sc-SPLASH 在条码单细胞测序中提供超高效的无参考发现
Roozbeh Dehghannasiri1, Marek Kokot2, Alexander L Starr3
1Department of Biomedical Data Science, Stanford University, Stanford, 94305, USA.
bioRxiv : the preprint server for biology
|January 7, 2025
概括
sc-SPLASH是一个新的生物信息学管道,用于分析单细胞RNA测序数据. 它发现了新的转录组多样性,包括基因表达和突变,而不依赖参考基因组.
科学领域:
- 基因组学就是基因组学.
- 生物信息学是一种生物信息学.
- 分子生物学分子生物学
背景情况:
- 标准的单细胞RNA测序 (scRNA-seq) 方法往往错过了转录组的多样性,因为它们依赖基因模型和参考基因组.
- 诸如替代拼接和V(D) J重组等机制产生了目前分析无法捕捉的显著的转录基因变异.
- 不完美的参考基因组可能导致相关生物序列的遗漏.
研究的目的:
- 引入sc-SPLASH,这是一个有效的管道,用于在条形码的单细胞和空间转录组学数据中进行无引用的转录组学发现.
- 提供BKC,一个优化的模块用于预处理和k-mer计数条码数据,作为一个独立的工具.
- 为了证明sc-SPLASH在发现各种物种中各种生物现象中的实用性.
主要方法:
- 扩展SPLASH框架用于统计第一,无参考分析.
- 对于10x Chromium (scRNA-seq) 和10x Visium (空间转录学) 数据的应用.
- 在条码数据集中开发BKC模块用于预处理和k-mer计数.
主要成果:
- 在人类数据中,sc-SPLASH成功识别了V(D) J重组和细胞类型特定的替代拼接.
- 在空间数据集中检测到衣动物 (Ciona) 的转接和序列变异,包括瘤特异性体质突变.
- 在海绵 (Spongilla) 和衣 (Ciona) 的免疫类型细胞中发现了新的分泌重复蛋白,包括没有参考组件的基因.
结论:
- sc-SPLASH为探索单细胞和空间数据中的转录组多样性提供了一个强大的,无引用的替代方案.
- 该管道有效地发现了众所周知的生物过程和跨多种生物体的新奇序列.
- sc-SPLASH增强了转录基因分析的范围,特别是对于非模型生物和复杂的生物变异.
相关概念视频
03:21RNA-seq
9.8K
RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
9.8K
03:00Next-generation Sequencing
87.3K
The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features....
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features....
87.3K