Search

SummaryCancers arise through the acquisition of oncogenic mutations and grow through clonal expansion1, 2. Here we reveal that most mutagenic DNA lesions are not resolved as mutations within a single cell-cycle. Instead, DNA lesions segregate unrepaired into daughter cells for multiple cell generations, resulting in the chromosome-scale phasing of subsequent mutations. We characterise this process in mutagen-induced mouse liver tumours and show that DNA replication across persisting lesions can generate multiple alternative alleles in successive cell divisions, thereby increasing both multi-allelic and combinatorial genetic diversity. The phasing of lesions enables the accurate measurement of strand biased repair processes, the quantification of oncogenic selection, and the fine mapping of sister chromatid exchange events. Finally, we demonstrate that lesion segregation is a unifying property of exogenous mutagens, including UV light and chemotherapy agents in human cells and tumours, which has profound implications for the evolution and adaptation of cancer genomes.

CRISPR/Cas9 system requires short guide RNAs (sgRNAs) to direct genome modification. Most currently available tools for sgRNA design operate only with standard reference genomes, and are best suited for small-scale projects. To address these limitations, we developed Crisflash, a software tool for fast sgRNA design and potential off-target discovery, built for performance and flexibility. Crisflash can rapidly design CRISPR guides against any sequenced genome or genome sequences, and can optimize guide accuracy by incorporating user-supplied variant data. Crisflash is over an order of magnitude faster than comparable tools, even using a single CPU core, and efficiently and robustly scores the potential off-targeting of all possible candidate CRISPR guide oligonucleotides.

SummaryThe mammalian radiation has corresponded with rapid changes in noncoding regions of the genome, but we lack a comprehensive understanding of regulatory evolution in mammals. Here, we track the evolution of promoters and enhancers active in liver across 20 mammalian species from six diverse orders by profiling genomic enrichment of H3K27 acetylation and H3K4 trimethylation. We report that rapid evolution of enhancers is a universal feature of mammalian genomes. Most of the recently evolved enhancers arise from ancestral DNA exaptation, rather than lineage-specific expansions of repeat elements. In contrast, almost all liver promoters are partially or fully conserved across these species. Our data further reveal that recently evolved enhancers can be associated with genes under positive selection, demonstrating the power of this approach for annotating regulatory adaptations in genomic sequences. These results provide important insight into the functional genetics underpinning mammalian regulatory evolution.

This thesis studies human gene expression space using high throughput gene expression data from DNA microarrays. In molecular biology, high throughput techniques allow numerical measurements of expression of tens of thousands of genes simultaneously. In a single study, this data is traditionally obtained from a limited number of sample types with a small number of replicates. For organism-wide analysis, this data has been largely unavailable and the global structure of human transcriptome has remained unknown. This thesis introduces a human transcriptome map of different biological entities and analysis of its general structure. The map is constructed from gene expression data from the two largest public microarray data repositories, GEO and ArrayExpress. The creation of this map contributed to the development of ArrayExpress by identifying and retrofitting the previously unusable and missing data and by improving the access to its data. It also contributed to creation of several new tools for microarray data manipulation and establishment of data exchange between GEO and ArrayExpress. The data integration for the global map required creation of a new large ontology of human cell types, disease states, organism parts and cell lines. The ontology was used in a new text mining and decision tree based method for automatic conversion of human readable free text microarray data annotations into categorised format. The data comparability and minimisation of the systematic measurement errors that are characteristic to each lab- oratory in this large cross-laboratories integrated dataset, was ensured by computation of a range of microarray data quality metrics and exclusion of incomparable data. The structure of a global map of human gene expression was then explored by principal component analysis and hierarchical clustering using heuristics and help from another purpose built sample ontology. A preface and motivation to the construction and analysis of a global map of human gene expression is given by analysis of two microarray datasets of human malignant melanoma. The analysis of these sets incorporate indirect comparison of statistical methods for finding differentially expressed genes and point to the need to study gene expression on a global level. Kaikki monisoluisen organismin solut sisältävät saman geenivalikoiman. Solujen ulkonako ja toiminta määräytyvät sen mukaan, mitkä geeniyhdistelmät ovat aktiivisia. Solun geenien ilmentymistä voidaan mitata korkeasaantoisilla molekyylibiologian menetelmillä kuten DNA-siruilla. Tyypillisessä DNA-sirukokeessa mitataan geenien aktiivisuutta pienessä määrässä erilaisia solu- tai kudostyyppejä. Geenien ilmentymisen tutkiminen käyttäen suurempia näytemääriä ei usein ole mahdollista ja tieto aktiivisuuseroista organismitasolla on tuntematta. Tämä väitöskirja esittelee ihmisen geeniaktiviteetin tutkimukseen käytettävää karttaa sadoista solu- ja kudostyypeistä ja tarkastelee sen rakennetta. Tarkasteltava tieto on kerätty yli 200 erillisestä tutkimuksesta ja sisältää informaatiota geenien ilmentymisestä normaaleissa ja sairaissa solu- ja kudostyypeissä, jotka ovat peräisin yli 160 laboratoriosta. Kartta on luotu yhdistämällä tietoa kahdesta maailman suurimmasta DNA-sirutietokannasta (GEO ja ArrayExpress). Tämän kartan luominen auttoi osaltaan ArrayExpressin kehittämisessä parantamalla tiedon saatavuutta tutkijoille ja korjaamalla tiedossa olevia virheitä. Se oli myös mukana kehittämässä laskennallisia välineitä DNA-sirudatan manipulointiin ja GEOn ja ArrayExpressin välisen tiedon vaihdon luomisessa. Suurten tietomäärien käsittely ja analysointi on mahdollista vain, jos tieto on järjestetty systemaattisesti. Geenien ilmentymiskarttaan liitettyjen biologisten näytteiden kuvaukset systematisoitiin korvaamalla alkuperäiset näytekuvaukset muutamalla hyvin informatiivisella avainsanalla. Nämä avainsanat järjestettiin edelleen hierarkkisesti. Tätä hierarkiaa käytettiin sitten näytteiden automaattiseen ryhmittelyyn tiedon visualisoinnissa ja analysoinnissa. On tiedossa, että biologisen näytteen geenien ilmentymisessä havaittavat erot ovat suuremmat, jos mittaukset suoritetaan kahdessa eri laboratoriossa kuin jos mittaus toistetaan samassa laboratoriossa. Koska kattavan geenien ilmentymiskartan luomiseen käytetty tieto tuli monesta laboratoriosta, oli tärkeää varmistaa, että tämä niin sanottu laboratorioefekti ei vinouttasi analyysituloksia. Tästä syystä kaikki kartan luomiseen käytetty tieto tarkastettiin huolellisesti laadun ja vertailukelpoisuuden suhteen. Alkuperäinen kannuste kattavan ihmisen geenien ilmentymiskartan perustamiseen tuli kahden pahanlaatuisen ihosyöpänäytteen analysoinnista. Ihosyöpätutkimuksen tavoitteena oli tunnistaa geenejä, joiden aktiivisuus olisi kytköksissä pahanlaatuiseen solutyyppiin. Naiden geenien etsintä toi esille pienten solu- ja kudosmäärien käytön rajoitukset ja tarpeen geenien ilmentymisen kokonaisvaltaisempaan tutkimukseen.

BACKGROUND & AIMS: Carcinogen-induced mouse models of liver cancer are used extensively to study the pathogenesis of the disease and are critical for validating candidate therapeutics. These models can recapitulate molecular and histological features of human disease. However, it is not known if the genomic alterations driving these mouse tumour genomes are comparable to those found in human tumours. Herein, we provide a detailed genomic characterisation of tumours from a commonly used mouse model of hepatocellular carcinoma (HCC). METHODS: We analysed whole exome sequences of liver tumours arising in mice exposed to diethylnitrosamine (DEN). Mutational signatures were compared between liver tumours from DEN-treated and untreated mice, and human HCCs. RESULTS: DEN-initiated tumours had a high, uniform number of somatic single nucleotide variants (SNVs), with few insertions, deletions or copy number alterations, consistent with the known genotoxic action of DEN. Exposure of hepatocytes to DEN left a reproducible mutational imprint in resulting tumour exomes which we could computationally reconstruct using six known COSMIC mutational signatures. The tumours carried a high diversity of low-incidence, non-synonymous point mutations in many oncogenes and tumour suppressors, reflecting the stochastic introduction of SNVs into the hepatocyte genome by the carcinogen. We identified four recurrently mutated genes that were putative oncogenic drivers of HCC in this model. Every neoplasm carried activating hotspot mutations either in codon 61 of Hras, in codon 584 of Braf or in codon 254 of Egfr. Truncating mutations of Apc occurred in 21% of neoplasms, which were exclusively carcinomas supporting a role for deregulation of Wnt/β-catenin signalling in cancer progression. CONCLUSIONS: Our study provides detailed insight into the mutational landscape of tumours arising in a commonly used carcinogen model of HCC, facilitating the future use of this model to better understand the human disease. LAY SUMMARY: Mouse models are widely used to study the biology of cancer and to test potential therapies. Herein, we have described the mutational landscape of tumours arising in a carcinogen-induced mouse model of liver cancer. Since cancer is a disease caused by genomic alterations, information about the patterns and types of mutations in the tumours in this mouse model should facilitate its use to study human liver cancer.

Cancers arise through the acquisition of oncogenic mutations and grow through clonal expansion. Here we reveal that most mutagenic DNA lesions are not resolved as mutations within a single cell-cycle. Instead, DNA lesions segregate unrepaired into daughter cells for multiple cell generations, resulting in the chromosome-scale phasing of subsequent mutations. We characterise this process in mutagen-induced mouse liver tumours and show that DNA replication across persisting lesions can produce multiple alternative alleles in successive cell divisions, thereby generating both multi-allelic and combinatorial genetic diversity. The phasing of lesions enables the accurate measurement of strand biased repair processes, quantification of oncogenic selection, and fine mapping of sister chromatid exchange events. Finally, we demonstrate that lesion segregation is a unifying property of exogenous mutagens, including UV light and chemotherapy agents in human cells and tumours, which has profound implications for the evolution and adaptation of cancer genomes.