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PubMed2026

Intratumoral collagen correlates with histological grade and patient prognosis in breast cancer.

Histological grading, using the Nottingham Grading System (NGS), is a major prognostic indicator for breast cancer. NGS involves the scoring of cancer cell-related morphological features, yet it overlooks tumor microenvironment (TME) components such as collagen. Collagen proteins, integral to the extracellular matrix (ECM), influence tumor architecture and progression but their relationship with histological grade is not fully characterized. Here, we assessed intratumoral collagen deposition using Masson Trichrome staining of whole slides (n = 166), proteomic profiling (n = 2) and transcriptomic analyses of the METABRIC (n = 1827) and TCGA-BRCA (n = 753) cohorts. We showed that low-grade tumors display significantly higher intratumoral collagen deposition compared to high-grade tumors. Moreover, we demonstrated that collagen expression at the transcript and protein levels (Masson Trichrome) could discriminate Grade II carcinomas into distinct prognostic groups, in which patients with Grade II carcinomas with elevated levels of collagen expression were associated with lower pTNM stage and better survival outcomes. Our results support the inclusion of TME features, such as collagen deposition, to enhance prognostic accuracy in breast cancer.

Humans↗

PubMed2026

A pro-inflammatory metastasis-associated macrophage subset induces tumor-promoting mesothelial cell conversion in ovarian cancer via IL-1α secretion.

Tumor-associated macrophages (TAMs) are key regulators of the tumor microenvironment, yet the functional specialization of TAM subsets in metastatic progression remains incompletely defined. Here, we characterized distinct TAM populations contributing to tumor-promoting mesothelial cell conversion in high-grade ovarian carcinoma using single-cell RNA sequencing of patient-derived macrophages from ascites (ascTAMs) and omental metastases (omTAMs). TAMs from these anatomical sites were clearly distinguishable by polarization states, with omTAMs exhibiting a mixed M1⁺/M2⁺ phenotype, in contrast to the M1low/M2⁺ profile observed in ascTAMs. Transcriptomic analysis further revealed functional divergence of these subsets. Notably, omTAMs displayed gene signatures associated with mesothelial-to-mesenchymal transition (MMT), a critical process enabling tumor invasion across the peritoneal lining. Functionally, conditioned media from omTAMs, similar to that from classically activated M1 macrophages, induced MMT in primary mesothelial cells via TGFβ and ERK/p38 MAPK signaling pathways. This phenotypic transition enhanced transmesothelial tumor cell invasion. Proteomic analysis identified IL-1α as a key MMT-inducing factor secreted by pro-inflammatory macrophages. Mechanistically, IL-1α cooperates with TGFβ by activating an autocrine TGFβ/TGFBR1 feedback loop in mesothelial cells, thereby amplifying MMT. Consistent with these findings, IL1A expression was enriched in omTAM clusters across independent patient samples and was confirmed by immunohistochemical analysis of clinical samples. From a therapeutic perspective, our study identifies new avenues to counteract the mesothelial reprogramming driven by IL-1α⁺ TAMs, potentially impeding metastatic progression. Created in BioRender. Heidemann, S. (2026) https://BioRender.com/aeu6yd0 .

Female↗

PubMed2025

Iterative, multimodal, and scalable single-cell profiling for discovery and characterization of signaling regulators.

Cell signaling plays a critical role in regulating cellular state, yet uncovering regulators of signaling pathways and understanding their molecular consequences remains challenging. Here, we present an iterative experimental and computational framework to identify and characterize regulators of signaling proteins, using the mTOR marker phosphorylated RPS6 (pRPS6) as a case study. We present a customized workflow that uses the 10x Flex assay to jointly profile intracellular protein levels, transcriptomes, and CRISPR perturbations in single cells. We use this to generate a "glossary" dataset of paired protein-RNA measurements across targeted perturbations, which we leverage to train a predictive model of pRPS6 levels based solely on transcriptomic data. Applying this model to a genome-wide Perturb-seq dataset enables in silico screening for pRPS6 and nominates novel regulators of mTOR signaling. Experimental validation confirms these predictions and reveals mechanistic diversity among hits, including changes in signaling output driven by anabolic activity, cellular proliferation and multiple stress pathways. Our work demonstrates how integrated experimental and computational approaches provide a scalable framework for multimodal phenotyping and discovery.

Journal Article↗

PubMed2025

The chloroplast 16S rRNA dimethyltransferase BrPFC1 is required for Brassica rapa development under chilling stress.

Chloroplast ribosomal RNA (Ch-rRNA) methylation is critical for plant development and response to low temperatures. Several Ch-rRNA methyltransferases and their catalytic modes, as well as biological relevance, have been reported in model plant species. However, Ch-rRNA methyltransferases and their functional significance remain poorly characterized in crops, including leafy vegetables such as Chinese cabbage. In this study, we screened an EMS-mutagenized Chinese cabbage population and identified a yellow inner leaf (yif) mutant. This mutant develops yellowing inner leaves with reduced chlorophyll accumulation and ultrastructure-impaired chloroplasts under low-temperature conditions. Genetic analysis revealed a premature termination mutation in BrPFC1, encoding the chloroplast-localized 16S rRNA dimethyltransferase. The BrPFC1 mutation (yif) disrupts the dimethylation of 16S rRNA. The cold-sensitive phenotype of the yif mutant can be explained by temperature-dependent defects in the maturation and assembly of chloroplast ribosomes at 4°C. Through integrated analysis of chloroplast and nuclear transcriptomes coupled with translational profiling at 25°C and 4°C, we established that low temperature preferentially upregulates transcripts encoding nuclear-derived ribosomal proteins, while defective 16S rRNA specifically compromises the translational efficiency of chloroplast-encoded photosynthetic complex and ribosomal protein at 4°C. These findings establish rRNA modification by BrPFC1 as a critical regulatory layer for optimizing chloroplast translational efficiency at 4°C, providing mechanistic insights into post-translational adaptation strategies in Chinese cabbage.

Chloroplasts↗

PubMed2026

Beyond Canonical Neoantigens: Emerging Technologies for Identification of Noncanonical Antigens and Implications for Personalized Cancer Vaccines.

Over the past decade, advances in sequencing technologies and computational pipelines enabled the development of personalized cancer vaccines (PCVs). Current PCV strategies primarily target cancer neoantigens generated by non-synonymous DNA mutations, which can result in altered amino acid sequences capable of eliciting tumor-specific immune responses. More recently, a distinct class of tumor-specific antigens (TSA), termed noncanonical or cryptic antigens, has emerged as an additional source of immunogenic targets. Unlike canonical neoantigens, noncanonical antigens typically cannot be identified by tumor/normal whole-exome sequencing, as they do not arise from classical DNA mutations. Instead, they are often associated with less well recognized and/or aberrant processes in the pathways from DNA to human leukocyte antigen (HLA)-presented peptides. Examples include transposable elements, circular RNA, translation of alternative open reading frames and/or long non-coding RNA, among others. Emerging evidence suggests that noncanonical antigens represent a substantial portion of the tumor-specific immunopeptidome and, similar to canonical neoantigens, are absent during thymic selection and can evade central tolerance and elicit T cell responses. Technological advances have increasingly facilitated the identification of noncanonical antigens. Long-read RNA sequencing reveals noncanonical transcripts by improving transcriptome assembly, while ribosome profiling provides genome-wide maps of actively translated regions, facilitating the discovery of peptides from aberrant translation events. Specialized molecular approaches enable enrichment and sequencing of circular RNAs, and immunopeptidomics using mass spectrometry allows for direct characterization of HLA-presented peptides. Together, these technological advances have led to an increasing interest in prioritizing and targeting noncanonical antigens in the next generation of PCVs. This review provides an overview of the diverse origins of TSAs beyond classical neoantigens and discusses emerging approaches that may enable the integration of these antigens in future clinical trials.

circular RNA↗

PubMed2026

CCT2 defines a highly cisplatin-resistant and poor-prognosis subtype of lung adenocarcinoma.

Cisplatin-based chemotherapy is a standard treatment for lung adenocarcinoma (LUAD), yet acquired cisplatin resistance remains a marked cause of treatment failure. The molecular mechanisms driving cisplatin resistance in LUAD have not been fully elucidated. The present study integrated bulk transcriptomic data, genomic mutation profiles and single-cell RNA sequencing data to systematically investigate cisplatin resistance in LUAD. Resistance-associated genes were identified through differential expression, survival analysis and database integration. Unsupervised clustering was used to define cisplatin resistance-associated subtypes. Functional characteristics were explored using pathway enrichment, immune infiltration, tumor mutation burden and weighted gene co-expression network analysis. A machine learning framework incorporating 101 algorithms was applied to identify key genes and construct a prognostic model. Single-cell analyses and in vitro experiments were performed to validate the biological role of the core gene. Molecular docking and molecular dynamics simulations were conducted to identify potential therapeutic compounds. A total of two molecular subtypes with distinct cisplatin resistance levels and prognostic outcomes were identified. The high-resistance subtype exhibited enhanced cell cycle activity, DNA repair signaling and immune heterogeneity. Machine learning analysis revealed a five-gene signature, with chaperonin-containing TCP1 subunit 2 (CCT2) emerging as a key regulator of cisplatin resistance. Single-cell analyses showed that CCT2 was predominantly enriched in resistant epithelial cell subpopulations. Functional experiments demonstrated that CCT2 knockdown significantly inhibited cell proliferation and enhanced cisplatin sensitivity in LUAD cell lines. A number of candidate compounds targeting CCT2 exhibited stable binding in silico. The present findings identified CCT2 as a key mediator of cisplatin resistance in LUAD and provided potential therapeutic strategies to overcome chemotherapy resistance.

chaperonin-containing TCP-1 subunit 2↗

PubMed2026

The ASH HematOmics Program supports integrative analysis of genomic and clinical data in hematologic diseases.

The increasing availability of genomic and transcriptomic sequencing has uncovered diverse genomic alterations and distinct gene expression profiles driving hematologic diseases, yet a data integration and sharing platform dedicated to hematology remains lacking. We developed the American Society of Hematology (ASH) HematOmics Program (ASHOP; ashop.hematology.org), a resource for exploring somatic alterations and gene fusions, transcriptomic results, and clinical data from 5960 patients spanning B-cell precursor and T-cell acute lymphoblastic leukemia, acute myeloid leukemia, myelodysplastic syndromes, and chronic lymphocytic leukemia. Users can explore genomic alteration landscapes and comutation patterns via lollipop and matrix plots and analyze significantly altered genes in user-defined subcohorts. Transcriptomes can be explored through interactive uniform manifold approximation and projections, clustering, differential expression, and pathway enrichment. Genomic, transcriptomic features, and clinical outcomes can be correlated in a user-driven manner or combined to precisely define study cohorts. We illustrate the following 4 use cases of ASHOP: (1) stratification of DUX4-rearranged B-cell leukemias into Early/Multipotent and Committed subgroups with distinct outcomes, (2) characterization of HOXA/HOXB expression patterns in acute myeloid leukemias, (3) correlating mutational burden with mismatch repair deficiency and mutational signatures, and (4) investigation of TP53 alteration landscape. ASHOP is an open-access resource to inform genomic and transcriptomic data interpretation for hematologic malignancies and will expand to support additional diseases and data modalities from the ASH community.

Humans↗

PubMed2026

Integrative pooled transcriptomic analysis reveals shared and distinct molecular signatures in adult T-cell leukemia/lymphoma and peripheral T-cell lymphoma.

Adult T-cell leukemia/lymphoma (ATLL) and peripheral T-cell lymphomas (PTCLs) are aggressive neoplasms of mature T cells with poor prognosis and limited therapies. ATLL originates from HTLV-1 infection, while PTCL comprises heterogeneous subtypes without a defined etiologic factor. Comparative molecular profiling of these malignancies remains limited. We conducted an integrative pooled transcriptomic analysis of publicly available Gene Expression Omnibus (GEO) microarray datasets to compare ATLL, PTCL, and normal T-cell samples. Differential expression, functional enrichment, and protein-protein interaction (PPI) network analyses were performed using STRING, Cytoscape, and Gephi. Key hub genes and functional modules were further analyzed through KEGG and Enrichr databases. Comparative analyses revealed upregulation of extracellular matrix (ECM) components (COL1A1, COL3A1, FN1, SPARC, THBS1) and immune-regulatory molecules (CD163, CXCL12-CXCR4, complement subunits). Shared pathways included ECM-receptor interaction, focal adhesion, and PI3K-Akt signaling. PTCL showed enrichment in coagulation and angiogenesis, while ATLL displayed distinct enrichment of cytoskeletal, chemokine, immune-regulatory, and signaling-associated pathways. PPI networks identified ECM and chemokine signaling as key hubs, with subtype-specific modules related to immune regulation, proliferation, and metabolism. This integrative approach uncovers common and distinct oncogenic programs in ATLL and PTCL, emphasizing ECM remodeling and immune modulation as shared hallmarks. Hub genes such as COL1A1, FN1, and CXCL12-CXCR4 may represent candidate molecular signatures that warrant validation in independent patient cohorts and functional studies before their clinical utility can be established.

Humans↗

PubMed2025

RNA sequencing offers new diagnostic opportunities in neurodevelopmental disorders: A systematic review.

PURPOSE: Transcriptomics by way of RNA sequencing (RNAseq) has emerged as a means to increase the diagnostic yield in genetic conditions. In this systematic review, we focus on the contribution of transcriptomics to improve the diagnostic yield in neurodevelopmental disorders. METHODS: We performed a systematic literature search in PubMed until January 2024, including articles describing diagnostic RNAseq on at least 1 individual with a primary neurodevelopmental phenotype. We extracted data on cohort size, phenotype, sample tissue, previously used diagnostic methods, added diagnostic yield of RNAseq, the use of control samples, and technical aspects of the RNA sequencing methodology. RESULTS: A total of 17 articles were eligible for inclusion in the systematic review. We found an average added diagnostic yield of 15.5% through RNA sequencing for individuals with neurodevelopmental disorders. There is heterogeneity in the tissue type, reported quality measures, and the computational pipeline. CONCLUSION: The significantly increased diagnostic yield demonstrates the value of this novel tool in the diagnostic setting of neurodevelopmental disorders. Our results offer an overview of common methodologies for RNAseq and allow us to formulate recommendations for genetic labs and clinicians when implementing RNAseq as a diagnostic tool. Lastly, we provide recommendations for future publications to increase transparency and reproducibility.

Humans↗

PubMed2026

CoxFormer enables spatial omics inference with multimodal generative modeling.

Gene co-expression maps transcriptome-wide gene-gene relationships, yet high-quality estimates cover less than half the genome. Meanwhile, spatial omics either profiles restricted in situ panels or lacks cellular resolution. Extending co-expression transcriptome-wide could overcome these limitations by inferring unassayed gene expression at subcellular resolution. Here we show that CoxFormer integrates literature-derived gene knowledge with co-expression networks from bulk tissues and large-scale single-cell atlases to learn 512-dimensional representations for 32,016 human genes. These embeddings capture functional gene relationships and serve as a generative prior for spatial inference across platforms and modalities. Without requiring a matched single-cell RNA-sequencing reference, CoxFormer supports four applications beyond measured genes: histology-based expression imputation, gene activity prediction from chromatin accessibility, subcellular super-resolution inference, and pathological region detection. Together, CoxFormer extends gene embedding from gene- and cell-level tasks to whole-transcriptome spatial inference, providing a unified framework for biological analysis beyond the limited gene coverage of current spatial omics technologies.

Humans↗

PubMed2025

Interaction of host gene-gut microbiota in male grading of Macrobrachium rosenbergii.

UNLABELLED: The giant freshwater prawn (GFP; Macrobrachium rosenbergii), a crustacean of high nutritional and economic value, is crucial for aquaculture. During the same growth cycle, male GFPs develop into three distinct forms: small males, orange claw males, and blue claw males. These morphotypes display varying social behaviors, which severely constrain their industrial development. To address this, this study collected male GFP samples at critical developmental time points (100, 110, and 120 days post-hatching) for phenotypic trait measurement and analysis to obtain external morphological data. Through gut microbiota diversity analysis, we identified key gut bacteria (Lactococcus garvieae and Lactobacillus taiwanensis) influencing male morphotype differentiation. Transcriptomic analysis revealed host Kyoto Encyclopedia of Gene and Genome pathways and key genes (Wnt-6, CTSB, CTSL, PPAE, and TP53) associated with morphotype differentiation. The interactions among phenotypic traits, gut microbiota, and key genes were systematically studied through association analysis. Weighted gene co-expression network analysis was employed to construct co-expression modules, from which critical gene modules influencing phenotypic variation were identified. Through association network analysis, we established an "Achromobacter-CD-TRINITY_DN93139_c0_g2 (calpain clp-1)" interaction model. Our findings provide novel insights into the genetic enhancement of GFPs and offer guidelines for future research regarding gut symbiotic bacteria and breeding initiatives. IMPORTANCE: Male Macrobrachium rosenbergii (giant freshwater prawn [GFP]) in the same growth cycle will develop into small males, orange claw males, and blue claw males. This individual heterogeneity in growth significantly impacts the benefits of aquaculture. However, the factors influencing the differentiation of male GFP morphotype remain unclear. This study analyzed the phenotypic data of various GFP levels, the structure of the intestinal microbiota, and the differential genes within the gonadal transcriptome at critical time points of male GFP-level type differentiation. The aim was to explore the potential role of intestinal microbiota and differential genes in this phenomenon. This study offers new insights into the research on the phenomenon of male GFP-level type differentiation.

Animals↗

PubMed2026

Systemic immune activation in hereditary cancer predisposition syndromes: a cross-sectional study.

BACKGROUND: Immune surveillance mechanisms contribute to the elimination of precancerous lesions in hereditary cancer predisposition syndromes (HCPSs). METHODS: By combining single-cell transcriptomics, multiparametric mass cytometry and cytokine profiling of the systemic immune environment in 391 individuals among whom 227 are living with HCPSs we investigated phenotypic alterations in cancer-free individuals with HCPS. RESULTS: A decrease in peripheral B cell abundance and their more differentiated phenotype have been confirmed both in breast cancer patients with germline pathogenic variants in BRCA1 (gpath(BRCA1)) and in patients living with Lynch syndrome (LS). Pre-cancer women with gpath(BRCA1) exhibited an activated phenotype of multiple immune cell lineages, similar to those with manifest disease. In LS, B cell phenotypes exhibited the largest changes in response to cancer eradication, while increased peripheral IL-6 levels was detected even in presymptomatic individuals with LS. CONCLUSIONS: HCPS-specific differences in the phenotype of the systemic immune system might be leveraged in future risk-reducing strategies.

Humans↗

PubMed2026

Profiler: an open web platform for multi-omics analysis.

MOTIVATION: High-throughput multi-omics technologies produce increasingly large and heterogeneous datasets that are difficult to analyze without advanced computational expertise. Existing bioinformatics tools are often fragmented or limited to specific omics types, hindering reproducibility and accessibility. There is a critical need for an integrated, user-friendly, and scalable platform capable of supporting multi-omics analyses across different data modalities. RESULTS: We present Profiler, an open-source, modular platform that unifies data import, quality control, preprocessing, statistical testing, machine and deep learning, biomarker discovery, pathway and drug-target enrichment, and survival modeling within a single reproducible environment. Built in Python with Streamlit, Profiler is available as both a web-based platform deployed on high-performance computing and a desktop version for local execution, enabling flexible usage across computational infrastructures. Profiler supports diverse omics modalities, including proteomics, transcriptomics, lipidomics, and electroencephalogram data. Through applications to glioblastoma proteomic, pancancer, and multi-omics datasets, Profiler reproduced known molecular subtypes, revealed potential therapeutic targets, and generated fully traceable analysis reports within minutes. By integrating advanced analytics behind an intuitive interface, Profiler democratizes multi-omics analysis and provides a robust, scalable foundation for systems biology and precision medicine research. AVAILABILITY AND IMPLEMENTATION: Profiler is open-source and freely available via its web platform (https://prism-profiler.univ-lille.fr) and GitHub (web version: https://github.com/yanisZirem/Profiler_v1_requests_datatests, desktop version: https://github.com/yanisZirem/prism-profiler), and archived on Zenodo (DOI: https://doi.org/10.5281/zenodo.17478158).

Software↗

PubMed2024

Integration of Imaging-based and Sequencing-based Spatial Omics Mapping on the Same Tissue Section via DBiTplus.

Spatially mapping the transcriptome and proteome in the same tissue section can significantly advance our understanding of heterogeneous cellular processes and connect cell type to function. Here, we present Deterministic Barcoding in Tissue sequencing plus (DBiTplus), an integrative multi-modality spatial omics approach that combines sequencing-based spatial transcriptomics and image-based spatial protein profiling on the same tissue section to enable both single-cell resolution cell typing and genome-scale interrogation of biological pathways. DBiTplus begins with in situ reverse transcription for cDNA synthesis, microfluidic delivery of DNA oligos for spatial barcoding, retrieval of barcoded cDNA using RNaseH, an enzyme that selectively degrades RNA in an RNA-DNA hybrid, preserving the intact tissue section for high-plex protein imaging with CODEX. We developed computational pipelines to register data from two distinct modalities. Performing both DBiT-seq and CODEX on the same tissue slide enables accurate cell typing in each spatial transcriptome spot and subsequently image-guided decomposition to generate single-cell resolved spatial transcriptome atlases. DBiTplus was applied to mouse embryos with limited protein markers but still demonstrated excellent integration for single-cell transcriptome decomposition, to normal human lymph nodes with high-plex protein profiling to yield a single-cell spatial transcriptome map, and to human lymphoma FFPE tissue to explore the mechanisms of lymphomagenesis and progression. DBiTplusCODEX is a unified workflow including integrative experimental procedure and computational innovation for spatially resolved single-cell atlasing and exploration of biological pathways cell-by-cell at genome-scale.

Journal Article↗

PubMed2024

Integration of Imaging-based and Sequencing-based Spatial Omics Mapping on the Same Tissue Section via DBiTplus.

Journal Article↗

PubMed2026

Whole-transcriptome-scale isoform-resolved spatial imaging of single cells in tissues.

Cell and tissue functions arise from complex interactions among numerous genes, and a systematic understanding of these functions requires isoform-resolved transcriptomic analysis of single cells with high spatial resolution. Here, we introduce an in situ RNA amplification method and its integration with multiplexed error-robust fluorescence in situ hybridization (MERFISH) to detect short RNA sequences and enable whole-transcriptome-scale, isoform-resolved spatial transcriptomics of individual cells in intact tissues. Using this approach, we imaged ∼33,000 distinct RNAs-including ∼23,000 genes and ∼10,000 isoforms-in the mouse brain. Our data enabled systematic analyses of region- and cell-type-specific gene programs and ligand-receptor-based cell-cell communications. These data further revealed rich spatial diversity and cell-type specificity in isoform usage across numerous genes, as well as brain structures particularly rich in isoform specificity. We anticipate broad application of this method for characterizing the molecular and cellular basis of tissue functions, unlocking previously inaccessible discoveries in cell and organismal biology.

Animals↗

PubMed2026

A High-Resolution Stereo-Seq Spatial Transcriptomic Resource for Adult Holstein Cattle Liver.

The bovine liver is a highly compartmentalized organ that plays essential roles in continuous gluconeogenesis and nitrogen recycling; however, its spatial molecular architecture has remained largely uncharacterized due to the limitations of traditional bulk and single-cell approaches. To address this gap, Spatial Enhanced Resolution Omics-sequencing (Stereo-seq) was utilized to generate a subcellular-resolution (500 nm) transcriptomic map of an adult Holstein cattle liver, and a refined reference-guided workflow was implemented to overcome standard annotation limitations in livestock. Raw sequencing data were processed using the Stereo-seq Analysis Workflow and analyzed with Stereopy, Seurat, SingleR, and reference-guided workflows. Spatial aggregation was evaluated at Bin20, Bin50, Bin100, Bin150, and Bin200. Increasing bin size increased molecular identifier counts and detected-gene complexity while progressively reducing spatial granularity. Bin50, corresponding to 50 × 50 DNA nanoballs and an approximate nominal footprint of 25 × 25 µm, was therefore selected as a practical intermediate aggregation level for the primary analyses. Quality-control assessment, Leiden clustering, UMAP visualization, reference-based cell-type annotation, cluster-marker analysis, and spatial mapping of canonical hepatic genes demonstrated preservation of biologically interpretable liver transcriptional organization. Raw sequencing data processed spatial matrices, annotated objects, and analysis code are publicly available to support reanalysis and computational benchmarking. In summary, we present a Stereo-seq spatial transcriptomic resource generated from liver tissue of an adult Holstein cow. This initial resource provides a valuable foundation for future studies of bovine liver biology, comparative genomics, and the spatial basis of livestock health and production traits.

Animals↗

PubMed2026

Mining the sHSP20 (small heat-shock protein) gene family in finger millet (Eleusine coracana (L.) Gaertn.): structural, evolutionary and predicted abiotic-stress-responsive insights.

Small heat-shock proteins (sHSPs, the HSP20 family) are ATP-independent molecular chaperones that hold partially unfolded substrates and protect the proteome during heat and other abiotic stresses; every member is defined by a conserved α-crystallin domain (ACD). Finger millet (Eleusine coracana) is a climate-resilient, calcium-rich allotetraploid cereal of the semi-arid tropics whose HSP20 repertoire had not been catalogued. The present study is an entirely computational (in silico) analysis of the chromosome-scale reference genome of finger millet (NCBI GenBank assembly GCA_032690845.1, cultivar KNE 796-S). Mining the predicted proteome with the ACD profile (Pfam PF00011) and confirming every candidate by NCBI CD-search recovered 76 non-redundant ACD-bearing HSP20 genes (EcHSP20-1-EcHSP20-76). Based on phylogeny and TargetP-predicted localization, the members were classified into ten subfamilies: seven cytosolic/nuclear classes (C-I to C-VII, 60 members) together with chloroplastic (11), mitochondrial (3) and endoplasmic-reticulum (2) groups. The proteins ranged from 110 to 355 amino acids (12.1-39.2 kDa) with theoretical pI of 4.85-9.69. The 76 loci were distributed over 14 of the 18 chromosomes and were conspicuously absent from chromosomes 8 A, 8B, 9 A and 9B, with pronounced clustering on chromosomes 1, 2, 3 and 6. Duplication analysis detected 149 paralogous pairs (49 homoeologous, 80 segmental/dispersed and 18 tandem); 147 of 148 pairs for which substitution rates could be calculated returned Ka/Ks < 1 (mean 0.20), indicating strong purifying selection consistent with retention after whole-genome/allopolyploid duplication. Promoter analysis (PlantCARE) revealed enrichment of abscisic-acid-responsive (ABRE), MYB/MYC drought-related, STRE, DRE, low-temperature (LTR) and methyl-jasmonate/salicylic-acid elements, whereas canonical heat-shock elements (HSE) were not recovered. Expression profiling against a public drought transcriptome (SRP081350) showed that about half of the genes (39 of 76) are transcribed in leaf tissue, the expressed fraction being dominated by the cytosolic class C-I. This first finger-millet HSP20 catalogue provides a verified, reproducible framework and nominates computationally predicted candidate genes for future functional work on thermotolerance in cereals.

Allotetraploid↗