SNP-ChIP: a versatile and tag-free method to quantify changes in protein binding across the genome

Dataset: SNP-ChIP: a versatile and tag-free method to quantify changes in protein binding across the genome

External ID: GSE115092
Reference: Vale-Silva LA, et al. (2019)
Channels: 1
Conditions: 86
Description: SNP-ChIP is a novel method leveraging small-scale intra-species genetic polymorphisms, mainly SNPs, to allow quantitative spike-in normalization of ChIP-seq results. SNP-ChIP uses a different strain of the same organism as the spike-in material and can be applied to any organism for which genome assemblies are available for two different strains or individuals with sufficient genetic diversity. This ensures antibody cross-reactivity and thus extends the applicability of the method beyond the small number of highly conserved proteins. It also ensures complete physiological coherence between the test and the spike-in cells. In this work we develop and validate the method using test cases from budding yeast meiosis. We use strains with ~0.7% genomic sequence divergence as test strain background and the spike-in strain, respectively. Sequencing reads are mapped to a hybrid genome, with naturally occurring sequence polymorphisms allowing assignment of most reads to one of the two genomes. By targeting the yeast chromosomal protein Red1, we show that SNP-ChIP reliably identifies previously reported changes in overall protein levels, irrespective of changes in binding distribution. We also show that SNP-ChIP is robust to wide changes in sequencing depth, as well as the amount of spike-in material. SNP-ChIP allowed discovery of novel regulators of global Red1 protein accumulation and is also shown to allow quantitative analysis of the DNA-damage associated histone modification gamma-H2AX. SNP-ChIP is a robust and versatile spike-in normalization method that can be used with any target against which a ChIP-grade antibody is available and for any organisms with sufficient intra-species diversity, including most model organisms as well as human cells. Grant ID: FY16-208 Grant title: Meiotic segregation of small chromosomes Funding source: March of Dimes Grantee name: Andreas Hochwagen, New York University, New York, NY, United States
Categories: physical interaction

Conditions

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