美国斯坦福大学Julia Salzman研究组的研究开发出SPLASH——一个统计的、无参考的基因组算法。这一研究成果发表在2023年12月7日出版的国际学术期刊《细胞》上。

他们引入了一个统一的范例，SPLASH (statistical Primary aLignment Agnostic Sequence Homing)，它直接分析原始测序数据，使用统计检验来检测调节的特征:样本特异性序列变化。SPLASH可以检测多种类型的变化，并且可以有效地大规模运行。

他们发现，SPLASH识别了SARS-CoV-2中复杂的突变模式，在单细胞水平上发现了受调控的RNA同种异构体，检测了适应性免疫受体的巨大序列多样性，并揭示了参考基因组中未记录的非模式生物的生物学——大叶藻(一种受气候变化影响的海洋植物)的地理和季节变化和硅藻关联，以及章鱼的组织特异性转录物。SPLASH是一种统一的基因组分析方法，可以在没有元数据或参考的情况下进行广泛的发现。

据介绍，今天的基因组学工作流程通常需要与参考序列对齐，这限制了发现。

附：英文原文

Title: SPLASH: A statistical, reference-free genomic algorithm unifies biological discovery

Author: Kaitlin Chaung, Tavor Z. Baharav, George Henderson, Ivan N. Zheludev, Peter L. Wang, Julia Salzman

Issue&Volume: 2023/12/07

Abstract: Today’s genomics workflows typically require alignment to a reference sequence, which limits discovery. We introduce a unifying paradigm, SPLASH (Statistically Primary aLignment Agnostic Sequence Homing), which directly analyzes raw sequencing data, using a statistical test to detect a signature of regulation: sample-specific sequence variation. SPLASH detects many types of variation and can be efficiently run at scale. We show that SPLASH identifies complex mutation patterns in SARS-CoV-2, discovers regulated RNA isoforms at the single-cell level, detects the vast sequence diversity of adaptive immune receptors, and uncovers biology in non-model organisms undocumented in their reference genomes: geographic and seasonal variation and diatom association in eelgrass, an oceanic plant impacted by climate change, and tissue-specific transcripts in octopus. SPLASH is a unifying approach to genomic analysis that enables expansive discovery without metadata or references.

DOI: 10.1016/j.cell.2023.10.028

Source: https://www.cell.com/cell/fulltext/S0092-8674(23)01179-0