Biology subjects

Wang, J. K.

Publications and source records attributed to Wang, J. K..

6 recordsLinked to original sources

bioRxiv2025

Embryonic Stem Cell-Specific Responses to DNA Replication Stress

Genome maintenance is of the utmost importance in stem cells, as mutations can be propagated and cause defects in derivative tissues. Many stem cell types display low mutation rates, with embryonic stem cells (ESCs) being a notable example. The bases for this property are unclear but may be achieved by optimization of various processes including high-fidelity DNA repair, cell cycle checkpoint controls, and hypersensitivity to genotoxic insults that trigger cell death. Here, we investigate the mechanisms underlying the unique responses of mouse ESCs (mESCs) to replication stress (RS) using an array of small molecule inhibitors and genotoxins. We find that whereas mESCs survive under acute RS in an ATR- and CHK1-dependent manner similar to somatic cells, they lack a strong G2/M checkpoint and fail to repair DNA crosslinks in the absence of ATR signaling. Despite the lack of a strong G2/M checkpoint, mESCs maintain a spindle assembly checkpoint (SAC). We posit that mESCs preferentially repair DNA crosslinks in S phase via homology-directed mechanisms, and cells that fail to complete repair before mitosis undergo mitotic catastrophe and cell death. These findings shed light on mutation avoidance mechanisms in ESCs that may extend to other stem cell types.

cell biology↗

bioRxiv2024

Characterization of FLOWERING LOCUS T related genes and their putative gene regulatory network in semi-winter Brassica napus cultivar Zhongshaung11

In many species, FLOWERING LOCUS T (FT)-like genes promote the floral transition by integrating environmental signals, in particular photoperiod, and internal cues. Here we show that Brassica napus contains 6 FT-like genes and 2 pseudogenes belonging to 3 orthogroups. All B. napus FT-like genes induce early flowering when expressed at the shoot apical meristems of Arabidopsis thaliana ft mutants, but BnaFT.C6 and non-orthologous FT-like genes do not encode fully functional mobile florigens. In the case of BnFT.C6, the functional change is associated with a T to C amino acid change that is restricted to semi-winter accessions. Expression of orthologs of FT is photoperiod-dependent and two distal enhancers are conserved; however, the homeologs BnaFT.A7 and BnaFT.C6 show rearrangements of DNA motifs binding NF-Y/CO and NF-Y transcriptional activator complexes between the promoter and downstream enhancers. Motif rearrangements correlate with differences in tissue-specific expression. Furthermore, homeologs with rearranged motifs could not be trans-activated by B. napus CO in transient assays although they genes show LD photoperiod-dependent expression. We propose that differential diurnal expression of NF-Y genes contributes to the photoperiod-dependent regulation of B. napus FT genes. Significance statementB. napus FT-like genes are a case study for gene retention and retraction after multiple rounds of polyploidisation. Retained B. napus FT-like genes show preferred expression in different developmental stages and amino-acid changes that affect florigen function.

plant biology↗

bioRxiv2022

DNA methylation Dependent Restriction of Tyrosine Hydroxylase Contributes to Pancreatic β-cell Heterogeneity

The molecular and functional heterogeneity of pancreatic {beta}-cells is well recognized. Pancreatic islets harbor a small subset of {beta}-cells that co-express Tyrosine Hydroxylase (TH), an enzyme involved in synthesis of catecholamines that repress insulin secretion. Restriction of this sub-population within islets is essential for appropriate insulin secretion. However, the distinguishing characteristics of this subpopulation and the mechanisms that restrict TH expression in {beta}-cells are not known. Here, we define the specific molecular and metabolic characteristics of the TH+ {beta}-cells and show that TH expression in {beta}-cells is restricted by DNA methylation patterning during {beta}-cell lineage specification. Ablation of de novo DNA methyltransferase Dnmt3a in the pancreatic- and endocrine-progenitor lineages results in a dramatic increase in the proportion of TH+ {beta}-cells, while {beta}-cell specific ablation of Dnmt3a has no effect on this sub-population. We demonstrate that maintenance of Th promoter DNA methylation patterns is essential for its continued restriction in postnatal {beta}-cells, and that loss of DNA methylation dysregulates TH expression in {beta}-cells in response to chronic overnutrition, contributing to impairment of {beta}-cell identity. These data highlight the essential requirement of DNA methylation patterning in regulating endocrine cell fates, and reveal a novel role of DNA methylation in {beta}-cell heterogeneity.

developmental biology↗

bioRxiv2020

Dense, high-resolution mapping of cells and tissues from pathology images for the interpretable prediction of molecular phenotypes in cancer

While computational methods have made substantial progress in improving the accuracy and throughput of pathology workflows for diagnostic, prognostic, and genomic prediction, lack of interpretability remains a significant barrier to clinical integration. In this study, we present a novel approach for predicting clinically-relevant molecular phenotypes from histopathology whole-slide images (WSIs) using human-interpretable image features (HIFs). Our method leverages >1.6 million annotations from board-certified pathologists across >5,700 WSIs to train deep learning models for high-resolution tissue classification and cell detection across entire WSIs in five cancer types. Combining cell- and tissue-type models enables computation of 607 HIFs that comprehensively capture specific and biologically-relevant characteristics of multiple tumors. We demonstrate that these HIFs correlate with well-known markers of the tumor microenvironment (TME) and can predict diverse molecular signatures, including immune checkpoint protein expression and homologous recombination deficiency (HRD). Our HIF-based approach provides a novel, quantitative, and interpretable window into the composition and spatial architecture of the TME.

bioinformatics↗

bioRxiv2020

Sex-Specific Cross Tissue Meta-Analysis Identifies Immune Dysregulation in Women with Alzheimer's Disease

In spite of evidence of females having a greater lifetime risk of developing Alzheimers Disease (AD) and greater apolipoprotein E4-related (apoE4) AD risk compared to males, molecular signatures underlying these findings remain elusive. We took a meta-analysis approach to study gene expression in the brains of 1,084 AD patients and age-matched controls and whole blood from 645 AD patients and age-matched controls. Gene-expression, network-based analysis and cell type deconvolution approaches revealed a consistent immune signature in the brain and blood of female AD patients that was absent in males. Machine learning-based classification of AD using gene expression from whole blood in addition to clinical features revealed an improvement in classification accuracy upon stratifying by sex, achieving an AUROC of 0.91 for females and 0.80 for males. These results help identify sex and apoE4 genotype-specific transcriptomic signatures of AD and underscore the importance of considering sex in the development of biomarkers and therapeutic strategies for AD.

neuroscience↗

bioRxiv2018

Characterizing Inpatient Medicine Resident Electronic Health Record Usage Patterns Using Event Log Data

Amid growing rates of burnout, physicians report increasing electronic health record (EHR) usage alongside decreasing clinical facetime with patients. There exists a pressing need to improve physician-computer-patient interactions by streamlining EHR workflow.\n\nTo identify interventions to improve EHR design and usage, we systematically characterize EHR activity among internal medicine residents at a tertiary academic hospital across various inpatient rotations and roles from June 2013 to November 2016.\n\nLogged EHR timestamps were extracted from Stanford Hospitals EHR system (Epic) and cross-referenced against resident rotation schedules. We tracked the quantity of EHR logs across 24-hour cycles to reveal daily usage patterns. In addition, we decomposed daily EHR time into time spent on specific EHR actions (e.g. chart review, note entry and review, results review).\n\nIn examining 24-hour usage cycles from general medicine day and night team rotations, we identified a prominent trend in which night team activity promptly ceased at the shifts end, while day team activity tended to linger post-shift. Across all rotations and roles, residents spent on average 5.38 hours (standard deviation=2.07) using the EHR. PGY1 (post-graduate year one) interns and PGY2+ residents spent on average 2.4 and 4.1 times the number of EHR hours on information review (chart, note, and results review) as information entry (note and order entry).\n\nAnalysis of EHR event log data can enable medical educators and programs to develop more targeted interventions to improve physician-computer-patient interactions, centered on specific EHR actions.

epidemiology↗