参考样本的表观基因组、转录物组和蛋白质组特征描述

Chirag Nepal, Wanqiu Chen, Zhong Chen, John A Wroble, Ling Xie, Wenjing Liao, Chunlin Xiao, Andrew Farmer, Malcolm Moos, Wendell Jones, Xian Chen, Charles Wang
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引用次数: 0

摘要

各种新开发的新一代测序技术正迅速进入研究和临床应用领域,其准确性和跨实验室的可重复性至关重要,因此非常需要参考标准。我们之前在 SEQC-2 框架下利用乳腺癌细胞系和配对的 B 细胞系进行的多中心研究已经产生了大量不同的基因组数据,包括全基因组测序(Illumina、PacBio、Nanopore)、HiC 和 scRNA-seq,并对体细胞突变、单核苷酸变异(SNV)和结构变异(SV)进行了详细分析。然而,目前仍缺乏包括表观基因组和蛋白质组数据在内的特征良好的参考材料。在这里,我们进一步进行了 ATAC-seq、Methyl-seq、RNA-seq 和蛋白质组分析,并提供了表观基因组图谱的综合目录,该目录与两个细胞系的转录组和蛋白质组重叠。我们发现了 7,700 种肽同工酶,其中大多数(95%)基因只有一种肽同工酶。在两种细胞系中,与 CGI 重叠的转录本的蛋白质表达量远高于非 CGI 转录本的蛋白质表达量。我们进一步证明了某些 SNV 被整合到突变肽中的证据。我们观察到,开放染色质区域的甲基化程度较低,这在很大程度上受 CG 密度的调控。CG贫乏区域具有更高的抑制性表观遗传调控(更高的DNA甲基化)和更少的开放染色质,从而形成了细胞系特有的甲基化和基因表达模式。我们的研究提供了由两个细胞系组成的定义明确的参考材料,这些细胞系具有基因组、表观基因组、转录组、scRNA-seq 和蛋白质组特征,不仅可以作为验证和基准各种 omics 检测方法的标准,还可以作为生物信息学方法的标准。它将成为研究界和临床界的宝贵资源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Epigenomic, transcriptomic and proteomic characterizations of reference samples
A variety of newly developed next-generation sequencing technologies are making their way rapidly into the research and clinical applications, for which accuracy and cross-lab reproducibility are critical, and reference standards are much needed. Our previous multicenter studies under the SEQC-2 umbrella using a breast cancer cell line with paired B-cell line have produced a large amount of different genomic data including whole genome sequencing (Illumina, PacBio, Nanopore), HiC, and scRNA-seq with detailed analyses on somatic mutations, single-nucleotide variations (SNVs), and structural variations (SVs). However, there is still a lack of well-characterized reference materials which include epigenomic and proteomic data. Here we further performed ATAC-seq, Methyl-seq, RNA-seq, and proteomic analyses and provided a comprehensive catalog of the epigenomic landscape, which overlapped with the transcriptomes and proteomes for the two cell lines. We identified >7,700 peptide isoforms, where the majority (95%) of the genes had a single peptide isoform. Protein expression of the transcripts overlapping CGIs were much higher than the protein expression of the non-CGI transcripts in both cell lines. We further demonstrated the evidence that certain SNVs were incorporated into mutated peptides. We observed that open chromatin regions had low methylation which were largely regulated by CG density, where CG-rich regions had more accessible chromatin, low methylation, and higher gene and protein expression. The CG-poor regions had higher repressive epigenetic regulations (higher DNA methylation) and less open chromatin, resulting in a cell line specific methylation and gene expression patterns. Our studies provide well-defined reference materials consisting of two cell lines with genomic, epigenomic, transcriptomic, scRNA-seq and proteomic characterizations which can serve as standards for validating and benchmarking not only on various omics assays, but also on bioinformatics methods. It will be a valuable resource for both research and clinical communities.
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