Biology subjects

Jin, S. C.

Publications and source records attributed to Jin, S. C..

7 recordsLinked to original sources

bioRxiv2026

Leveraging Human Pangenome for Improved Somatic Variant Detection

Somatic variant detection is technically challenging due to low variant allele fractions, the confounding presence of germline variation, and reference bias. Linear references such as GRCh38 miss sample-specific variation, causing misalignments and incorrect variant calls. Although telomere-to-telomere donor-specific assemblies (DSAs) accurately represent individual genomes, their application is limited by cost and technical barriers. Alternatively, the graph-based human pangenome provides a scalable framework to improve read alignment and perform genome inference. Here, we benchmarked somatic variant detection using GRCh38, graph-based pangenomes, and pangenome-inferred DSAs with a HapMap mixture dataset and the COLO829 melanoma cell line. Pangenome-guided alignment improves read mapping and somatic variant calling accuracy. Furthermore, personalized pangenomes partially reconstruct donor-specific genomic content, improving accuracy, reducing germline contamination, and enabling detection of events in loci absent or poorly represented in GRCh38. These findings demonstrate that graph-based and personalized pangenomes are effective strategies for enhancing somatic variant detection compared with GRCh38.

genomics↗

bioRxiv2025

Himito: a Graph-based Toolkit for Mitochondrial Genome Analysis using Long Reads

Understanding the genetic and epigenetic regulation of mitochondrial DNA (mtDNA) is essential for elucidating mechanisms of aging and disease. Long-read sequencing can span the entire mitochondrial genome and directly capture base-modification signals, yet analytical tools for such data remain limited. We developed Himito, a graph-based toolkit for analyzing mitochondrial genome using long reads. Himito filters reads originating from nuclear mitochondrial insertions (NUMTs), constructs a sequence graph to represent mtDNA diversity, assembles primary haplotypes, calls variants, and analyzes 5-methylcytosine (5mC) modifications within a unified framework. Benchmarking on high-quality reference datasets shows Himito achieves superior performance in assembly and variant calling compared with existing tools. Applied to the All of Us (AoU) v8 dataset, Himito identified pathogenic mtDNA variants, revealed population-scale haplogroup diversity, and uncovered age-related genetic and epigenetic patterns. These results demonstrate that long-read sequencing, combined with graph-based analysis, enables integrated characterization of mitochondrial genomic and epigenomic variation. Himito is available at https://github.com/broadinstitute/Himito.

bioinformatics↗

bioRxiv2025

A Pangenomic Method for Establishing a Somatic Variant Detection Resource in HapMap Mixtures

Somatic mosaicism is essential in human biology and disease, yet robust benchmarks are scarce. The SMaHT Consortium mixed six HapMap cell lines to create artificial somatic variants spanning 0.25% to 16.5% variant allele fractions. We developed a technology-agnostic method that builds pangenome graphs from individual assemblies to create unified benchmarking sets: > 6M single-nucleotide variants, 1.8M small insertions/deletions, 49K structural variations, and 10K mobile element insertions across autosomes, X, and mitochondrial chromosomes. We validated the variants using ultra-deep simulated reads and developed a binomial-based model to estimate coverage requirements for variant detection. Evaluating multiple callers showed CHM13 alignment improves structural variant detection and offers advantages in difficult-to-map regions compared to GRCh38. Systematic characterization showed regions with low detection rate are enriched in centromeres, satellite sequences, tandem repeats, and falsely duplicated genes. This accurate, versatile resource enables systematic evaluation of somatic variant detection technologies.

genomics↗

bioRxiv2025

SnakeAltPromoter Facilitates Differential Alternative Promoter Analysis

BackgroundAlternative promoter usage regulates isoform diversity in mammals, playing critical roles in development, disease, and cellular reprogramming. While Cap Analysis of Gene Expression (CAGE) enables precise transcription start site mapping, its high cost and limited coverage hinder scalability. In contrast, RNA-seq is abundant across biological contexts; several algorithms (ProActiv, Salmon, DEXSeq) infer promoter activity from these data, yet no unified, reproducible framework exists to execute, benchmark, and compare them or to scale alternative promoter analyses across large compendia. ResultsWe developed snakeAltPromoter, an end-to-end Snakemake workflow that ingests raw FASTQ files, performs quality control and alignment, quantifies promoter activity using three complementary strategies (junction-based, transcript-based, and first-exon-based), classifies promoters into major, minor/alternative, and inactive categories, and conducts both differential promoter activity and usage analysis. Crucially, snakeAltPromoter integrates a systematic benchmarking module against matched CAGE profiles to reveal method-specific strengths and limitations. ProActiv showed the highest concordance with CAGE in promoter classification, activity and differential analysis, Salmon was robust at low coverage and intronless cases. Overall, the complete workflow recovered a majority of CAGE-validated active promoters and processed a 50 M-read RNA-seq sample in around 2h on a 32-core node, demonstrating both accuracy and scalability. ConclusionssnakeAltPromoter is, to our knowledge, the first reproducible framework that pairs comparative method evaluation with scalable differential alternative promoter analysis. It provides concrete guidance for method selection under different experimental scenarios and enables high-throughput mining of promoter-level regulation from public RNA-seq repositories. Code and example data are freely available at https://github.com/YidanSunResearchLab/SnakeAltPromoter.git.

bioinformatics↗

bioRxiv2023

Dual impact of PTEN mutation on CSF dynamics and cortical networks via the dysregulation of neural precursors and their interneuron descendants

Expansion of the cerebrospinal fluid (CSF)-filled cerebral ventricles (ventriculomegaly) is the quintessential feature of congenital hydrocephalus (CH) but also seen in autism spectrum disorder (ASD) and several neuropsychiatric diseases. PTEN is frequently mutated in ASD; here, we show PTEN is a bona fide risk gene for the development of ventriculomegaly, including neurosurgically-treated CH. Pten-mutant hydrocephalus is associated with aqueductal stenosis due to the hyperproliferation of periventricular Nkx2.1+ neural precursors (NPCs) and CSF hypersecretion from inflammation-dependent choroid plexus hyperplasia. The hydrocephalic Pten-mutant cortex exhibits ASD-like network dysfunction due to impaired activity of Nkx2.1+ NPC-derived inhibitory interneurons. Raptor deletion or post-natal Everolimus corrects ventriculomegaly, rescues cortical deficits, and increases survival by antagonizing mTORC1-dependent Nkx2.1+ cell pathology. These results implicate a dual impact of PTEN mutation on CSF dynamics and cortical networks via the dysregulation of NPCs and their interneuron descendants. These data identify a non-surgical treatment target for hydrocephalus and have implications for other developmental brain disorders. HIGHLIGHTSO_LIPTEN de novo mutations are associated with cerebral ventriculomegaly in autism spectrum disorder (ASD) and congenital hydrocephalus (CH). C_LIO_LIPten-mutant hydrocephalus is associated with aqueductal stenosis due to the hyperproliferation of medial ganglionic eminence Nkx2.1+ neural precursors and CSF hypersecretion from inflammation-induced choroid plexus hyperplasia. C_LIO_LIThe hydrocephalic Pten-mutant cortex exhibits ASD-like network dysfunction due to impaired activity of Nkx2.1+ NPC-derived inhibitory interneurons. C_LIO_LImTORC1 inhibition via Raptor deletion or early post-natal treatment with rapamycin or everolimus increases survival and ameliorates Pten-mutant ventriculomegaly and cortical pathology. C_LI

neuroscience↗

bioRxiv2021

Quantifying concordant genetic effects of de novo mutations on multiple disorders

Exome sequencing on tens of thousands of parent-proband trios has identified numerous deleterious de novo mutations (DNMs) and implicated risk genes for many disorders. Recent studies have suggested shared genes and pathways are enriched for DNMs across multiple disorders. However, existing analytic strategies only focus on genes that reach statistical significance for multiple disorders and require large trio samples in each study. As a result, these methods are not able to characterize the full landscape of genetic sharing due to polygenicity and incomplete penetrance. In this work, we introduce EncoreDNM, a novel statistical framework to quantify shared genetic effects between two disorders characterized by concordant enrichment of DNMs in the exome. EncoreDNM makes use of exome-wide, summary-level DNM data, including genes that do not reach statistical significance in single-disorder analysis, to evaluate the overall and annotation-partitioned genetic sharing between two disorders. Applying EncoreDNM to DNM data of nine disorders, we identified abundant pairwise enrichment correlations, especially in genes intolerant to pathogenic mutations and genes highly expressed in fetal tissues. These results suggest that EncoreDNM improves current analytic approaches and may have broad applications in DNM studies.

genetics↗

bioRxiv2017

A common haplotype lowers SPI1 (PU.1) expression in myeloid cells and delays age at onset for Alzheimer’s disease

In this study we used age at onset of Alzheimers disease (AD), cerebrospinal fluid (CSF) biomarkers, and cis-expression quantitative trait loci (cis-eQTL) datasets to identify candidate causal genes and mechanisms underlying AD GWAS loci. In a genome-wide survival analysis of 40,255 samples, eight of the previously reported AD risk loci are significantly (P < 5x10-8) or suggestively (P < 1x10-5) associated with age at onset-defined survival (AAOS) and a further fourteen novel loci reached suggestive significance. Using stratified LD score regression we demonstrated a significant enrichment of AD heritability in hematopoietic cells of the myeloid and B-lymphoid lineage. We then investigated the impact of these 22 AAOS-associated variants on CSF biomarkers and gene expression in cells of the myeloid lineage. In particular, the minor allele of rs1057233 (G), within the previously reported CELF1 AD risk locus, shows association with higher age at onset of AD (P=8.40x10-6), higher CSF levels of A{beta}42 (P=1.2x10-4), and lower expression of SPI1 in monocytes (P=1.50x10-105) and macrophages (P=6.41x10-87). SPI1 encodes PU.1, a transcription factor critical for myeloid cell development and function. AD heritability is enriched within the SPI1 cistromes of monocytes and macrophages, implicating a myeloid PU.1 target gene network in the etiology of AD. Finally, experimentally altered PU.1 levels are correlated with phagocytic activity of BV2 mouse microglial cells and specific changes in the expression of multiple myeloid-expressed genes, including the mouse orthologs of AD-associated genes, APOE, CLU/APOJ, CD33, MS4A4A/MS4A6A, and TYROBP. Our results collectively suggest that lower SPI1 expression reduces AD risk by modulating myeloid cell gene expression and function.

neuroscience↗