对来自 "1000 基因组计划 "的样本进行高覆盖率纳米孔测序,建立人类遗传变异综合目录。

IF 6.2 2区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY Genome research Pub Date : 2024-11-20 DOI:10.1101/gr.279273.124
Jonas A Gustafson, Sophia B Gibson, Nikhita Damaraju, Miranda P G Zalusky, Kendra Hoekzema, David Twesigomwe, Lei Yang, Anthony A Snead, Phillip A Richmond, Wouter De Coster, Nathan D Olson, Andrea Guarracino, Qiuhui Li, Angela L Miller, Joy Goffena, Zachary B Anderson, Sophie H R Storz, Sydney A Ward, Maisha Sinha, Claudia Gonzaga-Jauregui, Wayne E Clarke, Anna O Basile, André Corvelo, Catherine Reeves, Adrienne Helland, Rajeeva Lochan Musunuri, Mahler Revsine, Karynne E Patterson, Cate R Paschal, Christina Zakarian, Sara Goodwin, Tanner D Jensen, Esther Robb, William Richard McCombie, Fritz J Sedlazeck, Justin M Zook, Stephen B Montgomery, Erik Garrison, Mikhail Kolmogorov, Michael C Schatz, Richard N McLaughlin, Harriet Dashnow, Michael C Zody, Matt Loose, Miten Jain, Evan E Eichler, Danny E Miller
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引用次数: 0

摘要

只有不到一半的孟德尔或单基因疑似病例在经过全面的临床基因检测后获得了精确的分子诊断。数据质量和成本的提高提高了人们对使用长读程测序(LRS)简化临床基因组检测的兴趣,但由于缺乏用于变异筛选和优先排序的对照数据集,LRS 数据的三级分析具有挑战性。为了解决这个问题,1000 基因组计划 ONT 测序联盟的目标是从 1000 基因组计划中至少 800 个样本中生成 LRS 数据。我们的目标是利用 LRS 来识别更广泛的变异,从而提高我们对人类正常变异模式的理解。在这里,我们展示了对代表所有 5 个超级种群和 19 个亚种群的前 100 个样本的分析数据。这些样本的平均测序覆盖深度为 37 倍,测序读数 N50 为 54 kbp,在识别同源多聚物区域之外的单核苷酸和滞后变异方面与之前的研究具有很高的一致性。通过使用多个结构变异(SV)调用器,我们在每个基因组中平均鉴定出 24,543 个高置信度 SV,其中包括可能破坏基因功能的共享和私有 SV,以及使用短读数无法检测到的疾病相关重复序列中的致病性扩增。对甲基化特征的评估揭示了已知印迹位点的预期模式、具有偏斜 X 失活模式的样本以及新的差异甲基化区域。所有原始测序数据、处理过的数据和统计摘要都是公开的,为临床遗传学界发现致病性 SV 提供了宝贵的资源。
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High-coverage nanopore sequencing of samples from the 1000 Genomes Project to build a comprehensive catalog of human genetic variation.

Fewer than half of individuals with a suspected Mendelian or monogenic condition receive a precise molecular diagnosis after comprehensive clinical genetic testing. Improvements in data quality and costs have heightened interest in using long-read sequencing (LRS) to streamline clinical genomic testing, but the absence of control data sets for variant filtering and prioritization has made tertiary analysis of LRS data challenging. To address this, the 1000 Genomes Project (1KGP) Oxford Nanopore Technologies Sequencing Consortium aims to generate LRS data from at least 800 of the 1KGP samples. Our goal is to use LRS to identify a broader spectrum of variation so we may improve our understanding of normal patterns of human variation. Here, we present data from analysis of the first 100 samples, representing all 5 superpopulations and 19 subpopulations. These samples, sequenced to an average depth of coverage of 37× and sequence read N50 of 54 kbp, have high concordance with previous studies for identifying single nucleotide and indel variants outside of homopolymer regions. Using multiple structural variant (SV) callers, we identify an average of 24,543 high-confidence SVs per genome, including shared and private SVs likely to disrupt gene function as well as pathogenic expansions within disease-associated repeats that were not detected using short reads. Evaluation of methylation signatures revealed expected patterns at known imprinted loci, samples with skewed X-inactivation patterns, and novel differentially methylated regions. All raw sequencing data, processed data, and summary statistics are publicly available, providing a valuable resource for the clinical genetics community to discover pathogenic SVs.

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来源期刊
Genome research
Genome research 生物-生化与分子生物学
CiteScore
12.40
自引率
1.40%
发文量
140
审稿时长
6 months
期刊介绍: Launched in 1995, Genome Research is an international, continuously published, peer-reviewed journal that focuses on research that provides novel insights into the genome biology of all organisms, including advances in genomic medicine. Among the topics considered by the journal are genome structure and function, comparative genomics, molecular evolution, genome-scale quantitative and population genetics, proteomics, epigenomics, and systems biology. The journal also features exciting gene discoveries and reports of cutting-edge computational biology and high-throughput methodologies. New data in these areas are published as research papers, or methods and resource reports that provide novel information on technologies or tools that will be of interest to a broad readership. Complete data sets are presented electronically on the journal''s web site where appropriate. The journal also provides Reviews, Perspectives, and Insight/Outlook articles, which present commentary on the latest advances published both here and elsewhere, placing such progress in its broader biological context.
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