@article{Cao01012026,
author = {Cao, Yuwei and Patel, Lauren and Alcoser, Lauren and Mendenhall, Eric and Benner, Christopher and Heinz, Sven and Goren, Alon}, 
title = {Automated chromatin profiling with spa-ChIP-seq uncovers the impacts of condition variations},
volume = {36}, 
number = {1}, 
pages = {129-141}, 
year = {2026}, 
doi = {10.1101/gr.281320.125}, 
abstract ={Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is widely used to study the genomic localization of DNA-associated proteins. However, conventional protocols include multiple manual steps that can introduce inconsistency and limit scalability, thereby restricting the inclusion of appropriate replicates and controls. Although the introduction of liquid handling platforms has improved reproducibility, most existing efforts have automated only a subset of the workflow, and extending automation to efficiently map nonhistone proteins, such as chromatin regulators, remains challenging. Here, we present a fully automated implementation of our previously developed single-pot ChIP-seq protocol, named spa-ChIP-seq, which enables scalable processing of eight to 96 ChIP-seq samples from cross-linked cells to a sequencing-ready library in approximately 3 days with an estimated cost of $70 per sample. Benchmarking spa-ChIP-seq against manual ChIP-seq performed in parallel demonstrates a comparable signal-to-noise ratio between the two workflows. Using spa-ChIP-seq, we systematically evaluate multiple parameters including shearing and cross-linking conditions, buffer compositions, and the ratio of antibody to cell number. We find, for the first time to our knowledge, that weaker genomic localization signals are sensitive to changing the antibody–to–cell-number ratio, whereas the stronger signals remain unaffected. This finding underscores the importance of maintaining consistent antibody–to–cell-number ratio for comparative studies, such as treatment responses or chromatin-QTL mapping. The spa-ChIP-seq protocol is publicly available, including deck setups, operational parameters, and scripts. We envision that this robust, cost-efficient protocol will facilitate high-throughput, reproducible ChIP-seq analyses, supporting large-scale studies of antibody validation, compound screening, population genomics, and diagnostic frameworks.}, 
URL = {http://genome.cshlp.org/content/36/1/129.abstract}, 
eprint = {http://genome.cshlp.org/content/36/1/129.full.pdf+html}, 
journal = {Genome Research} 
}