Biology subjects

McCue, K.

Publications and source records attributed to McCue, K..

3 recordsLinked to original sources

bioRxiv2023

Improved modeling of RNA-binding protein motifs in an interpretable neural model of RNA splicing

Sequence-specific RNA-binding proteins (RBPs) play central roles in splicing decisions, but their exact binding locations and activities are difficult to predict. Here, we describe a modular splicing architecture that leverages in vitro-derived RNA affinity models for 79 human RBPs and the annotated human genome to produce improved models of RBP binding and activity. Binding and activity are modeled by separate Motif and Aggregator components that can be mixed and matched, enforcing sparsity to improve interpretability. Standard affinity models yielded reasonable predictions, but substantial improvements resulted from using a new Adjusted Motif (AM) architecture. While maintaining accurate modeling of in vitro binding, training these AMs on the splicing task yielded improved predictions of binding sites in vivo and of splicing activity, using independent crosslinking and massively parallel splicing reporter assay data. The modular structure of our model enables improved generalizability to other species (insects, plants) and to exons of different evolutionary ages.

genomics↗

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

A new method for rapid genome classification, clustering, visualization, and novel taxa discovery from metagenome

Current supervised phylogeny-based methods fall short on recognizing species assembled from metagenomic datasets from under-investigated habitats, as they are often incomplete or lack closely known relatives. Here, we report an efficient software suite, \"Genome Constellation\", that estimates similarities between genomes based on their k-mer matches, and subsequently uses these similarities for classification, clustering, and visualization. The clusters of reference genomes formed by Genome Constellation closely resemble known phylogenetic relationships while simultaneously revealing unexpected connections. In a dataset containing 1,693 draft genomes assembled from the Antarctic lake communities where only 40% could be placed in a phylogenetic tree, Genome Constellation improves taxa assignment to 61%. It revealed six clusters derived from new bacterial phyla and 63 new giant viruses, 3 of which missed by the traditional marker-based approach. In summary, we demonstrate that Genome Constellation can tackle the computational and algorithmic challenges in large-scale taxonomy analyses in metagenomics.

bioinformatics↗