A personalized multi-platform assessment of somatic mosaicism in the human frontal cortex DOI Creative Commons
Weichen Zhou, Camille Mumm, Yanming Gan

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Дек. 21, 2024

Somatic mutations in individual cells lead to genomic mosaicism, contributing the intricate regulatory landscape of genetic disorders and cancers. To evaluate refine detection somatic mosaicism across different technologies with personalized donor-specific assembly (DSA), we obtained tissue from dorsolateral prefrontal cortex (DLPFC) a post-mortem neurotypical 31-year-old individual. We sequenced bulk DLPFC using Oxford Nanopore Technologies (~60X), NovaSeq (~30X), linked-read sequencing (~28X). Additionally, applied Cas9 capture methodology coupled long-read (TEnCATS), targeting active transposable elements. also isolated amplified DNA flow-sorted single neurons MALBAC, 115 these MALBAC libraries on 94 NovaSeq. constructed haplotype-resolved total length 5.77 Gb phase block 2.67 Mb (N50) facilitate cross-platform analysis variations. observed an increase phasing rate 11.6% 38.0% between short-read technologies. By generating catalog phased germline SNVs, CNVs, TEs assembled genome, standard approaches recall variants achieved aggregated rates 97.3% 99.4% based data, setting upper bound for limits. Moreover, utilizing haplotype-based DSA, remarkable reduction false positive calls tissue, ranging 14.9% 72.4%. developed pipelines leveraging DSA information enhance large variant calling cells. examining variation long-reads neurons, identified 468 candidate heterozygous deletions (1.5Mb - 20Mb), 137 which intersected single-cell data. 61 putative (60 Alus, one LINE-1) Collectively, our spans calling, providing comprehensive ab initio ad finem approach resource real human tissue.

Язык: Английский

DeepSomatic: Accurate somatic small variant discovery for multiple sequencing technologies DOI Creative Commons
J.H. Park, Daniel E. Cook, Pi-Chuan Chang

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Авг. 19, 2024

Somatic variant detection is an integral part of cancer genomics analysis. While most methods have focused on short-read sequencing, long-read technologies now offer potential advantages in terms repeat mapping and phasing. We present DeepSomatic, a deep learning method for detecting somatic SNVs insertions deletions (indels) from both data, with modes whole-genome exome able to run tumor-normal, tumor-only, FFPE-prepared samples. To help address the dearth publicly available training benchmarking data detection, we generated make openly dataset five matched tumor-normal cell line pairs sequenced Illumina, PacBio HiFi, Oxford Nanopore Technologies, along benchmark sets. Across samples (short-read long-read), DeepSomatic consistently outperforms existing callers, particularly indels.

Язык: Английский

Процитировано

3
Long-read sequencing of hundreds of diverse brains provides insight into the impact of structural variation on gene expression and DNA methylation DOI Creative Commons

Kimberley J. Billingsley,

Melissa Meredith, Kensuke Daida

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Дек. 18, 2024

Structural variants (SVs) drive gene expression in the human brain and are causative of many neurological conditions. However, most existing genetic studies have been based on short-read sequencing methods, which capture fewer than half SVs present any one individual. Long-read (LRS) enhances our ability to detect disease-associated functionally relevant structural (SVs); however, its application large-scale genomic has limited by challenges sample preparation high costs. Here, we leverage a new scalable wet-lab protocol computational pipeline for whole-genome Oxford Nanopore Technologies apply it neurologically normal control samples from North American Brain Expression Consortium (NABEC) (European ancestry) Human Collection Core (HBCC) (African or African admixed cohorts. Through this work, publicly available long-read resource 351 (median N50: 27 Kbp at an average depth ~40x genome coverage). We discover approximately 234,905 produce locally phased assemblies that cover 95% all protein-coding genes GRCh38. Utilizing matched datasets these samples, quantitative trait locus (QTL) analyses identify impact post-mortem frontal cortex tissue. Further, determine haplotype-specific methylation signatures millions CpGs and, with data, cis-acting SVs. In summary, results highlight LRS can complex regulatory mechanisms were inaccessible using previous approaches. believe provides critical step toward understanding biological effects variation brain.

Язык: Английский

Процитировано

3
Detecting Somatic Mutations Without Matched Normal Samples Using Long Reads DOI Creative Commons
Jared T. Simpson

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Фев. 29, 2024

DNA sequencing of tumours to identify somatic mutations has become a critical tool guide the type treatment given cancer patients. The gold standard for mutation calling is comparing data from tumour matched normal sample avoid mis-classifying inherited SNPs as mutations. This procedure works extremely well, but in certain situations only available. While approaches have been developed find without normal, they limited accuracy or require specific types input (e.g. ultra-deep sequencing). Here we explore application single molecule long read samples. We develop simple theoretical framework show how haplotype phasing an important source information determining whether variant mutation. then use simulations assess range experimental parameters (tumour purity, depth) where this approach effective. These ideas are into prototype caller, smrest, and its demonstrated on two highly mutated cell lines. Finally, argue that potential measure clinically biomarkers based genome-wide distribution mutations: burden signatures.

Язык: Английский

Процитировано

0
A personalized multi-platform assessment of somatic mosaicism in the human frontal cortex DOI Creative Commons
Weichen Zhou, Camille Mumm, Yanming Gan

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Дек. 21, 2024

Somatic mutations in individual cells lead to genomic mosaicism, contributing the intricate regulatory landscape of genetic disorders and cancers. To evaluate refine detection somatic mosaicism across different technologies with personalized donor-specific assembly (DSA), we obtained tissue from dorsolateral prefrontal cortex (DLPFC) a post-mortem neurotypical 31-year-old individual. We sequenced bulk DLPFC using Oxford Nanopore Technologies (~60X), NovaSeq (~30X), linked-read sequencing (~28X). Additionally, applied Cas9 capture methodology coupled long-read (TEnCATS), targeting active transposable elements. also isolated amplified DNA flow-sorted single neurons MALBAC, 115 these MALBAC libraries on 94 NovaSeq. constructed haplotype-resolved total length 5.77 Gb phase block 2.67 Mb (N50) facilitate cross-platform analysis variations. observed an increase phasing rate 11.6% 38.0% between short-read technologies. By generating catalog phased germline SNVs, CNVs, TEs assembled genome, standard approaches recall variants achieved aggregated rates 97.3% 99.4% based data, setting upper bound for limits. Moreover, utilizing haplotype-based DSA, remarkable reduction false positive calls tissue, ranging 14.9% 72.4%. developed pipelines leveraging DSA information enhance large variant calling cells. examining variation long-reads neurons, identified 468 candidate heterozygous deletions (1.5Mb - 20Mb), 137 which intersected single-cell data. 61 putative (60 Alus, one LINE-1) Collectively, our spans calling, providing comprehensive ab initio ad finem approach resource real human tissue.

Язык: Английский

Процитировано

0