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Biology subjects

Shiyas, S.

Publications and source records attributed to Shiyas, S..

4 recordsLinked to original sources

Phenotype Dependent Segregation of a Novel EPS8 Variant for Hearing Loss and an HPDL Variant for Neurodevelopmental Disorders in a Complex Consanguineous Family

Consanguinity increases the risk of autosomal recessive disorders and may result in the co-segregation of multiple pathogenic variants within the same family. Although most affected families are explained by a single genetic diagnosis, multilocus pathogenic variation can produce complex and overlapping clinical phenotypes. We investigated a consanguineous Pakistani family with three affected siblings, including dizygotic twins presenting with neurodevelopmental disorder and hearing loss, using detailed clinical evaluation, long-read whole-genome sequencing, bulk transcriptomics, protein profiling, and segregation analysis to determine the underlying molecular diagnoses. One sibling presented with isolated non-syndromic hearing loss, whereas the dizygotic twins exhibited severe neurodevelopmental impairment characterized by global developmental delay, spastic quadriplegic cerebral palsy, microcephaly, and white matter abnormalities. Long-read whole-genome sequencing identified a homozygous start-loss variant in HPDL (c.3G>C) in both twins, consistent with HPDL-related neurodevelopmental disorder with progressive spasticity and brain white matter abnormalities (NEDSWMA). In addition, a novel homozygous nonsense variant in EPS8 (c.1294C>T) was identified in one twin and the sibling with isolated hearing loss, explaining the auditory phenotype. Long-read transcriptomic analysis demonstrated absence of detectable EPS8 transcripts in both individuals homozygous for the nonsense variant, providing transcript-level evidence consistent with a loss-of-function mechanism. Genome-wide comprehensive proteomic profiling (SomaScan) identified distinct protein abundance profiles across family members, with the most pronounced alterations observed in the twins affected by HPDL-related neurodevelopmental disease, particularly the individual harboring pathogenic variants in both EPS8 and HPDL. This study expands the mutational spectrum of EPS8 and highlights the independent segregation of two autosomal recessive disorders within the complex consanguineous family, resulting in distinct and blended phenotypes.

genetics↗

PanScan: A Tool for Tertiary Analysis of Human Pangenome Graphs

The genomic representation of populations across the globe is critical to ensuring a comprehensive and equitable human reference. Constructing a pangenome graph reference for different populations is the best approach to addressing local genomic diversities. Although major initiatives across continents are underway to construct pangenome graph references, the field lacks the necessary toolsets for tertiary analysis to characterize telomere-to-telomere (T2T) assemblies and the complexity of haplotypes. PanScan is a bioinformatics software package developed for human pangenome tertiary analysis. It includes multiple modules designed to detect duplicated gene sets from T2T assemblies, identify novel variants and sequences, as well as detect and visualize complex genomic regions through pangenome graph haplotype loops. We have used multiple pangenomes across different populations to assess the tertiary analysis and their accuracy. The tool is designed to streamline tertiary analysis and is compatible with multiple pangenome graph construction algorithms. PanScan is freely available on GitHub (https://github.com/CATG-Github/panscan), where users can provide human pangenome assemblies or VCF files as inputs for automated analyses through command-line operations on Linux systems. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=151 SRC="FIGDIR/small/651685v1_ufig1.gif" ALT="Figure 1"> View larger version (59K): org.highwire.dtl.DTLVardef@16cc212org.highwire.dtl.DTLVardef@13961d0org.highwire.dtl.DTLVardef@44d194org.highwire.dtl.DTLVardef@1b72aa_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

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↗

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↗