Biology subjects

Kearns, S.

Publications and source records attributed to Kearns, S..

4 recordsLinked to original sources

bioRxiv2020

Molecular determinants for α-tubulin methylation by SETD2

Post-translational modifications to tubulin are important for many microtubule-based functions inside cells. A recently identified tubulin modification, methylation, occurs on mitotic spindle microtubules during cell division, and is enzymatically added to tubulin by the histone methyltransferase SETD2. We used a truncated version of human SETD2 (tSETD2) containing the catalytic SET and C-terminal Set2 Rpb1 interacting (SRI) domains to investigate the biochemical mechanism of tubulin methylation. We found that recombinant tSETD2 has a higher activity towards tubulin dimers than polymerized microtubules. Using recombinant single-isotype tubulin, we demonstrate that methylation is restricted to lysine 40 (K40) of -tubulin. We then introduced pathogenic mutations into tSETD2 to probe the recognition of histone and tubulin substrates. A mutation in the catalytic domain, R1625C, bound to tubulin but could not methylate it whereas a mutation in the SRI domain, R2510H, caused loss of both tubulin binding and methylation. We thus further probed a role for the SRI domain in substrate binding and found that mutations within this region had differential effects on the ability of tSETD2 to bind to tubulin versus RNA Polymerase II substrates, suggesting distinct mechanisms for tubulin and histone methylation by SETD2. Lastly, we found that substrate recognition also requires the negatively-charged C-terminal tail of -tubulin. Together, this work provides a framework for understanding how SETD2 serves as a dual methyltransferase for histone and tubulin methylation.

biochemistry↗

bioRxiv2020

Trajectory analysis of cardiovascular phenotypes from biobank data uncovers novel genetic associations

Approximately 6 million adults in the US have heart failure (HF). HF progression is variable due in part to differences in sex, age, and genetic ancestry. Previous population-based genetic studies have largely focused on cross-sectional data related to HF, a disease known to change over time. Utilizing longitudinal data trajectory probabilities as a continuous trait may increase the likelihood of finding significant, biologically relevant associations in a genome-wide association (GWA) analysis. We analyzed data from the electronic health record in a medical biobank from a single, metropolitan US center to gather clinically pertinent data for analyses. We evaluated whole genome sequencing of 896 unrelated biobank participants, including 494 with at least 1 electrocardiogram and 324 who had more than 1 echocardiogram ([~]3 observations per person). A censored normal distribution multivariable mixture model was used to cluster phenotype measures for genome-wide analyses. GWA analysis on the trajectory probability of the corrected QT measurement (QTc) taken from electrocardiograms identified significant associations with variants in regulatory regions proximal to the WLS gene, which encodes the Wnt ligand secretion mediator, Wntless. WLS was previously associated with QT length using of approximately 16,000 participants supporting the utility of this method to uncover significant genetic associations in small datasets. GWA analysis on the trajectory probability of left ventricular diameter as taken from echocardiograms identified novel significant associations with variants in regulatory regions near MYO10, which encodes the unconventional Myosin-10. We found that trajectory probabilities improved the ability to discover significant and relevant genetic associations. This novel approach increased yield from smaller, well-phenotyped cohorts with longitudinal data from a medical biobank. AUTHOR SUMMARYApproximately 6 million adults in the US have heart failure, a disease known to change over time. In a hospital based electronic health record, electrocardiograms and echocardiograms, used to evaluate heart failure, can be tracked over time. We utilized these data to create a novel trait that can be applied to genetic analyses. We analyzed genome sequence of 896 biobank participants from diverse racial/ethnic backgrounds. Genome-wide association (GWA) analyses were performed on a subset of these individuals for heart failure outcomes. A statistical model that incorporates cardiac data that are tracked over time was used to cluster these data using a probabilistic approach. These probabilities were used for a GWA analysis for corrected QT measurement (QTc) and left ventricular diameter (LVID). The QTc interval analysis identified significant correlations with variants in regulatory regions near the WLS gene which encodes the Wnt ligand secretion mediator, Wntless. Analysis of LVID identified significant associations with variants in regulatory regions near the MYO10 gene which encodes the unconventional Myosin-10. Through these analyses, we found that using the trajectory probabilities can facilitate the discovery of novel significant, biologically relevant associations. This method reduces the need for larger cohorts, and increases yield from smaller, well-phenotyped cohorts.

genomics↗

bioRxiv2020

High-resolution cryo-EM using beam-image shift at 200 keV

Recent advances in single-particle cryo-electron microscopy (cryo-EM) data collection utilizes beam-image shift to improve throughput. Despite implementation on 300 keV cryo-EM instruments, it remains unknown how well beam-image shift data collection affects data quality on 200 keV instruments and how much aberrations can be computationally corrected. To test this, we collected and analyzed a cryo-EM dataset of aldolase at 200 keV using beam-image shift. This analysis shows that beam tilt on the instrument initially limited the resolution of aldolase to 4.9[A]. After iterative rounds of aberration correction and particle polishing in RELION, we were able to obtain a 2.8[A] structure. This analysis demonstrates that software correction of microscope aberrations can provide a significant improvement in resolution at 200 keV.

biophysics↗

bioRxiv2019

Pathogenic and uncertain genetic variants have clinical cardiac correlates in diverse biobank participants

BackgroundGenome sequencing coupled with electronic heath record data can uncover medically important genetic variation. Interpretation of rare genetic variation and its role in mediating cardiovascular phenotypes is confounded by variants of uncertain significance.\n\nMethods and ResultsWe analyzed the whole genome sequence of 900 racially and ethnically diverse biobank participants selected from a single US center. Participants were equally divided among European, African, Hispanic, and mixed race/ethnicities. We evaluated the American College of Medical Genetics and Genomics medically actionable list of 59 genes focusing on the cardiac genes. Variation was interpreted using the most recent reports in ClinVar, a database of medically relevant human variation. We identified 19 individuals with pathogenic/likely pathogenic variants in cardiac actionable genes (2%) and found evidence for clinical correlates in the electronic health record. African ancestry participants had more variants of uncertain significance in the medically actionable genes including the 30 cardiac actionable genes, even when normalized to total variant count per person. Longitudinal measures of left ventricle size, corrected for body surface area, from approximately 400 biobank participants (1,723 patient years) correlated with genetic findings. The presence of one or more uncertain variants in the actionable cardiac genes and a cardiomyopathy diagnosis correlated with increased left ventricular internal diameter in diastole and in systole. In particular, MYBPC3 was identified as a gene with excess variants of uncertain significance.\n\nConclusionsThese data indicate a subset of uncertain variants may confer risk and should not be considered benign.

genomics↗