GCAT|Panel, a comprehensive structural variant haplotype map of the Iberian population from high-coverage whole-genome sequencing.

The combined analysis of haplotype panels with phenotype clinical cohorts is a common approach to explore the genetic architecture of human diseases. However, genetic studies are mainly based on single nucleotide variants (SNVs) and small insertions and deletions (indels). Here, we contribute to fill this gap by generating a dense haplotype map focused on the identification, characterization, and phasing of structural variants (SVs). By integrating multiple variant identification methods and Logistic Regression Models (LRMs), we present a catalogue of 35 431 441 variants, including 89 178 SVs (≥50 bp), 30 325 064 SNVs and 5 017 199 indels, across 785 Illumina high coverage (30x) whole-genomes from the Iberian GCAT Cohort, containing a median of 3.52M SNVs, 606 336 indels and 6393 SVs per individual. The haplotype panel is able to impute up to 14 360 728 SNVs/indels and 23 179 SVs, showing a 2.7-fold increase for SVs compared with available genetic variation panels. The value of this panel for SVs analysis is shown through an imputed rare Alu element located in a new locus associated with Mononeuritis of lower limb, a rare neuromuscular disease. This study represents the first deep characterization of genetic variation within the Iberian population and the first operational haplotype panel to systematically include the SVs into genome-wide genetic studies.

Polymorphic Inversions Underlie the Shared Genetic Susceptibility of Obesity-Related Diseases.

The burden of several common diseases including obesity, diabetes, hypertension, asthma, and depression is increasing in most world populations. However, the mechanisms underlying the numerous epidemiological and genetic correlations among these disorders remain largely unknown. We investigated whether common polymorphic inversions underlie the shared genetic influence of these disorders. We performed an inversion association analysis including 21 inversions and 25 obesity-related traits on a total of 408,898 Europeans and validated the results in 67,299 independent individuals. Seven inversions were associated with multiple diseases while inversions at 8p23.1, 16p11.2, and 11q13.2 were strongly associated with the co-occurrence of obesity with other common diseases. Transcriptome analysis across numerous tissues revealed strong candidate genes for obesity-related traits. Analyses in human pancreatic islets indicated the potential mechanism of inversions in the susceptibility of diabetes by disrupting the cis-regulatory effect of SNPs from their target genes. Our data underscore the role of inversions as major genetic contributors to the joint susceptibility to common complex diseases.

Genomic and epigenomic insights into the origin, pathogenesis, and clinical behavior of mantle cell lymphoma subtypes.

Mantle cell lymphoma (MCL) is a mature B-cell neoplasm initially driven by CCND1 rearrangement with 2 molecular subtypes, conventional MCL (cMCL) and leukemic non-nodal MCL (nnMCL), that differ in their clinicobiological behavior. To identify the genetic and epigenetic alterations determining this diversity, we used whole-genome (n = 61) and exome (n = 21) sequencing (74% cMCL, 26% nnMCL) combined with transcriptome and DNA methylation profiles in the context of 5 MCL reference epigenomes. We identified that open and active chromatin at the major translocation cluster locus might facilitate the t(11;14)(q13;32), which modifies the 3-dimensional structure of the involved regions. This translocation is mainly acquired in precursor B cells mediated by recombination-activating genes in both MCL subtypes, whereas in 8% of cases the translocation occurs in mature B cells mediated by activation-induced cytidine deaminase. We identified novel recurrent MCL drivers, including CDKN1B, SAMHD1, BCOR, SYNE1, HNRNPH1, SMARCB1, and DAZAP1. Complex structural alterations emerge as a relevant early oncogenic mechanism in MCL, targeting key driver genes. Breakage-fusion-bridge cycles and translocations activated oncogenes (BMI1, MIR17HG, TERT, MYC, and MYCN), generating gene amplifications and remodeling regulatory regions. cMCL carried significant higher numbers of structural variants, copy number alterations, and driver changes than nnMCL, with exclusive alterations of ATM in cMCL, whereas TP53 and TERT alterations were slightly enriched in nnMCL. Several drivers had prognostic impact, but only TP53 and MYC aberrations added value independently of genomic complexity. An increasing genomic complexity, together with the presence of breakage-fusion-bridge cycles and high DNA methylation changes related to the proliferative cell history, defines patients with different clinical evolution.

CCND2 and CCND3 hijack immunoglobulin light-chain enhancers in cyclin D1- mantle cell lymphoma.

Mantle cell lymphoma (MCL) is characterized by the t(11;14)(q13;q32) translocation resulting in overexpression of cyclin D1. However, a small subset of cyclin D1- MCL has been recognized, and approximately one-half of them harbor CCND2 translocations while the primary event in cyclin D1-/D2- MCL remains elusive. To identify other potential mechanisms driving MCL pathogenesis, we investigated 56 cyclin D1-/SOX11+ MCL by fluorescence in situ hybridization (FISH), whole-genome/exome sequencing, and gene-expression and copy-number arrays. FISH with break-apart probes identified CCND2 rearrangements in 39 cases (70%) but not CCND3 rearrangements. We analyzed 3 of these negative cases by whole-genome/exome sequencing and identified IGK (n = 2) and IGL (n = 1) enhancer hijackings near CCND3 that were associated with cyclin D3 overexpression. By specific FISH probes, including the IGK enhancer region, we detected 10 additional cryptic IGK juxtapositions to CCND3 (6 cases) and CCND2 (4 cases) in MCL that overexpressed, respectively, these cyclins. A minor subset of 4 cyclin D1- MCL cases lacked cyclin D rearrangements and showed upregulation of CCNE1 and CCNE2. These cases had blastoid morphology, high genomic complexity, and CDKN2A and RB1 deletions. Both genomic and gene-expression profiles of cyclin D1- MCL cases were indistinguishable from cyclin D1+ MCL. In conclusion, virtually all cyclin D1- MCLs carry CCND2/CCND3 rearrangements with immunoglobulin genes, including a novel IGK/L enhancer hijacking mechanism. A subset of cyclin D1-/D2-/D3- MCL with aggressive features has cyclin E dysregulation. Specific FISH probes may allow the molecular identification and diagnosis of cyclin D1- MCL.

A cancer-associated polymorphism in ESCRT-III disrupts the abscission checkpoint and promotes genome instability.

Cytokinetic abscission facilitates the irreversible separation of daughter cells. This process requires the endosomal-sorting complexes required for transport (ESCRT) machinery and is tightly regulated by charged multivesicular body protein 4C (CHMP4C), an ESCRT-III subunit that engages the abscission checkpoint (NoCut) in response to mitotic problems such as persisting chromatin bridges within the midbody. Importantly, a human polymorphism in CHMP4C (rs35094336, CHMP4CT232) increases cancer susceptibility. Here, we explain the structural and functional basis for this cancer association: The CHMP4CT232 allele unwinds the C-terminal helix of CHMP4C, impairs binding to the early-acting ESCRT factor ALIX, and disrupts the abscission checkpoint. Cells expressing CHMP4CT232 exhibit increased levels of DNA damage and are sensitized to several conditions that increase chromosome missegregation, including DNA replication stress, inhibition of the mitotic checkpoint, and loss of p53. Our data demonstrate the biological importance of the abscission checkpoint and suggest that dysregulation of abscission by CHMP4CT232 may synergize with oncogene-induced mitotic stress to promote genomic instability and tumorigenesis.

Multitrait genome association analysis identifies new susceptibility genes for human anthropometric variation in the GCAT cohort.

BACKGROUND: Heritability estimates have revealed an important contribution of SNP variants for most common traits; however, SNP analysis by single-trait genome-wide association studies (GWAS) has failed to uncover their impact. In this study, we applied a multitrait GWAS approach to discover additional factor of the missing heritability of human anthropometric variation. METHODS: We analysed 205 traits, including diseases identified at baseline in the GCAT cohort (Genomes For Life- Cohort study of the Genomes of Catalonia) (n=4988), a Mediterranean adult population-based cohort study from the south of Europe. We estimated SNP heritability contribution and single-trait GWAS for all traits from 15 million SNP variants. Then, we applied a multitrait-related approach to study genome-wide association to anthropometric measures in a two-stage meta-analysis with the UK Biobank cohort (n=336 107). RESULTS: Heritability estimates (eg, skin colour, alcohol consumption, smoking habit, body mass index, educational level or height) revealed an important contribution of SNP variants, ranging from 18% to 77%. Single-trait analysis identified 1785 SNPs with genome-wide significance threshold. From these, several previously reported single-trait hits were confirmed in our sample with LINC01432 (p=1.9×10-9) variants associated with male baldness, LDLR variants with hyperlipidaemia (ICD-9:272) (p=9.4×10-10) and variants in IRF4 (p=2.8×10-57), SLC45A2 (p=2.2×10-130), HERC2 (p=2.8×10-176), OCA2 (p=2.4×10-121) and MC1R (p=7.7×10-22) associated with hair, eye and skin colour, freckling, tanning capacity and sun burning sensitivity and the Fitzpatrick phototype score, all highly correlated cross-phenotypes. Multitrait meta-analysis of anthropometric variation validated 27 loci in a two-stage meta-analysis with a large British ancestry cohort, six of which are newly reported here (p value threshold <5×10-9) at ZRANB2-AS2, PIK3R1, EPHA7, MAD1L1, CACUL1 and MAP3K9. CONCLUSION: Considering multiple-related genetic phenotypes improve associated genome signal detection. These results indicate the potential value of data-driven multivariate phenotyping for genetic studies in large population-based cohorts to contribute to knowledge of complex traits.

A kidney-disease gene panel allows a comprehensive genetic diagnosis of cystic and glomerular inherited kidney diseases.

Molecular diagnosis of inherited kidney diseases remains a challenge due to their expanding phenotypic spectra as well as the constantly growing list of disease-causing genes. Here we develop a comprehensive approach for genetic diagnosis of inherited cystic and glomerular nephropathies. Targeted next generation sequencing of 140 genes causative of or associated with cystic or glomerular nephropathies was performed in 421 patients, a validation cohort of 116 patients with previously known mutations, and a diagnostic cohort of 207 patients with suspected inherited cystic disease and 98 patients with glomerular disease. In the validation cohort, a sensitivity of 99% was achieved. In the diagnostic cohort, causative mutations were found in 78% of patients with cystic disease and 62% of patients with glomerular disease, mostly familial cases, including copy number variants. Results depict the distribution of different cystic and glomerular inherited diseases showing the most likely diagnosis according to perinatal, pediatric and adult disease onset. Of all the genetically diagnosed patients, 15% were referred with an unspecified clinical diagnosis and in 2% genetic testing changed the clinical diagnosis. Therefore, in 17% of cases our genetic analysis was crucial to establish the correct diagnosis. Complex inheritance patterns in autosomal dominant polycystic kidney disease and Alport syndrome were suspected in seven and six patients, respectively. Thus, our kidney-disease gene panel is a comprehensive, noninvasive, and cost-effective tool for genetic diagnosis of cystic and glomerular inherited kidney diseases. This allows etiologic diagnosis in three-quarters of patients and is especially valuable in patients with unspecific or atypical phenotypes.

Enterotypes of the human gut microbiome.

Our knowledge of species and functional composition of the human gut microbiome is rapidly increasing, but it is still based on very few cohorts and little is known about variation across the world. By combining 22 newly sequenced faecal metagenomes of individuals from four countries with previously published data sets, here we identify three robust clusters (referred to as enterotypes hereafter) that are not nation or continent specific. We also confirmed the enterotypes in two published, larger cohorts, indicating that intestinal microbiota variation is generally stratified, not continuous. This indicates further the existence of a limited number of well-balanced host-microbial symbiotic states that might respond differently to diet and drug intake. The enterotypes are mostly driven by species composition, but abundant molecular functions are not necessarily provided by abundant species, highlighting the importance of a functional analysis to understand microbial communities. Although individual host properties such as body mass index, age, or gender cannot explain the observed enterotypes, data-driven marker genes or functional modules can be identified for each of these host properties. For example, twelve genes significantly correlate with age and three functional modules with the body mass index, hinting at a diagnostic potential of microbial markers.

Whole-genome sequencing identifies recurrent mutations in chronic lymphocytic leukaemia.

Chronic lymphocytic leukaemia (CLL), the most frequent leukaemia in adults in Western countries, is a heterogeneous disease with variable clinical presentation and evolution. Two major molecular subtypes can be distinguished, characterized respectively by a high or low number of somatic hypermutations in the variable region of immunoglobulin genes. The molecular changes leading to the pathogenesis of the disease are still poorly understood. Here we performed whole-genome sequencing of four cases of CLL and identified 46 somatic mutations that potentially affect gene function. Further analysis of these mutations in 363 patients with CLL identified four genes that are recurrently mutated: notch 1 (NOTCH1), exportin 1 (XPO1), myeloid differentiation primary response gene 88 (MYD88) and kelch-like 6 (KLHL6). Mutations in MYD88 and KLHL6 are predominant in cases of CLL with mutated immunoglobulin genes, whereas NOTCH1 and XPO1 mutations are mainly detected in patients with unmutated immunoglobulins. The patterns of somatic mutation, supported by functional and clinical analyses, strongly indicate that the recurrent NOTCH1, MYD88 and XPO1 mutations are oncogenic changes that contribute to the clinical evolution of the disease. To our knowledge, this is the first comprehensive analysis of CLL combining whole-genome sequencing with clinical characteristics and clinical outcomes. It highlights the usefulness of this approach for the identification of clinically relevant mutations in cancer.

Unravelling the hidden DNA structural/physical code provides novel insights on promoter location.

Although protein recognition of DNA motifs in promoter regions has been traditionally considered as a critical regulatory element in transcription, the location of promoters, and in particular transcription start sites (TSSs), still remains a challenge. Here we perform a comprehensive analysis of putative core promoter sequences relative to non-annotated predicted TSSs along the human genome, which were defined by distinct DNA physical properties implemented in our ProStar computational algorithm. A representative sampling of predicted regions was subjected to extensive experimental validation and analyses. Interestingly, the vast majority proved to be transcriptionally active despite the lack of specific sequence motifs, indicating that physical signaling is indeed able to detect promoter activity beyond conventional TSS prediction methods. Furthermore, highly active regions displayed typical chromatin features associated to promoters of housekeeping genes. Our results enable to redefine the promoter signatures and analyze the diversity, evolutionary conservation and dynamic regulation of human core promoters at large-scale. Moreover, the present study strongly supports the hypothesis of an ancient regulatory mechanism encoded by the intrinsic physical properties of the DNA that may contribute to the complexity of transcription regulation in the human genome.

Identification of novel type 2 diabetes candidate genes involved in the crosstalk between the mitochondrial and the insulin signaling systems.

Type 2 Diabetes (T2D) is a highly prevalent chronic metabolic disease with strong co-morbidity with obesity and cardiovascular diseases. There is growing evidence supporting the notion that a crosstalk between mitochondria and the insulin signaling cascade could be involved in the etiology of T2D and insulin resistance. In this study we investigated the molecular basis of this crosstalk by using systems biology approaches. We combined, filtered, and interrogated different types of functional interaction data, such as direct protein-protein interactions, co-expression analyses, and metabolic and signaling dependencies. As a result, we constructed the mitochondria-insulin (MITIN) network, which highlights 286 genes as candidate functional linkers between these two systems. The results of internal gene expression analysis of three independent experimental models of mitochondria and insulin signaling perturbations further support the connecting roles of these genes. In addition, we further assessed whether these genes are involved in the etiology of T2D using the genome-wide association study meta-analysis from the DIAGRAM consortium, involving 8,130 T2D cases and 38,987 controls. We found modest enrichment of genes associated with T2D amongst our linker genes (p = 0.0549), including three already validated T2D SNPs and 15 additional SNPs, which, when combined, were collectively associated to increased fasting glucose levels according to MAGIC genome wide meta-analysis (p = 8.12×10(-5)). This study highlights the potential of combining systems biology, experimental, and genome-wide association data mining for identifying novel genes and related variants that increase vulnerability to complex diseases.

Adaptation to environmental factors shapes the organization of regulatory regions in microbial communities.

BACKGROUND: It has been shown in a number of metagenomic studies that the addition and removal of specific genes have allowed microbiomes to adapt to specific environmental conditions by losing and gaining specific functions. But it is not known whether and how the regulation of gene expression also contributes to adaptation. RESULTS: We have here characterized and analyzed the metaregulome of three different environments, as well as their impact in the adaptation to particular variable physico-chemical conditions. For this, we have developed a computational protocol to extract regulatory regions and their corresponding transcription factors binding sites directly from metagenomic reads and applied it to three well known environments: Acid Mine, Whale Fall, and Waseca Farm. Taking the density of regulatory sites in promoters as a measure of the potential and complexity of gene regulation, we found it to be quantitatively the same in all three environments, despite their different physico-chemical conditions and species composition. However, we found that each environment distributes their regulatory potential differently across their functional space. Among the functions with highest regulatory potential in each niche, we found significant enrichment of processes related to sensing and buffering external variable factors specific to each environment, like for example, the availability of co-factors in deep sea, of oligosaccharides in soil and the regulation of pH in the acid mine. CONCLUSIONS: These results highlight the potential impact of gene regulation in the adaptation of bacteria to the different habitats through the distribution of their regulatory potential among specific functions, and point to critical environmental factors that challenge the growth of any microbial community.

Germline NPAT inactivating variants as cause of hereditary colorectal cancer.

Two independent exome sequencing initiatives aimed to identify new genes involved in the predisposition to nonpolyposis colorectal cancer led to the identification of heterozygous loss-of-function variants in NPAT, a gene that encodes a cyclin E/CDK2 effector required for S phase entry and a coactivator of histone transcription, in two families with multiple members affected with colorectal cancer. Enrichment of loss-of-function and predicted deleterious NPAT variants was identified in familial/early-onset colorectal cancer patients compared to non-cancer gnomAD individuals, further supporting the association with the disease. Previous studies in Drosophila models showed that NPAT abrogation results in chromosomal instability, increase of double strand breaks, and induction of tumour formation. In line with these results, colorectal cancers with NPAT somatic variants and no DNA repair defects have significantly higher aneuploidy levels than NPAT-wildtype colorectal cancers. In conclusion, our findings suggest that constitutional inactivating NPAT variants predispose to mismatch repair-proficient nonpolyposis colorectal cancer.

ReLA, a local alignment search tool for the identification of distal and proximal gene regulatory regions and their conserved transcription factor binding sites.

MOTIVATION: The prediction and annotation of the genomic regions involved in gene expression has been largely explored. Most of the energy has been devoted to the development of approaches that detect transcription start sites, leaving the identification of regulatory regions and their functional transcription factor binding sites (TFBSs) largely unexplored and with important quantitative and qualitative methodological gaps. RESULTS: We have developed ReLA (for REgulatory region Local Alignment tool), a unique tool optimized with the Smith-Waterman algorithm that allows local searches of conserved TFBS clusters and the detection of regulatory regions proximal to genes and enhancer regions. ReLA's performance shows specificities of 81 and 50% when tested on experimentally validated proximal regulatory regions and enhancers, respectively.

Exhaustive Variant Interaction Analysis using Multifactor Dimensionality Reduction.

One of the main goals of human genetics is to understand the connections between genomic variation and the predisposition to develop a complex disorder. These disease-variant associations are usually studied in a single independent manner, disregarding the possible effect derived from the interaction between genomic variants. In particular, in a background of complex diseases, these interactions can be directly linked to the disorder and may play an important role in disease development. Although their study has been suggested to help to complete the understanding of the genetic bases of complex diseases, this still represents a big challenge due to large computing demands. Here, we have taken advantage of High-Performance Computing technologies to tackle this problem using a combination of machine learning methods and statistical approaches. As a result, we have created a containerized framework that uses Multifactor Dimensionality Reduction to detect pairs of variants associated with Type 2 Diabetes (T2D). This methodology has been tested in the Northwestern University NUgene project cohort using a dataset of 1,883,192 variant pairs with a certain degree of association with T2D. Out of the pairs studied, we have identified 104 significant pairs, two of which exhibit a potential functional relationship with T2D.

Mutational topography reflects clinical neuroblastoma heterogeneity.

Neuroblastoma is a pediatric solid tumor characterized by strong clinical heterogeneity. Although clinical risk-defining genomic alterations exist in neuroblastomas, the mutational processes involved in their generation remain largely unclear. By examining the topography and mutational signatures derived from all variant classes, we identified co-occurring mutational footprints, which we termed mutational scenarios. We demonstrate that clinical neuroblastoma heterogeneity is associated with differences in the mutational processes driving these scenarios, linking risk-defining pathognomonic variants to distinct molecular processes. Whereas high-risk MYCN-amplified neuroblastomas were characterized by signs of replication slippage and stress, homologous recombination-associated signatures defined high-risk non-MYCN-amplified patients. Non-high-risk neuroblastomas were marked by footprints of chromosome mis-segregation and TOP1 mutational activity. Furthermore, analysis of subclonal mutations uncovered differential activity of these processes through neuroblastoma evolution. Thus, clinical heterogeneity of neuroblastoma patients can be linked to differences in the mutational processes that are active in their tumors.

A transposase-derived gene required for human brain development.

DNA transposable elements and transposase-derived genes are present in most living organisms, including vertebrates, but their function is largely unknown. PiggyBac Transposable Element Derived 5 (PGBD5) is an evolutionarily conserved vertebrate DNA transposase-derived gene with retained nuclease activity in cells. Vertebrate brain development is known to be associated with prominent neuronal cell death and DNA breaks, but their causes and functions are not well understood. Here, we show that PGBD5 contributes to normal brain development in mice and humans, where its deficiency causes disorder of intellectual disability, movement and seizures. In mice, Pgbd5 is required for the developmental induction of post-mitotic DNA breaks and recurrent somatic genome rearrangements in neurons. Together, these studies nominate PGBD5 as the long-hypothesized neuronal DNA nuclease required for brain function in mammals.

Impact of methylation on the physical properties of DNA.

There is increasing evidence for the presence of an alternative code imprinted in the genome that might contribute to gene expression regulation through an indirect reading mechanism. In mammals, components of this coarse-grained regulatory mechanism include chromatin structure and epigenetic signatures, where d(CpG) nucleotide steps are key players. We report a comprehensive experimental and theoretical study of d(CpG) steps that provides a detailed description of their physical characteristics and the impact of cytosine methylation on these properties. We observed that methylation changes the physical properties of d(CpG) steps, having a dramatic effect on enriched CpG segments, such as CpG islands. We demonstrate that methylation reduces the affinity of DNA to assemble into nucleosomes, and can affect nucleosome positioning around transcription start sites. Overall, our results suggest a mechanism by which the basic physical properties of the DNA fiber can explain parts of the cellular epigenetic regulatory mechanisms.

Clustering and graph mining techniques for classification of complex structural variations in cancer genomes.

For many years, a major question in cancer genomics has been the identification of those variations that can have a functional role in cancer, and distinguish from the majority of genomic changes that have no functional consequences. This is particularly challenging when considering complex chromosomal rearrangements, often composed of multiple DNA breaks, resulting in difficulties in classifying and interpreting them functionally. Despite recent efforts towards classifying structural variants (SVs), more robust statistical frames are needed to better classify these variants and isolate those that derive from specific molecular mechanisms. We present a new statistical approach to analyze SVs patterns from 2392 tumor samples from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium and identify significant recurrence, which can inform relevant mechanisms involved in the biology of tumors. The method is based on recursive KDE clustering of 152,926 SVs, randomization methods, graph mining techniques and statistical measures. The proposed methodology was able not only to identify complex patterns across different cancer types but also to prove them as not random occurrences. Furthermore, a new class of pattern that was not previously described has been identified.

Sequence diversity of the uniparentally transmitted portions of the genome in the resident population of Catalonia.

Genomic reference databases of residing populations are available in different countries and regions. Since they represent the whole genetic diversity of a geographical region, they have wide applications, from biomedical studies to forensic identifications. Uniparentally transmitted portions of the genome specifically are highly suitable for kinship analyses, mixed DNA cases and geographical ancestry inferences. We have sampled 808 individuals currently residing in Catalonia within the GCAT cohort, from which we have generated 808 high-quality whole mitochondrial DNA (mtDNA) genomes and 399 sequences of the male-specific part of the Y chromosome (MSY). We observe higher genetic diversity than in classical population genetics datasets. We test the robustness of whole sequences for unequivocal identifications, and we found that they have higher resolution than mitochondrial control region and Y chromosome short tandem repeats (Y-STRs), and that most of the variants they present are at low frequencies, increasing the discrimination capacity between individuals. These results confirm the forensic applicability of whole uniparental sequences and provide one of the largest high-quality reference datasets ever published.