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Small bowel adenocarcinoma (SBA) is an aggressive disease with limited treatment options. Despite previous studies, its molecular genetic background has remained somewhat elusive. To comprehensively characterize the mutational landscape of this tumor type, and to identify possible targets of treatment, we conducted the first large exome sequencing study on a population-based set of SBA samples from all three small bowel segments. Archival tissue from 106 primary tumors with appropriate clinical information were available for exome sequencing from a patient series consisting of a majority of confirmed SBA cases diagnosed in Finland between the years 2003–2011. Paired-end exome sequencing was performed using Illumina HiSeq 4000, and OncodriveFML was used to identify driver genes from the exome data. We also defined frequently affected cancer signalling pathways and performed the first extensive allelic imbalance (AI) analysis in SBA. Exome data analysis revealed significantly mutated genes previously linked to SBA (TP53, KRAS, APC, SMAD4, and BRAF), recently reported potential driver genes (SOX9, ATM, and ARID2), as well as novel candidate driver genes, such as ACVR2A, ACVR1B, BRCA2, and SMARCA4. We also identified clear mutation hotspot patterns in ERBB2 and BRAF. No BRAF V600E mutations were observed. Additionally, we present a comprehensive mutation signature analysis of SBA, highlighting established signatures 1A, 6, and 17, as well as U2 which is a previously unvalidated signature. Finally, comparison of the three small bowel segments revealed differences in tumor characteristics. This comprehensive work unveils the mutational landscape and most frequently affected genes and pathways in SBA, providing potential therapeutic targets, and novel and more thorough insights into the genetic background of this tumor type., Author summary Small bowel adenocarcinoma is a rare but aggressive disease with limited treatment options. Of gastrointestinal tumors, small bowel tumors account for 3%, of which around one third are adenocarcinomas. Due to the scarcity of evidence-based treatment recommendations there is a dire need for knowledge on the biology of these tumors. Here, we performed the first large exome sequencing effort of 106 small bowel adenocarcinomas from a Finnish population-based cohort to comprehensively characterize the genetic background of this tumor type. The set included tumors from all three small bowel segments allowing us to also compare the genetic differences between these subsets. We defined significantly mutated genes and frequently affected pathways, providing potential therapeutic targets, such as BRAF, ERBB2, ERBB3, ERBB4, PIK3CA, KRAS, ATM, ACVR2A, ACVR1B, BRCA2, and SMARCA4, for this disease.

Microsatellite instability (MSI) leads to accumulation of an excessive number of mutations in the genome, mostly small insertions and deletions. MSI colorectal cancers (CRCs), however, also contain more point mutations than microsatellite-stable (MSS) tumors, yet they have not been as comprehensively studied. To identify candidate driver genes affected by point mutations in MSI CRC, we ranked genes based on mutation significance while correcting for replication timing and gene expression utilizing an algorithm, MutSigCV. Somatic point mutation data from the exome kit-targeted area from 24 exome-sequenced sporadic MSI CRCs and respective normals, and 12 whole-genome-sequenced sporadic MSI CRCs and respective normals were utilized. The top 73 genes were validated in 93 additional MSI CRCs. The MutSigCV ranking identified several well-established MSI CRC driver genes and provided additional evidence for previously proposed CRC candidate genes as well as shortlisted genes that have to our knowledge not been linked to CRC before. Two genes, SMARCB1 and STK38L, were also functionally scrutinized, providing evidence of a tumorigenic role, for SMARCB1 mutations in particular. © 2018 The Authors. Published under the terms of the CC BY 4.0 license

Uterine leiomyomas (ULs) are benign tumors that are a major burden to women’s health. A genome-wide association study on 15,453 UL cases and 392,628 controls was performed, followed by replication of the genomic risk in six cohorts. Effects of the risk alleles were evaluated in view of molecular and clinical characteristics. 22 loci displayed a genome-wide significant association. The likely predisposition genes could be grouped to two biological processes. Genes involved in genome stability were represented by TERT, TERC, OBFC1 - highlighting the role of telomere maintenance - TP53 and ATM. Genes involved in genitourinary development, WNT4, WT1, SALL1, MED12, ESR1, GREB1, FOXO1, DMRT1 and uterine stem cell marker antigen CD44, formed another strong subgroup. The combined risk contributed by the 22 loci was associated with MED12 mutation-positive tumors. The findings link genes for uterine development and genetic stability to leiomyomagenesis, and in part explain the more frequent occurrence of UL in women of African origin., eLife digest Fibroids – also known as uterine leiomyomas, or myomas – are a very common form of benign tumor that grows in the muscle wall of the uterus. As many as 70% of women develop fibroids in their lifetime. About a fifth of women report symptoms including severe pain, heavy bleeding during periods and complications in pregnancy. In the United States, the cost of treating fibroids is estimated to be $34 billion each year. Despite the prevalence of fibroids in women, there are few treatments available. Drugs to target them have limited effect and often an invasive procedure such as surgery is needed to remove the tumors. However, a better understanding of the genetics of fibroids could lead to a way to develop better treatment options. Välimäki, Kuisma et al. used a genome-wide association study to seek out DNA variations that are more common in people with fibroids. Using data from the UK Biobank, the genomes of over 15,000 women with fibroids were analyzed against a control population of over 392,000 individuals. The analysis revealed 22 regions of the genome that were associated with fibroids. These regions included genes that may well contribute to fibroid development, such as the gene TP53, which influences the stability of the genome, and ESR1, which codes for a receptor for estrogen – a hormone known to play a role in the growth of fibroids. Variation in a set of genes known to control development of the female reproductive organs was also identified in women with fibroids. The findings are the result of the largest genome-wide association study on fibroids, revealing a set of genes that could influence the development of fibroids. Studying these genes could lead to more effective drug development to treat fibroids. Revealing this group of genes could also help to identify women at high risk of developing fibroids and help to prevent or manage the condition.

Point mutations in cancer have been extensively studied but chromosomal gains and losses have been more challenging to interpret due to their unspecific nature. Here we examine high-resolution allelic imbalance (AI) landscape in 1699 colorectal cancers, 256 of which have been whole-genome sequenced (WGSed). The imbalances pinpoint 38 genes as plausible AI targets based on previous knowledge. Unbiased CRISPR-Cas9 knockout and activation screens identified in total 79 genes within AI peaks regulating cell growth. Genetic and functional data implicate loss of TP53 as a sufficient driver of AI. The WGS highlights an influence of copy number aberrations on the rate of detected somatic point mutations. Importantly, the data reveal several associations between AI target genes, suggesting a role for a network of lineage-determining transcription factors in colorectal tumorigenesis. Overall, the results unravel the contribution of AI in colorectal cancer and provide a plausible explanation why so few genes are commonly affected by point mutations in cancers., In this study the authors examine the allelic imbalance (AI) landscape of colorectal cancer, reporting loss of TP53 as a driver of AI. They use CRISPR-Cas9 screens to identify 79 genes (within AI regions) regulating cell growth and identify a network of transcription factors that may contribute to colorectal tumorigenesis.

Long interspersed nuclear elements-1 (L1s) are a large family of retrotransposons. Retrotransposons are repetitive sequences that are capable of autonomous mobility via a copy-and-paste mechanism. In most copy events, only the L1 sequence is inserted, however, they can also mobilize the flanking non-repetitive region by a process known as 3′ transduction. L1 insertions can contribute to genome plasticity and cause potentially tumorigenic genomic instability. However, detecting the activity of a particular source L1 and identifying new insertions stemming from it is a challenging task with current methodological approaches. We developed a long-distance inverse PCR (LDI-PCR) based approach to monitor the mobility of active L1 elements based on their 3′ transduction activity. LDI-PCR requires no prior knowledge of the insertion target region. By applying LDI-PCR in conjunction with Nanopore sequencing (Oxford Nanopore Technologies) on one L1 reported to be particularly active in human cancer genomes, we detected 14 out of 15 3′ transductions previously identified by whole genome sequencing in two different colorectal tumour samples. In addition we discovered 25 novel highly subclonal insertions. Furthermore, the long sequencing reads produced by LDI-PCR/Nanopore sequencing enabled the identification of both the 5′ and 3′ junctions and revealed detailed insertion sequence information.

Cohesin is present in almost all active enhancer regions, where it is associated with transcription factors. Cohesin frequently colocalizes with CTCF (CCCTC-binding factor), affecting genomic stability, expression and epigenetic homeostasis. Cohesin subunits are mutated in cancer, but CTCF/cohesin-binding sites (CBSs) in DNA have not been examined for mutations. Here we report frequent mutations at CBSs in cancers displaying a mutational signature where mutations in A•T base pairs predominate. Integration of whole-genome sequencing data from 213 colorectal cancer (CRC) samples and chromatin immunoprecipitation sequencing (ChIP-exo) data identified frequent point mutations at CBSs. In contrast, CRCs showing an ultramutator phenotype caused by defects in the exonuclease domain of DNA polymerase ɛ (POLE) displayed significantly fewer mutations at and adjacent to CBSs. Analysis of public data showed that multiple cancer types accumulate CBS mutations. CBSs are a major mutational hotspot in the noncoding cancer genome.

Next-generation sequencing (NGS) is being routinely applied in life sciences and clinical practice, where the interpretation of the resulting massive data has become a critical challenge. Computational workflows, such as the Broad GATK, have been established to take raw sequencing data and produce processed data for downstream analyses. Consequently, results of these computationally demanding workflows, consisting of e.g. sequence alignment and variant calling, are increasingly being provided for customers by sequencing and bioinformatics facilities. However, downstream variant analysis, whole-genome level in particular, has been lacking a multi-purpose tool, which could take advantage of rapidly growing genomic information and integrate genetic variant, sequence, genomic annotation and regulatory (e.g. ENCODE) data interactively and in a visual fashion. Here we introduce a highly efficient and user-friendly software, BasePlayer (http://baseplayer.fi), for biological discovery in large-scale NGS data. BasePlayer enables tightly integrated comparative variant analysis and visualization of thousands of NGS data samples and millions of variants, with numerous applications in disease, regulatory and population genomics. Although BasePlayer has been designed primarily for whole-genome and exome sequencing data, it is well-suited to various study settings, diseases and organisms by supporting standard and upcoming file formats. BasePlayer transforms an ordinary desktop computer into a large-scale genomic research platform, enabling also a non-technical user to perform complex comparative variant analyses, population frequency filtering and genome level annotations under intuitive, scalable and highly-responsive user interface to facilitate everyday genetic research as well as the search of novel discoveries.

While elevated blood cholesterol has been associated with an increased risk of colorectal cancer (CRC) in observational studies, causality is uncertain. Here we apply a Mendelian randomisation (MR) analysis to examine the potential causal relationship between lipid traits and CRC risk. We used single nucleotide polymorphisms (SNPs) associated with blood levels of total cholesterol (TC), triglyceride (TG), low-density lipoprotein (LDL), and high-density lipoprotein (HDL) as instrumental variables (IV). We calculated MR estimates for each risk factor with CRC using SNP-CRC associations from 9,254 cases and 18,386 controls. Genetically predicted higher TC was associated with an elevated risk of CRC (odds ratios (OR) per unit SD increase = 1.46, 95% confidence interval [CI]: 1.20-1.79, P=1.68x10−4). The pooled ORs for LDL, HDL, and TG were 1.05 (95% CI: 0.92-1.18, P=0.49), 0.94 (95% CI: 0.84-1.05, P= 0.27), and 0.98 (95% CI: 0.85-1.12, P=0.75) respectively. A genetic risk score for 3-hydoxy-3-methylglutaryl-coenzyme A reductase (HMGCR) to mimic the effects of statin therapy was associated with a reduced CRC risk (OR=0.69, 95% CI: 0.49-0.99, P=0.046). This study supports a causal relationship between higher levels of TC with CRC risk, and a further rationale for implementing public health strategies to reduce the prevalence of hyperlipidaemia. This article is protected by copyright. All rights reserved.

Approximately 15% of colorectal cancers exhibit microsatellite instability (MSI), which leads to accumulation of large numbers of small insertions and deletions (indels). Genes that provide growth advantage to cells via loss-of-function mutations in microsatellites are called MSI target genes. Several criteria to define these genes have been suggested, one of them being simple mutation frequency. Microsatellite mutation rate, however, depends on the length and nucleotide context of the microsatellite. Therefore, assessing the general impact of mismatch repair deficiency on the likelihood of mutation events is paramount when following this approach. To identify MSI target genes, we developed a statistical model for the somatic background indel mutation rate of microsatellites to assess mutation significance. Exome sequencing data of 24 MSI colorectal cancers revealed indels at 54 million mononucleotide microsatellites of three or more nucleotides in length. The top 105 microsatellites from 71 genes were further analyzed in 93 additional MSI colorectal cancers. Mutation significance and estimated clonality of mutations determined the most likely MSI target genes to be the aminoadipate-semialdehyde dehydrogenase AASDH and the solute transporter SLC9A8. Our findings offer a systematic profiling of the somatic background mutation rate in protein-coding mononucleotide microsatellites, allowing a full cataloging of the true targets of MSI in colorectal cancer. Cancer Res; 77(15); 4078–88. ©2017 AACR.

Up to 86% of uterine leiomyomas harbour somatic mutations in mediator complex subunit 12 (MED12). These mutations have been associated with conventional histology, smaller tumour size, and larger number of tumours within the uterus. Prior studies, with limited sample sizes, have failed to detect associations between other clinical features and MED12 mutations. Here, we prospectively collected 763 uterine leiomyomas and the corresponding normal myometrial tissue from 244 hysterectomy patients, recorded tumour characteristics, collected clinical data from medical records, and screened the tissue samples for MED12 mutations to assess potential associations between clinical variables and mutation status. Out of 763 leiomyomas, 599 (79%) harboured a MED12 mutation. In the analysis of tumour characteristics, positive MED12-mutation status was significantly associated with smaller tumour size, conventional histology, and subserous location, relative to intramural. In the analysis of clinical variables, the number of MED12-mutation-positive tumours showed an inverse association with parity, and the number of mutation-negative tumours showed a positive association with a history of pelvic inflammatory disease. This study confirmed the previously reported differences and discovered novel differentiating features for MED12-mutation-positive and -negative leiomyomas. These findings emphasise the relevance of specific driver mutations in genesis and presentation of uterine leiomyomas.

// Esa Pitkanen 1,2 , Tatiana Cajuso 1,2 , Riku Katainen 1,2 , Eevi Kaasinen 1,2 , Niko Valimaki 1,2 , Kimmo Palin 1,2 , Jussi Taipale 1,3 , Lauri A. Aaltonen 1,2 , and Outi Kilpivaara 1,2 1 Genome-Scale Biology Research Program, Research Programs Unit, University of Helsinki, Helsinki, Finland 2 Department of Medical Genetics, University of Helsinki, Helsinki, Finland 3 Science for Life Center, Department of Biosciences and Nutrition, Karolinska Institutet, Stockholm, Sweden Correspondence: Lauri A. Aaltonen, email: // Keywords : colorectal cancer, genome, sequencing, retrotransposon, L1 Received : February 10, 2014 Accepted : February 14, 2014 Published : February 14, 2014 Abstract L1 element retrotranspositions have been found to alter expression of genes neighboring the insertion sites, potentially involving them in tumorigenesis and tumor progression. In colorectal cancer (CRC), L1 insertions have been found to target genes with a role in tumorigenesis. Structural changes such as L1 insertions are identifiable by whole genome sequencing (WGS). In this study, we observed frequent somatic L1 retrotranspositions originating from TTC28 using deep coverage WGS data from 92 CRC tumor-normal sample pairs. In two cases the event had targeted NOVA1 gene (p=0.025). In addition, a germline retrotransposition event from TTC28 to GABRA4 was found to be a common polymorphism in the Finnish population. Thus while some events may be tumorigenic, others are likely to be neutral. Our data contradict a recent study where a similar signal in TTC28 was interpreted as a common inactivating translocation. While much work remains to be performed to understand the biological significance of retrotranspositions in cancer, accurate identification of these events is a prerequisite for success.

SummaryAlthough the proteins that read the gene regulatory code, transcription factors (TFs), have been largely identified, it is not well known which sequences TFs can recognize. We have analyzed the sequence-specific binding of human TFs using high-throughput SELEX and ChIP sequencing. A total of 830 binding profiles were obtained, describing 239 distinctly different binding specificities. The models represent the majority of human TFs, approximately doubling the coverage compared to existing systematic studies. Our results reveal additional specificity determinants for a large number of factors for which a partial specificity was known, including a commonly observed A- or T-rich stretch that flanks the core motifs. Global analysis of the data revealed that homodimer orientation and spacing preferences, and base-stacking interactions, have a larger role in TF-DNA binding than previously appreciated. We further describe a binding model incorporating these features that is required to understand binding of TFs to DNA.

Copy number variants (CNVs) account for a major proportion of human genetic polymorphism and have been predicted to have an important role in genetic susceptibility to common disease. To address this we undertook a large, direct genome-wide study of association between CNVs and eight common human diseases. Using a purpose-designed array we typed 19,000 individuals into distinct copy-number classes at 3,432 polymorphic CNVs, including an estimated 50% of all common CNVs larger than 500 base pairs. We identified several biological artefacts that lead to false-positive associations, including systematic CNV differences between DNAs derived from blood and cell lines. Association testing and follow-up replication analyses confirmed three loci where CNVs were associated with diseaseIRGM for Crohns disease, HLA for Crohns disease, rheumatoid arthritis and type 1 diabetes, and TSPAN8 for type 2 diabetesalthough in each case the locus had previously been identified in single nucleotide polymorphism (SNP)-based studies, reflecting our observation that most common CNVs that are well-typed on our array are well tagged by SNPs and so have been indirectly explored through SNP studies. We conclude that common CNVs that can be typed on existing platforms are unlikely to contribute greatly to the genetic basis of common human diseases. © 2010 Macmillan Publishers Limited. All rights reserved.

To identify new risk loci for colorectal cancer (CRC), we conducted a meta-analysis of seven genome-wide association studies (GWAS) with independent replication, totalling 13 656 CRC cases and 21 667 controls of European ancestry. The combined analysis identified a new risk association for CRC at 2q35 marked by rs992157 (P = 3.15 x 10(-8), odds ratio = 1.10, 95% confidence interval = 1.06-1.13), which is intronic to PNKD (paroxysmal non-kinesigenic dyskinesia) and TMBIM1 (transmembrane BAX inhibitor motif containing 1). Intriguingly this susceptibility single-nucleotide polymorphism (SNP) is in strong linkage disequilibrium (r(2) = 0.90, D' = 0.96) with the previously discovered GWAS SNP rs2382817 for inflammatory bowel disease (IBD). Following on from this observation we examined for pleiotropy, or shared genetic susceptibility, between CRC and the 200 established IBD risk loci, identifying an additional 11 significant associations (false discovery rate [FDR])

Accurate knowledge of haplotypes, the combination of alleles co-residing on a single copy of a chromosome, enables powerful gene mapping and sequence imputation methods. Since humans are diploid, haplotypes must be derived from genotypes by a phasing process. In this study, we present a new computational model for haplotype phasing based on pairwise sharing of haplotypes inferred to be Identical-By-Descent (IBD). We apply the Bayesian network based model in a new phasing algorithm, called systematic long-range phasing (SLRP), that can capitalize on the close genetic relationships in isolated founder populations, and show with simulated and real genome-wide genotype data that SLRP substantially reduces the rate of phasing errors compared to previous phasing algorithms. Furthermore, the method accurately identifies regions of IBD, enabling linkage-like studies without pedigrees, and can be used to impute most genotypes with very low error rate. Genet. Epidemiol. 2011. © 2011 Wiley Periodicals, Inc.35:853-860, 2011

The genetic code—the binding specificity of all transfer-RNAs—defines how protein primary structure is determined by DNA sequence. DNA also dictates when and where proteins are expressed, and this information is encoded in a pattern of specific sequence motifs that are recognized by transcription factors. However, the DNA-binding specificity is only known for a small fraction of the ∼1400 human transcription factors (TFs). We describe here a high-throughput method for analyzing transcription factor binding specificity that is based on systematic evolution of ligands by exponential enrichment (SELEX) and massively parallel sequencing. The method is optimized for analysis of large numbers of TFs in parallel through the use of affinity-tagged proteins, barcoded selection oligonucleotides, and multiplexed sequencing. Data are analyzed by a new bioinformatic platform that uses the hundreds of thousands of sequencing reads obtained to control the quality of the experiments and to generate binding motifs for the TFs. The described technology allows higher throughput and identification of much longer binding profiles than current microarray-based methods. In addition, as our method is based on proteins expressed in mammalian cells, it can also be used to characterize DNA-binding preferences of full-length proteins or proteins requiring post-translational modifications. We validate the method by determining binding specificities of 14 different classes of TFs and by confirming the specificities for NFATC1 and RFX3 using ChIP-seq. Our results reveal unexpected dimeric modes of binding for several factors that were thought to preferentially bind DNA as monomers.

SummaryUnderstanding the regulation of human gene expression requires knowledge of the “second genetic code,” which consists of the binding specificities of transcription factors (TFs) and the combinatorial code by which TF binding sites are assembled to form tissue-specific enhancer elements. Using a novel high-throughput method, we determined the DNA binding specificities of GLIs 1–3, Tcf4, and c-Ets1, which mediate transcriptional responses to the Hedgehog (Hh), Wnt, and Ras/MAPK signaling pathways. To identify mammalian enhancer elements regulated by these pathways on a genomic scale, we developed a computational tool, enhancer element locator (EEL). We show that EEL can be used to identify Hh and Wnt target genes and to predict activated TFs based on changes in gene expression. Predictions validated in transgenic mouse embryos revealed the presence of multiple tissue-specific enhancers in mouse c-Myc and N-Myc genes, which has implications for organ-specific growth control and tumor-type specificity of oncogenes.

We propose a novel method to identify functionally related genes based on comparisons of neighborhoods in gene networks. This method does not rely on gene sequence or protein structure homologies, and it can be applied to any organism and a wide variety of experimental data sets. The character of the predicted gene relationships depends on the underlying networks;they concern biological processes rather than the molecular function. We used the method to analyze gene networks derived from genome-wide chromatin immunoprecipitation experiments, a large-scale gene deletion study, and from the genomic positions of consensus binding sites for transcription factors of the yeast Saccharomyces cerevisiae. We identified 816 functional relationships between 159 genes and show that these relationships correspond to protein-protein interactions, co-occurrence in the same protein complexes, and/or co-occurrence in abstracts of scientific articles. Our results suggest functions for seven previously uncharacterized yeast genes: KIN3 and YMR269W may be involved in biological processes related to cell growth and/or maintenance, whereas IES6, YEL008W, YEL033W, YHL029C, YMR010W, and YMR031W-A are likely to have metabolic functions.

Colorectal cancer, a major cause of cancer deaths worldwide, is often preventable by screening and surveillance, especially in patients at increased risk; however, its heritability is incompletely understood, and studies in isolated populations such as Finland may be valuable for gene discovery. We analyzed whole-genome or whole-exome sequencing data in 322 Finnish colorectal cancer cases of unknown etiology and 928 population-matched controls. To enrich for susceptibility alleles, cases were selected on the basis of early-onset colorectal cancer (age at diagnosis Citation Format: Tomas Tanskanen, Ulrika Hänninen, Tatiana Cajuso, Johanna Kondelin, Riku Katainen, Jiri Hamberg, Niko Välimäki, Esa Pitkänen, Kimmo Palin, Lauri A. Aaltonen. Germline loss-of-function alleles in Finnish colorectal cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1440. doi:10.1158/1538-7445.AM2017-1440

The aim of this study is to characterize the landscape of retrotransposon insertions in 202 colorectal cancer (CRC) patients to elucidate their role in colorectal tumorigenesis. Retrotransposons are genetic sequences that can copy themselves into an mRNA intermediate and insert elsewhere in the genome. Germline retrotranspositions can contribute to genetic variation however, high retrotransposon activity can also lead to genetic instability. Albeit retrotransposons are usually repressed in normal adult tissues, they become highly active in several cancer types, being most active in epithelial cancers such as CRC. Moreover, retrotransposon insertions have been difficult to detect with previous methodological approaches, which has resulted in very few genome-wide studies. Whole genome sequencing (WGS) was performed in 202 tumors and their corresponding normal tissue on the Illumina HiSeq 2000 platform; with 100 base-pairs paired-end reads. Each sample was sequenced to a minimum of 40x median coverage. To detect retrotransposon insertions we utilized TraFiC (Transposome Finder in Cancer). To identify retrotransposon-mediated transductions that were not identifiable using TraFiC, we utilized DELLY and the European database of L1-HS retrotransposon insertions in humans (euL1db). To characterize somatic insertions and decrease the rate of false positives, all insertions present in any of the normal genomes were filtered. After careful visual inspection of the paired-end read data, we estimated 80% of true somatic calls. We detected high retrotransposon activity in CRC with remarkable variation among patients. The mean number of insertions per tumor was 25, ranging from 0 to 197 insertions. In addition, we were able to identify few highly active retrotransposons that accounted for 70% of the retrotransposon-mediated transductions. We identified a total of 5065 somatic insertions, 2% of these insertions were located in exons, whereas 45% were in introns. We identified several genes with recurrent insertions, some of these loci being known fragile sites. However, we identified 13 known cancer genes with two or more insertions. Furthermore, we identified two patients with insertions in exon 16 of APC, suggesting that these insertions could be initiating tumorigenic events. To conclude, we found retrotransposon insertions to be a common phenomenon in CRC, contributing to genome instability and colorectal tumorigenesis. Citation Format: Tatiana Cajuso, Päivi Sulo, Riku Katainen, Ulrika Hänninen, Tomas Tanskanen, Johanna Kondelin, Jiri Hamberg, Niko Välimäki, Kimmo Palin, Outi Kilpivaara, Esa Pitkänen, Lauri A. Aaltonen. The mobile genome of colorectal cancer: Characterization of retrotransposon insertions in 202 colorectal cancer whole genomes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4381. doi:10.1158/1538-7445.AM2017-4381

The heritability of colorectal cancer (CRC) is incompletely understood, and the contribution of undiscovered rare variants may be important. In search of rare disease-causing variants, we exome sequenced 22 CRC patients who were diagnosed before the age of 40 years. Exome sequencing data from 95 familial CRC patients were available as a validation set. Cases with known CRC syndromes were excluded. All patients were from Finland, a country known for its genetically homogenous population. We searched for rare nonsynonymous variants with allele frequencies below 0.1% in 3,374 Finnish and 58,112 non-Finnish controls. In addition, homozygous and compound heterozygous variants were studied. No genes with rare loss-of-function variants were present in more than one early-onset CRC patient. Three genes ( ADAMTS4 , CYTL1 , and SYNE1 ) harbored rare loss-of-function variants in both early-onset and familial CRC cases. Five genes with homozygous variants in early-onset CRC cases were found ( MCTP2 , ARHGAP12 , ATM , DONSON , and ROS1 ), including one gene ( MCTP2 ) with a homozygous splice site variant. All discovered homozygous variants were exclusive to one early-onset CRC case. Independent replication is required to associate the discovered variants with CRC. These findings, together with a lack of family history in 19 of 22 (86%) early-onset patients, suggest genetic heterogeneity in unexplained early-onset CRC patients, thus emphasizing the requirement for large sample sizes and careful study designs to elucidate the role of rare variants in CRC susceptibility.

SummarySomatic mutations in exon 2 of the RNA polymerase II transcriptional Mediator subunit MED12 occur at very high frequency (∼70%) in uterine leiomyomas. However, the influence of these mutations on Mediator function and the molecular basis for their tumorigenic potential remain unknown. To clarify the impact of these mutations, we used affinity-purification mass spectrometry to establish the global protein-protein interaction profiles for both wild-type and mutant MED12. We found that uterine leiomyoma-linked mutations in MED12 led to a highly specific decrease in its association with Cyclin C-CDK8/CDK19 and loss of Mediator-associated CDK activity. Mechanistically, this occurs through disruption of a MED12-Cyclin C binding interface that we also show is required for MED12-mediated stimulation of Cyclin C-dependent CDK8 kinase activity. These findings indicate that uterine leiomyoma-linked mutations in MED12 uncouple Cyclin C-CDK8/19 from core Mediator and further identify the MED12/Cyclin C interface as a prospective therapeutic target in CDK8-driven cancers.

We identified six patients presenting with a strikingly similar clinical phenotype of profound syndromic intellectual disability of unknown etiology. All patients lived in the same village. Extensive genealogical work revealed that the healthy parents of the patients were all distantly related to a common ancestor from the 17th century, suggesting autosomal recessive inheritance. In addition to intellectual disability, the clinical features included hypotonia, strabismus, difficulty to fix the eyes to an object, planovalgus in the feet, mild contractures in elbow joints, interphalangeal joint hypermobility and coarse facial features that develop gradually during childhood. The clinical phenotype did not fit any known syndrome. Genome-wide SNP genotyping of the patients and genetic mapping revealed the longest shared homozygosity at 3p22.1-3p21.1 encompassing 11.5 Mb, with no other credible candidate loci emerging. Single point parametric linkage analysis showed logarithm of the odds score of 11 for the homozygous region, thus identifying a novel intellectual disability predisposition locus. Whole-genome sequencing of one affected individual pinpointed three genes with potentially protein damaging homozygous sequence changes within the predisposition locus: transketolase (TKT), prolyl 4-hydroxylase transmembrane (P4HTM), and ubiquitin specific peptidase 4 (USP4). The changes were found in heterozygous form with 0.3–0.7% allele frequencies in 402 whole-genome sequenced controls from the north-east of Finland. No homozygotes were found in this nor additional control data sets. Our study facilitates clinical and molecular diagnosis of patients with this novel autosomal recessive intellectual disability syndrome. However, further studies are needed to unambiguously identify the underlying genetic defect.

Microsatellite instability can be found in approximately 15% of all colorectal cancers. To detect new oncogenes we sequenced the exomes of 25 colorectal tumors and respective healthy colon tissue. Potential mutation hot spots were confirmed in 15 genes; ADAR, DCAF12L2, GLT1D1, ITGA7, MAP1B, MRGPRX4, PSRC1, RANBP2, RPS6KL1, SNCAIP, TCEAL6, TUBB6, WBP5, VEGFB, and ZBTB2; these were validated in 86 tumors with microsatellite instability. ZBTB2, RANBP2, and PSRC1 also were found to contain hot spot mutations in the validation set. The form of ZBTB2 associated with colorectal cancer increased cell proliferation. The mutation hot spots might be used to develop personalized tumor profiling and therapy.

Accurate knowledge of haplotypes, the combination of alleles co-residing on a single copy of a chromosome, enables powerful gene mapping and sequence imputation methods. Since humans are diploid, haplotypes must be derived from genotypes by a phasing process. In this study, we present a new computational model for haplotype phasing based on pairwise sharing of haplotypes inferred to be Identical-By-Descent (IBD). We apply the Bayesian network based model in a new phasing algorithm, called systematic long-range phasing (SLRP), that can capitalize on the close genetic relationships in isolated founder populations, and show with simulated and real genome-wide genotype data that SLRP substantially reduces the rate of phasing errors compared to previous phasing algorithms. Furthermore, the method accurately identifies regions of IBD, enabling linkage-like studies without pedigrees, and can be used to impute most genotypes with very low error rate. Genet. Epidemiol. 2011. © 2011 Wiley Periodicals, Inc.35:853-860, 2011

Members of the large ETS family of transcription factors (TFs) have highly similar DNA-binding domains (DBDs)—yet they have diverse functions and activities in physiology and oncogenesis. Some differences in DNA-binding preferences within this family have been described, but they have not been analysed systematically, and their contributions to targeting remain largely uncharacterized. We report here the DNA-binding profiles for all human and mouse ETS factors, which we generated using two different methods: a high-throughput microwell-based TF DNA-binding specificity assay, and protein-binding microarrays (PBMs). Both approaches reveal that the ETS-binding profiles cluster into four distinct classes, and that all ETS factors linked to cancer, ERG, ETV1, ETV4 and FLI1, fall into just one of these classes. We identify amino-acid residues that are critical for the differences in specificity between all the classes, and confirm the specificities in vivo using chromatin immunoprecipitation followed by sequencing (ChIP-seq) for a member of each class. The results indicate that even relatively small differences in in vitro binding specificity of a TF contribute to site selectivity in vivo.

Homozygosity for the G allele of rs6983267 at 8q24 increases colorectal cancer (CRC) risk approximately 1.5 fold. We report here that the risk allele G shows copy number increase during CRC development. Our computer algorithm, Enhancer Element Locator (EEL), identified an enhancer element that contains rs6983267. The element drove expression of a reporter gene in a pattern that is consistent with regulation by the key CRC pathway Wnt. rs6983267 affects a binding site for the Wnt-regulated transcription factor TCF4, with the risk allele G showing stronger binding in vitro and in vivo. Genome-wide ChIP assay revealed the element as the strongest TCF4 binding site within 1 Mb of MYC. An unambiguous correlation between rs6983267 genotype and MYC expression was not detected, and additional work is required to scrutinize all possible targets of the enhancer. Our work provides evidence that the common CRC predisposition associated with 8q24 arises from enhanced responsiveness to Wnt signaling.

Finding transcription factor binding sites in regulatory regions of the genome, With genome analysis expanding from the study of genes to the study of gene regulation, 'regulatory genomics' utilizes sequence information, evolution and functional genomics measurements to unravel how regulatory information is encoded in the genome.

This protocol describes the use of Enhancer Element Locator (EEL), a computer program that was designed to locate distal enhancer elements in long mammalian sequences. EEL will predict the location and structure of conserved enhancers after being provided with two orthologous DNA sequences and binding specificity matrices for the transcription factors (TFs) that are expected to contribute to the function of the enhancers to be identified. The freely available EEL software can analyze two 1-Mb sequences with 100 TF motifs in about 15 min on a modern Windows, Linux or Mac computer. The output provides several hypotheses about enhancer location and structure for further evaluation by an expert on enhancer function.

Colorectal cancer (CRC) is the third most common cancer in Western countries. Approximately 15% of CRCs display microsatellite instability (MSI) caused by defective cellular mismatch repair. Most of the MSI CRCs are sporadic and result from biallelic inactivation of the MLH1 gene, which is most often due to hypermethylation of its promoter. Cells displaying MSI accumulate a high number of mutations throughout the genome, especially in short repeat areas called microsatellites. These mutations typically lead to a premature stop codon resulting in a truncated protein product that may inactivate the gene, a mechanism known typical of tumor suppressor genes. The aim of this study is to identify new target genes in MSI CRC. To date, several genes have been proposed as MSI target genes based on high mutation frequency in targeted searches of microsatellites. The availability of new sequencing and bioinformatic technologies has enabled genome-wide investigation of mutations in human cancers. This has led to identification of a vast amount of mutations in cancer, most of which are passenger mutations that do not confer selective growth advantage. The challenge is therefore to distinguish true driver genes from passengers. The high number of mutations in MSI tumors augments this challenge. In this study, 25 sporadic MSI CRCs and their corresponding normal samples have been exome sequenced to identify changes of somatic origin. An analysis and visualization program developed in our group, “RikuRator” (unpublished), will be utilized along with a script to estimate the accurate somatic mutation frequency of each coding mononucleotide repeat. A statistical model based on exome sequencing data will be developed that takes into account the background mutation frequency of microsatellites depending on the repeat length and nucleotide context. The most mutated repeats will be validated by Sanger sequencing in a set of additional MSI CRCs. Functional studies will be carried out to further investigate the pathogenic effect of the new target genes identified. The systematic screening of mutations in microsatellites will improve our understanding on the mutation profile typical of these tumors. With our approach that takes into account the background mutation frequency of microsatellites we aim to identify true driver genes in MSI CRC. A detailed understanding of the molecular background of this tumor type is important for the development of more efficient screening methods and personalized treatments to improve the prognosis of patients diagnosed with MSI type CRC. Citation Format: Johanna Kondelin, Esa Pitkänen, Alexandra E. Gylfe, Kimmo Palin, Heikki Ristolainen, Riku Katainen, Eevi Kaasinen, Minna Taipale, Jussi Taipale, Laura Renkonen-Sinisalo, Heikki Järvinen, Jan Böhm, Jukka-Pekka Mecklin, Pia Vahteristo, Sari Tuupanen, Lauri A. Aaltonen. Identification of new target genes in microsatellite unstable colorectal cancer by exome sequencing. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2401. doi:10.1158/1538-7445.AM2014-2401

Around 15% of colorectal cancers (CRCs) show microsatellite instability (MSI). A characteristic high passenger mutation load has discouraged systematic mutation screens in MSI CRCs. To systematically search for novel MSI CRC oncogenes, the exomes of 25 MSI CRC-normal pairs were sequenced as the discovery set. Observed hot spots were confirmed by Sanger sequencing and further validated in a set of 86 MSI CRCs. Mutational hot spots were confirmed in 15 genes and three genes showed additional hot spot mutations in the validation set. These three sites were highly conserved across species. The hot spot sites of these three genes were screened in 75 microsatellite stable CRCs and 12 MSI CRC cell lines with negative results. Next, we analyzed the subcellular localization of wild-type and mutant proteins. The findings of this study support the idea that cancer genomes are heterogeneous and characterized by few, frequently mutated “mountains” (e.g. BRAF and KRAS) and numerous, less frequently mutated “hills”. The identified mutational hot spots may prove important in developing personalized tumor profiling and therapy. Citation Format: Alexandra E. Gylfe, Johanna Kondelin, Mikko Turunen, Heikki Ristolainen, Riku Katainen, Esa Pitkänen, Eevi Kaasinen, Ville Rantanen, Tomas Tanskanen, Heli J. Lehtonen, Kimmo Palin, Minna Taipale, Jussi Taipale, Laura Renkonen-Sinisalo, Heikki Järvinen, Jan Böhm, Jukka-Pekka Mecklin, Ari Ristimäki, Sari Tuupanen, Auli Karhu, Outi Kilpivaara, Pia Vahteristo, Lauri A. Aaltonen. New candidate oncogenes discovered in microsatellite unstable colorectal cancer. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 3156. doi:10.1158/1538-7445.AM2013-3156

Motivation: Finding putative transcription factor binding sites in the upstream sequences of similarly expressed genes has recently become a subject of intensive studies. In this paper we investigate how much gene expression regulation can be attributed to the presence of various binding sites in the gene promoters by correlating the binding sites and the changes in gene expression resulting from gene disruptions (e.g. knockouts). Results: We have developed a data analysis method for comparing mRNA measurements of gene disruption experiments with information about gene promoters. The method was applied to a well–known dataset to uncover correlations between known transcription factor binding site motifs in the upstream regions of all S. cerevisiae genes and the gene expression changes in various gene disruption experiments. The possible explanations of the correlations were categorized and analyzed using e.g. expression cascades. Several correlations turned out to be consistent with existing biological knowledge while some new ones suggest themselves for further study. Availability: The resulting tables are available at http://www.cs.helsinki.fi/u/kpalin/CorrDisrupt/. Contact: kimmo.palin@cs.helsinki.fi

This thesis presents methods for locating and analyzing cis-regulatory DNA elements involved with the regulation of gene expression in multicellular organisms. The regulation of gene expression is carried out by the combined effort of several transcription factor proteins collectively binding the DNA on the cis-regulatory elements. Only sparse knowledge of the 'genetic code' of these elements exists today. An automatic tool for discovery of putative cis-regulatory elements could help their experimental analysis, which would result in a more detailed view of the cis-regulatory element structure and function. We have developed a computational model for the evolutionary conservation of cis-regulatory elements. The elements are modeled as evolutionarily conserved clusters of sequence-specific transcription factor binding sites. We give an efficient dynamic programming algorithm that locates the putative cis-regulatory elements and scores them according to the conservation model. A notable proportion of the high-scoring DNA sequences show transcriptional enhancer activity in transgenic mouse embryos. The conservation model includes four parameters whose optimal values are estimated with simulated annealing. With good parameter values the model discriminates well between the DNA sequences with evolutionarily conserved cis-regulatory elements and the DNA sequences that have evolved neutrally. In further inquiry, the set of highest scoring putative cis-regulatory elements were found to be sensitive to small variations in the parameter values. The statistical significance of the putative cis-regulatory elements is estimated with the Two Component Extreme Value Distribution. The p-values grade the conservation of the cis-regulatory elements above the neutral expectation. The parameter values for the distribution are estimated by simulating the neutral DNA evolution. The conservation of the transcription factor binding sites can be used in the upstream analysis of regulatory interactions. This approach may provide mechanistic insight to the transcription level data from, e.g., microarray experiments. Here we give a method to predict shared transcriptional regulators for a set of co-expressed genes. The EEL (Enhancer Element Locator) software implements the method for locating putative cis-regulatory elements. The software facilitates both interactive use and distributed batch processing. We have used it to analyze the non-coding regions around all human genes with respect to the orthologous regions in various other species including mouse. The data from these genome-wide analyzes is stored in a relational database which is used in the publicly available web services for upstream analysis and visualization of the putative cis-regulatory elements in the human genome. Kun ihmisen genomi saatiin sekvensoitua eli ihmisen geenit oli löydetty ja eritelty vuosituhannen alussa, tiedemiehet yllättyivät ihmisen geenien pienestä määrästä. Ihmisellä havaittiin olevan vain vähän enemmän geenejä kuin yksinkertaisella sukkulamadolla. Koska geenien lukumäärä ei pystykään selittämään ihmisen ja sukkulamadon ulkoisia eroavaisuuksia, selitystä ruvettiin etsimään geenien toiminnan eroista. Geenien toimintaa säädellään monisoluisissa eliöissä hyvin tarkasti tiettyyn paikkaan ja tiettyyn osaan ruumista. Tietyt proteiinit toteuttavat geenien säätelyä sitoutumalla tiettyihin kohtiin DNA:ta säädeltävän geenin läheisyydessä. Näiden DNA:han sitoutumiskohtien löytäminen genomista on kokeellisesti hyvin haastavaa: ne saattavat sijaita hyvin kaukana säädeltävästä geenistä eikä proteiinien sitoutumissääntöjä tunneta vielä kovin hyvin. Väitöstyössä on kehitetty laskennallisia menetelmiä geenisäätelyyn liittyvien DNA sitoutumiskohtien paikantamiseen eri nisäkkäiden genomeja vertailemalla. Esimerkiksi ihmisen ja hiiren genomeja vertailemalla voidaan paikantaa DNA:n pätkiä, jotka ovat olleet hiirien ja ihmisten viimeisessä yhteisessä esivanhemmassa noin 65 miljoonaa vuotta sitten ja lisäksi vaikuttavat mahdollisilta proteiinien sitoutumiskohdilta. Tällaisia mahdollisia DNA:han sitoutumiskohtia on löydetty ihmisen genomista tuhansia, ja osan niistä on kokeellisesti havaittu säätelevän lähellä sijaitsevaa geeniä. Sitoutumiskohtien analysointiin kehitettiin väitöstutkimuksessa menetelmä, jolla voidaan ennustaa geenijoukoille säätelyproteiineja. Nykyaikaiset tehoseulontamenetelmät löytävät nopeasti geenijoukkoja, joilla on jokin kiinnostava ominaisuus, jonka säätelystä ollaan kiinnostuneita. Kehitetyllä menetelmällä voidaan helposti ennustaa esimerkiksi tiettyyn sairauteen liittyvien geenien säätelijä. Kun mahdollinen säätelijäproteiini tunnetaan, sitä vastaan voidaan kehittää lääke. Työn tulokset antavat uusia menetelmiä erityisesti vaikeasti tutkittavien yksilönkehityksen aikana säädeltyjen geenien analyysiin. Kehitettyjen menetelmien lääketieteelliset sovellukset liittyvät esimerkiksi kudosspesifiin kasvun säätelyyn ja syöpägeenien kasvainspesifisyyteen. Nämä sovellukset pyrkivät selvittämään mm. syytä ihmisen suhteettoman suurille aivoille ja pienille lihaksille ja toisaalta pyrkivät avaamaan uusia lähestymistapoja esimerkiksi syövän diagnostiikkaan ja hoitoon.

Transcription factors, by binding to particular DNA sequences termed transcription factor-binding sites, play an important role in regulating gene expression in both prokaryotic and eukaryotic organisms. These binding sites lie within promoters (which are located just upstream of a gene and promote transcription of that gene) and enhancers (short DNA elements enhancing transcription levels of genes in a gene cluster, and which need not be particularly close to the genes they act on, or even located on the same chromosome). Binding of transcription factors in these genomic regulatory regions can influence gene transcription rates either positively or negatively. The binding may also be dependant on the interaction with co-activators and co-repressors, in addition to context (e.g. particular histone modifications in the vicinity of the regulatory element). Identifying all transcription factors and their respective binding sites would be an important step towards a more thorough understanding of gene regulation. Regular expression type patterns, as well as nucleotide distribution matrices, have both been used for describing transcription factor-binding sites, e.g. (Bucher 1990; Ghosh 1990; Chen et al. 1995; Wingender et al. 1996). Here we will discuss some of the computational approaches that are used in binding site identification.