Biomedical subjects

Vineet Bafna

Publications and source records attributed to Vineet Bafna.

At least 19 recordsLinked to original sources

PubMed2026

scAmp enables focal gene amplification analysis from single-cell data.

Oncogene amplification on extrachromosomal DNA is a common driver of tumor progression and is associated with acquired drug resistance and poor patient survival. While bulk whole genome sequencing studies have revealed the landscape of genes amplified on extrachromosomal DNA in tumors, it remains challenging to study the subclonal heterogeneity and functional (e.g., transcriptomic) consequences of extrachromosomal DNA on tumors. To address this, we introduce scAmp: a probabilistic algorithm for detecting and analyzing extrachromosomal DNA from single-cell datasets. Using well-characterized cell lines, we demonstrate that scAmp has improved specificity over bulk genome sequencing in predicting extrachromosomal DNA status and can resolve the status of chromosomal amplifications that were historically extrachromosomal. We further showcase scAmp by analyzing 73 patient tumors profiled with single-cell assay for transposase-accessible chromatin by sequencing, where we characterize the subclonal evolution of subclones with extrachromosomal DNA and identify the effect of these amplifications on the chromatin accessibility landscape of cancer cells. Finally, we provide proof-of-concept analyses that scAmp aids in the detection of extrachromosomal DNA from clinical histopathology assays. Together, we anticipate that scAmp will broadly enable further studies - both retrospective and prospective - that dissect critical questions of how extrachromosomal DNAs affect cancer cells and the tumors in which they reside.

Humans↗

PubMed2026

Detecting and reconstructing breakage-fusion-bridge cycles from long-read sequencing using BFBArchitect.

MOTIVATION: Focal oncogene amplification is a key driver of tumor progression. Remarkably, the increased pathology depends on the context-whether the amplification is extrachromosomal (ecDNA) or intrachromosomal. EcDNA amplifications promote heterogeneity, therapy resistance, and poor prognosis. Focal intrachromosomal amplifications often arise through breakage-fusion-bridge (BFB) cycles, which produce highly rearranged but stable chromosomes. Distinguishing BFB from ecDNA remains challenging due to overlapping genomic signatures. To address this, we present BFBArchitect, a computational method leveraging long-read Oxford Nanopore data to identify BFB sequences consistent with both copy number and structural variations. RESULTS: We provide a novel combinatorial characterization of BFB, which naturally leads to an integer linear programming (ILP) optimization. The ILP optimization generates a BFB sequence that best explains experimentally observed copy numbers and foldback structural variants. We implement this idea in a tool called BFBArchitect, which achieves near-perfect accuracy in distinguishing BFB from non-BFB structures in extensive simulations as well as on 18 validated tumor samples. Moreover, it generates sequence-level BFB reconstructions that provide mechanistic insights into BFB formation, including repair mechanisms with template switching and other structural variants, and recapture of telomere for stabilization. AVAILABILITY AND IMPLEMENTATION: BFBArchitect is available at https://github.com/AmpliconSuite/BFBArchitect.

Sequence Analysis, DNA↗

PubMed2025

Enhancer activation from transposable elements in extrachromosomal DNA.

Extrachromosomal DNA (ecDNA) drives oncogene amplification and intratumoral heterogeneity in aggressive cancers. While transposable element (TE) reactivation is common in cancer, its role on ecDNA remains unexplored. Here, we map the 3D architecture of MYC-amplified ecDNA in colorectal cancer cells and identify 68 ecDNA-interacting elements (EIEs)-genomic loci enriched for TEs that are frequently integrated onto ecDNA. We focus on an L1M4a1#LINE/L1 fragment co-amplified with MYC, which functions only in the ecDNA amplified context. Using CRISPR-CATCH, CRISPR interference, and reporter assays, we confirm its presence on ecDNA, enhancer activity, and essentiality for cancer cell fitness. These findings reveal that repetitive elements can be reactivated and co-opted as functional rather than inactive sequences on ecDNA, potentially driving oncogene expression and tumor evolution. Our study uncovers a mechanism by which ecDNA harnesses repetitive elements to shape cancer phenotypes, with implications for diagnosis and therapy.

Journal Article↗

PubMed2025

Analysis of targeted and whole genome sequencing of PacBio HiFi reads for a comprehensive genotyping of gene-proximal and phenotype-associated Variable Number Tandem Repeats.

Variable Number Tandem repeats (VNTRs) refer to repeating motifs of size greater than five bp. VNTRs are an important source of genetic variation, and have been associated with multiple Mendelian and complex phenotypes. However, the highly repetitive structures require reads to span the region for accurate genotyping. Pacific Biosciences HiFi sequencing spans large regions and is highly accurate but relatively expensive. Therefore, targeted sequencing approaches coupled with long-read sequencing have been proposed to improve efficiency and throughput. In this paper, we systematically explored the trade-off between targeted and whole genome HiFi sequencing for genotyping VNTRs. We curated a set of 10 , 787 gene-proximal (G-)VNTRs, and 48 phenotype-associated (P-)VNTRs of interest. Illumina reads only spanned 46% of the G-VNTRs and 71% of P-VNTRs, motivating the use of HiFi sequencing. We performed targeted sequencing with hybridization by designing custom probes for 9,999 VNTRs and sequenced 8 samples using HiFi and Illumina sequencing, followed by adVNTR genotyping. We compared these results against HiFi whole genome sequencing (WGS) data from 28 samples in the Human Pangenome Reference Consortium (HPRC). With the targeted approach only 4,091 (41%) G-VNTRs and only 4 (8%) of P-VNTRs were spanned with at least 15 reads. A smaller subset of 3,579 (36%) G-VNTRs had higher median coverage of at least 63 spanning reads. The spanning behavior was consistent across all 8 samples. Among 5,638 VNTRs with low-coverage ( < 15), 67% were located within GC-rich regions ( > 60%). In contrast, the 40X WGS HiFi dataset spanned 98% of all VNTRs and 49 (98%) of P-VNTRs with at least 15 spanning reads, albeit with lower coverage. Spanning reads were sufficient for accurate genotyping in both cases. Our findings demonstrate that targeted sequencing provides consistently high coverage for a small subset of low-GC VNTRs, but WGS is more effective for broad and sufficient sampling of a large number of VNTRs.

Minisatellite Repeats↗

PubMed2025

Spatial-Temporal Diversity of Extrachromosomal DNA Shapes Urothelial Carcinoma Evolution and Tumor-Immune Microenvironment.

Extrachromosomal DNA (ecDNA) presents a promising target for cancer therapy; however, its spatial-temporal diversity and influence on tumor evolution and the immune microenvironment remain largely unclear. We apply computational methods to analyze ecDNA from whole-genome sequencing data of 595 urothelial carcinoma (UC) patients. We demonstrate that ecDNA drives clonal evolution through structural rearrangements during malignant transformation and recurrence of UC. This supports a model wherein tumors evolve via the selective expansion of ecDNA-bearing cells. Through multi-regional sampling of tumors, we demonstrate that ecDNA contributes to the evolution of multifocality and increased intratumoral heterogeneity. EcDNA is present in 36% of UC tumors and correlates with an immunosuppressive phenotype and poor prognosis. Single-cell RNA sequencing analyses reveal that ecDNA+ malignant cells exhibit diminished expression of major histocompatibility complex class I molecules, enabling them to evade T-cell immunity. Finally, we show that sequencing of urinary sediment-derived DNA has excellent specificity in detecting ecDNA.

Journal Article↗

PubMed2022

The evolutionary dynamics of extrachromosomal DNA in human cancers.

Oncogene amplification on extrachromosomal DNA (ecDNA) is a common event, driving aggressive tumor growth, drug resistance and shorter survival. Currently, the impact of nonchromosomal oncogene inheritance-random identity by descent-is poorly understood. Also unclear is the impact of ecDNA on somatic variation and selection. Here integrating theoretical models of random segregation, unbiased image analysis, CRISPR-based ecDNA tagging with live-cell imaging and CRISPR-C, we demonstrate that random ecDNA inheritance results in extensive intratumoral ecDNA copy number heterogeneity and rapid adaptation to metabolic stress and targeted treatment. Observed ecDNAs benefit host cell survival or growth and can change within a single cell cycle. ecDNA inheritance can predict, a priori, some of the aggressive features of ecDNA-containing cancers. These properties are facilitated by the ability of ecDNA to rapidly adapt genomes in a way that is not possible through chromosomal oncogene amplification. These results show how the nonchromosomal random inheritance pattern of ecDNA contributes to poor outcomes for patients with cancer.

Biological Evolution↗

PubMed2022

Heterozygous Tropomodulin 3 mice have improved lung vascularization after chronic hypoxia.

The molecular mechanisms leading to high-altitude pulmonary hypertension (HAPH) remains poorly understood. We previously analyzed the whole genome sequence of Kyrgyz highland population and identified eight genomic intervals having a potential role in HAPH. Tropomodulin 3 gene (TMOD3), which encodes a protein that binds and caps the pointed ends of actin filaments and inhibits cell migration, was one of the top candidates. Here we systematically sought additional evidence to validate the functional role of TMOD3. In-silico analysis reveals that some of the SNPs in HAPH associated genomic intervals were positioned in a regulatory region that could result in alternative splicing of TMOD3. In order to functionally validate the role of TMOD3 in HAPH, we exposed Tmod3-/+ mice to 4 weeks of constant hypoxia, i.e. 10% O2 and analyzed both functional (hemodynamic measurements) and structural (angiography) parameters related to HAPH. The hemodynamic measurements, such as right ventricular systolic pressure, a surrogate measure for pulmonary arterial systolic pressure, and right ventricular contractility (RV- ± dP/dt), increases with hypoxia did not separate between Tmod3-/+ and control mice. Remarkably, there was a significant increase in the number of lung vascular branches and total length of pulmonary vascular branches (P < 0.001) in Tmod3-/+ after 4 weeks of constant hypoxia as compared with controls. Notably, the Tmod3-/+ endothelial cells migration was also significantly higher than that from the wild-type littermates. Our results indicate that, under chronic hypoxia, lower levels of Tmod3 play an important role in the maintenance or neo-vascularization of pulmonary arteries.

Actin Cytoskeleton↗

PubMed2006

Improving gene annotation using peptide mass spectrometry.

Annotation of protein-coding genes is a key goal of genome sequencing projects. In spite of tremendous recent advances in computational gene finding, comprehensive annotation remains a challenge. Peptide mass spectrometry is a powerful tool for researching the dynamic proteome and suggests an attractive approach to discover and validate protein-coding genes. We present algorithms to construct and efficiently search spectra against a genomic database, with no prior knowledge of encoded proteins. By searching a corpus of 18.5 million tandem mass spectra (MS/MS) from human proteomic samples, we validate 39,000 exons and 11,000 introns at the level of translation. We present translation-level evidence for novel or extended exons in 16 genes, confirm translation of 224 hypothetical proteins, and discover or confirm over 40 alternative splicing events. Polymorphisms are efficiently encoded in our database, allowing us to observe variant alleles for 308 coding SNPs. Finally, we demonstrate the use of mass spectrometry to improve automated gene prediction, adding 800 correct exons to our predictions using a simple rescoring strategy. Our results demonstrate that proteomic profiling should play a role in any genome sequencing project.

Algorithms↗

PubMed2006

Evidence for large inversion polymorphisms in the human genome from HapMap data.

Knowledge about structural variation in the human genome has grown tremendously in the past few years. However, inversions represent a class of structural variation that remains difficult to detect. We present a statistical method to identify large inversion polymorphisms using unusual Linkage Disequilibrium (LD) patterns from high-density SNP data. The method is designed to detect chromosomal segments that are inverted (in a majority of the chromosomes) in a population with respect to the reference human genome sequence. We demonstrate the power of this method to detect such inversion polymorphisms through simulations done using the HapMap data. Application of this method to the data from the first phase of the International HapMap project resulted in 176 candidate inversions ranging from 200 kb to several megabases in length. Our predicted inversions include an 800-kb polymorphic inversion at 7p22, a 1.1-Mb inversion at 16p12, and a novel 1.2-Mb inversion on chromosome 10 that is supported by the presence of two discordant fosmids. Analysis of the genomic sequence around inversion breakpoints showed that 11 predicted inversions are flanked by pairs of highly homologous repeats in the inverted orientation. In addition, for three candidate inversions, the inverted orientation is represented in the Celera genome assembly. Although the power of our method to detect inversions is restricted because of inherently noisy LD patterns in population data, inversions predicted by our method represent strong candidates for experimental validation and analysis.

Biometry↗

PubMed2006

A sequence-based filtering method for ncRNA identification and its application to searching for riboswitch elements.

MOTIVATION: Recent studies have uncovered an "RNA world", in which non coding RNA (ncRNA) sequences play a central role in the regulation of gene expression. Computational studies on ncRNA have been directed toward developing detection methods for ncRNAs. State-of-the-art methods for the problem, like covariance models, suffer from high computational cost, underscoring the need for efficient filtering approaches that can identify promising sequence segments and speedup the detection process. RESULTS: In this paper we make several contributions toward this goal. First, we formalize the concept of a filter and provide figures of merit that allow comparison between filters. Second, we design efficient sequence based filters that dominate the current state-of-the-art HMM filters. Third, we provide a new formulation of the covariance model that allows speeding up RNA alignment. We demonstrate the power of our approach on both synthetic data and real bacterial genomes. We then apply our algorithm to the detection of novel riboswitch elements from the whole bacterial and archaeal genomes. Our results point to a number of novel riboswitch candidates, and include genomes that were not previously known to contain riboswitches. AVAILABILITY: The program is available upon request from the authors.

Algorithms↗

PubMed2006

Consensus folding of unaligned RNA sequences revisited.

As one of the earliest problems in computational biology, RNA secondary structure prediction (sometimes referred to as "RNA folding") problem has attracted attention again, thanks to the recent discoveries of many novel non-coding RNA molecules. The two common approaches to this problem are de novo prediction of RNA secondary structure based on energy minimization and the consensus folding approach (computing the common secondary structure for a set of unaligned RNA sequences). Consensus folding algorithms work well when the correct seed alignment is part of the input to the problem. However, seed alignment itself is a challenging problem for diverged RNA families. In this paper, we propose a novel framework to predict the common secondary structure for unaligned RNA sequences. By matching putative stacks in RNA sequences, we make use of both primary sequence information and thermodynamic stability for prediction at the same time. We show that our method can predict the correct common RNA secondary structures even when we are given only a limited number of unaligned RNA sequences, and it outperforms current algorithms in sensitivity and accuracy.

Algorithms↗

PubMed2006

Inference about recombination from haplotype data: lower bounds and recombination hotspots.

Recombination is an important evolutionary mechanism responsible for creating the patterns of haplotype variation observable in human populations. Recently, there has been extensive research on understanding the fine-scale variation in recombination across the human genome using DNA polymorphism data. Historical recombination events leave signature patterns in haplotype data. A nonparametric approach for estimating the number of historical recombination events is to compute the minimum number of recombination events in the history of a set of haplotypes. In this paper, we provide new and improved methods for computing lower bounds on the minimum number of recombination events. These methods are shown to detect a higher number of recombination events for a haplotype dataset from a region in the lipoprotein lipase gene than previous lower bounds. We apply our methods to two datasets for which recombination hotspots have been experimentally determined and demonstrate a high density of detectable recombination events in the regions annotated as recombination hotspots. The programs implementing the methods in this paper are available at www.cs.ucsd.edu/users/vibansal/RecBounds/.

Chromosomes, Human↗

PubMed2005

Identification of post-translational modifications by blind search of mass spectra.

Most tandem mass spectrometry (MS/MS) database search algorithms perform a restrictive search that takes into account only a few types of post-translational modifications (PTMs) and ignores all others. We describe an unrestrictive PTM search algorithm, MS-Alignment, that searches for all types of PTMs at once in a blind mode, that is, without knowing which PTMs exist in nature. Blind PTM identification makes it possible to study the extent and frequency of different types of PTMs, still an open problem in proteomics. Application of this approach to lens proteins resulted in the largest set of PTMs reported in human crystallins so far. Our analysis of various MS/MS data sets implies that the biological phenomenon of modification is much more widespread than previously thought. We also argue that MS-Alignment reveals some uncharacterized modifications that warrant further experimental validation.

Algorithms↗

PubMed2005

InsPecT: identification of posttranslationally modified peptides from tandem mass spectra.

Reliable identification of posttranslational modifications is key to understanding various cellular regulatory processes. We describe a tool, InsPecT, to identify posttranslational modifications using tandem mass spectrometry data. InsPecT constructs database filters that proved to be very successful in genomics searches. Given an MS/MS spectrum S and a database D, a database filter selects a small fraction of database D that is guaranteed (with high probability) to contain a peptide that produced S. InsPecT uses peptide sequence tags as efficient filters that reduce the size of the database by a few orders of magnitude while retaining the correct peptide with very high probability. In addition to filtering, InsPecT also uses novel algorithms for scoring and validating in the presence of modifications, without explicit enumeration of all variants. InsPecT identifies modified peptides with better or equivalent accuracy than other database search tools while being 2 orders of magnitude faster than SEQUEST, and substantially faster than X!TANDEM on complex mixtures. The tool was used to identify a number of novel modifications in different data sets, including many phosphopeptides in data provided by Alliance for Cellular Signaling that were missed by other tools.

Databases, Factual↗

PubMed2005

Orthologous repeats and mammalian phylogenetic inference.

Determining phylogenetic relationships between species is a difficult problem, and many phylogenetic relationships remain unresolved, even among eutherian mammals. Repetitive elements provide excellent markers for phylogenetic analysis, because their mode of evolution is predominantly homoplasy-free and unidirectional. Historically, phylogenetic studies using repetitive elements have relied on biological methods such as PCR analysis, and computational inference is limited to a few isolated repeats. Here, we present a novel computational method for inferring phylogenetic relationships from partial sequence data using orthologous repeats. We apply our method to reconstructing the phylogeny of 28 mammals, using more than 1000 orthologous repeats obtained from sequence data available from the NISC Comparative Sequencing Program. The resulting phylogeny has robust bootstrap numbers, and broadly matches results from previous studies which were obtained using entirely different data and methods. In addition, we shed light on some of the debatable aspects of the phylogeny. With rapid expansion of available partial sequence data, computational analysis of repetitive elements holds great promise for the future of phylogenetic inference.

Animals↗

PubMed2005

Identification of post-translational modifications via blind search of mass-spectra.

Post-translational modifications (PTMs) are of great biological importance. Most existing approaches perform a restrictive search that can only take into account a few types of PTMs and ignore all others. We describe an unrestrictive PTM search algorithm that searches for all types of PTMs at once in a blind mode, i.e., without knowing which PTMs exist in a sample. The blind PTM identification opens a possibility to study the extent and frequencies of different types of PTMs, still an open problem in proteomics. Using our new algorithm, we were able to construct a two-dimensional PTM frequency matrix that reflects the number of MS/MS spectra in a sample for each putative PTM type and each amino acid. Application of this approach to a large IKKb dataset resulted in the largest set of PTMs reported for a single MS/MS sample so far. We demonstrate an excellent correlation between high values in the PTM frequency matrix and known PTMs thus validating our approach. We further argue that the PTM frequency matrix may reveal some still unknown modifications that warrant further experimental validation.

Algorithms↗

PubMed2004

Shotgun protein sequencing by tandem mass spectra assembly.

The analysis of mass spectrometry data is still largely based on identification of single MS/MS spectra and does not attempt to make use of the extra information available in multiple MS/MS spectra from partially or completely overlapping peptides. Analysis of MS/MS spectra from multiple overlapping peptides opens up the possibility of assembling MS/MS spectra into entire proteins, similarly to the assembly of overlapping DNA reads into entire genomes. In this paper, we present for the first time a way to detect, score, and interpret overlaps between uninterpreted MS/MS spectra in an attempt to sequence entire proteins rather than individual peptides. We show that this approach not only extends the length of reconstructed amino acid sequences but also dramatically improves the quality of de novo peptide sequencing, even for low mass accuracy MS/MS data.

Amino Acid Sequence↗

PubMed2004

A note on efficient computation of haplotypes via perfect phylogeny.

The problem of inferring haplotype phase from a population of genotypes has received a lot of attention recently. This is partly due to the observation that there are many regions on human genomic DNA where genetic recombination is rare (Helmuth, 2001; Daly et al., 2001; Stephens et al., 2001; Friss et al., 2001). A Haplotype Map project has been announced by NIH to identify and characterize populations in terms of these haplotypes. Recently, Gusfield introduced the perfect phylogeny haplotyping problem, as an algorithmic implication of the no-recombination in long blocks observation, together with the standard population-genetic assumption of infinite sites. Gusfield's solution based on matroid theory was followed by direct theta(nm2) solutions that use simpler techniques (Bafna et al., 2003; Eskin et al., 2003), and also bound the number of solutions to the PPH problem. In this short note, we address two questions that were left open. First, can the algorithms of Bafna et al. (2003) and Eskin et al. (2003) be sped-up to O(nm + m2) time, which would imply an O(nm) time-bound for the PPH problem? Second, if there are multiple solutions, can we find one that is most parsimonious in terms of the number of distinct haplotypes. We give reductions that suggests that the answer to both questions is "no." For the first problem, we show that computing the output of the first step (in either method) is equivalent to Boolean matrix multiplication. Therefore, the best bound we can presently achieve is O(nm(omega-1)), where omega < or = 2.52 is the exponent of matrix multiplication. Thus, any linear time solution to the PPH problem likely requires a different approach. For the second problem of computing a PPH solution that minimizes the number of distinct haplotypes, we show that the problem is NP-hard using a reduction from Vertex Cover (Garey and Johnson, 1979).

Computational Biology↗