Biology subjects

Doddapaneni, H. V.

Publications and source records attributed to Doddapaneni, H. V..

5 recordsLinked to original sources

bioRxiv2026

Somatic variant detection in normal tissues from single-cell sequencing data

A crucial advantage of single-cell sequencing (SCS) is its ability to identify somatic variants in individual cells, enabling phylogenetic analysis of cellular populations within bulk tissues. While identifying somatic variants in tumor tissues via SCS has become a common practice, doing so in normal tissues remains challenging due to the rarity of somatic variants in normal cells. To evaluate the feasibility of somatic variant calling from widely available single-nucleus RNA-seq (snRNA-seq) and single-nucleus ATAC-seq (snATAC-seq) data, we profiled a Cell-line mix of six HapMap samples prepared by the SMaHT consortium using 10x Genomics 5 snRNA-seq (12k cells with 36k mean reads per cell) and snATAC-seq (11k cells with 14k median high-quality fragments per cell) for variant calling. PacBio long-read whole genome sequencing (WGS) data (109x) generated from individual cell lines were used as ground truth. Two computational tools, Monopogen and SComatic, were used for somatic variant calling from the SCS data. Monopogen achieved single nucleotide variant (SNV) detection accuracies of 93.30% in the snRNA-seq and 99.64% in the snATAC-seq data, both of which outperformed SComatic (74.35% and 94.29%, respectively). Monopogen also consistently detected somatic SNVs at cellular fractions as low as 0.5% (2.54% in snRNA and 0.81% in snATAC) in individual samples. Notably, snATAC-seq exhibited higher genomic coverage breadth and larger number of variants detected than snRNA-seq. While the SCS data have lower overall genome coverage than that of the bulk WGS, the single-cell level variant resolution allows Monopogen to assign variants to their cells of origin with over 80% accuracy in both RNA and ATAC modalities, thereby facilitating studies of clonal evolution and cell-type-specific mutagenesis. Other benchmarking methods were also evaluated (DeepVariant, Cellsnp-lite and Mutect2) for comparison. In conclusion, our study demonstrated the feasibility of performing reliable single-cell somatic mutation calling in a cell-line mixture and discussed the strengths and limitations of current computational methods when applied to normal tissues.

bioinformatics↗

bioRxiv2025

Expanding the Genome in a Bottle Truth Set: Detection and Validation of Novel Low-frequency Variants Using High-accuracy NanoSeq

HighlightsO_LINanoSeq-MBN achieves near-genome, Poisson-like coverage with minimal trinucleotide bias. C_LIO_LIExpands the GIAB truth set by up to 160k de novo variants. C_LIO_LIAdds a somatic layer to GIAB, enabling benchmarking and calibration of rare variants. C_LIO_LIHigh-CADD exonic and splice variants highlight value for surveillance and clinical triage. C_LI Somatic mutations record tissue molecular history and inform risk, prognosis, and therapy, yet their variant allele fractions often fall below the reliable detection limit of conventional short-read sequencing. In contrast, duplex sequencing technology featured by NanoSeq applies the principle of single molecule detection and thereby overcomes the limitation. However, the original NanoSeq protocol relies on the restriction enzyme-based genome fragmentation, which constrained its genome coverage to 30-40%. To enable whole-genome discovery with duplex-level fidelity, we pursued two complementary approaches to optimize the NanoSeq protocol: (i) a restriction-enzyme strategy densifies accessible sites using orthogonal 4-bp cutters; and (ii) a workflow using sonication followed by mung bean nuclease with T4 polynucleotide kinase, Klenow fragment and dATP/ddBTP mixture (NanoSeq-MBN) to blunt and repair/A-tailing DNA, while minimizing repair artifacts. We systematically benchmarked their performance using Genome in a Bottle (GIAB) gold-standard sample mixtures. As a result, NanoSeq-MBN achieved near genome-wide, Poissonlike coverage with minimal trinucleotide-context bias and ultra-high accuracy. Beyond variants already present in the GIAB truth set, NanoSeq-MBN identified approximately 120,000-160,000 de novo mutations per sample missing in the truth set, Notably, over 98% had orthogonal support in reanalyzed GIAB bulk Illumina HiSeq libraries. These novel variants extended GIAB from germline benchmarking to rare-variant discovery and calibration of subclonal detection. Functional annotation revealed enrichment of high Combined Annotation Dependent Depletion (CADD) scores mutations in exonic and splice-related regions. Variants intersecting ClinVar entries and OMIM genes highlighted potential for surveillance and clinical triage. Collectively, these results add a somatic layer to GIAB, enabling calibration of burdens and mutational signatures in lymphoblastoid lines and provide reference material for rare-variant assays. The NanoSeq-MBN workflow offers a path to whole-genome, high-fidelity discovery of ultra-rare somatic variation with relevance to clinical assay validation.

molecular biology↗

bioRxiv2025

Pre-Sequencing Assessment of RNA-Seq Library Quality Using Real-Time qPCR

RNA sequencing (RNA-Seq) is an essential sequencing assay for studying transcriptome profiling. Ribosomal RNA (rRNA) comprises more than 80 - 90% of total cellular RNA, efficient rRNA removal is essential for accurately capturing the transcriptome, particularly to sequence low-abundance mRNAs. Inefficient rRNA removal during library preparation can result from variations in sample quality, preparation methods and handling. Estimating rRNA content in RNA-Seq libraries pre-sequencing is therefore challenging due to the absence of a reliable and cost-effective assessment method. This study addresses the issue by introducing a scalable qPCR-based assay targeting 18S rRNA to evaluate rRNA depletion efficiency pre-sequencing. qPCR efficiency was optimized using serial dilutions of Universal Human Reference (UHR) control and Ct thresholds were established using pilot data from 644 libraries. Following this optimization, analysis of 1,748 Total RNA-Seq libraries and 445 Poly A+ two widely used RNA-Seq library methods, demonstrated a strong correlation between 18S rRNA qPCR results and post-sequencing rRNA rates. This assay was also used to evaluate the performance of Oligo dT beads from four different vendors to enrich mRNA. This 18S rRNA qPCR assay is a cost-effective, scalable approach for reliably predicting rRNA read percentage in RNA-Seq libraries pre-sequencing. Method SummaryThe 18S rRNA-specific qPCR assay is a cost-effective method for evaluating rRNA depletion efficiency in RNA-Seq libraries prior to sequencing by targeting the 18S ribosomal RNA. qPCR efficiency was optimized, and Ct thresholds were set from pilot data and validated across 1,748 Total RNA and 445 Poly A+ RNA-Seq libraries. A Ct threshold of [≥]16 for Total RNA and Ct 13-14 or greater for Poly A+ libraries demonstrates a strong correlation between qPCR results and post-sequencing rRNA read percentages. The assay enables early identification of poorly depleted samples, reducing unnecessary sequencing costs. Additionally, the method was employed to benchmark oligo-dT beads from four vendors, showing its utility in evaluating RNA-seq library preparation kits. This scalable approach supports quality control in both research and high-throughput sequencing environments.

molecular biology↗

bioRxiv2020

Oligonucleotide capture sequencing of the SARS-CoV-2 genome and subgenomic fragments from COVID-19 individuals

The newly emerged and rapidly spreading SARS-CoV-2 causes coronavirus disease 2019 (COVID-19). To facilitate a deeper understanding of the viral biology we developed a capture sequencing methodology to generate SARS-CoV-2 genomic and transcriptome sequences from infected patients. We utilized an oligonucleotide probe-set representing the full-length genome to obtain both genomic and transcriptome (subgenomic open reading frames [ORFs]) sequences from 45 SARS-CoV-2 clinical samples with varying viral titers. For samples with higher viral loads (cycle threshold value under 33, based on the CDC qPCR assay) complete genomes were generated. Analysis of junction reads revealed regions of differential transcriptional activity and provided evidence of expression of ORF10. Heterogeneous allelic frequencies along the 20kb ORF1ab gene suggested the presence of a defective interfering viral RNA species subpopulation in one sample. The associated workflow is straightforward, and hybridization-based capture offers an effective and scalable approach for sequencing SARS-CoV-2 from patient samples.

microbiology↗

bioRxiv2020

Genome-enabled insights into the biology of thrips as crop pests

BackgroundThe western flower thrips, Frankliniella occidentalis (Pergande), is a globally invasive pest and plant virus vector on a wide array of food, fiber and ornamental crops. While there are numerous studies centered on thrips pest and vector biology, feeding behaviors, ecology, and insecticide resistance, the underlying genetic mechanisms of the processes governing these areas of research are largely unknown. To address this gap, we present the F. occidentalis draft genome assembly and official gene set. ResultsWe report on the first genome sequence for any member of the insect order Thysanoptera. Benchmarking Universal Single-Copy Ortholog (BUSCO) assessments of the genome assembly (size = 415.8 Mb, scaffold N50 = 948.9 Kb) revealed a relatively complete and well-annotated assembly in comparison to other insect genomes. The genome is unusually GC-rich (50%) compared to other insect genomes to date. The official gene set (OGS v1.0) contains 16,859 genes, of which [~]10% were manually verified and corrected by our consortium. We focused on manual annotation, phylogenetic and expression evidence analyses for gene sets centered on primary themes in the life histories and activities of plant-colonizing insects. Highlights include: 1) divergent clades and large expansions in genes associated with environmental sensing (chemosensory receptors) and detoxification (CYP4, CYP6 and CCE enzymes) of substances encountered in agricultural environments; 2) a comprehensive set of salivary gland-associated genes supported by enriched expression; 3) apparent absence of members of the IMD innate immune defense pathway; and 4) developmental- and sex-specific expression analyses of genes associated with progression from larvae to adulthood through neometaboly, a distinct form of maturation compared to complete metamorphosis in the Holometabola. ConclusionsAnalysis of the F. occidentalis genome offers insights into the polyphagous behavior of this insect pest to find, colonize and survive on a widely diverse array of plants. The genomic resources presented here enable a more complete analysis of insect evolution and biology, providing a missing taxon for contemporary insect genomics-based analyses. Our study also offers a genomic benchmark for molecular and evolutionary investigations of other thysanopteran species.

genomics↗