases in the United States alone. Previous studies have demonstrated an association between 21 distinct genetic loci and BCC risk. Here, we report the results of a two-stage genome-wide association study of BCC, totalling 17,187 cases and 287,054 controls. We confirm 17 previously reported loci and identify 14 new susceptibility loci reaching genome-wide significance (P<5 × 10(-8), logistic regression). These newly associated SNPs lie within predicted keratinocyte regulatory elements and in expression quantitative trait loci; furthermore, we identify candidate genes and non-coding RNAs involved in telomere maintenance, immune regulation and tumour progression, providing deeper insight into the pathogenesis of BCC.
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Affiliation(s)
- Harvind S. Chahal
- Department of Dermatology, Stanford University School of Medicine, Stanford, California 94305, USA
| | - Wenting Wu
- Department of Epidemiology, Richard M. Fairbanks School of Public Health, Melvin & Bren Simon Cancer Center, Indiana University, Indianapolis, Indiana 46202, USA
| | - Katherine J. Ransohoff
- Department of Dermatology, Stanford University School of Medicine, Stanford, California 94305, USA
| | - Lingyao Yang
- Department of Medicine (Quantitative Sciences Unit), Stanford University School of Medicine, Stanford, California 94305, USA
| | - Haley Hedlin
- Department of Medicine (Quantitative Sciences Unit), Stanford University School of Medicine, Stanford, California 94305, USA
| | - Manisha Desai
- Department of Medicine (Quantitative Sciences Unit), Stanford University School of Medicine, Stanford, California 94305, USA
| | - Yuan Lin
- Department of Epidemiology, Richard M. Fairbanks School of Public Health, Melvin & Bren Simon Cancer Center, Indiana University, Indianapolis, Indiana 46202, USA
| | - Hong-Ji Dai
- Department of Epidemiology, Richard M. Fairbanks School of Public Health, Melvin & Bren Simon Cancer Center, Indiana University, Indianapolis, Indiana 46202, USA
- Department of Epidemiology and Biostatistics, Tianjin Medical University Cancer Hospital and Institute, National Clinical Research Center for Cancer, Tianjin & Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Abrar A. Qureshi
- Department of Dermatology, Warren Alpert Medical School, Brown University, Providence, Rhode Island 02903, USA
- Department of Epidemiology, School of Public Health, Brown University, Providence, Rhode Island 02903, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Wen-Qing Li
- Department of Dermatology, Warren Alpert Medical School, Brown University, Providence, Rhode Island 02903, USA
- Department of Epidemiology, School of Public Health, Brown University, Providence, Rhode Island 02903, USA
| | - Peter Kraft
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 02115, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 02115, USA
| | | | - Jean Y. Tang
- Department of Dermatology, Stanford University School of Medicine, Stanford, California 94305, USA
| | - Jiali Han
- Department of Epidemiology, Richard M. Fairbanks School of Public Health, Melvin & Bren Simon Cancer Center, Indiana University, Indianapolis, Indiana 46202, USA
- Department of Epidemiology and Biostatistics, Tianjin Medical University Cancer Hospital and Institute, National Clinical Research Center for Cancer, Tianjin & Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 02115, USA
| | - Kavita Y. Sarin
- Department of Dermatology, Stanford University School of Medicine, Stanford, California 94305, USA
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37
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Genome-wide association study identifies novel susceptibility loci for cutaneous squamous cell carcinoma. Nat Commun 2016; 7:12048. [PMID: 27424798 PMCID: PMC4960294 DOI: 10.1038/ncomms12048] [Citation(s) in RCA: 95] [Impact Index Per Article: 11.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2015] [Accepted: 05/23/2016] [Indexed: 01/08/2023] Open
Abstract
Cutaneous squamous cell carcinoma represents the second most common cutaneous malignancy, affecting 7–11% of Caucasians in the United States. The genetic determinants of susceptibility to cutaneous squamous cell carcinoma remain largely unknown. Here we report the results of a two-stage genome-wide association study of cutaneous squamous cell carcinoma, totalling 7,404 cases and 292,076 controls. Eleven loci reached genome-wide significance (P<5 × 10−8) including seven previously confirmed pigmentation-related loci: MC1R, ASIP, TYR, SLC45A2, OCA2, IRF4 and BNC2. We identify an additional four susceptibility loci: 11q23.3 CADM1, a metastasis suppressor gene involved in modifying tumour interaction with cell-mediated immunity; 2p22.3; 7p21.1 AHR, the dioxin receptor involved in anti-apoptotic pathways and melanoma progression; and 9q34.3 SEC16A, a putative oncogene with roles in secretion and cellular proliferation. These susceptibility loci provide deeper insight into the pathogenesis of squamous cell carcinoma. Cutaneous squamous cell carcinoma is the second most common type of skin cancer. In this genome-wide association study, which includes over 7,000 cases, the authors identify 4 new susceptibility loci for this cancer and also provide independent replication of 9 previously reported susceptibility loci.
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38
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Huang M, Graham BE, Zhang G, Harder R, Kodaman N, Moore JH, Muglia L, Williams SM. Evolutionary triangulation: informing genetic association studies with evolutionary evidence. BioData Min 2016; 9:12. [PMID: 27042214 PMCID: PMC4818851 DOI: 10.1186/s13040-016-0091-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2015] [Accepted: 03/29/2016] [Indexed: 01/13/2023] Open
Abstract
Genetic studies of human diseases have identified many variants associated with pathogenesis and severity. However, most studies have used only statistical association to assess putative relationships to disease, and ignored other factors for evaluation. For example, evolution is a factor that has shaped disease risk, changing allele frequencies as human populations migrated into and inhabited new environments. Since many common variants differ among populations in frequency, as does disease prevalence, we hypothesized that patterns of disease and population structure, taken together, will inform association studies. Thus, the population distributions of allelic risk variants should reflect the distributions of their associated diseases. Evolutionary Triangulation (ET) exploits this evolutionary differentiation by comparing population structure among three populations with variable patterns of disease prevalence. By selecting populations based on patterns where two have similar rates of disease that differ substantially from a third, we performed a proof of principle analysis for this method. We examined three disease phenotypes, lactase persistence, melanoma, and Type 2 diabetes mellitus. We show that for lactase persistence, a phenotype with a simple genetic architecture, ET identifies the key gene, lactase. For melanoma, ET identifies several genes associated with this disease and/or phenotypes related to it, such as skin color genes. ET was less obviously successful for Type 2 diabetes mellitus, perhaps because of the small effect sizes in known risk loci and recent environmental changes that have altered disease risk. Alternatively, ET may have revealed new genes involved in conferring disease risk for diabetes that did not meet nominal GWAS significance thresholds. We also compared ET to another method used to filter for phenotype associated genes, population branch statistic (PBS), and show that ET performs better in identifying genes known to associate with diseases appropriately distributed among populations. Our results indicate that ET can filter association results to improve our ability to discover disease loci.
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Affiliation(s)
- Minjun Huang
- Department of Genetics, Dartmouth College, Geisel School of Medicine, Hanover, NH USA ; Institute for Quantitative Biomedical Sciences, Dartmouth College, Hanover, NH USA
| | - Britney E Graham
- Department of Genetics, Dartmouth College, Geisel School of Medicine, Hanover, NH USA ; Institute for Quantitative Biomedical Sciences, Dartmouth College, Hanover, NH USA
| | - Ge Zhang
- Human Genetics Division, Cincinnati Children's Hospital Medical Center, Cincinnati, OH USA
| | - Reed Harder
- Department of Genetics, Dartmouth College, Geisel School of Medicine, Hanover, NH USA ; Institute for Quantitative Biomedical Sciences, Dartmouth College, Hanover, NH USA
| | - Nuri Kodaman
- Department of Genetics, Dartmouth College, Geisel School of Medicine, Hanover, NH USA ; Institute for Quantitative Biomedical Sciences, Dartmouth College, Hanover, NH USA
| | - Jason H Moore
- Institute for Quantitative Biomedical Sciences, Dartmouth College, Hanover, NH USA ; Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
| | - Louis Muglia
- Center for Prevention of Preterm Birth, Perinatal Institute, Cincinnati Children's Hospital Medical Center, and March of Dimes Prematurity Research Center Ohio Collaborative, Cincinnati, OH USA
| | - Scott M Williams
- Department of Genetics, Dartmouth College, Geisel School of Medicine, Hanover, NH USA ; Institute for Quantitative Biomedical Sciences, Dartmouth College, Hanover, NH USA ; Present Address: Department of Epidemiology and Biostatistics, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106 USA
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39
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Asgari MM, Wang W, Ioannidis NM, Itnyre J, Hoffmann T, Jorgenson E, Whittemore AS. Identification of Susceptibility Loci for Cutaneous Squamous Cell Carcinoma. J Invest Dermatol 2016; 136:930-937. [PMID: 26829030 DOI: 10.1016/j.jid.2016.01.013] [Citation(s) in RCA: 78] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2015] [Revised: 01/04/2016] [Accepted: 01/06/2016] [Indexed: 12/20/2022]
Abstract
We report a genome-wide association study of cutaneous squamous cell carcinoma conducted among non-Hispanic white members of the Kaiser Permanente Northern California health care system. The study includes a genome-wide screen of 61,457 members (6,891 cases and 54,566 controls) genotyped on the Affymetrix Axiom European array and a replication phase involving an independent set of 6,410 additional members (810 cases and 5,600 controls). Combined analysis of screening and replication phases identified 10 loci containing single-nucleotide polymorphisms (SNPs) with P-values < 5 × 10(-8). Six loci contain genes in the pigmentation pathway; SNPs at these loci appear to modulate squamous cell carcinoma risk independently of the pigmentation phenotypes. Another locus contains HLA class II genes studied in relation to elevated squamous cell carcinoma risk following immunosuppression. SNPs at the remaining three loci include an intronic SNP in FOXP1 at locus 3p13, an intergenic SNP at 3q28 near TP63, and an intergenic SNP at 9p22 near BNC2. These findings provide insights into the genetic factors accounting for inherited squamous cell carcinoma susceptibility.
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Affiliation(s)
- Maryam M Asgari
- Department of Dermatology, Massachusetts General Hospital, Boston, Massachusetts, USA; Division of Research, Kaiser Permanente Northern California, Oakland, California, USA
| | - Wei Wang
- Department of Health Research and Policy, Stanford University School of Medicine, Stanford, California, USA
| | - Nilah M Ioannidis
- Department of Health Research and Policy, Stanford University School of Medicine, Stanford, California, USA; Department of Genetics, Stanford University School of Medicine, Stanford, California, USA
| | - Jacqueline Itnyre
- Department of Health Research and Policy, Stanford University School of Medicine, Stanford, California, USA
| | - Thomas Hoffmann
- Department of Epidemiology and Biostatistics and Institute for Human Genetics, University of California, San Francisco, California, USA
| | - Eric Jorgenson
- Division of Research, Kaiser Permanente Northern California, Oakland, California, USA
| | - Alice S Whittemore
- Department of Health Research and Policy, Stanford University School of Medicine, Stanford, California, USA.
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40
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Liu F, Hamer MA, Heilmann S, Herold C, Moebus S, Hofman A, Uitterlinden AG, Nöthen MM, van Duijn CM, Nijsten TE, Kayser M. Prediction of male-pattern baldness from genotypes. Eur J Hum Genet 2015; 24:895-902. [PMID: 26508577 DOI: 10.1038/ejhg.2015.220] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2015] [Revised: 08/27/2015] [Accepted: 09/01/2015] [Indexed: 01/21/2023] Open
Abstract
The global demand for products that effectively prevent the development of male-pattern baldness (MPB) has drastically increased. However, there is currently no established genetic model for the estimation of MPB risk. We conducted a prediction analysis using single-nucleotide polymorphisms (SNPs) identified from previous GWASs of MPB in a total of 2725 German and Dutch males. A logistic regression model considering the genotypes of 25 SNPs from 12 genomic loci demonstrates that early-onset MPB risk is predictable at an accuracy level of 0.74 when 14 SNPs were included in the model, and measured using the area under the receiver-operating characteristic curves (AUC). Considering age as an additional predictor, the model can predict normal MPB status in middle-aged and elderly individuals at a slightly lower accuracy (AUC 0.69-0.71) when 6-11 SNPs were used. A variance partitioning analysis suggests that 55.8% of early-onset MPB genetic liability can be explained by common autosomal SNPs and 23.3% by X-chromosome SNPs. For normal MPB status in elderly individuals, the proportion of explainable variance is lower (42.4% for autosomal and 9.8% for X-chromosome SNPs). The gap between GWAS findings and the variance partitioning results could be explained by a large body of common DNA variants with small effects that will likely be identified in GWAS of increased sample sizes. Although the accuracy obtained here has not reached a clinically desired level, our model was highly informative for up to 19% of Europeans, thus may assist decision making on early MPB intervention actions and in forensic investigations.
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Affiliation(s)
- Fan Liu
- Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands.,Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Merel A Hamer
- Department of Dermatology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Stefanie Heilmann
- Department of Genomics, Life and Brain Center, University of Bonn, Bonn, Germany.,Institute of Human Genetics, University of Bonn, Bonn, Germany
| | - Christine Herold
- German Center for Neurodegenerative Disease (DZNE), Bonn, Germany
| | - Susanne Moebus
- Institute of Medical Informatics, Biometry, and Epidemiology, University Hospital of Essen, University Duisburg-Essen, Essen, Germany
| | - Albert Hofman
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - André G Uitterlinden
- Department of Internal Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands.,Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Markus M Nöthen
- Department of Genomics, Life and Brain Center, University of Bonn, Bonn, Germany.,Institute of Human Genetics, University of Bonn, Bonn, Germany
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Tamar Ec Nijsten
- Department of Dermatology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Manfred Kayser
- Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
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41
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Forensic DNA Phenotyping: Predicting human appearance from crime scene material for investigative purposes. Forensic Sci Int Genet 2015; 18:33-48. [DOI: 10.1016/j.fsigen.2015.02.003] [Citation(s) in RCA: 227] [Impact Index Per Article: 25.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2014] [Revised: 01/29/2015] [Accepted: 02/11/2015] [Indexed: 01/17/2023]
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42
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Liu F, Visser M, Duffy DL, Hysi PG, Jacobs LC, Lao O, Zhong K, Walsh S, Chaitanya L, Wollstein A, Zhu G, Montgomery GW, Henders AK, Mangino M, Glass D, Bataille V, Sturm RA, Rivadeneira F, Hofman A, van IJcken WFJ, Uitterlinden AG, Palstra RJTS, Spector TD, Martin NG, Nijsten TEC, Kayser M. Genetics of skin color variation in Europeans: genome-wide association studies with functional follow-up. Hum Genet 2015; 134:823-35. [PMID: 25963972 PMCID: PMC4495261 DOI: 10.1007/s00439-015-1559-0] [Citation(s) in RCA: 99] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2015] [Accepted: 04/20/2015] [Indexed: 02/05/2023]
Abstract
In the International Visible Trait Genetics (VisiGen) Consortium, we investigated the genetics of human skin color by combining a series of genome-wide association studies (GWAS) in a total of 17,262 Europeans with functional follow-up of discovered loci. Our GWAS provide the first genome-wide significant evidence for chromosome 20q11.22 harboring the ASIP gene being explicitly associated with skin color in Europeans. In addition, genomic loci at 5p13.2 (SLC45A2), 6p25.3 (IRF4), 15q13.1 (HERC2/OCA2), and 16q24.3 (MC1R) were confirmed to be involved in skin coloration in Europeans. In follow-up gene expression and regulation studies of 22 genes in 20q11.22, we highlighted two novel genes EIF2S2 and GSS, serving as competing functional candidates in this region and providing future research lines. A genetically inferred skin color score obtained from the 9 top-associated SNPs from 9 genes in 940 worldwide samples (HGDP-CEPH) showed a clear gradual pattern in Western Eurasians similar to the distribution of physical skin color, suggesting the used 9 SNPs as suitable markers for DNA prediction of skin color in Europeans and neighboring populations, relevant in future forensic and anthropological
investigations.
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Affiliation(s)
- Fan Liu
- Department of Forensic Molecular Biology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands,
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Zubakov D, Kokmeijer I, Ralf A, Rajagopalan N, Calandro L, Wootton S, Langit R, Chang C, Lagace R, Kayser M. Towards simultaneous individual and tissue identification: A proof-of-principle study on parallel sequencing of STRs, amelogenin, and mRNAs with the Ion Torrent PGM. Forensic Sci Int Genet 2015; 17:122-128. [PMID: 25966466 DOI: 10.1016/j.fsigen.2015.04.002] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2014] [Revised: 03/13/2015] [Accepted: 04/03/2015] [Indexed: 11/26/2022]
Abstract
DNA-based individual identification and RNA-based tissue identification represent two commonly-used tools in forensic investigation, aiming to identify crime scene sample donors and helping to provide links between DNA-identified sample donors and criminal acts. Currently however, both analyses are typically performed separately. In this proof-of-principle study, we developed an approach for the simultaneous analysis of forensic STRs, amelogenin, and forensic mRNAs based on parallel targeted DNA/RNA sequencing using the Ion Torrent Personal Genome Machine(®) (PGM™) System coupled with the AmpliSeq™ targeted amplification. We demonstrated that 9 autosomal STRs commonly used for individual identification (CSF1PO, D16S539, D3S1358, D5S818, D7S820, D8S1179, TH01, TPOX, and vWA), the AMELX/AMELY system widely applied for sex identification, and 12 mRNA markers previously established for forensic tissue identification (ALAS2 and SPTB for peripheral blood, MMP10 and MMP11 for menstrual blood, HTN3 and STATH for saliva, PRM1 and TGM4 for semen, CYP2B7P1 and MUC4 for vaginal secretion, CCL27 and LCE1C for skin) together with two candidate reference mRNA markers (HPRT1 and SDHA) can all be successfully combined. Unambiguous mRNA-based tissue identification was achieved in all samples from all forensically relevant tissues tested, and STR sequencing analysis of the tissue sample donors was 100% concordant with conventional STR profiling using a commercial kit. Successful STR analysis was obtained from 1ng of genomic DNA and mRNA analysis from 10ng total RNA; however, sensitivity limits were not investigated in this proof-of-principle study and are expected to be much lower. Since dried materials with noticeable RNA degradation and small DNA/RNA amplicons with high-coverage sequencing were used, the achieved correct individual and tissue identification demonstrates the suitability of this approach for analyzing degraded materials in future forensic applications. Overall, our study demonstrates the feasibility of simultaneously obtaining multilocus STR, amelogenin, and multilocus mRNA information for combined individual and tissue identification from a small sample of degraded biological material. Moreover, our study marks the first step towards combining many DNA/RNA markers for various forensic purposes to increase the effectiveness of molecular forensic analysis and to allow more forensically relevant information to be obtained from limited forensic material.
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Affiliation(s)
- D Zubakov
- Department of Forensic Molecular Biology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - I Kokmeijer
- Department of Forensic Molecular Biology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - A Ralf
- Department of Forensic Molecular Biology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - N Rajagopalan
- Thermo Fisher Scientific/Life Technologies, South San Francisco, CA, USA
| | - L Calandro
- Thermo Fisher Scientific/Life Technologies, South San Francisco, CA, USA
| | - S Wootton
- Thermo Fisher Scientific/Life Technologies, South San Francisco, CA, USA
| | - R Langit
- Thermo Fisher Scientific/Life Technologies, South San Francisco, CA, USA
| | - C Chang
- Thermo Fisher Scientific/Life Technologies, South San Francisco, CA, USA
| | - R Lagace
- Thermo Fisher Scientific/Life Technologies, South San Francisco, CA, USA
| | - M Kayser
- Department of Forensic Molecular Biology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands.
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Visser M, Palstra RJ, Kayser M. Allele-specific transcriptional regulation of IRF4 in melanocytes is mediated by chromatin looping of the intronic rs12203592 enhancer to the IRF4 promoter. Hum Mol Genet 2015; 24:2649-61. [PMID: 25631878 DOI: 10.1093/hmg/ddv029] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2014] [Accepted: 01/24/2015] [Indexed: 01/07/2023] Open
Abstract
The majority of significant single-nucleotide polymorphisms (SNPs) identified with genome-wide association studies are located in non-coding regions of the genome; it is therefore possible that they are involved in transcriptional regulation of a nearby gene rather than affecting an encoded protein's function. Previously, it was demonstrated that the SNP rs12203592, located in intron 4 of the IRF4 gene, is strongly associated with human skin pigmentation and modulates an enhancer element that controls expression of IRF4. In our study, we investigated the allele-specific effect of rs12203592 on IRF4 expression in epidermal skin samples and in melanocytic cells from donors of different skin color. We focused on the characteristics and activity of the enhancer, and on long-range chromatin interactions in melanocytic cells homozygous and heterozygous for rs12203592. We found that, irrespective of the trans-activating environment, IRF4 transcription is strongly correlated with the allelic status of rs12203592, the activity of the rs12203592 enhancer and that the chromatin features depend on the rs12203592 genotype. Furthermore, we demonstrate that the rs12203592 enhancer physically interacts with the IRF4 promoter through an allele-dependent chromatin loop, and suggest that subsequent allele-specific activation of IRF4 transcription is stabilized by another allele-specific loop from the rs12203592 enhancer to an additional regulatory element in IRF4. We conclude that the non-coding SNP rs12203592 is located in a regulatory region and affects a wide range of enhancer characteristics, resulting into modulation of the enhancer's activity, its interaction with the IRF4 promoter and subsequent allele-specific transcription of IRF4. Our findings provide another example of a non-coding SNP affecting skin color by modulating enhancer-mediated transcriptional regulation.
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Affiliation(s)
- Mijke Visser
- Department of Forensic Molecular Biology, Erasmus MC University Medical Centre Rotterdam, Wytemaweg 80, 3015 CN Rotterdam, The Netherlands
| | - Robert-Jan Palstra
- Department of Forensic Molecular Biology, Erasmus MC University Medical Centre Rotterdam, Wytemaweg 80, 3015 CN Rotterdam, The Netherlands
| | - Manfred Kayser
- Department of Forensic Molecular Biology, Erasmus MC University Medical Centre Rotterdam, Wytemaweg 80, 3015 CN Rotterdam, The Netherlands
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