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di Iulio, J.

Publications and source records attributed to di Iulio, J..

3 recordsLinked to original sources

Identification of essential regulatory elements in the human genome

The identification of essential regulatory elements is central to the understanding of the consequences of genetic variation. Here we use novel genomic data and machine learning techniques to map essential regulatory elements and to guide functional validation. We train an XGBoost model using 38 functional and structural features, including genome essentiality metrics, 3D genome organization and enhancer reporter STARR-seq data to differentiate between pathogenic and control non-coding genetic variants. We validate the accuracy of prediction by using data from tiling-deletion-based and CRISPR interference screens of activity of cis-regulatory elements. In neurodevelopmental disorders, the model (ncER, non-coding Essential Regulation) maps essential genomic segments within deletions and rearranged topologically associated domains linked to human disease. We show that the approach successfully identifies essential regulatory elements in the human genome.

genomics

Functional characterization of 3D-protein structures informed by human genetic diversity

Sequence variation data of the human proteome can be used to analyze 3-dimensional (3D) protein structures to derive functional insights. We used genetic variant data from nearly 150,000 individuals to analyze 3D positional conservation in 4,390 protein structures using 481,708 missense and 264,257 synonymous variants. Sixty percent of protein structures harbor at least one intolerant 3D site as defined by significant depletion of observed over expected missense variation. We established an Angstrom-scale distribution of annotated pathogenic missense variants and showed that they accumulate in proximity to the most intolerant 3D sites. Structural intolerance data correlated with experimental functional read-outs in vitro. The 3D structural intolerance analysis revealed characteristic features of ligand binding pockets, orthosteric and allosteric sites. The identification of novel functional 3D sites based on human genetic data helps to validate, rank or predict drug target binding sites in vivo.

genomics

The human functional genome defined by genetic diversity

Large scale efforts to sequence whole human genomes provide extensive data on the non-coding portion of the genome. We used variation information from 11,257 human genomes to describe the spectrum of sequence conservation in the population. We established the genome-wide variability for each nucleotide in the context of the surrounding sequence in order to identify departure from expectation at the population level (context-dependent conservation). We characterized the population diversity for functional elements in the genome and identified the coordination of conserved sequences of distal and cis enhancers, chromatin marks, promoters, coding and intronic regions. The most context-dependent conserved regions of the genome are associated with unique functional annotations and a genomic organization that spreads up to one megabase. Importantly, these regions are enriched by over 100-fold of non-coding pathogenic variants. This analysis of human genetic diversity thus provides a detailed view of sequence conservation, functional constraint and genomic organization of the human genome. Specifically, it identifies highly conserved non-coding sequences that are not captured by analysis of interspecies conservation and are greatly enriched in disease variants.

genomics