Biology subjects

Su, X. A.

Publications and source records attributed to Su, X. A..

7 recordsLinked to original sources

bioRxiv2026

Streamline CNV - A Handy Nextflow Pipeline for Chromosomal Copy Number Variation Analysis

Background Aneuploidy, characterized by imbalanced chromosomal copy number variation (CNV), occurs in both normal somatic tissues and a wide range of diseases. Low pass whole genome sequencing (LP-WGS) to detect CNVs in cells and tissues has been widely used in all biological research. Existing informatics tools for detecting CNV often require computational expertise, often posing challenges for wet-lab biologists. To address this need, we developed Streamline CNV (SLCNV) - a user-friendly and flexible copy number analysis pipeline that allows researchers to perform many copy number-related analyses steps with a single, straightforward command. Results Streamline CNV is based on Nextflow and is packaged in a Docker image that can be executed using Singularity, making it portable and reproducible across different user environments. The pipeline automatically processes input data, performs sequencing quality control to filter problematic samples, outputs mapping statistics, CNV calling, and generates outputs including intuitive CNV plots, segmentation files (with statistics), annotation of genes on altered chromosomes, evaluation of proportion of chromosomal regions that are non-euploid. Based on user preferences, it can cluster samples solely based on CNV patterns, map the genomic location and density of genes of interest along chromosomes, and visually highlight regions with evident CNVs. In addition, it allows users to select and order chromosomes for display in plots, define sample label color palettes, and choose whether to include sample labels in the clustering visualizations. It also allows users to specify the amount of computing resources to allocate to the pipeline, such as CPU, memory, and runtime. Streamline CNV can be customizable and upgradable. It works with any species and genome assembly and efficiently supports both single-cell and bulk sequencing data with improved performance coding. Jobs can be distributed across cores of a basic Unix workstation, multiple nodes in a high-performance computing cluster using the Slurm scheduler, or cloud environments, as needed. Conclusions We demonstrated the tool using an in-house sequencing dataset of human and mouse cell lines. Our results showed that the Streamline CNV pipeline effectively detected copy number patterns and generated informative summaries. It annotated the findings by identifying affected genes within the copy-number segments and at the break-end regions. It also reported the proportions of altered chromosomal regions impacted by copy number changes for each sample. The clustering plot demonstrated the relationships between samples based on their copy number profiles. Gene density plots aid in interpreting how genes from distinct pathways are associated with CNV pattern alterations. This tool enables researchers, regardless of bioinformatics expertise, to perform comprehensive CNV analyses across a wide range of scenarios. It also facilitates the interpretation of the copy number results and makes it possible for transforming raw CNV data into further exploration of meaningful biological insights.

bioinformatics↗

bioRxiv2026

Stage-Specific Regulation of DNA Damage Repair by the Circadian Regulator, CRY1, in Prostate Cancer

Circadian dysregulation is increasingly linked to prostate cancer (PCa) progression, yet its role in directing DNA damage response (DDR) pathway selection remains poorly understood. Here, we identify circadian cryptochrome 1 (CRY1), a core circadian regulator, as a stage-specific determinant of DDR dependencies. Integrated transcriptomic and CRISPR-based analyses reveal that CRY1 promotes non-homologous end joining (NHEJ) and base excision repair (BER)-associated programs in hormone-sensitive disease (HTS), while driving a switch toward homologous recombination (HR) dependency in castration-resistant prostate cancer (CRPC). Mechanistically, CRY1 couples proliferative signaling to genome maintenance, enabling tumor cells to tolerate genotoxic stress and sustain progression. Notably, loss of CRY1 exposes distinct, context-dependent DDR vulnerabilities, revealing repair plasticity as a targetable actionable feature of disease evolution. These findings position CRY1 as a central regulator of DDR rewiring and support CRY1-directed combination strategies with DDR inhibitors as a rationale to delay or prevent progression to advanced, treatment-resistant PCa.

cancer biology↗

bioRxiv2025

Integrated proteogenomics uncovers ancestry-specific and shared molecular drivers in localized prostate cancer

Our integrative proteogenomics (genome, proteome and phosphoproteome) of localized prostate cancer (PCa) in an equal-access Military Health System patient cohort (57 Black and 55 White) revealed significant ancestry-associated differences. Somatic and germline regulatory differences converged on androgen, metabolic, PI3K/AKT/mTOR, and DNA damage response (DDR) pathways, with ancestry-specific immune- and stromal-associated signals. Black patients displayed greater genomic variability, enhanced androgen response, fatty-acid metabolism, and epithelial-mesenchymal transition, while White patients showed prevalent DDRG alterations, activated oncogenic signaling (MYC, E2F, mTORC1), and cell cycle regulation. Phosphoproteomics highlighted distinct kinase activities and candidate druggable dependencies. Multiomics integration revealed three exploratory tumor subtypes whose distinct biological programs were reproducibly validated. Ancestry-associated eQTLs supported inherited regulation of the proteome independent of CNAs. Ancestry-specific CNA and protein panels improved progression risk prediction beyond PSA and pathology models. These findings provide a framework for ancestry-informed prognostic models and generate testable hypotheses for precision therapies to reduce outcome disparities.

cancer biology↗

bioRxiv2024

SpotMAX: a generalist framework for multi-dimensional automatic spot detection and quantification

The analysis of spot-like structures is a widespread task in microscopy-based cell biology. Existing solutions are typically specific to single applications and do not use multi-dimensional information from 5D datasets. Therefore, experimental scientists often resort to subjective manual annotation. Here, we present SpotMAX, a generalist AI-driven framework for automated spot detection and quantification. SpotMAX leverages the full scope of multi-dimensional datasets with an easy-to-use interface and an embedded framework for cell segmentation and tracking. SpotMAX outperforms state-of-the-art tools, and in some cases, even expert human annotators. We applied SpotMAX across diverse experimental questions, ranging from meiotic crossover events in C. elegans to mitochondrial DNA dynamics in S. cerevisiae and telomere length in mouse stem cells, leading to new biological insights. With its flexibility in integrating AI workflows, we anticipate that SpotMAX will become the standard for spot analysis in microscopy data. Source code: https://github.com/SchmollerLab/SpotMAX

cell biology↗

bioRxiv2024

AR coactivators, CBP/p300, are critical mediators of DNA repair in prostate cancer

Castration resistant prostate cancer (CRPC) remains an incurable disease stage with ineffective treatments options. Here, the androgen receptor (AR) coactivators CBP/p300, which are histone acetyltransferases, were identified as critical mediators of DNA damage repair (DDR) to potentially enhance therapeutic targeting of CRPC. Key findings demonstrate that CBP/p300 expression increases with disease progression and selects for poor prognosis in metastatic disease. CBP/p300 bromodomain inhibition enhances response to standard of care therapeutics. Functional studies, CBP/p300 cistrome mapping, and transcriptome in CRPC revealed that CBP/p300 regulates DDR. Further mechanistic investigation showed that CBP/p300 attenuation via therapeutic targeting and genomic knockdown decreases homologous recombination (HR) factors in vitro, in vivo, and in human prostate cancer (PCa) tumors ex vivo. Similarly, CBP/p300 expression in human prostate tissue correlates with HR factors. Lastly, targeting CBP/p300 impacts HR-mediate repair and patient outcome. Collectively, these studies identify CBP/p300 as drivers of PCa tumorigenesis and lay the groundwork to optimize therapeutic strategies for advanced PCa via CBP/p300 inhibition, potentially in combination with AR-directed and DDR therapies.

cancer biology↗

bioRxiv2022

Nucleotide depletion promotes cell fate transitions by inducing DNA replication stress

Control of cellular identity requires coordination of developmental programs with environmental factors such as nutrient availability, suggesting that modulating aspects of metabolism could alter cell state along differentiation trajectories. Here we find that nucleotide depletion and DNA replication stress are common drivers of cell state progression across a variety of normal and transformed hematopoietic systems. DNA replication stress-induced cell state transitions begin during S phase and are independent of ATR/ATM checkpoint signaling, double-stranded DNA break formation, and changes in cell cycle length. In systems where differentiation is blocked by oncogenic transcription factor expression, replication stress leads to increased activity at primed regulatory loci and expression of lineage-appropriate maturation genes while progenitor TF activity is still present. Altering the baseline cell state by manipulating the cohort of transcription factors expressed redirects the effect of replication stress towards induction of a different set of lineage-specific genes. The ability of replication stress to selectively activate primed maturation programs across different cellular contexts suggests a general mechanism by which metabolism can promote lineage-appropriate and potentially therapeutically relevant cell state transitions.

cancer biology↗

bioRxiv2021

THO and TRAMP complexes prevent transcription-replication conflicts, DNA breaks, and CAG repeat contractions

Expansion of structure-forming CAG/CTG repetitive sequences is the cause of several neurodegenerative disorders and deletion of repeats is a potential therapeutic strategy. Transcription-associated mechanisms are known to cause CAG repeat instability. In this study, we discovered that Thp2, an RNA export factor and member of the THO complex, and Trf4, a key component of the TRAMP complex involved in nuclear RNA degradation, are necessary to prevent CAG fragility and repeat contractions in a S. cerevisiae model system. Depletion of both Thp2 and Trf4 proteins causes a highly synergistic increase in CAG repeat fragility, indicating a complementary role of the THO and TRAMP complexes in preventing genome instability. Loss of either Thp2 or Trf4 causes an increase in RNA polymerase stalling at the CAG repeats and genome-wide transcription-replication conflicts (TRCs), implicating impairment of transcription elongation as a cause of CAG fragility and instability in their absence. Analysis of the effect of RNase H1 overexpression on CAG fragility and TRCs suggests that co-transcriptional R-loops are the main cause of CAG fragility in the thp2{Delta} mutants. In contrast, CAG fragility and TRCs in the trf4{Delta} mutant can be compensated for by RPA overexpression, suggesting that excess unprocessed RNA in TRAMP4 mutants leads to reduced RPA availability and high levels of TRCs. Our results show the importance of RNA surveillance pathways in preventing RNAPII stalling, TRCs, and DNA breaks, and show that RNA export and RNA decay factors work collaboratively to maintain genome stability.

genetics↗