Biology subjects

Steinberg, P.

Publications and source records attributed to Steinberg, P..

4 recordsLinked to original sources

bioRxiv2025

High-throughput neutralization measurements correlate strongly with evolutionary success of human influenza strains

Human influenza viruses rapidly acquire mutations in their hemagglutinin (HA) protein that erode neutralization by antibodies from prior exposures. Here, we use a sequencing-based assay to measure neutralization titers for 78 recent H3N2 HA strains against a large set of children and adult sera, measuring [~]10,000 total titers. There is substantial person-to-person heterogeneity in the titers against different viral strains, both within and across age cohorts. The growth rates of H3N2 strains in the human population in 2023 are highly correlated with the fraction of sera with low titers against each strain. Notably, strain growth rates are less correlated with neutralization titers against pools of human sera, demonstrating the importance of population heterogeneity in shaping viral evolution. Overall, these results suggest that high-throughput neutralization measurements of human sera against many different viral strains can help explain the evolution of human influenza.

evolutionary biology↗

bioRxiv2025

RNA Transcripts Serve as a Template for Double-Strand Break Repair in Human Cells

Double-strand breaks (DSBs) are toxic lesions that lead to genome instability. While canonical DSB repair pathways typically operate independently of RNA, emerging evidence suggests that RNA:DNA hybrids and transcripts near damaged sites can influence repair outcomes. However, a direct role for transcript RNA as a template during DSB repair in human cells is yet to be established. In this study, we designed fluorescent- and sequencing-based assays, which demonstrated that RNA-containing oligonucleotides and messenger RNA serve as templates to promote DSB repair. We conducted a CRISPR/Cas9-based genetic screen to identify factors that promote RNA-templated DSB repair (RT-DSBR), and of the candidate polymerases, we identified DNA polymerase-zeta (Pol{zeta}) as the potential reverse transcriptase that facilitates RT-DSBR. Furthermore, by analyzing sequencing data from cancer genomes, we identified the presence of whole intron deletions, a unique genomic scar reflective of RT-DSBR activity generated when spliced mRNA serves as the repair template. These findings highlight RT-DSBR as an alternative pathway for repairing DSBs in transcribed genes, with potential mutagenic consequences.

molecular biology↗

bioRxiv2024

Metapipeline-DNA: A Comprehensive Germline & Somatic Genomics Nextflow Pipeline

SummaryThe price, quality and throughout of DNA sequencing continue to improve. Algorithmic innovations have allowed inference of a growing range of features from DNA sequencing data, quantifying nuclear, mitochondrial and evolutionary aspects of both germline and somatic genomes. To automate analyses of the full range of genomic characteristics, we created an extensible Nextflow meta-pipeline called metapipeline-DNA. Metapipeline-DNA analyzes targeted and whole-genome sequencing data from raw reads through pre-processing, feature detection by multiple algorithms, quality-control and data- visualization. Each step can be run independently and is supported robust software engineering including automated failure-recovery, robust testing and consistent verifications of inputs, outputs and parameters. Metapipeline-DNA is cloud-compatible and highly configurable, with options to subset and optimize each analysis. Metapipeline-DNA facilitates high-scale, comprehensive analysis of DNA sequencing data. AvailabilityMetapipeline-DNA is an open-source Nextflow pipeline under the GPLv2 license and is available at https://github.com/uclahs-cds/metapipeline-DNA.

bioinformatics↗

bioRxiv2021

Tissue-specific impacts of aging and genetics on gene expression patterns in humans

Age is the primary risk factor for many common human diseases including heart disease, Alzheimers dementias, cancers, and diabetes. Determining how and why tissues age differently is key to understanding the onset and progression of such pathologies. Here, we set out to quantify the relative contributions of genetics and aging to gene expression patterns from data collected across 27 tissues from 948 humans. We show that age impacts the predictive power of expression quantitative trait loci across several tissues. Jointly modelling the contributions of age and genetics to transcript level variation we find that the heritability (h2) of gene expression is largely consistent among tissues. In contrast, the average contribution of aging to gene expression variance varied by more than 20-fold among tissues with [Formula] in 5 tissues. We find that the coordinated decline of mitochondrial and translation factors is a widespread signature of aging across tissues. Finally, we show that while in general the force of purifying selection is stronger on genes expressed early in life compared to late in life as predicted by Medawars hypothesis, a handful of highly proliferative tissues exhibit the opposite pattern. These non-Medawarian tissues exhibit high rates of cancer and age-of-expression associated somatic mutations in cancer. In contrast, gene expression variation that is under genetic control is strongly enriched for genes under relaxed constraint. Together we present a novel framework for predicting gene expression phenotypes from genetics and age and provide insights into the tissue-specific relative contributions of genes and the environment to phenotypes of aging.

genetics↗