BioML Seminar 2.2 - A Unifying Model of Gene Regulation with David Kelley

​David Kelley is a Principal Investigator at Calico Life Sciences, where he studies gene regulation in aging. He completed his PhD in computer science at the U. of Maryland with Steven Salzberg, working on algorithms for genome assembly and gene prediction. Subsequently, he worked as a postdoc with John Rinn at Harvard on computational analyses of long noncoding RNA regulation and function. David developed the deep convolutional neural network toolkits Basset, Basenji, and Enformer to predict tissue-specific regulatory activity of DNA sequences. His group is interested in fully elucidating the mechanisms by which a regulatory environment acts on whole chromosomes to determine the expression of every gene. At Calico, he’s applying such models to study how disturbed regulatory connections influence the increased rate of disease onset over human lifespans.

​Title: Predicting RNA-seq coverage from DNA sequence as a unifying model of gene regulation
Abstract: Sequence-based machine learning models trained on genome-scale biochemical assays improve our ability to interpret genetic variants by providing functional predictions describing their impact on the cis-regulatory code. I’ll introduce a new model, Borzoi, which learns to predict cell- and tissue-specific RNA-seq coverage from DNA sequence. Using statistics derived from Borzoi’s predicted coverage, we isolate and accurately score variant effects across multiple layers of regulation, including transcription, splicing, and polyadenylation. Evaluated on QTLs, Borzoi is competitive with, and often outperforms, state-of-the-art models trained on individual regulatory functions. By applying attribution methods to the derived statistics, we extract cis-regulatory patterns driving RNA expression and post-transcriptional regulation in normal tissues. The wide availability of RNA-seq data across species, conditions, and assays profiling specific aspects of regulation emphasizes the potential of this approach to decipher the mapping from DNA sequence to regulatory function.