小柯机器人

PhyloVelo使用单调表达基因增强转录组速度场映射，这一成果由中国科学院深圳先进技术研究院Zheng Hu和深圳大学Da Zhou团队合作经过不懈努力而取得。该项研究成果发表在2023年7月31日出版的《自然-生物技术》上。

研究人员研发了PhyloVelo，这是一种计算框架，通过使用单调表达基因（MEG）或增加或减少但不循环基因的表达模式来估算个体发育时的转录组动力学。通过将scRNA-seq数据与谱系信息整合，PhyloVelo识别MEG并重建转录组速度场。研究人员使用模拟数据和秀丽隐杆线虫的真实数据验证了PhyloVelo，成功重塑了线性、分叉和收敛分化。

将PhyloVelo应用于CRISPR-Cas9编辑、慢病毒条形码或免疫库分析生成的七个谱系追踪scRNA-seq数据集，研究证明了其在推断复杂谱系轨迹方面的高精度和稳定性，同时优于RNA速度。此外，研究发现跨组织和生物体的MEG在基因翻译和核糖体生物发生方面具有相似的功能。

研究人员表示，单细胞RNA测序（scRNA-seq）是研究细胞分化的有利工具，但准确跟踪细胞命运转变具有挑战性，尤其是在疾病个体中。

附：英文原文

Title: PhyloVelo enhances transcriptomic velocity field mapping using monotonically expressed genes

Author: Wang, Kun, Hou, Liangzhen, Wang, Xin, Zhai, Xiangwei, Lu, Zhaolian, Zi, Zhike, Zhai, Weiwei, He, Xionglei, Curtis, Christina, Zhou, Da, Hu, Zheng

Issue&Volume: 2023-07-31

Abstract: Single-cell RNA sequencing (scRNA-seq) is a powerful approach for studying cellular differentiation, but accurately tracking cell fate transitions can be challenging, especially in disease conditions. Here we introduce PhyloVelo, a computational framework that estimates the velocity of transcriptomic dynamics by using monotonically expressed genes (MEGs) or genes with expression patterns that either increase or decrease, but do not cycle, through phylogenetic time. Through integration of scRNA-seq data with lineage information, PhyloVelo identifies MEGs and reconstructs a transcriptomic velocity field. We validate PhyloVelo using simulated data and Caenorhabditis elegans ground truth data, successfully recovering linear, bifurcated and convergent differentiations. Applying PhyloVelo to seven lineage-traced scRNA-seq datasets, generated using CRISPR–Cas9 editing, lentiviral barcoding or immune repertoire profiling, demonstrates its high accuracy and robustness in inferring complex lineage trajectories while outperforming RNA velocity. Additionally, we discovered that MEGs across tissues and organisms share similar functions in translation and ribosome biogenesis.

DOI: 10.1038/s41587-023-01887-5

Source: https://www.nature.com/articles/s41587-023-01887-5

Nature Biotechnology：《自然—生物技术》，创刊于1996年。隶属于施普林格·自然出版集团，最新IF：68.164
官方网址：https://www.nature.com/nbt/
投稿链接：https://mts-nbt.nature.com/cgi-bin/main.plex