Yang Li

This paper introduces RAD-seq, a method to quantify RNA accessibility by protein binding, and shows it can detect RBP footprints and RNA structure changes under stress.

Torino, a reference-free framework for isoform discovery, identifies RNA processing patterns linked to disease risk by analyzing read coverage variation across species and disease states.

This study develops a small-molecule approach to reduce prion protein by modulating pre-mRNA splicing, achieving ~70% PrP reduction in cells and demonstrating synergistic effects with a Luc7L activator in mice.

The paper identifies diet-dependent genetic loci affecting development time in Drosophila using outbred populations and phenotyping.

The paper identifies sex-specific genetic regulatory effects in chickens using whole-genome sequencing and transcriptomes, revealing sex-dependent gene regulation and structural variants.

The paper identifies chromatin accessibility QTLs (caQTLs) in immune cells and finds they colocalize more with GWAS loci than eQTLs, but often lack downstream gene expression effects.

LeafCutter2 identifies and quantifies unproductive splicing events from RNA-seq data, revealing their role in gene regulation and disease, including Alzheimer's.

The paper links trans-pQTLs to protein-protein interactions and GWAS loci, identifying therapeutic targets in autoimmune diseases.

The paper presents a chromosome-scale genome assembly of Alvinella pompejana and analyzes its gene content to understand adaptations to extreme environments.

The paper identifies two distinct categories of differentially expressed genes in tumor subclones based on their regulatory and functional characteristics using single-cell transcriptomic and genomic data from colorectal cancer patients.

The paper estimates the impact of alternative splicing coupled with nonsense-mediated decay on gene expression levels using population-scale genomic data and perturbation experiments.

The paper shows ancestry-related differences in transcriptional response to influenza are driven by epigenetic variation and genetic control of enhancer activity.

Pangolin is a deep learning model that predicts RNA splicing from DNA sequence, outperforming existing methods and accurately identifying pathogenic variants.

The paper introduces CoLa-seq to profile splicing timing and identifies genetic factors influencing co-transcriptional splicing in human cells.

The paper examines how regulatory variants in immune cells affect genetic risk for immune traits by analyzing QTLs and GWAS loci overlap.

Dmatch aligns scRNA-seq datasets to reduce batch effects without over-correction, enabling cell-type-specific comparisons and eQTL mapping.

The paper presents 64 haplotype-resolved human genomes using long-read sequencing and identifies structural variants, SV-eQTLs, and adaptive selection candidates.

The paper uses single-cell RNA-sequencing to show genetic ancestry affects gene expression during viral infection, with effects varying by cell type.

The paper identifies genetic variants affecting alternative polyadenylation (APA) and shows their impact on gene expression, protein levels, and disease risk.

The paper introduces LATE and TRANSLATE autoencoder-based methods for imputing single-cell RNA-seq data, showing improved performance over existing methods.

The paper proposes a model where trans-acting variation drives most genetic variance in complex traits through co-regulated networks of core genes.

This study identifies variance QTLs (vQTLs) in human iPSCs using scRNA-seq, finding that genetic variants affect gene expression variance but with smaller phenotypic impact than mean expression QTLs.

This study prioritizes Parkinson’s Disease genes using transcriptomic data, identifying 29 peripheral monocyte and 44 prefrontal cortex gene associations, including novel and known genes like MAPT.

This study identifies splicing variations in aging brains linked to Alzheimer’s Disease, finds genetic regulation of splicing, and highlights shared pathways with other neurodegenerative diseases.

The paper examines regulatory variation in iPSCs and differentiated cells, finding lower individual variation in iPSCs and identifying shared chromatin regions for some cell type-specific QTLs.

LeafCutter quantifies RNA splicing variation from short-read RNA-seq data without transcript annotations, identifying more sQTLs and improving disease gene associations.