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Scott Gradia

Researcher at Thomas Jefferson University

Publications -  10
Citations -  2370

Scott Gradia is an academic researcher from Thomas Jefferson University. The author has contributed to research in topics: MutS-1 & DNA. The author has an hindex of 9, co-authored 9 publications receiving 2074 citations.

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hMSH2 forms specific mispair-binding complexes with hMSH3 and hMSH6

TL;DR: Analysis of the mismatched nucleotide-binding specificity of the hMSH2-hMSH3 and hMSh2-HMSH6 protein complexes showed that they have overlapping but not identical binding specificity, which helps to explain the distribution of mutations in different mismatch-repair genes seen in hereditary nonpolyposis colon cancer.
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hMSH2-hMSH6 forms a hydrolysis-independent sliding clamp on mismatched DNA

TL;DR: The results support a model for bidirectional mismatch repair in which stochastic loading of multiple ATP-bound hMSH2-hMSH6 sliding clamps onto mismatch-containing DNA leads to activation of the repair machinery and/or other signaling effectors similar to G protein switches.
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DNA Repair Profiling Reveals Nonrandom Outcomes at Cas9-Mediated Breaks

TL;DR: This work demonstrates that the pattern of DNA repair following Cas9 cutting at each site is nonrandom and consistent across experimental replicates, cell lines, and reagent delivery methods, and elucidates a strategy for using "error-prone" DNA-repair machinery to generate precise edits.
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The Human Mismatch Recognition Complex hMSH2-hMSH6 Functions as a Novel Molecular Switch

TL;DR: It is shown that adenine nucleotide binding and hydrolysis by the human mismatch recognition complex hMSH2-hMSH6 functions as a novel molecular switch, suggesting a new model for the function of MutS proteins during mismatch repair in which the switch determines the timing of downstream events.
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Mapping the genomic landscape of CRISPR–Cas9 cleavage

TL;DR: This work developed a biochemical method (SITE-Seq), using Cas9 programmed with single-guide RNAs (sgRNAs), to identify the sequence of cut sites within genomic DNA, and found that the number of sites identified depended on sgRNA sequence and nuclease concentration.