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SWITCH deficient SUCROSE NONFERMENTING (SWI/SNF) class chromatin remodeling complexes (CRCs) use the energy derived from ATP hydrolysis to facilitate access of proteins to the genomic DNA for transcription, replication, and DNA repair. Uniquely, SWI/SNF CRCs can both slide the histone octamer along the DNA or eject it from the DNA. Given their ability to change the chromatin status quo, SWI/SNF remodelers are critical for cell fate reprogramming with pioneer and other transcription factors, for responses to environmental challenges, and for disease prevention. Recent cryo-electron microscopy and mass spectrometry approaches have uncovered different subtypes of SWI/SNF complexes with unique properties and functions. At the same time, tethering or rapid depletion and inactivation of SWI/SNF have provided novel insight into SWI/SNF requirements for enhancer activity and into balancing chromatin compaction and accessibility in concert with Polycomb complexes. Given their importance, SWI/SNF recruitment to genomic locations by transcription factors and their biochemical activity is tightly controlled. This review focuses on recent advances in our understanding of SWI/SNF CRCs in animals and plants and discusses the multiple nuclear and biological roles of SWI/SNF CRCs and how SWI/SNF activity is altered by complex subunit composition, posttranslational modifications, and the chromatin context to support proper development and response to extrinsic cues. Expected final online publication date for the Annual Review of Plant Biology, Volume 74 is May 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates. 

Abstract Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is widely used to identify factor binding to genomic DNA and chromatin modifications. ChIP-seq data analysis is affected by genomic regions that generate ultra-high artifactual signals. To remove these signals from ChIP-seq data, the Encyclopedia of DNA Elements (ENCODE) project developed comprehensive sets of regions defined by low mappability and ultra-high signals called blacklists for human, mouse (Mus musculus), nematode (Caenorhabditis elegans), and fruit fly (Drosophila melanogaster). However, blacklists are not currently available for many model and nonmodel species. Here, we describe an alternative approach for removing false-positive peaks called greenscreen. Greenscreen is easy to implement, requires few input samples, and uses analysis tools frequently employed for ChIP-seq. Greenscreen removes artifactual signals as effectively as blacklists in Arabidopsis thaliana and human ChIP-seq dataset while covering less of the genome and dramatically improves ChIP-seq peak calling and downstream analyses. Greenscreen filtering reveals true factor binding overlap and occupancy changes in different genetic backgrounds or tissues. Because it is effective with as few as two inputs, greenscreen is readily adaptable for use in any species or genome build. Although developed for ChIP-seq, greenscreen also identifies artifactual signals from other genomic datasets including Cleavage Under Targets and Release Using Nuclease. We present an improved ChIP-seq pipeline incorporating greenscreen that detects more true peaks than other methods.