Search bioRxiv⌕ Search

Biology subjects

O'Neil, S. T.

Publications and source records attributed to O'Neil, S. T..

3 recordsLinked to original sources

Phenomics Assistant: An Interface for LLM-based Biomedical Knowledge Graph Exploration

We introduce Phenomics Assistant, a prototype chat-based interface for querying the Monarch knowledge graph (KG), a comprehensive biomedical database. While unaided Large Large Language models (LLMs) are prone to mistakes in factual recall, their strong abilities in summarization and tool use suggest new opportunities to help non-expert users query and interact with complex data, while drawing on the KG to improve reliability of the answers. Leveraging the ability of LLMs to interpret queries in natural language, Phenomics Assistant enables a wide range of users to interactively discover relationships between diseases, genes, and phenotypes. To assess the reliability of our approach and compare the accuracy of different LLMs, we evaluated Phenomics Assistant answers on benchmark tasks for gene-disease association and gene alias queries. While comparisons across tested LLMs revealed differences in their ability to interpret KG-provided information, we found that even basic KG access markedly boosts the reliability of standalone LLMs. By enabling users to pose queries in natural language and summarizing results in familiar terms, Phenomics Assistant represents a new approach for navigating the Monarch KG.

bioinformatics↗

Accurate transcription start sites enable mining for the cis-regulatory determinants of tissue specific gene expression

Across tissues, gene expression is regulated by a combination of determinants, including the binding of transcription factors (TFs), along with other aspects of cellular state. Recent studies emphasize the importance of both genetic and epigenetic states - TF binding sites and binding site chromatin accessibility have emerged as potentially causal determinants of tissue specificity. To investigate the relative contributions of these determinants, we constructed three genome-scale datasets for both root and shoot tissues of the same Arabidopsis thaliana plants: TSS-seq data to identify Transcription Start Sites, OC-seq data to identify regions of Open Chromatin, and RNA-seq data to assess gene expression levels. For genes that are differentially expressed between root and shoot, we constructed a machine learning model predicting tissue of expression from chromatin accessibility and TF binding information upstream of TSS locations. The resulting model was highly accurate (over 90% auROC and auPRC), and our analysis of model contributions (feature weights) strongly suggests that patterns of TF binding sites within [~]500 nt TSS-proximal regions are predominant explainers of tissue of expression in most cases. Thus, in plants, cis-regulatory control of tissue-specific gene expression appears to be primarily determined by TSS-proximal sequences, and rarely by distal enhancer-like accessible chromatin regions. This study highlights the exciting future possibility of a native TF site-based design process for the tissue-specific targeting of plant gene promoters.

genomics↗

Patterns of divergence across the geographic and genomic landscape of a butterfly hybrid zone associated with a climatic gradient

Hybrid zones are a valuable tool for studying the process of speciation and for identifying the genomic regions undergoing divergence and the ecological (extrinsic) and non-ecological (intrinsic) factors involved. Here, we explored the genomic and geographic landscape of divergence in a hybrid zone between Papilio glaucus and Papilio canadensis. Using a genome scan of 28,417 ddRAD SNPs, we identified genomic regions under possible selection and examined their distribution in the context of previously identified candidate genes for ecological adaptations. We showed that differentiation was genome-wide, including multiple candidate genes for ecological adaptations, particularly those involved in seasonal adaptation and host plant detoxification. The Z-chromosome and four autosomes showed a disproportionate amount of differentiation, suggesting genes on these chromosomes play a potential role in reproductive isolation. Cline analyses of significantly differentiated genomic SNPs, and of species diagnostic genetic markers, showed a high degree of geographic coincidence (81%) and concordance (80%) and were associated with the geographic distribution of a climate-mediated developmental threshold (length of the growing season). A relatively large proportion (1.3%) of the outliers for divergent selection were not associated with candidate genes for ecological adaptations and may reflect the presence of previously unrecognized intrinsic barriers between these species. These results suggest that exogenous (climate-mediated) and endogenous (unknown) clines may have become coupled and act together to reinforce reproductive isolation. This approach of assessing divergence across both the genomic and geographic landscape can provide insight about the interplay between the genetic architecture of reproductive isolation and endogenous and exogenous selection.

evolutionary biology↗