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The concept of exploiting correlated mutations has been introduced and applied successfully to identify interactions within and between biological macromolecules. Its rationale lies in the preservation of physical interactions via compensatory mutations. With the massive increase of available sequence information, approaches based on correlated mutations have regained considerable attention. We analyzed a set of 10 707 430 single nucleotide polymorphisms detected in 1135 accessions of the plant Arabidopsis thaliana. To measure their covariance and to reveal the global genome-wide sequence correlation structure of the Arabidopsis genome, the adjusted mutual information has been estimated for each possible pair of polymorphic sites. We developed a series of filtering steps to account for genetic linkage and lineage relations between Arabidopsis accessions, as well as transitive covariance as possible confounding factors. We show that upon appropriate filtering, correlated mutations prove indeed informative with regard to molecular interactions, and furthermore, appear to reflect on chromosomal interactions. Our study demonstrates that the concept of correlated mutations can also be applied successfully to within-species sequence variation and establishes a promising approach to help unravel the complex molecular interactions in A. thaliana and other species with broad sequence information.

A genome-wide scan for correlated mutations detects macromolecular and chromatin interactions in Arabidopsis thaliana