Automated chromatin profiling with spa-ChIP seq uncovers the impacts of condition variations.

Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is a well-established method for studying the genomic localization of DNA-associated proteins. Yet, while useful, most ChIP-seq protocols include multiple manual steps that can introduce inconsistency and make it burdensome to analyze large sample sets, limiting the inclusion of appropriate replicates and other controls. Although some of these challenges were addressed by incorporation of liquid handling platforms, most of those previous efforts have automated only a subset of the ChIP-seq steps. Further, using automation for efficiently mapping non-histone proteins, such as chromatin regulators, has been challenging. We recently developed a single-pot ChIP-seq protocol. Here we established a liquid handler operation for this protocol and created an end-to-end fully automated version that is scalable from 8 to 96 ChIP-seq reactions. Our single-pot automated (spa-ChIP-seq) protocol requires about 3 days from cross-linked cells to library, and the costs to produce indexed libraries is approximately $70 per sample. We first benchmarked spa-ChIP-seq against manual ChIP-seq that was performed in parallel, showing a nearly indistinguishable signal-to-noise ratio between the two workflows. Next, we used spa-ChIP-seq to systematically evaluate multiple parameters including shearing and crosslinking conditions, buffer compositions, and antibody to cell-number ratios. Our method allowed us to identify optimal conditions for double crosslinked chromatin as well as easily and robustly conduct titrations and screening of different antibodies and reagents, eliminating many laborious and costly steps. We show, for the first time to our knowledge, that the effect of the ratio of antibody to cell-number is most pronounced in detecting weak genomic localization signals. In particular, while strong signal seems to be unimpacted by low antibody to cell-number ratio, weaker signals are sensitive to this ratio. We note the importance of maintaining a consistent antibody to cell-number ratio, especially when conducting comparative studies, e.g., between treatments such as small molecules, or individuals such as for chromatin-QTL mapping. Our automated ChIP-seq protocol is publicly available, including specific deck setups, software files and parameters. Lastly, we envision that our robust, cost-efficient protocol can advance research via multiple fronts, e.g., by (i) allowing the scaling up the number of replicates and conditions tested, (ii) improving quantification precision when using spike-in normalization in ChIP-seq experiments, (iii) enabling core facilities to provide high-throughput ChIP-seq as a service and (iv) being incorporated into antibody evaluation procedures, compound screening, population genomics and diagnostic frameworks.