A framework for mutational signature analysis based on DNA shape parameters

Abstract

The mutation risk of a DNA locus depends on its oligonucleotide context. In turn, mutability of oligonucleotides varies across individuals, due to exposure to mutagenic agents or due to variable efficiency and/or accuracy of DNA repair. Such variability is captured by mutational signatures, a mathematical construct obtained by a deconvolution of mutation frequency spectra across individuals. There is a need to enhance methods for inferring mutational signatures to make better use of sparse mutation data (e.g., resulting from exome sequencing of cancers), to facilitate insight into underlying biological mechanisms, and to provide more accurate mutation rate baselines for inferring positive and negative selection. We propose a conceptualization of mutational signatures that represents oligonucleotides via descriptors of DNA conformation: base pair, base pair step, and minor groove width parameters. We demonstrate how such DNA structural parameters can accurately predict mutation occurrence due to DNA repair failures or due to exposure to diverse mutagens such as radiation, chemical exposure, and the APOBEC cytosine deaminase enzymes. Furthermore, the mutation frequency of DNA oligomers classed by structural features can accurately capture systematic variability in mutagenesis of >1,000 tumors originating from diverse human tissues. A nonnegative matrix factorization was applied to mutation spectra stratified by DNA structural features, thereby extracting novel mutational signatures. Moreover, many of the known trinucleotide signatures were associated with an additional spectrum in the DNA structural descriptor space, which may aid interpretation and provide mechanistic insight. Overall, we suggest that the power of DNA sequence motif-based mutational signature analysis can be enhanced by drawing on DNA shape features.

DNA polymerase ε and δ variants drive mutagenesis in polypurine tracts in human tumors

“…Indeed, a recent study suggested that the sites of POLE -driven mutations in tumors have overtwisting of DNA at the −1 position and undertwisting at the +1 position in regard to the mutation site. 66 Guanines at certain positions within the y (A) n G(A) n y sequences could also be more prone to damage, as shown for guanines in G-tracts. 67 Polypurine tracts were also linked to recombination hotspots, 68 , 69 further illustrating their special features.…”

DNA Glycosylases Define the Outcome of Endogenous Base Modifications

“…Interestingly, of the three DNA glycosylases analysed (OGG1, TDG and UNG), only OGG1 and UNG knock-outs were able to leave a substitution signature [ 18 ]. Whole-genome sequencing of cancer genomes has revealed mutation signatures associated with defects in BER, due to compromised DNA glycosylase activity and by shaping mutation signatures connected with AID/APOBEC family enzymes [ 19 , 20 ]. Oxidative damage (8-oxoG formation) produces a G > T/C > A pattern, similar to the one identified in adrenocortical cancers and neuroblastomas (SBS18) and qualitatively analogous to the mutational signature of inactivating of germline mutations in MUTYH1 (SBS36) [ 18 , 21 ].…”

Understanding and diagnosing cancer through its mutational history

“…Nevertheless, the 1536 possible pentanucleotide contexts (base substitution with 2 flanking 5' and 3' bases) could be used instead of the 96 trinucleotides as a basis for extraction of extended SBS signatures [324,325]. Aside from the flanking bases, somatic point mutations could be stratified by at the mutation locus, such as replication timing [179] or position on the DNA groove [326]. However, having too many mutation contexts leads to too few mutations being attributed to each context (which is especially problematic for the pentanucleotide contexts), potentially preventing robust extraction of de novo signatures.…”