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DNA polymerase β nucleotide-stabilized template misalignment fidelity depends on local sequence context.

ABSTRACT: DNA polymerase β has two DNA-binding domains that interact with the opposite sides of short DNA gaps. These domains contribute two activities that modify the 5' and 3' margins of gapped DNA during base excision repair. DNA gaps greater than 1 nucleotide (nt) pose an architectural and logistical problem for the two domains to interact with their respective DNA termini. Here, crystallographic and kinetic analyses of 2-nt gap-filling DNA synthesis revealed that the fidelity of DNA synthesis depends on local sequence context. This was due to template dynamics that altered which of the two template nucleotides in the gap served as the coding nucleotide. We observed that, when a purine nucleotide was in the first coding position, DNA synthesis fidelity was similar to that observed with a 1-nt gap. However, when the initial templating nucleotide was a pyrimidine, fidelity was decreased. If the first templating nucleotide was a cytidine, there was a significantly higher probability that the downstream template nucleotide coded for the incoming nucleotide. This dNTP-stabilized misalignment reduced base substitution and frameshift deletion fidelities. A crystal structure of a binary DNA product complex revealed that the cytidine in the first templating site was in an extrahelical position, permitting the downstream template nucleotide to occupy the coding position. These results indicate that DNA polymerase β can induce a strain in the DNA that modulates the position of the coding nucleotide and thereby impacts the identity of the incoming nucleotide. Our findings demonstrate that "correct" DNA synthesis can result in errors when template dynamics induce coding ambiguity.

SUBMITTER: Howard MJ

PROVIDER: S-EPMC6956524 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BACKGROUND:The evolutionary history of genes serves as a cornerstone of contemporary biology. Most conserved sequences in mammalian genomes don't code for proteins, yielding a need to infer evolutionary history of sequences irrespective of what kind of functional element they may encode. Thus, sequence-, as opposed to gene-, centric modes of inferring paths of sequence evolution are increasingly relevant. Customarily, homologous sequences derived from the same direct ancestor, whose ancestral position in two genomes is usually conserved, are termed "primary" (or "positional") orthologs. Methods based solely on similarity don't reliably distinguish primary orthologs from other homologs; for this, genomic context is often essential. Context-dependent identification of orthologs traditionally relies on genomic context over length scales characteristic of conserved gene order or whole-genome sequence alignment, and can be computationally intensive. RESULTS:We demonstrate that short-range sequence context-as short as a single "maximal" match- distinguishes primary orthologs from other homologs across whole genomes. On mammalian whole genomes not preprocessed by repeat-masker, potential orthologs are extracted by genome intersection as "non-nested maximal matches:" maximal matches that are not nested into other maximal matches. It emerges that on both nucleotide and gene scales, non-nested maximal matches recapitulate primary or positional orthologs with high precision and high recall, while the corresponding computation consumes less than one thirtieth of the computation time required by commonly applied whole-genome alignment methods. In regions of genomes that would be masked by repeat-masker, non-nested maximal matches recover orthologs that are inaccessible to Lastz net alignment, for which repeat-masking is a prerequisite. mmRBHs, reciprocal best hits of genes containing non-nested maximal matches, yield novel putative orthologs, e.g. around 1000 pairs of genes for human-chimpanzee. CONCLUSIONS:We describe an intersection-based method that requires neither repeat-masking nor alignment to infer evolutionary history of sequences based on short-range genomic sequence context. Ortholog identification based on non-nested maximal matches is parameter-free, and less computationally intensive than many alignment-based methods. It is especially suitable for genome-wide identification of orthologs, and may be applicable to unassembled genomes. We are agnostic as to the reasons for its effectiveness, which may reflect local variation of mean mutation rate.

Project description:Alignment of large and diverse sequence sets is a common task in biological investigations, yet there remains considerable room for improvement in alignment quality. Multiple sequence alignment programs tend to reach maximal accuracy when aligning only a few sequences, and then diminish steadily as more sequences are added. This drop in accuracy can be partly attributed to a build-up of error and ambiguity as more sequences are aligned. Most high-throughput sequence alignment algorithms do not use contextual information under the assumption that sites are independent. This study examines the extent to which local sequence context can be exploited to improve the quality of large multiple sequence alignments.Two predictors based on local sequence context were assessed: (i) single sequence secondary structure predictions, and (ii) modulation of gap costs according to the surrounding residues. The results indicate that context-based predictors have appreciable information content that can be utilized to create more accurate alignments. Furthermore, local context becomes more informative as the number of sequences increases, enabling more accurate protein alignments of large empirical benchmarks. These discoveries became the basis for DECIPHER, a new context-aware program for sequence alignment, which outperformed other programs on large sequence sets.Predicting secondary structure based on local sequence context is an efficient means of breaking the independence assumption in alignment. Since secondary structure is more conserved than primary sequence, it can be leveraged to improve the alignment of distantly related proteins. Moreover, secondary structure predictions increase in accuracy as more sequences are used in the prediction. This enables the scalable generation of large sequence alignments that maintain high accuracy even on diverse sequence sets. The DECIPHER R package and source code are freely available for download at DECIPHER.cee.wisc.edu and from the Bioconductor repository.

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DNA polymerase β nucleotide-stabilized template misalignment fidelity depends on local sequence context.

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