Kumar, K. R. | Search bioRxiv

bioRxiv2025

Adaptively integrated sequencing and assembly of near-complete genomes

Advances in long-read sequencing (LRS) and assembly algorithms have made it possible to create highly complete genome assemblies for humans, animals and plants. However, ongoing development is needed to improve accessibility, affordability, and assembly quality and completeness. Cornetto is a new strategy in which we use programmable selective nanopore sequencing to focus LRS data production onto the unsolved regions of a nascent assembly. This improves assembly quality and streamlines the process, both for humans and non-human vertebrates. Cornetto enables us to generate highly complete diploid human genome assemblies using only nanopore LRS data, surpassing the quality of previous efforts at a fraction of the cost. Cornetto enables genome assembly from challenging sample types like human saliva. Finally, we obtain accurate assemblies for clinically-relevant repetitive loci at the extremes of the genome, demonstrating valid approaches for genetic diagnosis in facioscapulohumeral muscular dystrophy (FSHD) and MUC1-autosomal dominant tubulointerstitial kidney disease (MUC1-ADTKD).

genomics↗

bioRxiv2019

mity: A highly sensitive mitochondrial variant analysis pipeline for whole genome sequencing data

MotivationMitochondrial diseases (MDs) are the most common group of inherited metabolic disorders and are often challenging to diagnose due to extensive genotype-phenotype heterogeneity. MDs are caused by mutations in the nuclear or mitochondrial genome, where pathogenic mitochondrial variants are usually heteroplasmic and typically at much lower allelic fraction in the blood than affected tissues. Both genomes can now be readily analysed using unbiased whole genome sequencing (WGS), but most nuclear variant detection methods fail to detect low heteroplasmy variants in the mitochondrial genome. ResultsWe present mity, a bioinformatics pipeline for detecting and interpreting heteroplasmic SNVs and INDELs in the mitochondrial genome using WGS data. In 2,980 healthy controls, we observed on average 3,166x coverage in the mitochondrial genome using WGS from blood. mity utilises this high depth to detect pathogenic mitochondrial variants, even at low heteroplasmy. mity enables easy interpretation of mitochondrial variants and can be incorporated into existing diagnostic WGS pipelines. This could simplify the diagnostic pathway, avoid invasive tissue biopsies and increase the diagnostic rate for MDs and other conditions caused by impaired mitochondrial function. Availabilitymity is available from https://github.com/KCCG/mityunder an MIT license. Contactclare.puttick@crick.ac.uk, carolyn.sue@sydney.edu.au, MCowley@ccia.org.au

bioinformatics↗