Shiyas, S. | bioRxiv Science

bioRxiv2024

A draft Arab pangenome reference

Pangenomes represent a significant shift from relying on a single reference sequence to a robust set of assemblies, Arab populations remain significantly underrepresented; hence, we present the first Arab Pangenome Reference (APR) utilizing 53 individuals of diverse Arab ethnicities. We assembled nuclear and mitochondrial pangenomes using 35.27X high-fidelity long reads, 54.22X ultralong reads and 65.46X Hi-C reads yielded contiguous haplotype-phased de novo assemblies of exceptional quality, with an average N50 of 124.28 Mb. We discovered 111.96 million base pairs of novel euchromatic sequences absent from existing human pangenomes, the T2T-CHM13, GRCh38 reference human genomes, and other public datasets. We identified 8.94 million population-specific small variants and 235,195 structural variants within the Arab pangenome. We detected 883 gene duplications including 15.06% associated with recessive diseases and 1,436 bp of novel mitochondrial pangenome sequence. Our study provides a valuable resource for future genomic medicine initiatives in Arab population and other global populations.

genomics↗

bioRxiv2024

Horizon: CNV interpretation through rapid automated ACMG-aligned pathogenicity analysis

PurposeOur study assesses the Horizon model, a novel CNV classification tool developed in line with American College of Medical Genetics (ACMG) guidelines, to enhance the classification of pathogenicity in CNVs. MethodsHorizon utilizes a ranking-based algorithm, incorporating multiple proprietary databases and variant inheritance models as per ACMG standards. The models effectiveness was verified through Area Under the Curve (AUC) analyses on three datasets comprising 696 pathogenic inherited or de novo variants, as classified by clinical geneticists and several established tools. ResultsHorizon achieved an AUC of 0.97 in the discovery cohort, demonstrating high accuracy in CNV interpretation and proficiency in predicting pathogenicity. We observed an AUC of 0.87 in the de novo variant cohort and an overall AUC of 0.94 across all cohorts, surpassing tools like ClassifyCNV and AnnotSV. It showed particular effectiveness in interpreting duplication CNVs and the highest performance for CNVs sized 3-5 Mb. ConclusionThe Horizon model offers robust and accurate CNV interpretation, outperforming existing tools and aligning closely with clinical evaluations. Its comprehensive approach, integrating a range of genomic features and following ACMG guidelines, makes it a crucial tool in the genomic interpretation landscape, facilitating the rapid and accurate diagnosis of genetic disorders.

genomics↗