Biology subjects

Benjamin, D.

Publications and source records attributed to Benjamin, D..

5 recordsLinked to original sources

bioRxiv2025

Himito: a Graph-based Toolkit for Mitochondrial Genome Analysis using Long Reads

Understanding the genetic and epigenetic regulation of mitochondrial DNA (mtDNA) is essential for elucidating mechanisms of aging and disease. Long-read sequencing can span the entire mitochondrial genome and directly capture base-modification signals, yet analytical tools for such data remain limited. We developed Himito, a graph-based toolkit for analyzing mitochondrial genome using long reads. Himito filters reads originating from nuclear mitochondrial insertions (NUMTs), constructs a sequence graph to represent mtDNA diversity, assembles primary haplotypes, calls variants, and analyzes 5-methylcytosine (5mC) modifications within a unified framework. Benchmarking on high-quality reference datasets shows Himito achieves superior performance in assembly and variant calling compared with existing tools. Applied to the All of Us (AoU) v8 dataset, Himito identified pathogenic mtDNA variants, revealed population-scale haplogroup diversity, and uncovered age-related genetic and epigenetic patterns. These results demonstrate that long-read sequencing, combined with graph-based analysis, enables integrated characterization of mitochondrial genomic and epigenomic variation. Himito is available at https://github.com/broadinstitute/Himito.

bioinformatics↗

bioRxiv2025

Proteomics of Transglutaminase 2 polyaminated proteins

Post-translational modification of proteins by polyamines (putrescine, spermine and spermidine) is poorly studied due to technical challenges in identification. Polyamination is mainly performed by transglutaminases via transamidation of a polyamine to an acceptor glutamine-residue on the target protein. We performed polyamination reactions on whole cell lysates using 2 different polyamine probes (Biotin-pentylamine and DNP-pentylamine) and identified modified peptides by mass spectrometry. 51 protein targets modified on 66 different sites were identified, with an overlap between hits tagged with the different probes. Many of the targets are involved in translation, cytoskeletal organization or have roles in cancer.

molecular biology↗

bioRxiv2021

Mitochondrial DNA variation across 56,434 individuals in gnomAD

Databases of allele frequency are extremely helpful for evaluating clinical variants of unknown significance; however, until now, genetic databases such as the Genome Aggregation Database (gnomAD) have ignored the mitochondrial genome (mtDNA). Here we present a pipeline to call mtDNA variants that addresses three technical challenges: (i) detecting homoplasmic and heteroplasmic variants, present respectively in all or a fraction of mtDNA molecules, (ii) circular mtDNA genome, and (iii) misalignment of nuclear sequences of mitochondrial origin (NUMTs). We observed that mtDNA copy number per cell varied across gnomAD cohorts and influenced the fraction of NUMT-derived false-positive variant calls, which can account for the majority of putative heteroplasmies. To avoid false positives, we excluded samples prone to NUMT misalignment (few mtDNA copies per cell), cell line artifacts (many mtDNA copies per cell), or with contamination and we reported variants with heteroplasmy greater than 10%. We applied this pipeline to 56,434 whole genome sequences in the gnomAD v3.1 database that includes individuals of European (58%), African (25%), Latino (10%), and Asian (5%) ancestry. Our gnomAD v3.1 release contains population frequencies for 10,850 unique mtDNA variants at more than half of all mtDNA bases. Importantly, we report frequencies within each nuclear ancestral population and mitochondrial haplogroup. Homoplasmic variants account for most variant calls (98%) and unique variants (85%). We observed that 1/250 individuals carry a pathogenic mtDNA variant with heteroplasmy above 10%. These mitochondrial population allele frequencies are publicly available at gnomad.broadinstitute.org and will aid in diagnostic interpretation and research studies.

genomics↗

bioRxiv2019

Somatic Truth Data from Cell Lineage

Existing somatic benchmark datasets for human sequencing data use germline variants, synthetic methods, or expensive validations, none of which are satisfactory for providing a large collection of true somatic variation across a whole genome. Here we propose a dataset of short somatic mutations, that are validated using a known cell lineage. The dataset contains 56,974 (2,687 unique) Single Nucleotide Variations (SNV), 6,370 (316 unique) small Insertions and Deletions (Indels), and 144 (8 unique) Copy Number Variants (CNV) across 98 in silico mixed truth sets with a high confidence region covering 2.7 gigabases per mixture. The data is publicly available for use as a benchmarking dataset for somatic short mutation discovery pipelines.

bioinformatics↗

bioRxiv2019

mTOR dependent transformed human cells have a distinct set of essential genes from bcr-abl transformed cells

Constitutively active intracellular signaling drives and sustains cancer growth. The mTOR kinase integrates multiple inputs sensing nutrient, energy and growth factor levels to promote protein synthesis and anabolic metabolism, and is hyperactivated in a broad range of cancers. The bcr-abl kinase is a fusion protein generated by chromosomal translocation and gives rise to chronic myeloid leukemia and a small sub-set of leukemias. Using an in vitro transformed murine cell model, we performed shRNA knockdown of 25 genes previously shown to be essential for mTOR dependent oncogenic growth and survival. None of the genes were essential in the bcr-abl transformed line. Interrogation of this gene set in human cancer cell lines revealed that many of these genes were essential in cells dependent on mTOR signaling (defined by sensitivity to pharmacological mTOR inhibition). However, none of the genes were essential in bcr-abl transformed K562 cells that are insensitive to mTOR inhibition. Thus there is a clear divide between cells transformed via bcr-abl directed oncogenesis and other modes of transformation where mTOR, due to its central role in regulating cell growth and metabolism, is recruited as part of an oncogenic program. These validated hits represent a set of genes essential for executing critical functions downstream of mTOR and may be novel therapeutic targets for cancer.

cell biology↗