Characterization of population-based variation and putative functional elements for the multiple-cancer susceptibility loci at 5p15.33

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Chung" }, { "@type": "Person", "name": "Meredith Yeager" }, { "@type": "Person", "name": "Sharon A Savage" } ], "publisher": { "@type": "Organization", "name": "F1000Research", "logo": { "@type": "ImageObject", "url": "https://f1000research.com/img/AMP/F1000Research_image.png", "height": 480, "width": 60 } }, "image": { "@type": "ImageObject", "url": "https://f1000research.com/img/AMP/F1000Research_image.png", "height": 1200, "width": 150 }, "description": "Background:TERT encodes the telomerase reverse transcriptase, which is responsible for maintaining telomere ends by addition of (TTAGGG)n nucleotide repeats at the telomere. Recent genome-wide association studies have found common genetic variants at the TERT-CLPTM1L locus (5p15.33) associated with an increased risk of several cancers. Results:Data were acquired for 1627 variants in 1092 unrelated individuals from 14 populations within the 1000 Genomes Project. We assessed the population genetics of the 5p15.33 region, including recombination hotspots, diversity, heterozygosity, differentiation among populations, and potential functional impacts. There were significantly lower polymorphism rates, divergence, and heterozygosity for the coding variants, particularly for non-synonymous sites, compared with non-coding and silent changes. Many of the cancer-associated SNPs had differing genotype frequencies among ancestral groups and were associated with potential regulatory changes. Conclusions:Surrogate SNPs in linkage disequilibrium with the majority of cancer-associated SNPs were functional variants with a likely role in regulation of TERT and/or CLPTM1L. Our findings highlight several SNPs that future studies should prioritize for evaluation of functional consequences." } { "@context": "http://schema.org", "@type": "BreadcrumbList", "itemListElement": [ { "@type": "ListItem", "position": "1", "item": { "@id": "https://f1000research.com/", "name": "Home" } }, { "@type": "ListItem", "position": "2", "item": { "@id": "https://f1000research.com/browse/articles", "name": "Browse" } }, { "@type": "ListItem", "position": "3", "item": { "@id": "https://f1000research.com/articles/3-231/v1", "name": "Characterization of population-based variation and putative functional..." } } ] } Home Browse Characterization of population-based variation and putative functional... ALL Metrics - Views Downloads Get PDF Get XML Cite How to cite this article Mirabello L, Chung CC, Yeager M and Savage SA. Characterization of population-based variation and putative functional elements for the multiple-cancer susceptibility loci at 5p15.33 [version 1; peer review: 2 approved] . F1000Research 2014, 3 :231 ( https://doi.org/10.12688/f1000research.5186.1 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. Close Copy Citation Details Export Export Citation Sciwheel EndNote Ref. Manager Bibtex ProCite Sente EXPORT Select a format first Track Share ▬ ✚ Research Article Characterization of population-based variation and putative functional elements for the multiple-cancer susceptibility loci at 5p15.33 [version 1; peer review: 2 approved] Lisa Mirabello 1 , Charles C. Chung 1 , Meredith Yeager 2 , Sharon A Savage https://orcid.org/0000-0001-6006-0740 1 Lisa Mirabello 1 , Charles C. Chung 1 , Meredith Yeager 2 , Sharon A Savage https://orcid.org/0000-0001-6006-0740 1 PUBLISHED 02 Oct 2014 Author details Author details 1 Division of Cancer Epidemiology and Genetics, National Cancer Institute,National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20892, USA 2 Cancer Genomics Research Laboratory, National Cancer Institute, Division of Cancer Epidemiology and Genetics, Leidos Biomedical Research, Inc., Frederick, MD 20877, USA OPEN PEER REVIEW DETAILS REVIEWER STATUS Abstract Background: TERT encodes the telomerase reverse transcriptase, which is responsible for maintaining telomere ends by addition of (TTAGGG) n nucleotide repeats at the telomere. Recent genome-wide association studies have found common genetic variants at the TERT-CLPTM1L locus (5p15.33) associated with an increased risk of several cancers. Results: Data were acquired for 1627 variants in 1092 unrelated individuals from 14 populations within the 1000 Genomes Project. We assessed the population genetics of the 5p15.33 region, including recombination hotspots, diversity, heterozygosity, differentiation among populations, and potential functional impacts. There were significantly lower polymorphism rates, divergence, and heterozygosity for the coding variants, particularly for non-synonymous sites, compared with non-coding and silent changes. Many of the cancer-associated SNPs had differing genotype frequencies among ancestral groups and were associated with potential regulatory changes. Conclusions: Surrogate SNPs in linkage disequilibrium with the majority of cancer-associated SNPs were functional variants with a likely role in regulation of TERT and/or CLPTM1L. Our findings highlight several SNPs that future studies should prioritize for evaluation of functional consequences. READ ALL READ LESS Keywords TERT, CLPTM1L, population genetics, 5p15.33 Corresponding Author(s) Lisa Mirabello ( [email protected] ) Close Corresponding author: Lisa Mirabello Competing interests: No competing interests were disclosed. Grant information: This project has been funded by the Intramural Research Program of the Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, and with federal funds from the National Cancer Institute, National Institutes of Health, under contract number HHSN261200800001E to M.Y. and C.C.C. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Copyright: © 2014 Mirabello L et al . This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The author(s) is/are employees of the US Government and therefore domestic copyright protection in USA does not apply to this work. The work may be protected under the copyright laws of other jurisdictions when used in those jurisdictions. Data associated with the article are available under the terms of the Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication). How to cite: Mirabello L, Chung CC, Yeager M and Savage SA. Characterization of population-based variation and putative functional elements for the multiple-cancer susceptibility loci at 5p15.33 [version 1; peer review: 2 approved] . F1000Research 2014, 3 :231 ( https://doi.org/10.12688/f1000research.5186.1 ) First published: 02 Oct 2014, 3 :231 ( https://doi.org/10.12688/f1000research.5186.1 ) Latest published: 02 Oct 2014, 3 :231 ( https://doi.org/10.12688/f1000research.5186.1 ) Introduction The 5p15.33 locus includes the TERT (human telomerase reverse transcriptase) and the CLPTM1L (alias CRR9; cleft lip and palate transmembrane 1 like) genes. Telomerase reverse transcriptase (TERT) is the essential catalytic component of the telomerase holoenzyme responsible for maintaining telomere ends. Telomerase compensates for DNA polymerase’s inability to fully replicate the lagging DNA strand by adding hexanucleotide (5'-TTAGGG-3') n repeats to the 3’ end of chromosomes using a template sequence within the RNA component (TERC) of the enzyme 1 . Telomeres, consisting of these hexanucleotide repeats and several associated proteins, are responsible for preserving chromosomal stability by protecting chromosomes from end-to-end fusion, atypical recombination, and degradation 2 . In normal differentiated cells, expression of telomerase is very low or absent and telomeres erode by 50 to 200 base pairs with each cell division 1 . When the telomeres become critically short, they act as a cellular clock and signal cellular senescence and apoptosis 3 , 4 . In contrast, telomerase activity has been detected in 90% of human cancers 5 , 6 and allows these malignant cells to continually divide by bypassing cellular crisis 7 . CLPTM1L is located approximately 23 kilobases (kb) centromeric of TERT . Little is known about the function of the CLPTM1L protein. It is a predicted transmembrane protein that is expressed in a range of normal and malignant tissues including skin, lung, breast, ovary and cervix, and has been shown to sensitize ovarian cancer cells to cisplatin-induced apoptosis 8 . The clinically related telomere biology disorders (TBDs), such as pulmonary fibrosis or aplastic anemia, are associated with germline mutations causing amino acid substitutions, additions, deletions, and frame shift mutations within TERT 9 , 10 . Patients with the more severe TBD, dyskeratosis congenita (DC) have very high risks of bone marrow failure and cancer, and have telomeres below the 1 st percentile for their age 11 . DC represents the most clinically severe outcome of germline TERT mutations and often presents in childhood. Individuals with isolated aplastic anemia or pulmonary fibrosis due to TERT mutations tend to manifest clinical symptoms in adulthood. Genome-wide association studies (GWAS) have found that common genetic variants, in the form of single nucleotide polymorphisms (SNPs), within the TERT-CLPTM1L locus (5p15.33) are associated with relatively low but highly statistically significant risks (odds ratios for risk alleles ranging between 1.05–1.6) of several cancers, including glioma 12 , 13 , basal cell carcinoma 14 , 15 , testicular 16 , pancreatic 17 , lung 18 – 20 , bladder 21 , colorectal 22 , breast 23 , and overall cancers 24 [reviewed in 25 , 26 ]. Both TERT and CLPTM1L are evolutionarily conserved across diverse species, which suggests their functional importance 8 , 27 , 28 . TERT has low nucleotide diversity, and common SNPs in this gene region show low levels of differentiation among populations and high ancestral allele frequencies 28 , 29 ; this pattern of low overall diversity suggests that TERT may be constrained 29 . The 1000 Genomes Project Consortium has reported that different populations have different profiles of rare and common variants; and, varying degrees of purifying selection at functionally relevant low-frequency sites which lead to substantial local population differentiation 30 . Large surveys of human genetic variation have described an excess of rare genetic variants as a result of a recent population expansion and weak purifying selection 31 – 33 , particularly for variants in disease genes and for individuals of European ancestry 33 . In order to better understand the population genetics underlying the 5p13.3 locus associated with cancer, we conducted a detailed analysis of allele frequency patterns among ancestral group, levels of differentiation, and recombination at the 5p15.33 locus using 1000 Genomes Project 34 data. We retrieved data for the TERT-CLPTM1L genes and flanking regions for 1092 individuals from 14 populations. Analyses were focused on understanding how allele frequencies differ between populations, and evaluation of the cancer-associated SNPs and their surrogate markers for potential functional elements. Materials and methods Dataset Data were retrieved for 1627 variants on 5p15.33 (hg19, chr5: 1,243,287–1,355,002) for all individuals in the 14 populations (1092 individuals) included in the 1000 Genomes project (2012 February release) 34 . Eighteen potentially related individuals were removed, which resulted in 1074 individuals. We also retrieved data for a flanking region, approximately 10kb upstream and downstream, in order to improve understanding of these gene regions [ Data File 1 ]. Data analysis The package ARLEQUIN version 3.5 35 was used to compute F ST values, diversity, AMOVA, and heterozygosity. F ST values based on allele frequencies were calculated as a measure of population differentiation, and significance was estimated with 10,000 permutations; and, these levels were compared to the genome-wide average for autosomal SNPs ( F ST ≈ 0.1 36 – 39 ). The population of African-Americans in the Southwestern United States (ASW) was grouped with the two populations of West African ancestry (Luhya in Kenya [LWK] and Yoruba in Nigeria [YRI]) since in our population level analyses they were found to be most closely related to these individuals of African ancestry, as previously observed 40 . In order to apportion the fraction of the genetic variance due to differences between and within ancestral groups (European, East Asian, West African, and American) and infer the genetic structure of the populations, AMOVA was performed with 10,000 permutations. HAPLOVIEW version 4.1 41 was used to determine the degree of linkage disequilibrium (LD) and minor allele frequency (MAF). The GLU genetics’ ld.tagzilla module was used for the tag analysis with a LD pairwise r 2 threshold of 0.8. Pairwise LD was analyzed separately for the four ancestral groups and used to select tag SNPs for each region. SNPs within TERT and CLPTM1L were grouped by functional category ( i.e. , coding vs . non-coding, and synonymous vs . non-synonymous variants), and tested for significant differences in the normalized number of variant sites, allelic frequency divergence, heterozygosity, minor allele frequency (MAF), and levels of differentiation among populations; significant differences would suggest that these functional categories of loci were not affected similarly, as expected under the assumption of neutrality. The allelic frequency divergence between ancestral groups was computed using: d = 1-[( x 1 y 1 ) 1/2 + ( x 2 y 2 ) 1/2 ], where x 1 and y 1 are the frequencies of the first allele and x 2 and y 2 are the frequencies of the second allele 42 . The normalized number of variant sites was calculated as: θ^ = K/Σ n-1 i=1 i -1 L, where K is the number of variant sites, n is the number of chromosomes, and L is the total sequence length. Differences between the SNP functional categories were tested for significance with a two-tailed t -test. SIFT ( S orts I ntolerant F rom T olerant) and Polyphen 2 ( Poly morphism Phen otyping v 2 ) were used to predict the potential impact of an amino acid substitution 43 , 44 . To identify recombination hotspots in this region, we used SequenceLDhot 45 , a program that uses the approximate marginal likelihood method 46 and calculates likelihood ratio statistics at a set of possible hotspots. We used the four ancestral groups [European (EUR; n=379), East Asian (EA; n=286), American (AM; n=184), and African (AFR; n=246)] to calculate background recombination rates using PHASE v2.1 47 , 48 . The likelihood ratio statistics of 12 predicts the presence of a hotspot with a false-positive rate of 1 in 3,700 independent tests. Putative functional elements were assessed using the UCSC genome browser ( http://genome.ucsc.edu/ ), a publically available bioinformatics website, for ENCODE Regulation and Comparative Genomics tracks for all of the cancer-associated SNPs and their surrogates for each ancestral group. SNPs were considered surrogates for cancer-associated SNPs for each ancestral group if the r 2 ≥0.60, the inter-marker distance ≤200kb, and the MAF ≥0.05. We assessed potential regions of open chromatin with DNase hypersensitivity; potential regulatory histone marks (H3K4Me1, H3K4Me3, H3K27Ac); protein binding sites; regulatory motifs; CpG islands; conserved mammalian microRNA regulatory binding sites; and evolutionary conservation among placental mammals using the phylop basewise conservation measurement 49 . Functional elements were also assessed using RegulomeDB, an integrated database that annotates SNPs with known or predicted regulatory DNA elements, including DNase hypersensitivity, transcription factor binging sites, and promoter regions that regulate transcription using data from GEO, ENCODE, and published literature 50 . RegulomeDB scores are a heuristic scoring system based on confidence that a variant is located in a functional region and likely results in a functional consequence, these are used to assist comparison among annotations 50 . Lower scores indicate increased evidence; category 2 scores are variants likely to affect binding, category 3 scores are less likely to affect binding; and 4, 5, or 6 scores are variants with minimal binding evidence. Results SNP ID or position rs34614851 rs141268231 rs117361553 rs13361701 rs185750534 rs4075202 rs150217565 rs138815909 1243637 1243650 rs79457861 rs111236460 rs35661976 rs74581452 rs116761974 rs114952930 1243759 1243760 rs149391939 rs75434344 1243873 rs143776496 rs181138957 rs185631475 rs138520447 rs73731707 rs191004437 rs7448994 1244293 rs117052364 1244372 1244394 rs4073918 1244426 1244466 1244478 rs115620695 1244710 rs144078299 rs73034557 rs6871519 rs116221992 rs182346130 rs186113778 rs147333613 rs4975540 rs139450182 rs143460735 rs7716467 rs116997179 1245935 1245955 rs191838156 rs75499032 1246083 rs114331542 rs140965680 1246168 rs187474586 rs192324636 rs182677530 rs139516849 rs186992937 rs62331328 rs149711208 rs6883980 rs74891230 rs116980650 rs111429257 rs192932406 rs184171014 rs189549363 rs193056759 rs184819493 rs4975620 rs114459929 rs188901202 rs181687490 rs112135422 rs185868916 rs112854541 rs112375115 rs116121172 rs139338034 rs12513872 rs181426760 rs114121806 rs144136776 rs191173427 rs181906076 rs111230680 rs116137502 rs146530315 rs186597804 rs12656500 rs182888752 rs6554691 rs114282586 rs4583925 Individual ID_population ID HG00096_GBR AA GG CC GG TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA TT GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC TT AA GG GG TT AA GG GG GG CC TG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00097_GBR AA GG CC GT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA TC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC TC AA GG GG TT AA GG GG GG CT GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00099_GBR AA GG CC GT TT CC TT GG GG CC GG GG CC AG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA TC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC TC GA GG GG TT AA GG GG GG CT GG CC GG GG CC CC GG GG GG GA CC AA CC CC GG GG CC GG GG CC GG TA GG CC HG00100_GBR AA GG CC GT TT CC TT GG GG CC GG GG CC AG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA TC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC TC GA GG GG TT AA GG GG GG CT GG CC GG GG CC CC GG GG GG GA CC AA CC CC GG GG CC GG GG CC GG TA GG CC HG00101_GBR AA GG CC TT TT CC TT GG GG CC GG GG CC AG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TT CC CC GA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG GA CC AA CC CC GG GG CC GG GG CC GG TA GG CC HG00102_GBR AA GG CC GT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA TC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC TC AA GG GG TT AA GG GG GG CT GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00103_GBR AA GG CC GT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA TC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC TC AA GG GG TT AA GG GG GG CT GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00104_GBR AA GG CC GT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA TC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC TC AA GG GG TT AA GG GG GG CT GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00106_GBR AA GG CC GT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TC CC GG GG CC CT GG GG GG TT GG GG CC GG GG TT GG AA TC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC TC AA GG GG TT AA GG GG GG CT GG CC GG GG CC CC GG GG GG GA CC AA CC CC GG GG CC GG GG CC GG TA GG CC HG00108_GBR AA GG CC TT TT CC TT GG GG CC GG GG CC AG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TT CC CC GA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG GA CC AA CC CC GG GG CC GG GG CC GG TA GG CC HG00109_GBR AA GG CC GT TT CC TT GG GG CC GG GG CC AG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA TC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC TC GA GG GG TT AA GG GG GG CT GG CC GG GG CC CC GG GG GG GA CC AA CC CC GG GG CC GG GG CC GG TA GG CC HG00110_GBR AA GG CC TT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TC CC GG GG CC CT GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC CC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG GA CC AA CC CC GG GG CC GG GG CC GG TA GG CC HG00111_GBR AA GG CC GG TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA TT GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC TT AA GG GG TT AA GG GG GG CC GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00112_GBR AA GG CC TT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TT CC GG GG CC CC GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC CC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG GG CC AA CC CC GG GG CC GG GG CC GG TT GG CC HG00113_GBR AA GG CC GT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TC CC GG GG CC CT GG GG GG TT GG GG CC GG GG TT GG AA TC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC TC AA GG GG TT AA GG GG GG CT GG CC GG GG CC CC GG GG GG GA CC AA CC CC GG GG CC GG GG CC GG TA GG CC HG00114_GBR AA GG CC GT TT AC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC TC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG TC HG00116_GBR AA GG CC GT TT CC TT GG GG CC GG GG TC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA TC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC TC AA GG GG TT AA GG GG GG CT GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00117_GBR AA GG CC GG TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT CG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA TT GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC TT AA GG GG TT AA GG GG GG CC GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00118_GBR AA GG CC TT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TT CC GG GG CC CT GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC CC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG GA CC AA CC CC GG GG CC GG GG CC GG TA GG CC HG00119_GBR AA GG CC GT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TT CC GG GG CC CT GG GG GG TT GG GG CC GG GG TT GG AA TC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC TC AA GG GG TT AA GG GG GG CT GG CC GG GG CC CC GG GG GG GA CC AA CC CC GG GG CC GG GG CC GG TA GG CC HG00120_GBR AA GG CC GT TT CC TT GG GG CC GG GG TC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA TC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC TC AA GG GG TT AA GG GG GG CT GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00121_GBR AA GG CC TT TT CC TT GG GG CC GG GG TC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TC CC GG GG CC CT GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC CC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG GA CC AA CC CC GG GG CC GG GG CC GG TA GG CC HG00122_GBR AA GG CC GT TT AC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TT CC GG GG CC CT GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC TC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG GA CC AA CC CC GG GG CC GG GG CC GG TA GG TC HG00123_GBR AA GG CC TT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TC CC GG GG CC CT GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC CC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG GA CC AA CC CC GG GG CC GG GG CC GG TA GG CC HG00124_GBR AA GG CC TT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TC CC GG GG CC CT GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC CC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG GA CC AA CC CC GG GG CC GG GG CC GG TA GG CC HG00125_GBR AA GG CC GT TT CC TT GG GG CC GG GG TC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA TC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC TC AA GG GG TT AA GG GG GG CT GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00126_GBR AA GG CC GT TT AC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC TC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG TC HG00127_GBR AA GG CC GT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TT CC GG GG CC CT GG GG GG TT GG GG CC GG GG TT GG AA TC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC TC AA GG GG TT AA GG GG GG CT GG CC GG GG CC CC GG GG GG GA CC AA CC CC GG GG CC GG GG CC GG TA GG CC HG00128_GBR AA GG CC GT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA TC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC TC AA GG GG TT AA GG GG GG CT GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00129_GBR AA GG CC GT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA TC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC TC AA GG GG TT AA GG GG GG CT GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00130_GBR AA GG CC GT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA TC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC TC AA GG GG TT AA GG GG GG CT GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00131_GBR AA GG CC GG TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA TT GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC TT AA GG GG TT AA GG GG GG CC GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00133_GBR AA GG CC GG TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA TT GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC TT AA GG GG TT AA GG GG GG CC TT CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00134_GBR AA GG CC TT TT CC TT GG GG CC GG GG CC AG AA AA CC GG CC TT TT GG GG CC CC GG TT TT CC GG GG CC CT GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC CC GA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG GG CC AA CC CC GG GG CC GG GG CC GG TT GG CC HG00135_GBR AA GG CC TT TT CC TT GG GG CC GG GG CC AG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TT CC CC GA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG GA CC AA CC CC GG GG CC GG GG CC GG TA GG CC HG00136_GBR AA GG CC GT TT CC TT GG GG CC GG GG TC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG AG TT GG GG CC GG GG TT GG AA TC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC TC AA GG GG TT AA GG GG GG CT GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00137_GBR AA GG CC GT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TC CC GG GG CC CT GG GG GG TT GG GG CC GG GG TT GG AA TC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC TC AA GG GG TT AA GG GG GG CT GG CC GG GG CC CC GG GG GG GA CC AA CC CC GG GG CC GG GG CC GG TA GG CC HG00138_GBR AA GG CC GT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA TC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TT CC TC AA GG GG TT AA GG GG GG CT GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00139_GBR AA GG CC GT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA TC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC TC AA GG GG TT AA GG GG GG CT GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00140_GBR AA GG CC TT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TT CC GG GG CC CC GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC CC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG GG CC AA CC CC GG GG CC GG GG CC GG TT GG CC HG00141_GBR AA GG CC TT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TC CC GG GG CC CT GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC CC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG GA CC AA CC CC GG GG CC GG GG CC GG TA GG CC HG00142_GBR AA GG CC TT TT CC TT GG GG CC GG GG CC AG AA AA CC GG CC TT TT GG GG CC TC GG TT TC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TT CC CC GA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG GA CC AA CC CC GG GG CC GG GG CC GG TA GG CC HG00143_GBR AA GG CC TT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TT CC CC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00148_GBR AA GG CC TT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT TC GG GG GG CC TT CC CC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00149_GBR AA GG CC TT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TT CC CC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00150_GBR AA GG CC TT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TT CC CC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00151_GBR AA GG CC GG TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA TT GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC TT AA GG GG TT AA GG GG GG CC GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00152_GBR AA GG CC GT TT AC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC TC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG TC HG00154_GBR AA GG CC GT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TC CC GG GG CC CT GG GG GG TT GG GG CC GG GG TT GG AA TC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC TC AA GG GG TT AA GG GG GG CT GG CC GG GG CC CC GG GG GG GA CC AA CC CC GG GG CC GG GG CC GG TA GG CC HG00155_GBR AA GG CC GT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TC CC GG GG CC CT GG GG GG TT GG GG CC GG GG TT GG AA TC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC TC AA GG GG TT AA GG GG GG CT GG CC GG GG CC CC GG GG GG GA CC AA CC CC GG GG CC GG GG CC GG TA GG CC HG00156_GBR AA GG CC GT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA TC GG GG GG CC GG TT TT CC CC GG AA TT TC GG GG GG CC TC CC TC AA GG GG TT AA GG GG GG CT GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00158_GBR AA GG CC GT TT AC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC TC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG TC HG00159_GBR AA GG CC GT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA TC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC TC AA GG GG TT AA GG GG GG CC GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00160_GBR AA GG CC GT TT CC TT GG GG CC GG GG TC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA TC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC TC AA GG GG TT AA GG GG GG CT GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00171_FIN AA GG CC GG TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA TT GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TT CC TT AA GG GG TT AA GG GG GG CC GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00173_FIN AA GG CC TT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC TC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TT CC CC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00174_FIN AA GG CC GG TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC AG TT CC CC GG GG CC TT GG GG GG TT GG GG AC GG GG TT GG AA TT GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC TT AA GG GG TT AA GG GG GG CC GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00176_FIN AA GG CC GT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA TC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC TC AA GG GG TT AA GG GG GG CT GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00177_FIN AA GG CC GT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TC CC GG GG CC CT GG GG GG TT GG GG CC GG GG TT GG AA TC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC TC AA GG GG TT AA GG GG GG CT GG CC GG GG CC CC GG GG GG GA CC AA CC CC GG GG CC GG GG CC GG TA GG CC HG00178_FIN AA GG CC GT TT AC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TC CC GG GG CC CT GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC TC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG GA CC AA CC CC GG GG CC GG GG CC GG TA GG TC HG00179_FIN AA GG CC GG TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA TT GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC TT AA GG GG TT AA GG GG GG CC GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC 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GG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA TC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC TC AA GG GG TT AA GG GG GG CT GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00342_FIN AA GG CC TT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TT CC CC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00343_FIN AA GG CC TT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TT CC GG GG CC CC GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC CC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG GG CC AA CC CC GG GG CC GG GG CC GG TT GG CC HG00344_FIN AA GG CC TT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TC CC GG GG CC CT GG GG GG TT 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GG CC CC CC TC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG GA CC AA CC CC GG GG CC GG GG CC GG TA GG TC HG00350_FIN AA GG CC GG TT AC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT CG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA TC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC TT AA GG GG TT AA GG GG GG CT GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG TC HG00351_FIN AA GG CC GG TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA TT GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC TT AA GG GG TT AA GG GG GG CC GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00353_FIN AA GG CC GT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA TC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TT CC TC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG AA 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GG CC TT GG GG GG TT GG GG AC GG GG TT GG AA TC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC TC AA GG GG TT AA GG GG GG CT GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00362_FIN AA GG CC GG TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA TT GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC TT AA GG GG TT AA GG GG GG CC GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00364_FIN AA GG CC GG TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA TT GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC TT AA GG GG TT AA GG GG GG CC GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00366_FIN AA GG CC TT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TT CC GG GG CC CT GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC CC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG GA CC AA CC CC GG GG CC GG GG CC GG TA GG CC HG00367_FIN AA GG CC GT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TC CC GG GG CC CT GG GG GG TT GG GG CC GG GG TT GG AA TC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC TC AA GG GG TT AA GG GG GG CT GG CC GG GG CC CC GG GG GG GA CC AA CC CC GG GG CC GG GG CC GG TA GG CC HG00369_FIN AA GG CC GG TT AC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT CG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA TC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC TT AA GG GG TT AA GG GG GG CT GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG TC HG00372_FIN AA GG CC GT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA TC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC TT AA GG GG TT AA GG GG GG CC GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00373_FIN AA GG CC TT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TT CC GG GG CC CC GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC CC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG GG CC AA CC CC GG GG CC GG GG CC GG TT GG CC HG00375_FIN AA GG CC TT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TC CC GG GG CC CT GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC CC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG GA CC AA CC CC GG GG CC GG GG CC GG TA GG CC HG00376_FIN AA GG CC TT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TT CC CC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00377_FIN AA GG CC GT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC AG TT CC CC GG GG CC TT GG GG GG TT GG GG AC GG GG TT GG AA TC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC TC AA GG GG TT AA GG GG GG CT GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00378_FIN AA GG CC GT TT AC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TC CC GG GG CC CT GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC TC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG GA CC AA CC CC GG GG CC GG GG CC GG TA GG TC HG00381_FIN AA GG CC TT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TC CC GG GG CC CT GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC CC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG GA CC AA CC CC GG GG CC GG GG CC GG TA GG CC HG00382_FIN AA GG CC TT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TC CC GG GG CC CT GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC CC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG GA CC AA CC CC GG GG CC GG GG CC GG TA GG CC HG00383_FIN AA GG CC GT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TC CC GG GG CC CT GG GG GG TT GG GG CC GG GG TT GG AA TC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC TC AA GG GG TT AA GG GG GG CT GG CC GG GG CC CC GG GG GG GA CC AA CC CC GG GG CC GG GG CC GG TA GG CC HG00384_FIN AA GG CC TT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TC CC GG GG CC CT GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC CC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG GA CC AA CC CC GG GG CC GG GG CC GG TA GG CC HG00403_CHS AA GG CC TT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TT CC GG GG CC TC GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC CC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG AG CC AA CC CC GG GG CC GG GG CC GG AT GG CC HG00404_CHS AA GG CC TT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TT CC GG GG CC CC GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC CC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG GG CC AA CC CC GG GG CC GG GG CC GG TT GG CC HG00406_CHS AA GG CC TT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TT CC GG GG CC CC GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC CC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG GG CC AA CC CC GG GG CC GG GG CC GG TT GG CC HG00407_CHS AA GG CC TT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TT CC GG GG CC CC GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC CC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG GG CC AA CC CC GG GG CC GG GG CC GG TT GG CC HG00418_CHS AA GG CC TT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TT CC GG GG CC CC GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC CC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG GG CC AA CC CC GG GG CC GG GG CC GG TT GG CC HG00419_CHS AA GG CC TT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TT CC GG GG CC CC GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC CC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG GG CC AA CC CC GG GG CC GG GG CC GG TT GG CC HG00421_CHS AA GG CC TT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CC CC GG GG CC TT GG GG GG TT GG GG CC GG GG CT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TT CC CC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG AA CC AA CC CC GG GG CC GG GG CC GG AA GG CC HG00422_CHS AA GG CC TT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CT CC GG GG CC TC GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC CC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG AG CC AA CC CC GG GG CC GG GG CC GG AT GG CC HG00427_CHS AA GG CC GT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CT CC GG GG CC TC GG GG GG TT GG GG CC GG GG TT GG AA TC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC TC AA GG GG TT AA GG GG GG CT GG CC GG GG CC CC GG GG GG AG CC AA CC CC GG GG CC GG GG CC GG AT GG CC HG00428_CHS AA GG CC TT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TT CC GG GG CC CC GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG TC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC CC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG GG CC AA CC CC GG GG CC GG GG CC GG TT GG CC HG00436_CHS AA GG CC TT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CT CC GG GG CC TC GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC CC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG AG CC AA CC CC GG GG CC GG GG CC GG AT GG CC HG00437_CHS AA GG CC TT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TT CC GG GG CC CC GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC CC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG GG CC AA CC CC GG GG CC GG GG CC GG TT GG CC HG00442_CHS AA GG CC TT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TT CC GG GG CC CC GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG TC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC CC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG GG CC AA CC CC GG GG CC GG GG CC GG TT GG CC HG00443_CHS AA GG CC TT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CT CC GG GG CC TC GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC CC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG AG CC AA CC CC GG GG CC GG GG CC GG AT GG CC HG00445_CHS AA GG CC TT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CT CC GG GG CC TC GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC CC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG AG CC AA GC CC GG GG CC GG GG CC GG AT GG CC HG00446_CHS AA GG CC TT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TT CC GG GG CC CC GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC CC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG GG CC AA CC CC GG GG CC GG GG CC GG TT GG CC HG00448_CHS AA GG CC TT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT TT CC GG GG CC CC GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC CC CC CC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG GG CC AA CC CC GG GG CC GG GG CC GG TT GG CC HG00449_CHS AA GG CC TT TT CC TT GG GG CC GG GG CC GG AA AA CC GG CC TT TT GG GG CC CC GG TT CT CC GG GG CC TC GG GG GG TT GG GG CC GG GG TT GG AA CC GG GG GG CC GG TT TT CC CC GG AA TT CC GG GG GG CC TC CC CC AA GG GG TT AA GG GG GG TT GG CC GG GG CC CC GG GG GG AG CC AA CC CC GG GG CC GG GG CC GG AT GG CC This is a portion of the data; to view all the data, please download the file. Dataset 1. Genotype data for 1627 variants on 5p15.33 (hg19, chr5: 1,243,287–1,355,002) for 1074 individuals from 14 populations. Data were retrieved for 1627 variants on 5p15.33 (hg19, chr5: 1,243,287–1,355,002) for all individuals in the 14 populations (1092 individuals) included in the 1000 Genomes project (2012 February release). Eighteen potentially related individuals were removed, which resulted in 1074 individuals. Allele frequency spectrum There were 1627 variants in the TERT-CLPTM1L region among all individuals (N=1074): 167 were upstream of TERT , 563 in TERT (including UTR, intronic and exonic regions), 353 were between TERT and CLPTM1L (downstream of TERT and upstream of CLPTM1L ), 412 in CLPTM1L (including UTR, intronic and exonic regions), and 132 downstream of CLPTM1L . A summary of the variation for the different functional categories of polymorphisms in TERT and CLPTM1L is given in Table 1 . The majority of SNPs in TERT and CLPTM1L were in intronic regions (N=903), only 72 were exonic (49 in TERT and 18 in CLPTM1L ). 46 of the exonic variants were synonymous changes (32 in TERT and 9 in CLPTM1L ) and 26 were non-synonymous protein altering variants (PAV) (17 in TERT and 9 in CLPTM1L ). The SNPs previously associated with cancer at 5p15.33 25 are all located in the intronic regions of TERT or CLPTM1L or intergenic between these genes, except for one which is a coding synonymous SNP in TERT (rs2736098; Table 2 ). Table 1. Summary of variation for the different classes of polymorphisms for all individuals (n=1074). Polymorphism type bp screened No. Polys Frequency (SNP/bp) θ^ Het. MAF Non-coding* 61,757 903 1/68 1.77E -03 0.120 9.03% Coding 7,126 72 1/99 1.22E -03 0.036 2.14% Synonymous 46 1/155 7.82E -04 0.048 2.92% Non-synonymous 26 1/274 4.42E -04 0.014 0.69% * includes intronic and 3' UTR SNPs; bp = base-pairs; Polys = polymorphisms; θ^ = normalized number of variant sites; Het. = heterozygosity; MAF = minor allele frequency; F ST = level of differentiation among ancestral groups. Table 2. Summary of the cancer-associated SNPs at the TERT-CLPTM1L locus. SNP Position Gene Function Ethnicity † Cancer(s) Alleles ‡ RAF F ST AFR EUR AM EA rs4246742 1267356 TERT intron Misc. Lung T :A 67.4% 83.5% 77.7% 60.7% 0.055 rs10069690 1279790 TERT intron EUR, AFR Breast C: T 62.7% 27.5% 25.1% 15.9% 0.17 rs2242652 1280028 TERT intron EUR Prostate G: A 14.4% 21.0% 18.1% 16.4% 0.003 rs13167280 1280477 TERT intron EUR Bladder G: A 2.8% 13.0% 13.8% 19.1% 0.036 rs2736100 1286516 TERT intron Misc, EUR, Asian Lung, CNS, Bladder, Pancreas, Testis A: C 43.8% 50.0% 44.6% 39.3% 0.009 rs2853676 1288547 TERT intron Misc. CNS, Lung C: T 21.2% 27.5% 26.8% 16.1% 0.016 rs2736098 1294086 TERT coding, syn. Misc. Bladder, Lung C: T 6.0% 23.4% 19.5% 32.9% 0.062 rs2736108 1297488 Intergenic EUR Breast C: T 6.7% 27.5% 22.3% 25.9% 0.045 rs2853668 1300025 Intergenic EUR, Misc. Pancreas, Lung, Colon G: T 52.6% 25.8% 30.8% 24.3% 0.069 rs2735845 1300584 Intergenic Misc. Lung C: G 4.9% 20.1% 24.9% 30.1% 0.055 rs4635969 1308552 Intergenic Misc., EUR Lung, Pancreas, Testis G: A 34.1% 19.3% 12.7% 12.1% 0.055 rs4975615 1315343 Intergenic Misc. Lung A: G 49.4% 42.3% 28.3% 16.3% 0.088 rs4975616 1315660 Intergenic Misc., EUR Lung, Pancreas, Testis A: G 72.1% 44.3% 31.9% 16.3% 0.201 rs1801075 1317949 Intergenic near gene 3' Misc. Lung T: C 14.0% 19.1% 15.8% 4.4% 0.035 rs451360 1319680 CLPTM1L intron Misc., EUR Lung C: A 2.6% 21.6% 14.1% 11.9% 0.053 rs380286 1320247 CLPTM1L intron Misc. Lung G: A 61.6% 45.4% 35.6% 13.6% 0.156 rs402710 1320722 CLPTM1L intron Misc., EUR, Asian Bladder, Lung C: T 46.8% 35.5% 32.8% 29.4% 0.017 rs401681 1322087 CLPTM1L intron Misc, EUR, Asian Bladder, Prostate, Pancreas, BCC, Melanoma, SCC, Lung C: T 58.6% 45.9% 42.7% 30.4% 0.048 rs465498 1325803 CLPTM1L intron Misc, Asian Lung A: G 57.9% 46.2% 35.0% 16.4% 0.124 rs452932 1330253 CLPTM1L intron Misc. Lung T: C 58.2% 46.2% 35.6% 15.7% 0.128 rs452384 1330840 CLPTM1L intron Misc. Lung T: C 58.2% 45.9% 35.6% 15.7% 0.128 rs467095 1336221 CLPTM1L intron Misc. Lung T: C 71.2% 46.3% 35.9% 15.9% 0.194 rs31489 1342714 CLPTM1L intron Misc., EUR, Asian Lung, Pancreas, Testis C: A 47.2% 43.1% 31.4% 15.7% 0.084 † Ethnicity as reported in Mocellin et al. (2012); ‡ major allele:minor allele, and the risk allele is underlined; syn. = synonymous change; RAF = risk allele frequency; F ST = level of differentiation among ancestral groups; misc. = miscellany, indicating a mix of different races; AFR = African ancestry; EUR = European ancestry; AM = American ancestry; EA = East Asian ancestry. Since there were so few coding variants in the TERT and CLPTM1L loci, we combined them for the following analyses. The normalized number of variant sites, heterozygosity, and MAFs were significantly different by functional SNP category in TERT and CLPTM1L ( P values <0.01; Table 1 ). Specifically, the non-coding SNPs (compared with coding SNPs) and synonymous SNPs (compared with non-synonymous SNPs) had significantly higher numbers of variant sites, heterozygosity, and MAFs ( Table 1 ). These trends were consistent in all ancestral groups ( Figure 1A ). The most significant differences between coding and non-coding SNPs were in African populations (non-coding average MAF 9.8% vs. coding average MAF 0.9%); and, the most significant differences between synonymous (syn.) versus non-synonymous (non-syn.) SNPs were in East Asian populations (syn. average MAF 4.8% vs. non-syn. average MAF 0.2%) ( Figure 1A ). There were significantly different levels of differentiation among ancestral groups for coding versus non-coding and synonymous versus non-synonymous SNPs ( Figure 1B ). Figure 1. Variation in TERT-CLPTM1L by ancestral group. ( A. ) Average minor allele frequency of the polymorphisms by functional category for each group; ( B. ) average level of differentiation among ancestral groups ( F ST ) for the polymorphisms by functional category; ( C. ) minor allele frequency of each protein-altering variant by ancestral group, the underlined variants are predicted to be potentially deleterious with SIFT and/or Poly-Phen. ** indicates a significant difference with a P <0.01, * P <0.05. PAV = non-synonymous protein-altering variation; AFR = African ancestry; EUR = European ancestry; AM = American ancestry; EA = East Asian ancestry. Protein altering variation All PAVs were present at a rare or low frequency ( Figure 1C ). European ancestry individuals had higher MAFs for many of the PAVs in TERT and CLPTM1L , and there were significant MAF differences among ancestral groups for rs35719940, rs61748181, rs33955038, and rs113203740 ( Figure 1C ). Nine (53%) of the 17 PAVs observed in TERT and three (33%) of the nine PAVs observed in CLPTM1L were reported to be damaging by Polyphen and/or SIFT (two in silico approaches; underlined in Figure 1C ). Most of these potentially damaging variants were only observed in one individual. However, three possibly damaging variants in TERT were observed in multiple individuals [rs34094720 (N=3), rs61748181 (N=31), rs200843534 (N=5)] ( Figure 1C ). Patterns of diversity and recombination among ancestral groups A summary of the variation by ancestral group for this region is given in Table 3 . There was low nucleotide diversity (average of 5.0E -4 ) by ancestral group and low differentiation among ancestral groups (90.4% of loci in this region had low F ST <0.10; median F ST = 0.005) (data not shown). The median F ST among ancestral groups (AG) and within populations (WP) for SNPs located within TERT and CLPTM1L were low (AG F ST = 0.0039 and 0.0040, respectively; and, WP F ST = 0.0078 and 0.0091, respectively). The greatest level of pairwise differentiation was among African and East Asian ancestry populations (pairwise F ST = 0.208), and among European and East Asian ancestry populations (pairwise F ST = 0.104) ( Figure 2 and Supplementary Figure 1 ). The lowest level of pairwise differentiation was among European and American ancestry populations (pairwise F ST = 0.01). The MAFs and heterozygosity estimates for SNPs in this region in European and American ancestry populations were highly correlated (r 2 = 0.95 and 0.965, respectively). Table 3. Summary of the diversity at 5p15.33 by ancestral group. African (AFR) European (EUR) American (AM) East Asian (EA) No. individuals 233 378 177 286 No. polymorphic loci 1009 732 808 503 Heterozygosity (SD) 0.120 (0.16) 0.127 (0.18) 0.111 (0.16) 0.129 (0.16) Nucleotide diversity 6.5E -04 5.0E -04 4.9E -04 3.8E -04 SD = standard deviation. Figure 2. Summary of population genetics parameters in European ( A. ) and African ( B. ) ancestry individuals for 5p15.33. Linkage disequilibrium (LD), recombination hotspots, heterozygosity, and pairwise F st values are shown for the cancer-associated SNPs (red dots), surrogate SNPs (blue dots), and non-surrogate SNPs (grey dots). LD pattern (see color legend) is shown for SNPs with a MAF ≥0.05. The red lines represent an extension of the location of the cancer-associated SNPs. The blue lines in the heterozygosity plot indicate the location of the recombination hotspots. For the pairwise F st estimates, the populations are indicated in the top corner of each graph. AFR = African ancestry; EUR = European ancestry; AM = American ancestry; ASN = East Asian ancestry. There was little to no LD in the TERT gene region but high LD was present in the CLPTM1L gene region ( Figure 2 and Supplementary Figure 1 ). There were 4–5 main recombination hotspots in TERT and between TERT and CLPTM1L , there were no hotspots located within CLPTM1L ( Supplementary Table 1 ) . The greatest recombination was observed in individuals with African ancestry (5 recombination hotspots), and the lowest recombination in individuals with East Asian ancestry (4 recombination hotspots and lower likelihood ratio statistics) ( Figure 2 and Supplementary Figure 1 ). Cancer-associated SNPs Twenty-three SNPs significantly associated with cancer at 5p15.33 25 were included in the analysis ( Table 2 ). Many of the cancer associated SNPs in this region had differing allele frequencies and heterozygosity among ancestral groups and populations, and had F ST values close to or greater than 0.1 ( Table 2 and Supplementary Table 4 ). The risk allele was the rare allele at all of these SNPs, except at rs4246742 (associated with lung cancer; Table 2 ). Most of the cancer-associated SNPs in the CLPTM1L gene region are in regions of high LD, and therefore, have many surrogates (25–54 surrogate SNPs) with r 2 ≥0.6 ( Table 4 and Supplementary Table 2 ). In contrast, most of the SNPs in the TERT gene region are in a region of low LD and have no or few surrogates (0–5 surrogate SNPs) with r 2 ≥0.6 ( Table 4 and Supplementary Table 2 ). In East Asian ancestry individuals SNPs in the CLPTM1L gene region are particularly highly correlated, even some of the SNPs within TERT are in high LD in these individuals ( i.e. , rs10069690, rs2242652, and rs13167280; Supplementary Figure 1 ). Table 4. Previously reported multiple-cancer susceptibility loci at 5q15.33 and their surrogates at an r 2 ≥0.6 and regulatory elements. Locus Surrogates † H3K4 Me1 H3K4 Me3 H3K27 Ac DNase Regulatory motifs altered Proteins bound CpG island Regulome DB score Mammal Conserv. AFR EUR AM EA rs4246742 1267356 TERT 0 0 1 1 • (3) 5 rs10069690 1279790 TERT 2 1 0 2 • (19) 5 rs2242652 1280028 TERT 3 1 1 1 • (17) HEN1, ZFX, E2A, REST 5 rs13167280 1280477 TERT 0 0 1 0 • (19) NKX2 5 rs2736100 1286516 TERT 3 0 8 9 • (4) 5 rs2853676 1288547 TERT 0 0 1 1 5 rs2736098 1294086 TERT 3 2 2 4 • (4) • (4) • (8) NRSF, LRF • 5 rs2736108 1297488 Intergenic 3 2 3 3 • (3) • (25) EBF1 4 rs2853668 1300025 Intergenic 0 0 1 1 • (2) 5 rs2735845 1300584 Intergenic 0 2 2 3 — • rs4635969 1308552 Intergenic 13 4 3 45 • (2) • (2) FOXO1, SOX15 6 rs4975615 1315343 Intergenic 24 48 48 54 • (8) • (4) • (4) ZBTB3 5 rs4975616 1315660 Intergenic 9 47 38 54 • (11) • (5) • (4) • (8) 5 rs1801075 1317949 Intergenic 2 6 6 0 — rs451360 1319680 CLPTM1L 0 7 4 52 • (4) HIC1, OLF-1 5 rs380286 1320247 CLPTM1L 18 47 47 47 • (3) • (3) 5 rs402710 1320722 CLPTM1L 20 8 0 0 • (3) HEN1 5 rs401681 1322087 CLPTM1L 25 46 21 0 • (3) • (6) 5 rs465498 1325803 CLPTM1L 27 47 46 54 • (3) • (6) • (9) 5 rs452932 1330253 CLPTM1L 28 47 47 54 • (6) • (5) • (8) 6 rs452384 1330840 CLPTM1L 28 47 47 54 • (5) • (3) • (7) • (16) MYC 5 rs467095 1336221 CLPTM1L 8 47 46 54 • (2) POLR2A, ETS1 4 rs31489 1342714 CLPTM1L 31 47 47 54 MEF2 — • † r 2 ≥0.6, maximum inter-marker distance of 200kb and minimum MAF of 0.05; AFR = African ancestry; EUR = European ancestry; AM = American ancestry; EA = East Asian ancestry; Existence of a regulatory signature is indicated as dots (number of cell types this signature was observed, only indicated if occurring in ≥2 cell types); RegulomeDB score indicates: 4 = TF binding + DNase peak, 5 = TF binding or DNase peak, 6 = motif hit, — = no data available; Highlighted rows indicate that one or more surrogates for this SNP results in a likely functional consequence (RegulomeDB score of 2); Mammal Conserv. = measurement of evolutionary placental mammal basewise conservation, the conserved sites are indicated. Potential regulatory changes All previously reported cancer-associated SNPs and all possible surrogates at r 2 ≥0.6 were assessed for the presence of potential regulatory elements and evolutionary conservation among mammalian species (summarized in Table 4 and Supplementary Table 3 ). Surprisingly, none of the cancer-associated SNP surrogates were located in the coding regions of TERT or CLPTM1L . Many of these SNPs are associated with open chromatin (DNase hypersensitivity) and/or regulatory histone marks (H3K4Me1, H3K4Me3, H3K27Ac) in multiple cell types, alter known regulatory motifs and/or protein binding sites. One of the surrogate SNPs in the putative promoter region of TERT , rs2853669, is a conserved binding site for POLR2A, as were six other surrogate SNPs located intergenic between TERT and CLPTM1L , within the CLPTM1L gene region, and in the putative promoter region of CLPTM1L . One of the cancer-associated SNPs, rs2736098, and three surrogate SNPs in the 5’ region and putative promoter region of TERT were C>T SNPs located in the CpG island. Clusters of several surrogate SNPs located within CLPTM1L and just 3’ and 5’ of CLPTM1L were associated with many histone marks and open chromatin, and/or altered regulatory motifs and protein binding sites. None of the cancer-associated SNPs or their surrogates were associated with microRNA binding sites. We used the RegulomeDB scoring system to compare and prioritize potential functional consequences of these SNPs. The cancer-associated SNPs in the 5’ region of TERT , most of the intergenic cancer-associated SNPs, and all the cancer-associated SNPs within CLPTM1L had surrogates with a likely functional consequence of affecting binding, indicated by a category 2 score (highlighted in Table 4 and Supplementary Table 3 ). None of the SNPs were identified to be associated with changes in expression of these genes. Discussion Data from the 1000 Genomes Project 34 on 1627 variants at 5p15.33 for 1074 unrelated individuals were used to describe the population genetic patterns in this region. We evaluated differentiation among ancestral groups, allele frequency patterns, and the cancer-associated SNPs and surrogates for potential regulatory elements. We have previously shown that there is low nucleotide diversity and differentiation among populations in TERT and suggested that TERT may be constrained 28 , 29 ; however, our previous population genetics study focused on telomere genes as a gene set and was limited to only four SNPs located within the TERT gene 29 . In this study with better coverage of the TERT-CLPTM1L region, we determined that there is low nucleotide diversity across the 5p15.33 region in all ancestral groups and low differentiation among groups. As expected, African populations had more diversity, specifically at non-coding SNPs, compared to the other ancestral groups. However, East Asian populations had greater diversity at synonymous SNPs, and Europeans had the greatest frequency of non-synonymous changes. European and American ancestry individuals had very similar allele frequency patterns, as others have observed 51 . The significantly reduced normalized number of variant sites, heterozygosity, and MAFs, and low differentiation among ancestral groups for the coding sites, particularly for non-synonymous sites, compared with non-coding and silent changes suggests purifying selection in TERT and CLPTM1 . African ancestry individuals had the greatest difference between the frequencies of non-coding vs . coding variants, consistent with stronger purifying selection; in contrast, European ancestry individuals had an excess of potentially deleterious non-synonymous SNPs. These observations are consistent with reports of genes important in cancer and complex disease 42 , 52 – 54 and recent genomic reports 30 – 33 . European ancestry individuals have been reported to have an excess of recently arisen potentially deleterious variants in disease genes 33 . American and East Asian ancestry individuals also had an excess of coding variants compared to African ancestry individuals, suggesting weaker purifying selection in these populations as well. East Asian individuals had a particular excess of synonymous variants and very few non-synonymous variants. For the cancer-associated SNPs in this region, the risk allele was primarily the rare allele which additionally provides support for the hypothesis of constraint in this region. This evidence of purifying selection supports the importance of TERT and CLPTM1 in disease, and the variation by ancestry suggests the level of selection differs by geographic region. We found that several of the 23 SNPs that have been significantly associated with cancer at 5p15.33 [Reviewed in 25] had differing MAFs and heterozygosity among ancestral groups. Europeans and Americans had the most similar MAFs and heterozygosity estimates, which suggests significant admixture. These differences, reflected in the high F ST values, may correlate to varying disease incidence rates among ancestral groups. For example, the breast cancer associated SNP, rs10069690 23 , had significantly different minor allele frequencies among ancestral groups; the homozygous risk allele genotype was significantly more common in African ancestry individuals (genotype frequency of 40% vs . 2.4% in East Asian, 6.8% in American, and 8.4% in European ancestry individuals) and less common in East Asian ancestry individuals. This difference may be associated with the higher incidence of breast cancer in African ancestry individuals (particularly for estrogen receptor-negative breast cancer) and lower incidence in East Asian individuals. Many of the cancer-associated SNPs and surrogate SNPs were associated with potential regulatory elements, including histone marks, open chromatin, transcription factor binding sites, and/or regulatory motifs. There were only a few surrogates for the SNPs located within TERT and just 5’ of TERT due to the low levels of LD in these regions; and, there were a large number of surrogates for the SNPs located close to and within CLPTM1L where LD was strong and recombination low, most of these surrogates were shared among the cancer-associated SNPs in this region. Many of the surrogate markers were located in the putative promoter regions of TERT and CLPTM1L and may affect gene regulation. The RegulomeDB scoring approach allowed us to classify variants based on all of the regulatory information. This approach determined that surrogate SNPs for many of the cancer-associated SNPs are functional variants with a likely role in regulation; these should be prioritized for functional assays. Conclusions Our analysis of diversity in this important cancer-associated region of 5p15.33 provides background information for understanding variation in the general population. The functional impact of common variation in this region needs to be examined experimentally, but we could speculate that the diversity of coding variants among different ethnicities could have mild effects on the phenotype disparity observed among these populations. Many of the cancer-associated SNPs and/or surrogates at 5p15.33 are associated with regulatory changes and candidates for evolutionary selection. Evidence of purifying selection in TERT and CLPTM1L highlights their functional importance and associations with complex disease. We have identified SNPs in this region that are likely involved in regulation of the TERT and/or CLPTM1 genes. Future studies of the functional consequences of the 5p15.33 variants will be required to understand their contribution to cancer etiology. Data availability F1000Research: Dataset 1. Genotype data for 1627 variants on 5p15.33 (hg19, chr5: 1,243,287–1,355,002) for 1074 individuals from 14 populations, 10.5256/f1000research.5186.d35521 55 Author contributions Project design was carried out by S.A.S., L.M., and M.Y. Genotyping data were retrieved by C.C.C. Analyses were performed by L.M. The manuscript was written by L.M. and S.A.S., and reviewed by all co-authors. Competing interests No competing interests were disclosed. Grant information This project has been funded by the Intramural Research Program of the Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, and with federal funds from the National Cancer Institute, National Institutes of Health, under contract number HHSN261200800001E to M.Y. and C.C.C. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Supplementary material Supplementary Table 1. Recombination hotspot inference summary. Click here to access the data . Supplementary Table 2. All possible surrogate markers by ancestral group and their rank for the 23 cancer-associated SNPs based on a R 2 ≥0.60, maximum inter-marker distance of 200kb, and minimum MAF of 0.05. Click here to access the data . Supplementary Table 3. Previously reported multiple-cancer susceptibility loci at 5q15.33 and their surrogates at an r 2 ≥0.6 and regulatory elements. Click here to access the data . Supplementary Table 4. Risk allele frequencies of the cancer-associated SNPs at the TERT-CLPTM1L locus by population. Click here to access the data . Supplementary Figure 1. Summary of population genetics parameters in East Asian ( A. ) and American ( B. ) ancestry individuals for 5p15.33. Click here to access the data . Linkage disequilibrium (LD), recombination hotspots, heterozygosity, and pairwise F st values are shown for the cancer-associated SNPs (red dots), surrogate SNPs (blue dots), and non-surrogate SNPs (grey dots). LD pattern (see color legend) is shown for SNPs with a MAF ≥0.05. The red lines represent an extension of the location of the cancer-associated SNPs. The blue lines in the heterozygosity plot indicate the location of the recombination hotspots. For the pairwise F st estimates, the populations are indicated in the top corner of each graph. AFR = African ancestry; EUR = European ancestry; AM = American ancestry; ASN = East Asian ancestry. Faculty Opinions recommended References 1. Collins K, Mitchell JR: Telomerase in the human organism. Oncogene. 2002; 21 (4): 564–579. PubMed Abstract | Publisher Full Text 2. Moon IK, Jarstfer MB: The human telomere and its relationship to human disease, therapy, and tissue engineering. Front Biosci. 2007; 12 : 4595–4620. 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Freudenberg-Hua Y, Freudenberg J, Kluck N, et al. : Single nucleotide variation analysis in 65 candidate genes for CNS disorders in a representative sample of the European population. Genome Res. 2003; 13 (10): 2271–2276. PubMed Abstract | Publisher Full Text | Free Full Text 54. Halushka MK, Fan JB, Bentley K, et al. : Patterns of single-nucleotide polymorphisms in candidate genes for blood-pressure homeostasis. Nat Genet. 1999; 22 (3): 239–247. PubMed Abstract | Publisher Full Text 55. Mirabello L, Chung CC, Yeager M, et al. : Dataset 1. Genotype data for 1627 variants on 5p15.33 (hg19, chr5: 1,243,287–1,355,002) for 1074 individuals from 14 populations. F1000Research. 2014. Data Source Comments on this article Comments (0) Version 1 VERSION 1 PUBLISHED 02 Oct 2014 ADD YOUR COMMENT Comment Author details Author details 1 Division of Cancer Epidemiology and Genetics, National Cancer Institute,National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20892, USA 2 Cancer Genomics Research Laboratory, National Cancer Institute, Division of Cancer Epidemiology and Genetics, Leidos Biomedical Research, Inc., Frederick, MD 20877, USA Competing interests No competing interests were disclosed. Grant information This project has been funded by the Intramural Research Program of the Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, and with federal funds from the National Cancer Institute, National Institutes of Health, under contract number HHSN261200800001E to M.Y. and C.C.C. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Article Versions (1) version 1 Published: 02 Oct 2014, 3:231 https://doi.org/10.12688/f1000research.5186.1 Copyright © 2014 Mirabello L et al . This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The author(s) is/are employees of the US Government and therefore domestic copyright protection in USA does not apply to this work. The work may be protected under the copyright laws of other jurisdictions when used in those jurisdictions. Data associated with the article are available under the terms of the Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication). Download Export To Sciwheel Bibtex EndNote ProCite Ref. Manager (RIS) Sente metrics Views Downloads F1000Research - - PubMed Central info_outline Data from PMC are received and updated monthly. - - Citations open_in_new 0 open_in_new 0 open_in_new SEE MORE DETAILS CITE how to cite this article Mirabello L, Chung CC, Yeager M and Savage SA. Characterization of population-based variation and putative functional elements for the multiple-cancer susceptibility loci at 5p15.33 [version 1; peer review: 2 approved] . F1000Research 2014, 3 :231 ( https://doi.org/10.12688/f1000research.5186.1 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS track receive updates on this article Track an article to receive email alerts on any updates to this article. TRACK THIS ARTICLE Share Open Peer Review Current Reviewer Status: ? Key to Reviewer Statuses VIEW HIDE Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Version 1 VERSION 1 PUBLISHED 02 Oct 2014 Views 0 Cite How to cite this report: Hopper JL and Kapuscinski MK. Reviewer Report For: Characterization of population-based variation and putative functional elements for the multiple-cancer susceptibility loci at 5p15.33 [version 1; peer review: 2 approved] . F1000Research 2014, 3 :231 ( https://doi.org/10.5256/f1000research.5532.r9055 ) The direct URL for this report is: https://f1000research.com/articles/3-231/v1#referee-response-9055 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 16 Jun 2015 John L. Hopper , Centre for Molecular, Environmental, Genetic and Analytic Epidemiology, University of Melbourne, Carlton, Vic, Australia Miroslav K. Kapuscinski , Centre for Epidemiology and Biostatistics Melbourne School of Population and Global Health, University of Melbourne, Carlton, Vic, Australia Approved VIEWS 0 https://doi.org/10.5256/f1000research.5532.r9055 Mirabello et al present here a comprehensive bioinformatics investigation of genetic variation at the telomerase-containing locus (5p15.33) that has been associated with a range of malignancies. Given high biological plausibility of telomerase involvement in cancer pathology, this is an important ... Continue reading READ ALL Mirabello et al present here a comprehensive bioinformatics investigation of genetic variation at the telomerase-containing locus (5p15.33) that has been associated with a range of malignancies. Given high biological plausibility of telomerase involvement in cancer pathology, this is an important study that could assist in further research on this putative susceptibility locus. The research strategy described in this well written paper should be applauded as it can be easily applied to other genomic regions of interest and provides an excellent example of extracting more useful information from existing data. In particular, the use of 1000 Genomes data provides an opportunity to examine the distribution of a wider range of variants in detail not possible using GWAS genotyping alone. As the authors point out, highly significant associations of a number of SNP variants are paralleled by rather small phenotypic associations with these variants. The most common protein altering variant (rs61748181) identified in the available data appears to have modest associations. This is not a unique situation and it makes choosing variants for functional characterization difficult considering the investment required for such comprehensive studies. It should be stressed that direct identification of causal variants from GWAS data has not been very successful. The present report demonstrates the need for well-designed analytical approach based on the sequence information (1000 Genomes) together with other data (ENCODE) to reveal credible causal candidates and narrow the choices for subsequent experimental verification. The authors acknowledge the key role of future functional work in this discovery process. As the data from 1000 Genomes Consortium comes from unaffected people inclusion of other information in the analytical pipeline that allows comparison of germline and tumour sequence information (e.g. The Cancer Genome Atlas, eQTLs) might allow further refinement of variant evaluation with different mechanisms evident in different cancers (e.g. relevance of promoter mutations - Lindner et al., 2015 and Spiegl-Kreinecker et al., 2015 ). The evidence for purifying selection in TERT-CLPTM1L region points to the importance of maintaining the structural integrity of this locus but also suggests that mechanisms other than protein altering mutations may play significant role such as interactions with other genes such as MYC ( Koh et al. , 2015 ) or miR-34a ( Xu et al., 2015 ). The rationale for setting the threshold for marker surrogacy at r 2 = 0.6 (p7) while using r 2 = 0.8 for LD calculations (p3) should be explained. In summary, this is well designed and presented study that demonstrates the potential of using high throughput sequencing data together with growing resources such as ENCODE to enhance understanding of traditional genome-wide genotyping experiments. The title reflects well the contents, the abstract is appropriate and occlusions are justified and balanced. Competing Interests: No competing interests were disclosed. We confirm that we have read this submission and believe that we have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Hopper JL and Kapuscinski MK. Reviewer Report For: Characterization of population-based variation and putative functional elements for the multiple-cancer susceptibility loci at 5p15.33 [version 1; peer review: 2 approved] . F1000Research 2014, 3 :231 ( https://doi.org/10.5256/f1000research.5532.r9055 ) The direct URL for this report is: https://f1000research.com/articles/3-231/v1#referee-response-9055 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Respond or Comment COMMENT ON THIS REPORT Views 0 Cite How to cite this report: Baird D. Reviewer Report For: Characterization of population-based variation and putative functional elements for the multiple-cancer susceptibility loci at 5p15.33 [version 1; peer review: 2 approved] . F1000Research 2014, 3 :231 ( https://doi.org/10.5256/f1000research.5532.r6299 ) The direct URL for this report is: https://f1000research.com/articles/3-231/v1#referee-response-6299 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 10 Oct 2014 Duncan Baird , Institute of Cancer and Genetics, Cardiff University, Cardiff, UK Approved VIEWS 0 https://doi.org/10.5256/f1000research.5532.r6299 Numerous studies have identified variation at the TERT-CLPTM1L locus in conferring an increased risk of many different cancer types. Here the authors have examined the genetic architecture of the TERT-CLPTM1L locus using sequence data from the 1000 genomes project. Given the ... Continue reading READ ALL Numerous studies have identified variation at the TERT-CLPTM1L locus in conferring an increased risk of many different cancer types. Here the authors have examined the genetic architecture of the TERT-CLPTM1L locus using sequence data from the 1000 genomes project. Given the potential significance of this locus, this type of work is important as it has the potential to identify functional variants that might not have been uncovered with the various GWAS undertaken to identify risk variants. Thus far none of the risk variants identified at this locus with GWAS results in non-synonymous protein changes, however this study provides data to indicate that some of these variants may be associated with regulatory sequences and chromatin marks. This study also identified 26 variants that result in non-synonymous protein changes in the hTERT or the CLPTM1L genes. This is a well written manuscript and the conclusions are appropriately backed up by the data provided. The title is appropriate and the abstract adequately summarises the article. Overall this manuscript provides useful information that that will underpin future work to establish the importance of this locus in conferring cancer risk. I have no major criticisms of this work; however I recommend that a more rigorous statistical review, than I am able to provide, is undertaken of this manuscript. Competing Interests: No competing interests were disclosed. I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Baird D. Reviewer Report For: Characterization of population-based variation and putative functional elements for the multiple-cancer susceptibility loci at 5p15.33 [version 1; peer review: 2 approved] . F1000Research 2014, 3 :231 ( https://doi.org/10.5256/f1000research.5532.r6299 ) The direct URL for this report is: https://f1000research.com/articles/3-231/v1#referee-response-6299 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Respond or Comment COMMENT ON THIS REPORT Comments on this article Comments (0) Version 1 VERSION 1 PUBLISHED 02 Oct 2014 ADD YOUR COMMENT Comment keyboard_arrow_left keyboard_arrow_right Open Peer Review Reviewer Status info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Reviewer Reports Invited Reviewers 1 2 Version 1 02 Oct 14 read read Duncan Baird , Cardiff University, Cardiff, UK John L. Hopper , University of Melbourne, Carlton, Australia Miroslav K. Kapuscinski , University of Melbourne, Carlton, Australia Comments on this article All Comments (0) Add a comment Sign up for content alerts Sign Up You are now signed up to receive this alert Browse by related subjects keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2015 Hopper J et al. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 16 Jun 2015 | for Version 1 John L. Hopper , Centre for Molecular, Environmental, Genetic and Analytic Epidemiology, University of Melbourne, Carlton, Vic, Australia Miroslav K. Kapuscinski , Centre for Epidemiology and Biostatistics Melbourne School of Population and Global Health, University of Melbourne, Carlton, Vic, Australia 0 Views copyright © 2015 Hopper J et al. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (0) Approved info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Mirabello et al present here a comprehensive bioinformatics investigation of genetic variation at the telomerase-containing locus (5p15.33) that has been associated with a range of malignancies. Given high biological plausibility of telomerase involvement in cancer pathology, this is an important study that could assist in further research on this putative susceptibility locus. The research strategy described in this well written paper should be applauded as it can be easily applied to other genomic regions of interest and provides an excellent example of extracting more useful information from existing data. In particular, the use of 1000 Genomes data provides an opportunity to examine the distribution of a wider range of variants in detail not possible using GWAS genotyping alone. As the authors point out, highly significant associations of a number of SNP variants are paralleled by rather small phenotypic associations with these variants. The most common protein altering variant (rs61748181) identified in the available data appears to have modest associations. This is not a unique situation and it makes choosing variants for functional characterization difficult considering the investment required for such comprehensive studies. It should be stressed that direct identification of causal variants from GWAS data has not been very successful. The present report demonstrates the need for well-designed analytical approach based on the sequence information (1000 Genomes) together with other data (ENCODE) to reveal credible causal candidates and narrow the choices for subsequent experimental verification. The authors acknowledge the key role of future functional work in this discovery process. As the data from 1000 Genomes Consortium comes from unaffected people inclusion of other information in the analytical pipeline that allows comparison of germline and tumour sequence information (e.g. The Cancer Genome Atlas, eQTLs) might allow further refinement of variant evaluation with different mechanisms evident in different cancers (e.g. relevance of promoter mutations - Lindner et al., 2015 and Spiegl-Kreinecker et al., 2015 ). The evidence for purifying selection in TERT-CLPTM1L region points to the importance of maintaining the structural integrity of this locus but also suggests that mechanisms other than protein altering mutations may play significant role such as interactions with other genes such as MYC ( Koh et al. , 2015 ) or miR-34a ( Xu et al., 2015 ). The rationale for setting the threshold for marker surrogacy at r 2 = 0.6 (p7) while using r 2 = 0.8 for LD calculations (p3) should be explained. In summary, this is well designed and presented study that demonstrates the potential of using high throughput sequencing data together with growing resources such as ENCODE to enhance understanding of traditional genome-wide genotyping experiments. The title reflects well the contents, the abstract is appropriate and occlusions are justified and balanced. Competing Interests No competing interests were disclosed. We confirm that we have read this submission and believe that we have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. reply Respond to this report Responses (0) Hopper JL and Kapuscinski MK. Peer Review Report For: Characterization of population-based variation and putative functional elements for the multiple-cancer susceptibility loci at 5p15.33 [version 1; peer review: 2 approved] . F1000Research 2014, 3 :231 ( https://doi.org/10.5256/f1000research.5532.r9055) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/3-231/v1#referee-response-9055 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2014 Baird D. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 10 Oct 2014 | for Version 1 Duncan Baird , Institute of Cancer and Genetics, Cardiff University, Cardiff, UK 0 Views copyright © 2014 Baird D. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (0) Approved info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Numerous studies have identified variation at the TERT-CLPTM1L locus in conferring an increased risk of many different cancer types. Here the authors have examined the genetic architecture of the TERT-CLPTM1L locus using sequence data from the 1000 genomes project. Given the potential significance of this locus, this type of work is important as it has the potential to identify functional variants that might not have been uncovered with the various GWAS undertaken to identify risk variants. Thus far none of the risk variants identified at this locus with GWAS results in non-synonymous protein changes, however this study provides data to indicate that some of these variants may be associated with regulatory sequences and chromatin marks. This study also identified 26 variants that result in non-synonymous protein changes in the hTERT or the CLPTM1L genes. This is a well written manuscript and the conclusions are appropriately backed up by the data provided. The title is appropriate and the abstract adequately summarises the article. Overall this manuscript provides useful information that that will underpin future work to establish the importance of this locus in conferring cancer risk. I have no major criticisms of this work; however I recommend that a more rigorous statistical review, than I am able to provide, is undertaken of this manuscript. Competing Interests No competing interests were disclosed. I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. reply Respond to this report Responses (0) Baird D. Peer Review Report For: Characterization of population-based variation and putative functional elements for the multiple-cancer susceptibility loci at 5p15.33 [version 1; peer review: 2 approved] . F1000Research 2014, 3 :231 ( https://doi.org/10.5256/f1000research.5532.r6299) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/3-231/v1#referee-response-6299 Alongside their report, reviewers assign a status to the article: Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions Click here to access the data. The problem Spreadsheet data files may not format correctly if your computer is using different default delimiters (symbols used to separate values into separate cells) - a spreadsheet created in one region is sometimes misinterpreted by computers in other regions. You can change the regional settings on your computer so that the spreadsheet can be interpreted correctly. How to fix it Save downloaded CSV file Open spreadsheet program (e.g. Excel) Click the ‘Data’ tab at the top Click the ‘From text’ icon (top left) Browse for downloaded CSV file, click ‘Import’ Ensure ‘Delimited’ radio button is selected, click ‘Next’ Check one of the appropriate delimiter checkboxes (you can visualize the formatting by looking at the data preview below these options) Click ‘Finish’ Downloaded data do not display as expected? Download the data (5.04MB) Dataset citation: Mirabello L, Chung CC, Yeager M and Savage SA. Dataset 1 in: Characterization of population-based variation and putative functional elements for the multiple-cancer susceptibility loci at 5p15.33. 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