Biology subjects

Hillman, K.

Publications and source records attributed to Hillman, K..

5 recordsLinked to original sources

bioRxiv2025

Quantifying Misuse of Color in Biological Research

Colors are widely used to report biological research data. Effective interpretation of colors relies on accurate, intuitive, and accessible colormaps that are properly labeled. Misuse of colormaps, such as using rainbow, mismatched, and other inaccessible colormaps, hinders reader interpretation. Despite their ubiquitous use to represent biological data, the prevalence of colormap misuse has not been quantified. Using established guidelines, we analyzed over 6,000 articles in 10 high-impact biological journals spanning 2020-2024 to quantify the prevalence of colormap use and misuse. Over 67% of articles contain at least one colormap, of which 81% contain some form of misuse. Among the over 11,000 acquired colormap-associated figures, 60% contain some form of misuse. Heatmaps, scatter plots, images, and image overlays are the most commonly used figures with colormaps. These statistics vary by journal but remain constant over time, demonstrating the urgent need to increase awareness and education about color-based data reporting guidelines.

scientific communication and education↗

bioRxiv2025

Modification of Non-photochemical Quenching Pathways in the C4 Model Plant Setaria viridis Revealed Shared and Unique Photoprotection Mechanisms as Compared to C3 Plants

Light is essential for photosynthesis; however, excess light can increase the accumulation of photoinhibitory reactive oxygen species that reduce photosynthetic efficiency. Plants have evolved photoprotective non-photochemical quenching (NPQ) pathways to dissipate excess light energy. In tobacco and soybean (C3 plants), overexpression of three NPQ genes, violaxanthin de-epoxidase (VDE), Photosystem II Subunit S (PsbS), and zeaxanthin epoxidase (ZEP), hereafter VPZ, resulted in faster NPQ induction and relaxation kinetics, and increased crop yields in field conditions. NPQ is well-studied in C3 plants; however, NPQ and the translatability of the VPZ approach in C4 plants is poorly understood. The green foxtail Setaria viridis is an excellent model to study photosynthesis and photoprotection in C4 plants. To understand the regulation of NPQ and photosynthesis in C4 plants, we performed transient overexpression in Setaria protoplasts and generated (and employed) stable transgenic Setaria plants overexpressing one of the three Arabidopsis NPQ genes or all three NPQ genes (AtVPZ lines). Overexpressing (OE) AtVDE and AtZEP in Setaria produced similar results as in C3 plants, with increased or reduced zeaxanthin (thus NPQ), respectively. However, overexpressing AtPsbS appeared to be challenging in Setaria, with largely reduced NPQ in protoplasts and under-represented homozygous AtPsbS-OE lines, potentially due to competitive and tight heterodimerization of AtPsbS and SvPsbS proteins. Furthermore, Setaria AtVPZ lines had increased zeaxanthin, faster NPQ induction, higher NPQ level, but slower NPQ relaxation. Despite this, AtVPZ lines had improved growth as compared to wildtype under several conditions, especially high temperatures, which is not related to the faster relaxation of NPQ but may be attributable to increased zeaxanthin and NPQ in C4 plants. Our results identified shared and unique characteristics of the NPQ pathway in C4 model Setaria as compared to C3 plants and provide insights to improve C4 crop yields under fluctuating environmental conditions.

plant biology↗

bioRxiv2021

CRISPR screens identify gene targets and drug repositioning opportunities at breast cancer risk loci

Genome-wide association studies (GWAS) have identified >200 loci associated with breast cancer (BC) risk. The majority of candidate causal variants (CCVs) are in non-coding regions and are likely to modulate cancer risk by regulating gene expression. We recently developed a scoring system, INQUISIT, to predict candidate risk genes at BC-risk loci. Here, we used pooled CRISPR activation and suppression screens to validate INQUISIT predictions, and to define the cancer phenotypes they mediate. We measured proliferation in 2D, 3D, and in immune-deficient mice, as well as the effect on the DNA damage response. We performed 60 CRISPR screens and identified 21 high-confidence INQUISIT predictions that mediate a cancer phenotype. We validated the direct regulation of a subset of genes by BC-risk variants using HiCHIP and CRISPRqtl. Furthermore, we show the utility of expression profiling for drug repurposing against these targets. We provide a platform for identifying gene targets of risk variants, and lay a blueprint of interventions for BC risk reduction and treatment.

cancer biology↗

bioRxiv2019

Chromatin interactome mapping at 139 independent breast cancer risk signals

Genome-wide association studies have identified 196 high confidence independent signals associated with breast cancer susceptibility. Variants within these signals frequently fall in distal regulatory DNA elements that control gene expression. We designed a Capture Hi-C array to enrich for chromatin interactions between the credible causal variants and target genes in six human mammary epithelial and breast cancer cell lines. We show that interacting regions are enriched for open chromatin, histone marks for active enhancers and transcription factors relevant to breast biology. We exploit this comprehensive resource to identify candidate target genes at 139 independent breast cancer risk signals, and explore the functional mechanism underlying altered risk at the 12q24 risk region. Our results demonstrate the power of combining genetics, computational genomics and molecular studies to rationalize the identification of key variants and candidate target genes at breast cancer GWAS signals.

molecular biology↗

bioRxiv2019

High-throughput allelic expression imbalance analyses identify candidate breast cancer risk genes

Fine-mapping of breast cancer GWAS regions has identified 195 high confidence signals containing more than 5,000 credible causal variants (CCVs). The CCVs are predominantly noncoding and enriched in regulatory elements and thus may confer the risk by altering gene expression in cis. We analyzed allelic expression imbalance (AEI) of genes surrounding known breast cancer signals, using normal breast and breast tumor transcriptome data and imputed genotypes. Fourteen genes, including NTN4, were identified whose expression was associated with CCV genotype. We showed that CCVs at this signal were located within an enhancer that physically interacts with the NTN4 promoter. Furthermore, knockdown of NTN4 in breast cells increased cell proliferation in vitro and tumor growth in vivo. Here, we present the most comprehensive AEI analysis of breast cancer CCVs resulting in identification of new candidate risk genes.

genetics↗