Meet Giovanni Spirito and Borja Gomez Ramos – the two poster prize winners at the recent EMBL – Wellcome Genome Campus Conference: Target Validation Using Genomics and Informatics (8 – 10 Dec 2019).
Identification and prioritization of candidate causal genomic variations from individuals affected by ASD
Authors: Giovanni Spirito (1), Diego Vozzi (2), Martina Servetti (3), Margherita Lerone (3), Maria Teresa Divizia (3), Giulia Rosti (3), Livia Pisciotta (4), Lino Nobili (4), Irene Serio (4), Stefano Gustincich (2), Remo Sanges (1)
Next generation sequencing (NGS) technologies enabled the extensive study of the genomics underlying human diseases. Namely whole exome sequencing (WES) represents a cost-efficient method which can lead to the detection of multiple classes of genomic variants and the discovery of novel disease-associated genes. One of the drawbacks of this approach however, is the large number of genomic variants detected in each analysis. Automated variant prioritization strategies are therefore required. This is particularly important in the case of complex disease such as ASD, whose genetic etiology is still poorly understood. To this aim we built a custom computational framework capable, from raw WES data, to automatically detect four classes of genomic variants (SNPs, indels, copy number variants and short tandem repeat variants) and prioritize them in regards to their relevance to a specific phenotype. We tested this framework on a selection of 29 trios including probands affected by severe and undiagnosed rare phenotypes and a small cohort of 10 trios all featuring healthy parents and one offspring affected by autism spectrum disorder (ASD). We were able to successfully detect rare and de novo high penetrance variants which have been validated and confirmed as causative among the undiagnosed probands. In the specific case of the ASD cohort we could highlight several genes which are not implicated in autism susceptibility, but nevertheless whose connections to genes relevant for ASD could suggest a possible involvement in the phenotype. Furthermore, our approach enabled us to detect several instances characterized by the presence of multiple candidate variants within genes belonging to the same canonical pathway in one proband. Our workflow allows to detect and prioritize multiple classes of genomic variants in order to both highlight rare high penetrance disease-causative mutation, and possibly reconstruct the genomics at the basis of complex ASD phenotypes.
(1) SISSA, Italy, (2) IIT, Italy, (3) Gaslini Institute, Italy, (4) University of Genova, Italy
Omics data integration for the identification of cell-type-specific gene regulatory networks and regulatory variants in Parkinson’s disease
Authors: Borja Gomez Ramos (1,2), Jochen Ohnmacht (1,2), Nikola de Lange (2), Aurélien Ginolhac (1), Aleksandar Rakovic (5), Christine Klein (5), Roland Krause (2) , Marcel H. Schulz (6), Thomas Sauter (1), Rejko Krüger (2,3,4) and Lasse Sinkkonen (1)
Genome-Wide Association Studies (GWAS) have identified many variants associated with different diseases. However, it is still a challenge to make sense of this data as the majority of genetic variants are located in non-coding regions, complicating the understanding of their functionality. In the last few years, it has been found that non-coding genetic variants concentrate in regulatory regions in the genome, which are cell type and cell-stage specific. In this project, we seek to identify functional Parkinson’s disease GWAS non-coding genetic variants that could make carriers more prone to developing PD. To do so, we are using induced pluripotent stem cell (iPSC) technology to differentiate somatic cells into midbrain dopaminergic (mDA) neurons, astrocytes and microglia. Assessing their chromatin accessibility, active chromatin regions and transcriptome, we can identify crucial regulatory regions in the genome, key transcription factors and derive the gene regulatory networks for the three different cell types. Then, we will map the non-coding genetic variants to the different regulatory regions and predict their effect in silico for the subsequent validation in vitro. This innovative approach will also identify novel factors controlling cell fate and cell identity.
(1) Life Sciences Research Unit, University of Luxembourg, Luxembourg, (2) Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Luxembourg, (3) Centre Hospitalier de Luxembourg (CHL), Luxembourg, (4) Luxembourg Institute of Health (LIH), Luxembourg, (5) Institute of Neurogenetics, University of Lübeck, Germany, (6) Institute for Cardiovascular Regeneration, Uniklinikum and Goethe University Frankfurt, Germany
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