<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Perturb-seq | Jingshu Wang</title><link>https://jingshuw.org/tag/perturb-seq/</link><atom:link href="https://jingshuw.org/tag/perturb-seq/index.xml" rel="self" type="application/rss+xml"/><description>Perturb-seq</description><generator>Wowchemy (https://wowchemy.com)</generator><language>en-us</language><copyright>'@copy;' Jingshu Wang 2026</copyright><lastBuildDate>Sun, 11 Oct 2026 00:00:00 +0000</lastBuildDate><image><url>https://jingshuw.org/images/icon_hua2ec155b4296a9c9791d015323e16eb5_11927_512x512_fill_lanczos_center_2.png</url><title>Perturb-seq</title><link>https://jingshuw.org/tag/perturb-seq/</link></image><item><title>Preprint: Transcriptional Perturbation Effects Remain Structured Beyond the Leading Global Trend</title><link>https://jingshuw.org/post/perturbation-structure-2026/</link><pubDate>Sun, 11 Oct 2026 00:00:00 +0000</pubDate><guid>https://jingshuw.org/post/perturbation-structure-2026/</guid><description>&lt;p>We have posted a new preprint on bioRxiv, &amp;ldquo;Transcriptional perturbation effects remain structured beyond the leading global trend&amp;rdquo;, which investigates the structure of transcriptional responses to genetic perturbations across large-scale single-cell CRISPRi screens and its implications for predicting unseen perturbation effects.&lt;/p>
&lt;p>👉 medRxiv preprint: &lt;a href="https://www.biorxiv.org/content/10.64898/2026.10.05.756839v1">https://www.biorxiv.org/content/10.64898/2026.10.05.756839v1&lt;/a>&lt;/p>
&lt;p>Key highlights of our paper include:&lt;/p>
&lt;ul>
&lt;li>Across 12 large-scale CRISPRi screens covering a broad range of genetic perturbations, we identify a leading global transcriptional response shared by many perturbations, with its magnitude associated with gene essentiality.&lt;/li>
&lt;li>Beyond this leading global trend, substantial functional structure remains. Perturbation effects are correlated across datasets, and stronger residual effects tend to involve functionally related genes, including members of the same protein complexes and transcription factor regulatory networks.&lt;/li>
&lt;li>We identify a shared hierarchy of responsive genes, with some genes consistently more responsive to perturbations than others. This pattern persists even after removing the leading global trend.&lt;/li>
&lt;li>We find that simple methods leveraging shared transcriptional structures can perform competitively with more complex prediction models, while capturing perturbation-specific effects remains challenging.&lt;/li>
&lt;/ul>
&lt;p>Our findings provide insights into gene regulation and the opportunities and challenges of predicting cellular responses to genetic perturbations.&lt;/p></description></item></channel></rss>