Biology subjects

Liang, C. E.

Publications and source records attributed to Liang, C. E..

3 recordsLinked to original sources

bioRxiv2026

Uniformly processed transcriptome-wide alternative splicing profiles for pediatric cancer research

Alterations in regulatory processes like alternative splicing contribute to pediatric cancer development. Although splicing aberrations have been observed in pediatric leukemias, alternative splicing has yet to be studied in pediatric cancers at scale, due to a lack of uniformly processed, sample-level pediatric cancer splicing profiles with non-diseased tissue comparators. We address this need by quantifying splice event usage for a curated set of bulk RNA-seq datasets from the NCI's Therapeutically Applicable Research to Generate Effective Treatments (TARGET, n = 1152) and Genotype-Tissue Expression (GTEx, n = 1098) as a comparator. This Treehouse Splice Compendium is accompanied by a reproducible workflow that was used to generate the data in the compendium and reflects the largest known RNA-seq dataset processed by the splice quantification tool Shiba. The compendium is part of a suite of large, uniformly processed datasets aggregated by the UCSC Treehouse Childhood Cancer Initiative and Alex's Lemonade Stand Foundation's Childhood Cancer Data Lab, which include the Treehouse Expression Compendia, refine.bio, and the Single-cell Pediatric Cancer Atlas.

bioinformatics↗

bioRxiv2024

U2AF1 S34F enhances tumorigenic potential of lung cells by exhibiting synergy with KRAS mutation and altering response to environmental stress

Although U2AF1S34F is a recurrent splicing factor mutation in lung adenocarcinoma (ADC), U2AF1S34F alone is insufficient for producing tumors in previous models. Because lung ADCs with U2AF1S34F frequently have co-occurring KRAS mutations and smoking histories, we hypothesized that tumor-forming potential arises from U2AF1S34F interacting with oncogenic KRAS and environmental stress. To elucidate the effect of U2AF1S34F co-occurring with a second mutation, we generated human bronchial epithelial cells (HBEC3kt) with co-occurring U2AF1S34F and KRASG12V. Transcriptome analysis revealed that co-occurring U2AF1S34F and KRASG12V differentially impacts inflammatory, cell cycle, and KRAS pathways. Subsequent phenotyping found associated suppressed cytokine production, increased proliferation, anchorage-independent growth, and tumors in mouse xenografts. Additionally, HBEC3kts harboring U2AF1S34F alter splicing in stress granule protein genes, show increased stress granule formation, and have increased viability in cigarette smoke concentrate. Our results suggest that U2AF1S34F may potentiate transformation by granting precancerous cells survival advantage in environmental stress, permitting accumulation of additional mutations, like in KRAS, which synergize with U2AF1S34F to transform the cell.

cancer biology↗

bioRxiv2023

Systematic assessment of long-read RNA-seq methods for transcript identification and quantification

AbstractThe Long-read RNA-Seq Genome Annotation Assessment Project (LRGASP) Consortium was formed to evaluate the effectiveness of long-read approaches for transcriptome analysis. The consortium generated over 427 million long-read sequences from cDNA and direct RNA datasets, encompassing human, mouse, and manatee species, using different protocols and sequencing platforms. These data were utilized by developers to address challenges in transcript isoform detection and quantification, as well as de novo transcript isoform identification. The study revealed that libraries with longer, more accurate sequences produce more accurate transcripts than those with increased read depth, whereas greater read depth improved quantification accuracy. In well-annotated genomes, tools based on reference sequences demonstrated the best performance. When aiming to detect rare and novel transcripts or when using reference-free approaches, incorporating additional orthogonal data and replicate samples are advised. This collaborative study offers a benchmark for current practices and provides direction for future method development in transcriptome analysis.

genomics↗