Peak shape clustering reveals biological insights.
BACKGROUND
ChIP-seq experiments are widely used to detect and study DNA-protein interactions, such as transcription factor binding and chromatin modifications. However, downstream analysis of ChIP-seq data is currently restricted to the evaluation of signal intensity and the detection of enriched regions (peaks) in the genome. Other features of peak shape are almost always neglected, despite the remarkable differences shown by ChIP-seq for different proteins, as well as by distinct regions in a single experiment.


RESULTS
We hypothesize that statistically significant differences in peak shape might have a functional role and a biological meaning. Thus, we design five indices able to summarize peak shapes and we employ multivariate clustering techniques to divide peaks into groups according to both their complexity and the intensity of their coverage function. In addition, our novel analysis pipeline employs a range of statistical and bioinformatics techniques to relate the obtained peak shapes to several independent genomic datasets, including other genome-wide protein-DNA maps and gene expression experiments. To clarify the meaning of peak shape, we apply our methodology to the study of the erythroid transcription factor GATA-1 in K562 cell line and in megakaryocytes.


CONCLUSIONS
Our study demonstrates that ChIP-seq profiles include information regarding the binding of other proteins beside the one used for precipitation. In particular, peak shape provides new insights into cooperative transcriptional regulation and is correlated to gene expression.
MOX - Dipartimento di Matematica, Politecnico di Milano, Milan, Italy. marziaangela.cremona@polimi.it.
Marzia A
MA
Cremona
MOX - Dipartimento di Matematica, Politecnico di Milano, Milan, Italy. laura.sangalli@polimi.it.
Laura M
LM
Sangalli
MOX - Dipartimento di Matematica, Politecnico di Milano, Milan, Italy. simone.vantini@polimi.it.
Simone
S
Vantini
Department of Experimental Oncology, European Institute of Oncology, Milan, Italy. gaetano.dellino@ieo.eu.|Dipartimento di Scienze della salute, Università degli Studi di Milano, Milan, Italy. gaetano.dellino@ieo.eu.
Gaetano I
GI
Dellino
Department of Experimental Oncology, European Institute of Oncology, Milan, Italy. piergiuseppe.pelicci@ieo.eu.|Dipartimento di Scienze della salute, Università degli Studi di Milano, Milan, Italy. piergiuseppe.pelicci@ieo.eu.
Pier Giuseppe
PG
Pelicci
MOX - Dipartimento di Matematica, Politecnico di Milano, Milan, Italy. piercesare.secchi@polimi.it.
Piercesare
P
Secchi
Center for Genomic Science of IIT@SEMM, Fondazione Istituto Italiano di Tecnologia, Milan, Italy. laura.riva@iit.it.
Laura
L
Riva
D047369:Chromatin Immunoprecipitation; D016000:Cluster Analysis; D019295:Computational Biology; D004247:DNA / Q000737:chemistry / Q000378:metabolism; D050982:GATA1 Transcription Factor / Q000037:antagonists & inhibitors / Q000235:genetics / Q000378:metabolism; D055785:Gene Knockdown Techniques; D006801:Humans; D020014:K562 Cells; D008533:Megakaryocytes / Q000166:cytology / Q000378:metabolism; D011485:Protein Binding; D017422:Sequence Analysis, DNA
D050982:GATA1 Transcription Factor; C494688:GATA1 protein, human; D004247:DNA