Somatic CNV Detection by Single-Cell Whole-Genome Sequencing in Postmortem Human Brain.

Methods Mol Biol

Department of Clinical and Movement Neurosciences, Queen Square Institute of Neurology, University College London, London, UK.

Published: November 2022


Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

The evidence for a role of somatic mutations, including copy-number variants (CNVs), in neurodegeneration has increased in the last decade. However, the understanding of the types and origins of these mutations, and their exact contributions to disease onset and progression, is still in its infancy. The use of single-cell (or nuclear) whole-genome sequencing (scWGS) has emerged as a powerful tool to answer these questions. In the present chapter, we provide laboratory and bioinformatic protocols used successfully in our lab to detect megabase-scale CNVs in single cells from multiple system atrophy (MSA) human postmortem brains, using immunolabeling prior to selection of nuclei for whole-genome amplification (WGA). We also present an unpublished comparison of scWGS generated from the same control substantia nigra (SN) sample, using the latest versions of popular WGA chemistries, MDA and PicoPLEX. We have used this protocol to focus on brain cell types most relevant to synucleinopathies (dopaminergic [DA] neurons in Parkinson's disease [PD] and oligodendrocytes in MSA), but it can be applied to any tissue and/or cell type with appropriate markers.

Download full-text PDF

Source
http://dx.doi.org/10.1007/978-1-0716-2655-9_11DOI Listing

Publication Analysis

Top Keywords

whole-genome sequencing
8
somatic cnv
4
cnv detection
4
detection single-cell
4
single-cell whole-genome
4
sequencing postmortem
4
postmortem human
4
human brain
4
brain evidence
4
evidence role
4

Similar Publications

Purpose: To investigate the variants in 18 disease-causing genes associated with nonsyndromic myopia in 83 Chinese individuals diagnosed with early-onset high myopia(eo-HM).

Methods: Variants in 18 candidate genes in 83 probands with eo-HM were distinguished by whole-exome sequencing (WES) and assessed by multistep bioinformatics analysis.

Results: Four likely pathogenic variants were detected in 4 of the 83 probands (4.

View Article and Find Full Text PDF

Fragment dispersity index analysis of cfDNA fragments reveals chromatin accessibility and enables early cancer detection.

Cell Rep Methods

July 2025

Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, P.R. China; Key Laboratory of Smart Farming for Agricultural Animals, Ministry of Agriculture and Rural Affairs, Beijing, P.R. China; College of Informatics, Huazhong Agricult

We introduce a cell-free DNA (cfDNA) fragmentation pattern: the fragment dispersity index (FDI), which integrates information on the distribution of cfDNA fragment ends with the variation in fragment coverage, enabling precise characterization of chromatin accessibility in specific regions. The FDI shows a strong correlation with chromatin accessibility and gene expression, and regions with high FDI are enriched in active regulatory elements. Using whole-genome cfDNA data from five datasets, we developed and validated the FDI-oncology model, which demonstrates robust performance in early cancer diagnosis, subtyping, and prognosis.

View Article and Find Full Text PDF

Aim: To investigate the phenotypic and genomic features of three multidrug-resistant (MDR) clinical mucoid and non-mucoid uropathogenic Escherichia coli (UPEC) strains to understand their antimicrobial resistance, biofilm formation, and virulence in urinary tract infections (UTIs).

Methods And Results: The UPEC strains A5, A10, and A15 were isolated from two UTI patients. Phenotypic assays included colony morphology, antibiotic susceptibility, motility, and biofilm formation.

View Article and Find Full Text PDF

Accurate tumor mutation burden (TMB) quantification is critical for immunotherapy stratification, yet remains challenging due to variability across sequencing platforms, tumor heterogeneity, and variant calling pipelines. Here, we introduce TMBquant, an explainable AI-powered caller designed to optimize TMB estimation through dynamic feature selection, ensemble learning, and automated strategy adaptation. Built upon the H2O AutoML framework, TMBquant integrates variant features, minimizes classification errors, and enhances both accuracy and stability across diverse datasets.

View Article and Find Full Text PDF

CHRFS5, HL_CHRU_S18, S48B, HL_CHRU_S16, S19, HL_CHRU_S79, and HL_CHRU_S111 were isolated from the biofilm of catheter tip of renal failure patients. Whole genome sequencing predicted the presence of multiple antibiotic-resistant gene cassettes.

View Article and Find Full Text PDF