Regulatory landscape enrichment analysis (RLEA): a computational toolkit for non-coding variant enrichment and cell type prioritization.

BACKGROUND: As genomic studies continue to implicate non-coding sequences in disease, testing the roles of these variants requires insights into the cell type(s) in which they are likely to be mediating their effects. Prior methods for associating non-coding variants with cell types have involved approaches using linkage disequilibrium or ontological associations, incurring significant processing requirements. GaiaAssociation is a freely available, open-source software that enables thousands of genomic loci implicated in a phenotype to be tested for enrichment at regulatory loci of multiple cell types in minutes, permitting insights into the cell type(s) mediating the studied phenotype. RESULTS: In this work, we present Regulatory Landscape Enrichment Analysis (RLEA) by GaiaAssociation and demonstrate its capability to test the enrichment of 12,133 variants across the cis-regulatory regions of 44 cell types. This analysis was completed in 134.0 ± 2.3 s, highlighting the efficient processing provided by GaiaAssociation. The intuitive interface requires only four inputs, offers a collection of customizable functions, and visualizes variant enrichment in cell-type regulatory regions through a heatmap matrix. GaiaAssociation is available on PyPi for download as a command line tool or Python package and the source code can also be installed from GitHub at https://github.com/GreallyLab/gaiaAssociation . CONCLUSIONS: GaiaAssociation is a novel package that provides an intuitive and efficient resource to understand the enrichment of non-coding variants across the cis-regulatory regions of different cells, empowering studies seeking to identify disease-mediating cell types.

Genome integrity as a potential index of longevity in Ashkenazi Centenarian's families.

The aging process, or senescence, is characterized by age-specific decline in physical and physiological function, and increased frailty and genomic changes, including mutation accumulation. However, the mechanisms through which changes in genomic architecture influence human longevity have remained obscure. Copy number variants (CNVs), an abundant class of genomic variants, offer unique opportunities for understanding age-related genomic changes. Here we report the spectrum of CNVs in a cohort of 670 Ashkenazi Jewish centenarians, their progeny, and unrelated controls. The average ages of these groups were 97.4 ± 2.8, 69.2 ± 9.2, and 66.5 ± 7.0 respectively. For the first time, we compared different size classes of CNVs, from 1 kB to 100 MB in size. Using a high-resolution custom Affymetrix array, targeting 44,639 genomic regions, we identified a total of 12,166, 22,188, and 10,285 CNVs in centenarians, their progeny, and control groups, respectively. Interestingly, the offspring group showed the highest number of unique CNVs, followed by control and centenarians. While both gains and losses were found in all three groups, centenarians showed a significantly higher average number of both total gains and losses relative to their controls (p < 0.0327, 0.0182, respectively). Moreover, centenarians showed a lower total length of genomic material lost, suggesting that they may maintain superior genomic integrity over time. We also observe a significance fold increase of CNVs among the offspring, implying greater genomic integrity and a putative mechanism for longevity preservation. Genomic regions that experienced loss or gains appear to be distributed across many sites in the genome and contain genes involved in DNA transcription, cellular transport, developmental pathways, and metabolic functions. Our findings suggest that the exceptional longevity observed in centenarians may be attributed to the prolonged maintenance of functionally important genes. These genes are intrinsic to specific genomic regions as well as to the overall integrity of the genomic architecture. Additionally, a strong association between longer CNVs and differential gene expression observed in this study supports the notion that genomic integrity could positively influence longevity.