About

Angela N Brooks is a Professor in the Division of the Baskin School of Engineering at the University of California, Santa Cruz, within the Department of Biomolecular Engineering. Her areas of expertise include bioinformatics, molecular biology, cancer, RNA biology, biology, biomedical sciences, and diversity. She holds a Ph.D. in Molecular and Cell Biology from UC Berkeley, obtained in 2011, and a B.S. in Biology with a specialization in Bioinformatics from UC San Diego, earned in 2005. Her research focuses on integrating bioinformatics and molecular biology to advance understanding in these fields. She is actively involved in research and teaching within the Global and Community Health Program, which is part of both the Social Sciences Division and the Physical & Biological Sciences Division at UC Santa Cruz.

Research topics

• Biology
• Genetics
• Computational biology
• Evolutionary biology
• Computer Science
• Artificial Intelligence
• Physics
• Optics
• Computer vision
• Cell biology
• Statistics
• Virology
• Cancer research
• Biological system
• Mathematics

Selected publications

• Beyond Histology: A Unified Transcriptomic Atlas Defines Lung Cancer Biologic States and Subtypes

  bioRxiv (Cold Spring Harbor Laboratory) · 2026-03-18

  articleOpen access

  Lung cancer encompasses multiple histological entities with substantial molecular heterogeneity that remain incompletely resolved at population scale. Here, we constructed a unified reference landscape of lung cancer by analyzing raw RNA sequencing data from 1,558 tumors spanning adenocarcinoma (n=753), squamous cell carcinoma (n=540), small cell lung cancer (n=150), and unclassified non-small cell lung cancer (n=80). Following batch correction, samples were embedded using PaCMAP to generate a continuous molecular atlas annotated with clinical and biological metadata. Rather than segregating strictly by histology, tumors organized along conserved transcriptional axes defined by tumor-intrinsic proliferative or metabolic programs and immune-infiltrated states. Consensus clustering resolved nine robust molecular clusters, including a female non-smoker-enriched adenocarcinoma subgroup, a neuroendocrine-like adenocarcinoma marked by ASCL1 activation, immune-associated regions, and bifurcation of both small cell and squamous carcinomas into biologically distinct states. Spatially-restricted expression of clinically actionable targets revealed state-specific vulnerabilities. Projection of patient tumors and patient-derived xenografts onto the atlas demonstrated preservation of transcriptional identity and enabled quantitative assessment of model fidelity. This unified framework redefines lung cancer as a structured continuum of transcriptional states with translational relevance.

  PublisherOA PDFDOI

• Abstract 1501: Cancer gene variant identification and functional interpretation using long-read RNA sequencing with FLAIR3

  Cancer Research · 2026-04-03

  articleSenior author

  Abstract Although the impact of single nucleotide variants (SNVs) and changes in transcription and RNA processing are often analyzed separately, a comprehensive analysis facilitates a complete understanding of how cancer gene alterations impact oncogenesis. In traditional short-read RNA sequencing, phasing of alternative exons and cancer variants is lost because the read lengths are much shorter than typical mRNA transcripts (average > 1kb). Here, we show that long-read RNA-seq (lrRNA-seq) can identify full-length transcript isoforms on which variants are expressed, which can be used to more accurately identify the functional impact of oncogenic variants. We developed FLAIR3, which performs an integrated analysis of SNVs, gene fusions, and alternative splicing using lrRNA-seq and predicts functional changes to the amino acid sequence. We performed ONT lrRNA-seq on three osteosarcoma cell lines and PacBio lrRNA-seq on paired normal and tumor tissue from two lung adenocarcinomas. We then used FLAIR3 to identify cancer driver variants and to determine how splicing modulates their expression and function. In the osteosarcoma samples, FLAIR3 revealed alternatively spliced gene fusions in cancer driver genes and TP53 gene fusions with intergenic regions, predicted to cause TP53 truncations. In the lung adenocarcinomas, FLAIR3 revealed isoform-biased expression of oncogenic BRAF V600E. Through an isoform-specific analysis of somatic SNVs in CDKN2A, we found that TP53 loss significantly co-occurs with CDKN2A missense or nonsense variants of the p16 isoform, but not with CDKN2A deep deletion. Damaging variants in the p16 isoform would not have the same damaging effects in p14 isoform, which functions through TP53; therefore, TP53 loss would be necessary to have complete loss of CDKN2A functions. A deep deletion of CDKN2A removes both p16 and p14 isoform function and would not need to have additional TP53 loss. These findings reveal how alternative splicing interacts with and modulates the function of oncogenic variants. Citation Format: Colette Felton, Andrea Galvez, Tanvi Damle, Kevin Levine, Mark Diekhans, Eunice Lopez Fuentes, Taylor Won, Christopher Vollmers, Alejandro Sweet-Cordero, Alice Berger, Angela N. Brooks. Cancer gene variant identification and functional interpretation using long-read RNA sequencing with FLAIR3 [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 1501.

  PublisherDOI

• Abstract 5915: Utility of long-read RNA-sequencing for isoform and fusion discovery in lung cancer

  Cancer Research · 2026-04-03

  article

  Abstract Isoform expression is frequently dysregulated in lung cancer via cis-acting splice site mutations or trans-acting mutations in splicing factors such as U2AF1, RBM10, and SF3B1. While prior studies have sought to characterize the isoform landscape in cancers, the short reads of next-generation sequencing platforms, ranging in length from 50-150 bp, preclude the accurate phasing of alternative splicing events across the full transcript length (typically exceeding 1 kb). To provide a more comprehensive and accurate view of expressed isoforms in lung cancer, we performed long-read RNA-sequencing on 32 matched tumor/normal pairs of early stage resected lung adenocarcinoma, four biopsies from tumors that had progressed on targeted therapy treatment, and 14 non-small cell lung cancer cell lines. RNA was isolated from fresh frozen tissue specimens and cDNA prepared using the PacBio Kinnex full-length isoform method. PacBio HiFi data were generated per manufacturer's recommendations at the University of Washington Long Reads Sequencing Center or UC Davis DNA Technologies core. Libraries were sequenced on the PacBio Revio system to a read depth of >10M HiFi reads per sample, providing >80% saturation of known isoforms. FLAIR3 was used to identify and quantify isoforms, including novel isoforms, and phase isoform expression with somatic mutations including SNVs and insertion/deletion mutations. Analysis of alternative splicing patterns in RAS-pathway genes identified increased expression of the minor KRAS isoform, KRAS4A, in tumors compared to normal samples. Phasing of somatic variants enabled integration of KRAS mutation with KRAS isoform expression and validated the previously identified role of KRAS Q61 variants on aberrant KRAS splicing. In addition, we identified deletions predicted to inactivate tumor suppressor genes and identified novel rearrangements in clinically actionable oncogenes including EGFR. Together these data demonstrate the utility of long-read RNA sequencing for accurate and complete isoform characterization in cancer. Citation Format: Kevin Levine, Colette Felton, Tanvi Damle, Christina Baik, Angela Norie Brooks, Alice H. Berger. Utility of long-read RNA-sequencing for isoform and fusion discovery in lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 5915.

  PublisherDOI

• SMAdd-seq: probing chromatin accessibility with small molecule DNA intercalation and nanopore sequencing

  Nucleic Acids Research · 2025-07-19 · 1 citations

  articleOpen accessSenior author

  Studies of in vivo chromatin organization have relied on the accessibility of the underlying DNA to nucleases or methyltransferases, which is limited by their requirement for purified nuclei and enzymatic treatment. Here, we introduce a nanopore-based sequencing technique called small-molecule adduct sequencing (SMAdd-seq), where we profile chromatin accessibility by treating nuclei or intact cells with a small molecule, angelicin. Angelicin preferentially forms photoadducts with thymine bases in linker DNA, thereby labeling accessible DNA regions. By applying SMAdd-seq in Saccharomyces cerevisiae, we demonstrate that angelicin-modified DNA can be detected by its distinct nanopore current signals. To systematically identify angelicin modifications and analyze chromatin structure, we developed a neural network model, NEural network for mapping MOdifications in nanopore long-reads (NEMO). NEMO accurately called expected nucleosome occupancy patterns near transcription start sites at both bulk and single-molecule levels. We observe heterogeneity in chromatin structure and identify clusters of single-molecule reads with varying configurations at specific yeast loci. Furthermore, SMAdd-seq performs equivalently on purified yeast nuclei and intact cells, indicating the promise of this method for in vivo chromatin labeling on long single molecules to measure native chromatin dynamics and heterogeneity.

  PublisherOA PDFDOI

• Author Correction: Genomic basis for RNA alterations in cancer

  UNC Libraries · 2025-03-13

  articleOpen access
  PublisherDOI

• A novel splice site variant in <i>DEGS1</i> leads to aberrant splicing and loss of DEGS1 enzyme activity, a VUS resolved

  Human Genetics · 2025-04-11 · 1 citations

  preprintOpen access

  Purpose: variants have been reported in individuals with autosomal recessive hypomyelinating leukodystrophy 18 (HLD18; MIM# 618404). We sought to resolve a 5' +4/+5 splice site variant of uncertain significance found in three individuals with HLD features. Methods: We used next-generation DNA and transcriptome sequencing, cell-based splicing assays, and tandem mass spectrometry to detect and characterize the splice site variant. We then performed RNA structure probing and conventional antisense oligonucleotide screening to investigate molecular mechanisms for potential therapeutic intervention. Results: 5' splice site variant, c.825+4_825+5delAGinsTT (NM_003676.4) was identified in all three participants. Although the gene has been associated with autosomal recessive hypomyelinating leukodystrophy, the variant has not been previously reported in any available databases or literature. We show that the splice site variant: 1) was sufficient to induce exon two skipping in most detected transcripts; 2) resulted in structural changes to the 5' and 3' splice site regions using RNA structure probing; and 3) corresponds to plasma sphingolipid profiles consistent with loss of sphingolipid delta(4)-desaturase activity. Discussion: variant c.825+4_825+5delAGinsTT is pathogenic and suggested a mechanistic model to explain how exon two skipping is induced.

  PublisherDOI

• STEM-26. COMPREHENSIVE FUNCTIONAL GENOMIC SCREENS REVEAL HUMAN TRANSCRIPTION FACTORS REQUIRED TO MAINTAIN GLIOBLASTOMA OLIGODENDROCYTE PROGENITOR CELL-LIKE IDENTITY

  Neuro-Oncology · 2025-11-01

  articleOpen access

  Abstract For glioblastoma (GBM), like other solid tumors, intratumoral heterogeneity is likely a critical factor in promoting tumor growth, homeostasis, and therapeutic response. Recent applications of single-cell genomics techniques have revealed the scope and nature of GBM cell diversity. However, these techniques do not allow for the experimental manipulation of these same tumor subpopulations, raising a critical barrier to understanding tumor biology and developing effective therapies. To overcome this barrier, we developed endogenous gene reporter systems to enable the isolation, characterization, and manipulation of key GBM subpopulations directly in patient tumor isolates. This approach utilizes streamlined techniques for gene editing in GBM stem-like cells (GSCs), which eliminate the need for the cloning of individual cells. As proof of concept, we applied this approach to two genes in hGSC isolates: OLIG1 (GBM-OPC marker) and SOX9 (GSC/NSC stem cell homeostasis). We targeted the 3’ exon of each gene so that EGFP or RFP are in-frame with the upstream exon but separated by a 2A ribosome skip sequence. We then employed these GSC reporter isolates to comprehensively screen human transcription factors using a CRISPR-Cas9 library and LV-ORF library (1836 genes and 3548 isoforms) to identify transcription factors that activate or repress OLIG1 and SOX9. From these screens we identified 15 genes necessary and sufficient for regulating OLIG1 promoter activity, including known and novel regulators. These included SOX9 itself, which we find is a key factor linking OPC identify with self-renewal of GSCs. In addition, we identified dozens of transcription factor isoforms (validated by long read RNA-seq) that impact reporter activity, as well as ectopic factors not normally expressed in our GSCs which, nonetheless, significantly alter OLIG1 and SOX9 expression. At this meeting, we report results of these screens and present a functional genetic map of factors affecting the GBM-OPC cell identity, self-renewal, and plasticity.

  PublisherOA PDFDOI

• Abstract 2396: Gene fusion and variant-aware isoform detection with functional prediction from long-read RNA sequencing

  Cancer Research · 2025-04-21

  articleSenior author

  Abstract Although most cancer variant profiling is done with short-read-based methods, many cancers are driven by structural variants that are difficult to detect with these methods. Our current approach to understanding driver mutations is also limited to single variants and rarely considers the context in which they are expressed. Alterations in the expression and splicing of genes containing variants can both impact their tumorigenicity and allow them to develop resistance to therapies. We present FLAIR3, which generates a custom transcriptome from long-read RNA sequencing and identifies SNVs, insertions, deletions, and gene fusions from alignment to this transcriptome. We show that this improves accuracy above alignment to the genome or annotated transcripts. FLAIR3 then integrates these variants with the transcripts to predict functional changes to the amino acid sequence. We apply this approach to patient-derived osteosarcoma cell lines, a cancer whose pathology is driven by complex structural variation. In these samples, we identify more complex changes to previously identified amplified drivers such as alternative splicing of MYC and alternative splicing of a gene fusion in CCNE1. We also identify a novel set of actionable cancer gene alterations not previously detected by short-read methods. This includes a large deletion in KEAP1 and a number of novel gene fusions, including TP53 and other genes fused with intergenic regions and a complex 4-locus fusion in NOTCH1 not detected by any preexisting tools. We then validated the protein sequence of novel fusions with Quantum-Si protein sequencing. This analysis shows that long-read RNA sequencing can detect novel variants in actionable cancer genes and that integrating splicing and variant alterations provides the most complete picture of gene alterations in cancer. Citation Format: Colette Felton, Andrea Galvez, Leanne Sayles, Christopher Vollmers, Alejandro Sweet-Cordero, Angela Brooks. Gene fusion and variant-aware isoform detection with functional prediction from long-read RNA sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2396.

  PublisherDOI

• Detecting haplotype-specific transcript variation in long reads with FLAIR2

  Genome biology · 2024-07-02 · 20 citations

  articleOpen accessSenior author

  BACKGROUND: RNA-seq has brought forth significant discoveries regarding aberrations in RNA processing, implicating these RNA variants in a variety of diseases. Aberrant splicing and single nucleotide variants (SNVs) in RNA have been demonstrated to alter transcript stability, localization, and function. In particular, the upregulation of ADAR, an enzyme that mediates adenosine-to-inosine editing, has been previously linked to an increase in the invasiveness of lung adenocarcinoma cells and associated with splicing regulation. Despite the functional importance of studying splicing and SNVs, the use of short-read RNA-seq has limited the community's ability to interrogate both forms of RNA variation simultaneously. RESULTS: We employ long-read sequencing technology to obtain full-length transcript sequences, elucidating cis-effects of variants on splicing changes at a single molecule level. We develop a computational workflow that augments FLAIR, a tool that calls isoform models expressed in long-read data, to integrate RNA variant calls with the associated isoforms that bear them. We generate nanopore data with high sequence accuracy from H1975 lung adenocarcinoma cells with and without knockdown of ADAR. We apply our workflow to identify key inosine isoform associations to help clarify the prominence of ADAR in tumorigenesis. CONCLUSIONS: Ultimately, we find that a long-read approach provides valuable insight toward characterizing the relationship between RNA variants and splicing patterns.

  PublisherOA PDFDOI

• Steering research on mRNA splicing in cancer towards clinical translation

  Nature reviews. Cancer · 2024-10-09 · 38 citations

  reviewOpen access
  PublisherOA PDFDOI

Recent grants

• UCSC Research Mentoring Internship Program: An Initiative to Increase Diversity and Inclusion in Genomics Research

  NIH · $3.7M · 2013–2026

• UC Santa Cruz Training Program In Genomic Sciences

  NIH · $875k · 2015–2021

Frequent coauthors

• Natalie R. Davidson

  244 shared

• André Kahles

  SIB Swiss Institute of Bioinformatics

  225 shared

• Kjong-Van Lehmann

  RWTH Aachen University

  210 shared

• Gunnar Rätsch

  SIB Swiss Institute of Bioinformatics

  209 shared

• Roland F. Schwarz

  Berlin Institute for the Foundations of Learning and Data

  166 shared

• Stefan G. Stark

  ETH Zurich

  159 shared

• Rory Johnson

  University Hospital of Bern

  151 shared

• Thomas J. Mitchell

  Wellcome Sanger Institute

  150 shared

Education

• Ph.D., Public Health

  University of California, Los Angeles

  2005

• M.S., Public Health

  University of California, Los Angeles

  2001

• B.A., International Development Studies

  University of California, Los Angeles

  1998