Biology subjects

Johri, S.

Publications and source records attributed to Johri, S..

9 recordsLinked to original sources

bioRxiv2026

Metastatic Osteosarcoma is Characterized by Loss of Osteoblastic Lineage Fidelity

Osteosarcoma (OS) is a rare and aggressive bone cancer with limited therapeutic progress in several decades. To characterize the transcriptional diversity of malignant cell states in OS, we analyzed single-nucleus RNA sequencing data from 24 tumors, including both primary and metastatic lesions. We identified a canonical osteoblastic cell state that predominated in primary tumor cells, but was dampened in metastases. Integrating tumor data with data from embryonic skeletal development and an experimental osteoblast differentiation model revealed that metastatic OS cells resemble poorly specified mesenchyme enriched for non-osseous programs. Clonal populations in metastatic samples acquired mesenchymal cell states distinct from paired primary tumors. Similar cell state shifts were evident in post-treatment primary tumors relative to paired pre-treatment samples. Our results suggest that localized post-treatment and metastatic OS malignant cells lose osteoblastic lineage fidelity, which may represent a unifying axis of disease evolution and reveal new therapeutic vulnerabilities.

Cancer Biology↗

bioRxiv2026

Evaluating agentic AI for biological discovery in autonomous and copilot settings

Advances in large language models (LLMs)-based artificial intelligence (AI) agents have improved their ability to execute structured analytical workflows, including standard bioinformatic pipelines for biological discovery. However, computational biology rarely consists of deterministic pipeline execution alone. Biological datasets are heterogeneous and noisy, and meaningful discovery often requires open-ended hypothesis generation and iterative reasoning over multimodal evidence. These challenges are particularly evident in multi-omic studies, where paired molecular modalities and heterogeneous clinical contexts create both opportunities and obstacles for discovery. The extent to which emerging agentic AI systems can support or automate this mode of scientific discovery remains poorly understood. Here, we systematically evaluated the capabilities and limitations of agentic AI for biological discovery using multi-omic single cell datasets spanning 11 cancer types. We developed the Multistep Multimodal Multiomic Agentic (M3A) Framework to support LLM-driven reasoning over persistent multimodal data states and to capture agentic reasoning behavior in autonomous and human-AI copilot settings. Using this framework, we assessed AI agents across complementary tasks, including autonomous cell-type annotation, generation of falsifiable biological hypotheses from gene programs, and copilot experiments testing the effect of human involvement and domain expertise. We found that current AI agents are effective at broad, systemic exploration of complex data, whereas domain experts remain critical for methodological guidance and biological synthesis across analyses. Together, our results delineate the current potential and boundaries of agentic AI in computational biology, and establish a framework for evaluating AI systems designed to support biological discovery.

cancer biology↗

bioRxiv2025

Whole Genome Assembly of the Atlantic Bluefin Tuna Thunnus thynnus, with Phased Haplotypes

Atlantic bluefin tuna (Thunnus thynnus) are highly migratory fish, the largest tuna in the genus Thunnus. These fish possess a unique suite of traits, including regional endothermy, in their swimming muscle, viscera, brain and eyes that elevates tissue temperatures significantly above ambient water temperatures. Bluefin tuna also have an efficient thunniform locomotory style, involving a fusiform low drag external shape and a novel musculoskeletal system that enhances elastic energy storage. Together the unique swimming form and warm muscle temperatures enable this species to move across large expanses of the ocean. Atlantic bluefin tuna are targeted by high-value international fisheries of over fifty nations. Populations have recovered in recent years and the species is now actively farmed extensively within the Mediterranean Sea and eastern Atlantic. To date, fisheries management and evolutionary studies have been hampered by a lack of genomic resources. Here, we report a novel de novo chromosome-level phased genome assembly for the Atlantic bluefin tuna obtained using PacBio HiFi reads and Dovetail Omni-C scaffolding. This assembly was scaffolded into 24 chromosomes containing 98% of the genes in the BUSCO reference dataset, demonstrating a high level of contiguity with a contig N50 of 26.54 and assembly size of [~]800Mbp. We compare a diploid-resolved (2N) genome assembly of Atlantic bluefin tuna with a haplotype-collapsed (1N) genome assembly from a Pacific bluefin tuna caught in the eastern Pacific off California. We show the two species have a 98.47% sequence identity. These high-quality genomes for northern bluefin tunas provide the genomic tools necessary for improving phylogenomic and evolutionary physiology analyses of this lineage and are important for potential functional assays for population biology of these commercially important species.

evolutionary biology↗

bioRxiv2025

Empirical Evaluation of Single-Cell Foundation Models for Predicting Cancer Outcomes

Foundation models pretrained on large-scale single-cell RNA sequencing data present a promising opportunity to advance translational cancer research. However, their utility in clinically relevant, patient-level single-cell applications remains underexplored. Here, we developed an agentic strategy to systematically evaluate twelve emerging single-cell foundation models (scFMs) and three alternative baseline approaches across seven cancer-specific tasks, including cell-type annotation, cancer subtype classification, and treatment response prediction. We assessed model performance under zero-shot, continual training, and fine-tuning conditions, conducting 1,530 supervised model-fitting runs and 200 unsupervised subsample evaluations. We found that while current scFMs excelled at certain analysis tasks, such as tumor microenvironment cell annotation, they offered limited advantages in predicting clinical and biological outcomes of cancer patients compared to simpler baseline models. These insights highlight the critical role of scFM evaluation on biologically and clinically relevant tasks for precision oncology. Beyond identifying current limitations, this assessment reveals principles that can guide future methodological innovation and the use of expanded cancer single-cell cohorts to build more biologically informed and translationally effective scFMs. The resulting agentic framework supports the autonomous discovery of emerging scFMs and facilitates their standardized integration and evaluation across cancer-related tasks.

cancer biology↗

bioRxiv2025

Mapping Risk and Resilience Across Indo-Pacific Reefs with Shark Genomescapes

Overfishing has severely depleted marine populations worldwide, including within protected areas. Illegal and unreported fishing are major contributors to this decline. Large-bodied apex predators such as sharks are among the most affected, with overfishing causing dramatic species declines and ecosystem destabilization due to trophic downgrading. Key barriers to effective marine conservation and management include: Data deficiencies that hinder population benchmarks and impact assessments, limited surveillance, allowing illegal fisheries to disproportionately affect apex predators, and insufficient capacity in vulnerable nations to monitor and protect species within their waters. Our study addresses these challenges through a novel genomic framework that enables assessment of shark population diversity and health, while also improving fisheries traceability by detecting instances of illegal fishing across the Indian and Pacific Oceans. We present the Reefshark Genomescape, the first genome-wide reference database for Indo-Pacific reef sharks, an assessment of genetic diversity, structure, and connectivity of two key species across their Indo-Pacific range and geographic assignment of fished individuals using population-specific genetic signatures. We show that grey reef shark (Carcharhinus amblyrhynchos) populations exhibit high genetic diversity, strong population structure, and elevated Fst values, with previously unknown connectivity between the central and western Indian Ocean and clear isolation of populations in the Andaman Sea. In contrast, silvertip sharks (Carcharhinus albimarginatus) display high connectivity, but show genomic signals of declining population health, supporting a reassessment of their IUCN status. Using supervised machine learning with Monte Carlo cross-validation, we assigned geographic origins to fished grey reef sharks with 96% accuracy. These findings provide critical insights into population structure, connectivity, and health of two ecologically important reef shark species, while establishing a robust method for assigning geographic origin. We anticipate this framework will support regional conservation assessments and targeted management. Moreover, by enabling the identification of fishing hotspots and detection of IUU fishing, it lays the groundwork for a broader traceability system in marine ecosystems. Much like the landmark elephant ivory tracing study, our approach has the potential to transform marine conservation globally. Graphical AbstractWe developed the Reefshark Genomescape, a genomic framework for assessing shark population health and fisheries traceability across the Indo-Pacific. Genome-wide data from grey reef and silvertip sharks revealed contrasting patterns, unexpected connectivity, and genomic signals of decline. Geographic assignment of fished individuals reached 96% accuracy, enabling detection of illegal fishing and identification of hotspots. This framework strengthens regional management, supports IUCN reassessments, and lays the foundation for global marine traceability systems. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=175 SRC="FIGDIR/small/676358v2_ufig1.gif" ALT="Figure 1"> View larger version (84K): org.highwire.dtl.DTLVardef@1eafd3aorg.highwire.dtl.DTLVardef@96ebd1org.highwire.dtl.DTLVardef@541d02org.highwire.dtl.DTLVardef@3c9ca2_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2025

Unveiling the Diversity and Demography of Sharks and Rays at key landing sites in Bangladesh

In Bangladeshs marine waters in the Bay of Bengal, sharks and rays face grave threats from unsustainable fishing practices and habitat degradation. Findings from our taxonomic assessment of elasmobranchs landed at the two most important marine fish landing stations in Bangladesh bring new information and insights about the nature of the Threatened elasmobranch bycatch. This study presents findings from a taxonomic assessment at Coxs Bazar and Chattogram, two crucial landing stations in Bangladesh where most shark bycatch landings happen. Over two years, 525 fish were sampled; 206 samples were of sharks, 91 of rays, and 64 of rhino rays, representing over 29 species across 12 families. Among them are 4 families of sharks, 5 rays, and 3 rhino rays. The predominant families observed were Carcharhinidae, Glaucostegidae, and Rhinopteridae. The most frequently landed species were Sphyrna lewini, Glaucostegus younholeei, Carcharhinus leucas, Gymnura poecilura, and Mobula mobular. Out of the 525 samples, 65% (n=340) were female, 35% (n=183) were male, and the rest (n=2) were unidentified. Finding one sample of Pristis pristis indicates the severity of the decline. Additionally, for Glaucostegus granulatus, 12 among the 13 studied specimens were adult females. A significant proportion of the sampled specimens, 45%, were juveniles, while only 24% were adults. This is likely because these fishing boats bringing the catch operate in inshore water and nearshore seas, which are potential nursery grounds. The overlapping of fishing grounds and these critical habitats poses a significant challenge in elasmobranch conservation and hinders population recovery. The high number of juveniles and female adults in the catch reminds us of the necessity of integrating threatened bycatch reduction measures into the countrys fisheries management.

zoology↗

bioRxiv2025

Establishing a DNA reference library for the identification of elasmobranchs in the Indian Ocean using Oxford Nanopore Sequencing

Elasmobranchs, comprising sharks and rays, are among the most threatened species globally. The first elasmobranchs were added to the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) in 2002. Since then, the number of species listed has increased to 151, highlighting the urgent conservation challenges faced by these species. In Sri Lanka, where over 100 species have been recorded, the demand for elasmobranch products drives significant export and import activities, complicating conservation efforts. Accurate species identification is crucial for fisheries monitoring, trade regulation, and conservation management. However, relying solely on morphological characteristics is challenging, especially since key identifying features are unavailable in certain derivatives like meat and oil in market samples. This study aims to develop a robust DNA reference library for elasmobranch species in Sri Lanka and to showcase the application of Oxford Nanopore Technology (ONT) as a reliable tool for fisheries monitoring and conservation. Using DNA barcoding and ONT sequencing, we analysed 49 elasmobranch species, focusing on the Cytochrome Oxidase I (COI) and 12S ribosomal ribonucleic acid (rRNA) genes to develop a DNA reference library. The creation of reliable barcode reference libraries is essential for effective species identification in biomonitoring because it facilitates the assessment of population trends and the effectiveness of fishing and trade regulations. We conducted a phylogenetic analysis to assess the robustness of reference sequences in species discrimination. All DNA reference sequences are publicly accessible through GenBank. This study enhances the capacity to monitor and regulate the elasmobranch trade in Sri Lanka and beyond.

genetics↗

bioRxiv2022

Intertumoral lineage diversity and immunosuppressive transcriptional programs in well-differentiated gastroenteropancreatic neuroendocrine tumors

Neuroendocrine tumors (NETs) are rare cancers that may arise in the gastrointestinal tract and pancreas. The fundamental mechanisms driving gastroenteropancreatic (GEP) NET growth remain incompletely elucidated; however, the heterogeneous clinical behavior of GEP-NETs suggests that both cellular lineage dynamics and tumor microenvironment influence tumor pathophysiology. Here, we investigated the single-cell transcriptomes of tumor and immune cells from patients with gastroenteropancreatic NETs. Malignant GEP-NET cells expressed genes and regulons associated with normal, gastrointestinal endocrine cell differentiation and fate determination stages. While tumor and lymphoid compartments sparsely expressed immunosuppressive targets, infiltrating myeloid cells were enriched for alternative immunotherapy pathways including VSIR, Tim3/Gal9, and SIGLEC10. Finally, analysis of paired primary and metastatic tissue specimens from small intestinal NETs demonstrated transcriptional transformation between the primary tumor and its distant metastasis. Our findings highlight the transcriptomic heterogeneity that distinguishes the cellular landscapes of GEP-NET anatomic subtypes and reveal potential avenues for future precision medicine therapeutics.

cancer biology↗

bioRxiv2021

Dissecting tumor cell programs through group biology estimation in clinical single-cell transcriptomics

Given the growing number of clinically integrated cancer single-cell transcriptomic studies, robust differential enrichment methods for gene signatures to dissect tumor cellular states for discovery and translation are critical. Current analysis strategies neither adequately represent the hierarchical structure of clinical single-cell transcriptomic datasets nor account for the variability in the number of recovered cells per sample, leading to results potentially confounded by sample-driven biology with high false positives instead of accurately representing true differential enrichment of group-level biology (e.g., treatment responders vs. non-responders). This problem is especially prominent for single-cell analyses of the tumor compartment, because high intra-patient similarity (as opposed to inter-patient similarity) results in stricter hierarchical structured data that confounds enrichment analysis. Furthermore, to identify signatures which are truly representative of the entire group, there is a need to quantify the robustness of otherwise statistically significant signatures to sample exclusion. Here, we present a new nonparametric statistical method, BEANIE, to account for these issues, and demonstrate its utility in two cancer cohorts stratified by clinical groups to reduce biological hypotheses and guide translational investigations. Using BEANIE, we show how the consideration of sample-specific versus group biology greatly decreases the false positive rate and guides identification of robust signatures that can also be corroborated across different cell type compartments.

bioinformatics↗