Genomics

Mutational processes contributing to the development of cancer emerge from various risk factors of the disease and impose specific imprints of somatic alterations in the genomes of cancer patients. These mutational footprints, called “signatures”, can be read from the tumour sequencing data and reveal the main sources of DNA damage driving neoplastic progression. In this sense, they can be considered a form of evidence for historical mutational events that have acted during tumour evolution. I will discuss some of the insights we have obtained into the development and progression of oesophageal adenocarcinoma, an aggressive disease with limited treatment options, by tracking mutational signatures in human cancer tissues as well as 3D cell models of this malignancy. Using this strategy applied to whole-genome sequencing data from 129 cases, we have previously uncovered three subtypes of oesophageal cancer with distinct aetiologies related to DNA damage repair deficiencies, ageing and oxidative stress, and with different therapeutic options. Further, we have shown that organoids grown in vitro from patients’ tumours effectively recapitulate the genomic and transcriptomic profiles of the tumours of origin, and thus constitute a suitable model for this cancer type. By tracking the evolution of mutational processes during organoid culture growth we were also able to demonstrate a dynamic clonal architecture that mimics well the extensive intratumour heterogeneity observed in this cancer. Tracing mutational signature trajectories from early to later stages of cancer development in both primary tumours and organoid systems unveils a refined picture of evolution in this cancer, with frequent bottlenecks (~60% of cases) where mutational pressures shift. Finally, we suggest that the observed genomic signatures and their specific temporal dynamics could be further exploited for patient stratification in the clinic. Full Abstract

Expression of canonical, replication-dependent histones (RDH) is highly regulated during the cell cycle echoing their main role during cell division and epigenetic inheritance. RDH genes produce the only non-polyadenylated transcripts and for their correct expression recruit a battery of alternative 3’ end processing factors. Exploiting metaplots, positional heat maps and computational methods, we decipher CDK11 binding along RDH mRNA and DNA identifying it as key player in the molecular regulation of RDH biogenesis.
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Metric genetic maps in Linkage Disequilibrium Units (LDU) are analogous to Linkage maps in cM but at a much higher marker resolution. LDU blocks represent areas of conserved LD and low haplotype diversity, while steps (increasing LDU distances) define LD breakdown, primarily caused by recombination, since crossover profiles agree precisely with the corresponding LDU steps. However, LDU maps do not only capture recombination events but the detailed linkage disequilibrium information of the population in question. We recently constructed the LDU genetic maps in Europeans and African-Americans and applied these to large T2D case-control samples in order to estimate accurate locations for putative functional variants in both populations. Replicated T2D locations were tested for evidence of being regulatory locations using adipose expression. We identified 111 novel loci associated with T2D-susceptibility locations, 93 of which are cosmopolitan (co-localised on genetic maps for both populations) and 18 are European-specific. We also found that many previously known T2D signals are also risk loci in African-Americans and we obtained more refined causal locations for these signals than the published lead SNPs. Using the same LDU methods, we also showed that the majority of these T2D locations are also regulatory locations (eQTLs) conferring the risk of T2D via the regulation of expression levels for a very large number (266) of cis-regulated genes. We identified a highly significant overlap between T2D and regulatory locations with chromatin marks for different tissues/cells. Sequencing a sample of our locations provided candidate functional variants that
precisely co-locate pancreatic islet enhancers, leading to our conclusions that population specific genetic maps can: (i) provide commensurability when making comparisons between different populations and SNP-arrays; (ii) provide precise location estimates on the genetic map for potential functional variants, since these estimates are more efficient than using physical maps and (iii) effectively integrate disease-associated loci in different populations with gene expression and cell-specific regulatory annotation, by providing precision in co-localisation. Full Abstract

Empirical genomic studies and long-established genetic theory show that complex traits – including many common diseases – are likely to be polygenic with numerous non-coding variants conferring risk of disease via the regulation of gene expression1 and post-translational modification2. Using high-resolution genetic maps3, we have identified 173 Type 2 Diabetes (T2D) precise disease susceptibility location estimates4 and using gene expression quantitative trait loci (eQTL) analyses for subcutaneous adipose tissue, have shown strong evidence that approximately two thirds of these closely collocate (± 50Kb) of eQTL location estimates that regulate the expression neighbouring cis-genes (within ±1.5Mb of the disease locus; see Figure 1)4. Our follow up analyses show that ~80 of the 111 T2D disease loci are also eQTLs that regulate the expression of nuclear encoded mitochondrial cis-genes with the eQTLs showing a high degree of co-location with in silico functional annotation. In this talk I will discuss our current understanding of the genetic and allelic architecture of T2D and illustrate this with results from genomic analyses and follow-up fine-mapping studies conducted by our research groups. In particular, we are investigating two interesting novel loci for evidence of complex association with T2D and mitochondrial function. The first locus, a 79kb stretch in intron 3 of FGF14, was observed to harbour eQTL for genes including PCCA, for which the encoded carboxylase catalyses a terminal step in both branched chain amino acid (BCAA) catabolism and odd-chain fatty acid oxidation; two pathways relevant to T2D aetiology. The second is a predicted eQTL for the fatty acid dehydrogenase ACAD11. Full Abstract

In recent years, the number of genetic loci found to be associated with T2D has increased substantially, mostly through large-scale genome-wide association studies (GWAS). Recent work has, however, highlighted an underappreciated contribution of rare variants and variants in areas of low linkage disequilibrium (LD) to complex disease heritability1,2, both of which are difficult to map using single-SNP tests of association. High-resolution genetic maps offer increased power to detect associations in areas of low LD and were recently used to map and replicate 111 novel loci associated with T2D3. Co-location of eQTL (genetic ‘expression quantitative trait loci’ which associate with gene expression levels) with disease loci (genetic loci that associate with risk of T2D), based on population-specific LD, was used to identify genes regulated by disease-associated variants (cis-genes). A co-localization approach overcomes difficulties in replicating lead SNPs between studies, making it an effective tool to identify likely cis-genes and the corresponding biological pathways implicated in heritable risk of disease. In this work, a total of 255 nominally significant disease loci were co-located with adipose eQTL and cis-genes were studied at the individual and pathway level. Specifically, we aimed to address the hypothesis that changes in mitochondrial function are a heritable, causal risk factor for T2D, by searching for cis-genes involved in mitochondrial function. Full Abstract

Most previous genome-wide association studies for complex traits were based on samples with European ancestry. Consequently, it is important to determine the transferability of findings to other ancestry groups. Here we ask the fundamental question whether causal variants for lipids are shared between populations.
Differences in linkage disequilibrium structure, allele frequencies and sample size make it difficult to assess replication for individual loci. Therefore, we propose a new strategy to assess evidence for shared causal variants between two populations: trans-ethnic colocalization (TEColoc). We re-purposed a method originally developed for colocalization of GWAS and eQTL results: Joint Likelihood Mapping (JLIM). In order to assess its performance for GWAS results from samples with different ancestry, we carried out a simulation study. UK Biobank (UKB) was used as a European ancestry reference Full Abstract

Cardiovascular (CV) mortality is the main cause of death in the general population1. The analysis of the electrocardiogram (ECG) has potential for non-invasive diagnosis and prediction of CV risk. ECG markers are heritable and statistical genetic methods are available to estimate the cumulative contribution of genetic factors to CV events via genetic risk scores (GRSs)2. The T-wave morphology restitution (TMR)3 is an ECG marker that quantifies the rate of variation of the T-wave morphology with heart rate and has shown to be a strong predictor of sudden cardiac death in chronic heart failure patients3. We hypothesize that the interaction between repolarization dynamics and CV risk has a genetic component and that TMR can be used to capture it.
The objective was to identify single-nucleotide variants (SNVs) significantly associated with TMR using genome-wide association studies (GWASs) and to develop genetic risk scores (GRSs) to evaluate their association with CV risk. Full Abstract

The resting QT interval, an electrocardiographic measure of myocardial repolarisation, is a heritable risk factor for cardiovascular (CV) events and genetic studies have provided new insights into the underlying biology[1]. Patient studies have reported that QT adaptation to heart rate (QT dynamics) improves cardiac risk prediction[2], but its prognostic value in the general population remains to be investigated. Furthermore, it is well recognised that the QT interval is a heritable trait and characterisation of genetic variation has provided new insights and suggests candidate genes that could predispose to CV risk. However, common variants thus far reported leave an important part of its heritability unexplained. In addition, the genetic architecture underlying QT dynamics has not been explored and might further inform about new biological mechanisms that specifically target rate adaptation of the QT interval. The objectives of this work were: (1) Evaluate the CV prognostic value of QT dynamics in the general population, (2) discover genetic variants associated with QT dynamics and (3) further investigate the genetic basis and biology of resting QT interval. Full Abstract