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Christopher Bennett

The University of Texas Southwestern Medical Center

ORCID: 0000-0003-3329-2567

Publishes on Genomics and Phylogenetic Studies, Gene Regulatory Network Analysis, Enzyme Structure and Function. 18 papers and 16k citations.

18Publications
16kTotal Citations

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Top publicationsby citations

Rapid and accurate alignment of nucleotide conversion sequencing reads with HISAT-3N
Yun Zhang, Chanhee Park, Christopher Bennett et al.|Genome Research|2021
Cited by 374Open Access

Sequencing technologies using nucleotide conversion techniques such as cytosine to thymine in bisulfite-seq and thymine to cytosine in SLAM seq are powerful tools to explore the chemical intricacies of cellular processes. To date, no one has developed a unified methodology for aligning converted sequences and consolidating alignment of these technologies in one package. In this paper, we describe hierarchical indexing for spliced alignment of transcripts–3 nucleotides (HISAT-3N), which can rapidly and accurately align sequences consisting of any nucleotide conversion by leveraging the powerful hierarchical index and repeat index algorithms originally developed for the HISAT software. Tests on real and simulated data sets show that HISAT-3N is faster than other modern systems, with greater alignment accuracy, higher scalability, and smaller memory requirements. HISAT-3N therefore becomes an ideal aligner when used with converted sequence technologies.

valr: Reproducible genome interval analysis in R
Kent Riemondy, Ryan M. Sheridan, Austin E. Gillen et al.|F1000Research|2017
Cited by 93Open Access

New tools for reproducible exploratory data analysis of large datasets are important to address the rising size and complexity of genomic data. We developed the valr R package to enable flexible and efficient genomic interval analysis. valr leverages new tools available in the "tidyverse", including dplyr. Benchmarks of valr show it performs similar to BEDtools and can be used for interactive analyses and incorporated into existing analysis pipelines.

Genome-wide analysis of Musashi-2 targets reveals novel functions in governing epithelial cell migration
Christopher Bennett, Kent Riemondy, Douglas A. Chapnick et al.|Nucleic Acids Research|2016
Cited by 64Open Access

The Musashi-2 (Msi2) RNA-binding protein maintains stem cell self-renewal and promotes oncogenesis by enhancing cell proliferation in hematopoietic and gastrointestinal tissues. However, it is unclear how Msi2 recognizes and regulates mRNA targets in vivo and whether Msi2 primarily controls cell growth in all cell types. Here we identified Msi2 targets with HITS-CLIP and revealed that Msi2 primarily recognizes mRNA 3'UTRs at sites enriched in multiple copies of UAG motifs in epithelial progenitor cells. RNA-seq and ribosome profiling demonstrated that Msi2 promotes targeted mRNA decay without affecting translation efficiency. Unexpectedly, the most prominent Msi2 targets identified are key regulators that govern cell motility with a high enrichment in focal adhesion and extracellular matrix-receptor interaction, in addition to regulators of cell growth and survival. Loss of Msi2 stimulates epithelial cell migration, increases the number of focal adhesions and also compromises cell growth. These findings provide new insights into the molecular mechanisms of Msi2's recognition and repression of targets and uncover a key function of Msi2 in restricting epithelial cell migration.

HISAT-3N: a rapid and accurate three-nucleotide sequence aligner
Yun Zhang, Chanhee Park, Christopher Bennett et al.|bioRxiv (Cold Spring Harbor Laboratory)|2020
Cited by 2Open Access

Abstract Nucleotide conversion sequencing technologies such as bisulfite-seq and SLAM-seq are powerful tools to explore the intricacies of cellular processes. In this paper, we describe HISAT-3N (hierarchical indexing for spliced alignment of transcripts - 3 nucleotides), which rapidly and accurately aligns sequences consisting of nucleotide conversions by leveraging powerful hierarchical index and repeat index algorithms originally developed for the HISAT software. Tests on real and simulated data sets demonstrate that HISAT-3N is over 7 times faster, has greater alignment accuracy, and has smaller memory requirements than other modern systems. Taken together HISAT-3N is the ideal aligner for use with converted sequence technologies.