Biology subjects

Kalra, D.

Publications and source records attributed to Kalra, D..

6 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↗

bioRxiv2026

Multi-Omics Characterization of Human Molecular Responses to Spaceflight Across Two Independent Missions

Human spaceflight has historically been led by government agencies, but the emergence of commercial organizations is enabling broader participation and new research opportunities. In this study, we present a comprehensive molecular characterization of early human responses to spaceflight, leveraging multi-omics data across the first three weeks of two commercial missions. Biospecimens from six individuals, four from the Axiom 2 mission (10 days) and two from Axiom 3 (21 days), were analyzed using single-cell and bulk RNA sequencing, alongside proteomic profiling. Individual and integrative analyses of these datasets reveal systemic changes in cell types, transcripts, and proteins related to immune regulation, osteoclast differentiation, NF-{kappa}B signaling, and blood homeostasis pathways. Importantly, several of the detected pathways align with physiological patterns observed in longer-duration missions. This work establishes a foundational resource for understanding early adaptation to spaceflight at the cellular and molecular levels, providing insights to reduce future space-travel health risks. HighlightsO_LIFirst integrated multi-omics analysis using single-cell, bulk RNA sequencing and proteomic profiling of early human spaceflight responses across two commercial missions (Ax-2 and Ax-3). C_LIO_LIDistinct PBMC clustering was observed across Ax-2 and Ax-3, and post-flight samples. It showed fewer monocytes, dendritic cells, and megakaryocytes with increased naive CD4 and cytotoxic T cells. C_LIO_LIMulti-omics integration identifies shared biological signatures, including osteoclast differentiation, metabolic stress, and coagulation changes. C_LIO_LIThese findings lay the foundation for developing countermeasures to protect immune, skeletal, and vascular health during spaceflight. C_LI

molecular biology↗

bioRxiv2025

Comprehensive benchmarking of somatic single-nucleotide variant and indel detection at ultra-low allele fractions using short- and long-read data

Mosaic mutations in normal tissues occur at low variant allele fractions (VAFs), complicating detection. To benchmark strategies, the SMaHT Network created a cell-line mixture (1:49) and produced ultra-deep whole-genome sequencing using short and long reads (five centers, 180-500x each). We assembled a reference of 44,008 mosaic SNVs and 2,059 Indels, cross-validation between platforms to expose limits of short-read analysis. We also partitioned the genome by mappability to examine the impact of genomic context, added a negative reference set, and accounted for culture-derived mutations. When seven institutions applied eleven algorithms to mixture data, call sets were largely discordant across tools and replicates, partly reflecting stochastic presence of low-VAF mutations in biological replicants. For >2% VAF SNVs, sensitivity and precision approached [~]80% at [≥]300x, with little gain from additional sequencing. This work provides a comprehensive framework for reliable detection of low-VAF mutations in non-cancer tissues and a valuable resource for the community.

bioinformatics↗

bioRxiv2023

The GIAB genomic stratifications resource for human reference genomes

Stratification of the genome into different genomic contexts is useful when developing bioinformatics software like variant callers, to assess performance in difficult regions in the human genome. Here we describe a set of genomic stratifications for the human reference genomes GRCh37, GRCh38, and T2T-CHM13v2.0. Generating stratifications for the new complete CHM13 reference genome is critical to understanding improvements in variant caller performance when using this new complete reference. The GIAB stratifications can be used when benchmarking variant calls to analyze difficult regions of the human genome in a standardized way. Here we present stratifications in the CHM13 genome in comparison to GRCh37 and GRCh38, highlighting expansions in hard-to-map and GC-rich stratifications which provide useful insight for accuracy of variants in these newly-added regions. To evaluate the reliability and utility of the new stratifications, we used the stratifications of the three references to assess accuracy of variant calls in diverse, challenging genomic regions. The means to generate these stratifications are available as a snakemake pipeline at https://github.com/ndwarshuis/giab-stratifications.

genomics↗

bioRxiv2023

Monorhinal and Birhinal Odor Processing in Humans: an fMRI investigation

The olfactory nerve, also known as cranial nerve I, is known to have exclusive ipsilateral projections to primary olfactory cortical structures. It is still unclear whether these projections also correspond to functional pathways of odor processing. In an olfactory functional magnetic resonance imaging (fMRI) study of twenty young healthy subjects with a normal sense of smell, we tested whether nostril specific stimulation with phenyl ethyl alcohol (PEA), a pure olfactory stimulant, asymmetrically activates primary or secondary olfactory-related brain structures such as primary olfactory cortex, entorhinal cortex, and orbitofrontal cortex. The results indicated that without a challenging olfactory task, passive (no sniffing) and active (with sniffing) nostril-specific PEA stimulation did not produce asymmetrical fMRI activation in olfactory cortical structures.

neuroscience↗

bioRxiv2018

The Genomic Basis of Arthropod Diversity

BackgroundArthropods comprise the largest and most diverse phylum on Earth and play vital roles in nearly every ecosystem. Their diversity stems in part from variations on a conserved body plan, resulting from and recorded in adaptive changes in the genome. Dissection of the genomic record of sequence change enables broad questions regarding genome evolution to be addressed, even across hyper-diverse taxa within arthropods.\n\nResultsUsing 76 whole genome sequences representing 21 orders spanning more than 500 million years of arthropod evolution, we document changes in gene and protein domain content and provide temporal and phylogenetic context for interpreting these innovations. We identify many novel gene families that arose early in the evolution of arthropods and during the diversification of insects into modern orders. We reveal unexpected variation in patterns of DNA methylation across arthropods and examples of gene family and protein domain evolution coincident with the appearance of notable phenotypic and physiological adaptations such as flight, metamorphosis, sociality and chemoperception.\n\nConclusionsThese analyses demonstrate how large-scale comparative genomics can provide broad new insights into the genotype to phenotype map and generate testable hypotheses about the evolution of animal diversity.

genomics↗