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PubMed2026

Uncovering hub genes and key pathways responsive to drought stress in rice via meta-analysis of transcriptomic data.

Drought stress presents a formidable threat to global rice cultivation, triggering complex molecular responses that impact plant growth and productivity. To decipher the underlying gene expression dynamics, we performed a comprehensive meta-analysis of transcriptomic datasets derived from drought-tolerant rice genotypes. Via microarray data from three independent studies, we identified a set of consistently expressed differentially expressed genes (DEGs) under drought conditions. Integration of functional annotation tools, including GO and KEGG pathway enrichment, revealed key biological processes and signaling cascades involved in stress mitigation, such as ABA signaling, protein folding, and photosynthesis suppression. Protein-protein interaction (PPI) network construction, followed by hub gene identification via maximal clique centrality (MCC), highlighted pivotal regulators including LEA proteins, dehydrins, HSP70, and several transcription factors. Machine learning approaches further prioritize potential biomarkers, with Random Forest models achieving high classification accuracy and pinpointing key predictive genes. Chromosomal localization analysis provided spatial insights into the distribution of these hub genes, whose expression patterns were further compared against qRT-PCR data from previously published studies. This integrative approach identifies candidate genomic markers and mechanistic insights that may support future breeding strategies for drought-tolerant rice, pending experimental validation.

Cytoscape↗

PubMed2026

Beyond benchmarking: an expert-guided consensus approach to spatially aware clustering.

Spatial omics technologies have revolutionized the study of tissue architecture and cellular heterogeneity by integrating molecular profiles with spatial localization. In spatially resolved transcriptomics, delineating higher-order anatomical structures is critical for understanding how cellular organization affects function. However, the reliability of current benchmarks of spatially aware clustering (SAC) methods is undermined by their narrow focus on Visium and brain tissue datasets and the incorrect interpretation of manual annotation as ground truth. Here we present SACCELERATOR, a community-driven, extensible framework that standardizes data formatting, method integration and metric evaluation, enabling rapid inclusion of new methods and datasets. Our analysis revealed substantial limitations in the generalizability and reproducibility of SAC methods and shows that anatomical labels commonly used as ground truths are often biased, error prone and unsuitable for benchmarking. Rather than ranking methods, we propose a consensus-guided workflow where descriptive spatial metrics highlight high-entropy regions of method disagreement, enabling targeted feedback for tissue experts. Applied to brain and cancer datasets, this approach uncovered biologically meaningful patterns overlooked by individual SAC methods and manual annotations, highlighting the need for iterative, expert-in-the-loop evaluation.

Benchmarking↗

PubMed2026

Transcriptomic insights into the coordinated regulation of signaling, apoptosis, immunity, and metabolism during Sinonovacula constricta larval metamorphosis.

Metamorphosis is a critical ontogenetic transition for marine bivalves, marking the shift from planktonic to benthic lifestyles, where successful transformation dictates survival. The razor clam Sinonovacula constricta is economically important; however, low larval metamorphosis rates remain a major bottleneck in seedling production. To elucidate the mechanisms governing this process, we performed a comparative transcriptome analysis of S. constricta larvae at pre- and post-metamorphosis stages using Illumina sequencing. A total of 3701 differentially expressed genes (DEGs) were identified, including 3254 up-regulated and 447 down-regulated genes. Functional annotation of the respective top 20 significantly up-regulated and down-regulated DEGs indicated their potential pivotal roles in signal transduction (e.g., up-regulated: CAV1, CHRNA2; down-regulated: APP, NOTCH1), cellular proliferation and differentiation (e.g., up-regulated: TUBA, EGF1; down-regulated: KIF23, TTC25), transcriptional and epigenetic regulation (e.g., up-regulated: NFIL3; down-regulated: OVO, HMX1), substance transport (e.g., up-regulated: LRP2, LRP1B; down-regulated: SLC51A, Slc33a1), substance metabolism (e.g., up-regulated: CPK3, CYP26A1; down-regulated: RDMT1, ADAC), immunomodulation (e.g., up-regulated: CPN2, CRISP2), and protein homeostasis (e.g., up-regulated: HSP27, NAS-27). Functional enrichment analysis further revealed that DEGs were significantly enriched in pathways related to signal transduction and developmental regulation (e.g., Ras, TNF), cell death and homeostasis (e.g., apoptosis), immune responses (e.g., Toll-like receptor), energy metabolism (e.g., lipid), cardiovascular related (e.g., Fluid shear stress), cell junction and architecture (e.g., Tight junction), and infectious disease (e.g., measles). These results suggest a synergistic interplay between signaling, apoptosis, immunity, and metabolism during S. constricta metamorphosis. This study advances our understanding of marine bivalve metamorphosis and offers candidate genes for further mechanistic studies.

Animals↗

PubMed2026

A transcription factor regulatory atlas for activity inference and perturbation prediction.

Inferring transcription factor (TF) activity from transcriptomes and predicting transcriptome-wide responses to TF perturbations remain challenging, in part because available TF-mRNA resources often face a trade-off between precision and coverage and typically lack signed regulatory information. Here, we present TFActProfiler, a TF-mRNA resource and computational framework that learns signed, quantitative TF-mRNA regulatory coefficients by integrating heterogeneous prior evidence (ChIP-based, motif-based, and curated TF-mRNA annotations) with large-scale bulk and single-cell RNA-seq atlases. TFActProfiler contains 2 606 176 signed TF-mRNA interactions and improves TF activity inference in TF knockdown benchmarks relative to widely used regulon resources while retaining broad TF and target coverage. In addition, because the same learned regulatory coefficients can be used to model downstream transcriptional effects, TFActProfiler enables prediction of transcriptome-wide gene expression responses to TF knockdown without training on task-matched perturbation data. When perturbation datasets are available, TFActProfiler can be further refined to achieve performance comparable to state-of-the-art machine-learning baselines. By providing a direction-aware representation of TF-mRNA regulation for both activity inference and perturbation-response modeling, TFActProfiler supports systematic dissection of gene regulatory programs across diverse cellular contexts.

Transcription Factors↗

PubMed2024

Transcriptome-Wide Root Causal Inference.

Root causal genes correspond to the first gene expression levels perturbed during pathogenesis by genetic or non-genetic factors. Targeting root causal genes has the potential to alleviate disease entirely by eliminating pathology near its onset. No existing algorithm discovers root causal genes from observational data alone. We therefore propose the Transcriptome-Wide Root Causal Inference (TWRCI) algorithm that identifies root causal genes and their causal graph using a combination of genetic variant and unperturbed bulk RNA sequencing data. TWRCI uses a novel competitive regression procedure to annotate cis and trans-genetic variants to the gene expression levels they directly cause. The algorithm simultaneously recovers a causal ordering of the expression levels to pinpoint the underlying causal graph and estimate root causal effects. TWRCI outperforms alternative approaches across a diverse group of metrics by directly targeting root causal genes while accounting for distal relations, linkage disequilibrium, patient heterogeneity and widespread pleiotropy. We demonstrate the algorithm by uncovering the root causal mechanisms of two complex diseases, which we confirm by replication using independent genome-wide summary statistics.

Journal Article↗

PubMed2025

Chromosome-level genome assembly of Ampulex clypecomplana Chen & Li (Hymenoptera: Ampulicidae).

Ampulex clypecomplana Chen & Li, 2010 (Hymenoptera: Ampulicidae) is an important predatory insect in Hymenoptera. However, molecular information about this predatory insect is currently limited. In this study, we employed ONT long-read sequencing, MGI-SEQ short-read sequencing, Hi-C sequencing and transcriptomic data to assemble the high-quality genome of A. clypecomplana. The genome assembly length was 338.43 Mb, with a Scaffold N50 length of 19.05 Mb. Our BUSCO analysis further confirmed the gene coverage completeness of the genome assembly to be 99.2%. Phylogenetic analysis indicated that A. clypecomplana appeared approximately 132 million years ago. We annotated 110.75 Mb of repetitive sequences, accounting for 32.72% of the entire genome. In A. clypecomplana, we identified 180 gene expansions and 1029 genes that underwent contraction or loss. The high-quality genome of A. clypecomplana provides a valuable genetic resource for future research in evolution, molecular biology, and applied studies.

Animals↗

PubMed2026

Genomic Characterization of ETV6::RUNX1-Positive Childhood B-ALL in a Chinese Cohort: Novel Fusion Partners, Co-Occurring Mutations, and Risk-Stratifying Biomarkers.

BACKGROUND: ETV6::RUNX1 is the most common genetic abnormality in pediatric B-cell acute lymphoblastic leukemia (ALL; ∼25%), yet the comprehensive genetic architecture and molecular predictors of intermediate-risk (IR) stratification remain incompletely characterized. METHODS: We performed whole-transcriptome sequencing (Illumina NovaSeq 6000, rRNA depletion, 41.70 Gb/sample) on bone marrow samples from 93 pediatric ETV6::RUNX1-positive B-ALL patients. Bioinformatics analysis included STAR alignment, MuTect2 variant calling, FusionCatcher fusion detection, and VEP annotation. The Jaccard index with permutation testing assessed mutation co-occurrence; logistic regression identified independent predictors of IR classification. RESULTS: Beyond ETV6::RUNX1, we identified 51 distinct fusion genes across the cohort, including the reciprocal RUNX1-ETV6 (73.1%), chr8::KLF1210 (38.7%), and KLF12-chr8 (34.4%). Somatic mutations in 249 genes were detected; the most frequent were KIAA1715 (17.2%), KRAS (11.8%), and NSD2 (10.8%). Network analysis revealed significant chromatin modifier co-occurrence (KIAA1715-KMT2C: J = 0.136, p = 0.015) and KRAS-NRAS mutual exclusivity (J = 0.000, p = 0.042). PTCH1 (OR = 3.50, 95% CI 0.21-58.49, p = 0.41) and GNB1 (OR = 6.5, 95% CI 1.2-34.8, p = 0.029) mutations independently predicted IR classification. chr8::KLF1210 fusion correlated with higher Day-19 MRD levels (p = 0.038). CONCLUSIONS: GNB1 mutation represents a novel independent predictor of IR stratification in ETV6::RUNX1-positive B-ALL. The chromatin modifier co-occurrence module and extensive fusion architecture reveal biological heterogeneity within this favorable-risk subtype, with potential implications for risk-adapted therapeutic strategies.

B‐ALL↗

PubMed2026

An XRE-type regulator in Streptococcus mutans plays an important role in brpA expression and oxidative stress tolerance response.

This study used a functional genomics approach to explore the role of a xenobiotic response element (XRE)-type regulator (SMU.405c) in Streptococcus mutans physiology, including the expression of biofilm regulatory protein BrpA. Results showed that deletional mutation of xre significantly reduced the ability of the deficient mutant to grow in the presence of methyl viologen, a commonly used oxidative stressor (P < 0.001). When challenged in a hydrogen peroxide killing assay, the survival rate of the ∆xre mutant was >2-log less than the parent strain after 60 min (P < 0.001). Luciferase reporter fusion assays showed that xre deficiency had no significant effect on luciferase expression when it was under the control of the intact brpA promoter, but the reporter activity increased by >6-fold (P < 0.001) when the reporter gene was fused to a brpA promoter derivative with deletion of a putative XRE-binding box. Electrophoretic mobility shift assay (EMSA) showed that recombinant XRE interacted with the brpA promoter, resulting in an electrophoretic shift of the promoter probes. In vitro transcription assay also showed that inclusion of XRE caused transcription to fall off, significantly reducing full-length brpA transcripts. RNA-seq analysis revealed that deficiency of XRE led to altered expression of >102 genes by >2-fold (P < 0.05), including 28 with increased expression, and 74 with decreased expression. Among the down-regulated were genes for DNA repair and oxidative stress tolerance response. These results suggest that XRE (SMU.405c) in S. mutans plays an important role in brpA expression and oxidative stress tolerance response.IMPORTANCEStreptococcus mutans, a keystone pathogen in human dental caries, primarily lives in the highly diverse microbiota on tooth surfaces, where the conditions are often harsh and fluctuate frequently. Locus SMU.405c was annotated to encode a xenobiotic response element (XRE)-like transcriptional regulator, but no information is available concerning the role of this protein in S. mutans pathophysiology. This study used a functional genomics approach along with molecular and transcriptomic analysis to characterize a deletional xre mutant, and the results showed that xre deficiency in S. mutans resulted in weakened oxidative stress tolerance response and alterations in transcription of >102 genes, including those known to play an important role in cell envelope biogenesis and stress tolerance response. Reporter fusion assay, electrophoretic mobility shift assay (EMSA), and in vitro transcription further demonstrated that the XRE-like regulator encoded by SMU.405c is a repressor of brpA expression and plays an important role in oxidative stress tolerance response.

Streptococcus mutans↗

PubMed2026

Single-cell spatial transcriptomic atlas of the mouse adrenal gland reveals sexual dimorphism in steroidogenic enzyme and hormone receptor expression.

The adrenal cortex shows sexual dimorphism in structure and function. We analysed adrenal glands from 7-week-old male and female BALB/c mice using Visium HD with Cellpose 3 segmentation, comprising 236,077 cells across eleven populations, including four cortical zones. Using curated marker-gene-based zonal annotation, we focused on steroidogenic enzymes and hormone receptors, complementing our companion study based on the same primary dataset. The X-zone was nearly absent in males but prominent in females. Females showed higher Hsd3b1 expression across cortical zones and higher Cyp11b1 expression in outer cortical compartments. The strongest sex difference involved Srd5a2, with markedly higher expression in male zona fasciculata (inner: 77.1% vs. 28.9%), independently supported by RNAscope and immunohistochemistry. Mc2r and Mrap showed discordant spatial distributions, with limited co-expression, suggesting potential MC2R-independent MRAP roles. Agtr1a dominated angiotensin II receptor expression in zona glomerulosa without major sex differences, providing a zone-resolved reference for adrenal sexual dimorphism.

Adrenal cortex↗

PubMed2026

Shared genetic basis and spatial cellular atlas of psoriasis and metabolic syndrome.

BACKGROUND: Psoriasis (PS) and metabolic syndrome (MetS) frequently co-occur. Characterizing their shared genetic architecture and spatially enriched cellular populations may clarify the context of their co-occurrence and generate hypotheses for functional validation. METHODS: We integrated genome-wide association study (GWAS) summary statistics for PS, MetS, and five related components with spatially resolved single-cell transcriptomic data. Global and local genetic correlations were assessed using linkage disequilibrium score regression, genetic covariance analysis, high-definition likelihood, and local analysis of variant association. A bivariate causal mixture model quantified polygenic overlap. Conditional/conjunctional false discovery rate and composite-null pleiotropy analyses identified shared susceptibility loci. Finally, gsMap evaluated trait-associated enrichment across annotated embryonic tissues at single-cell resolution. RESULTS: Genetic approaches identified significant genome-wide correlations and polygenic sharing between PS, MetS, and its components. Local and cross-trait analyses identified region-specific signals and cross-validated shared loci. gsMap revealed trait-specific tissue enrichment. PS showed the strongest enrichment in the epidermis (pCauchy = 1.0573 × 10  - ⁴), adipose tissue (pCauchy = 1.5366 × 10 - ⁴), and liver (pCauchy = 1.0167 × 10 - ³). Across MetS, FBG, HDL-C, hypertension, and TG, enriched regions mainly involved the liver, adipose tissue, and epidermis. WC enrichment was predominantly observed in adipose tissue (pCauchy = 1.7823 × 10 - ⁴), with no significant liver or epidermal enrichment. CONCLUSION: Integrating GWAS with single-cell transcriptomic and spatial information characterized shared genetic architecture between PS and MetS-related phenotypes and their spatial enrichment patterns. These findings provide a framework for generating testable hypotheses about comorbidity biology and guiding future functional and clinical validation.

Psoriasis↗

PubMed2024

Deciphering the ghost proteome in ovarian cancer cells by deep proteogenomic characterization.

Proteogenomics is becoming a powerful tool in personalized medicine by linking genomics, transcriptomics and mass spectrometry (MS)-based proteomics. Due to increasing evidence of alternative open reading frame-encoded proteins (AltProts), proteogenomics has a high potential to unravel the characteristics, variants, expression levels of the alternative proteome, in addition to already annotated proteins (RefProts). To obtain a broader view of the proteome of ovarian cancer cells compared to ovarian epithelial cells, cell-specific total RNA-sequencing profiles and customized protein databases were generated. In total, 128 RefProts and 30 AltProts were identified exclusively in SKOV-3 and PEO-4 cells. Among them, an AltProt variant of IP_715944, translated from DHX8, was found mutated (p.Leu44Pro). We show high variation in protein expression levels of RefProts and AltProts in different subcellular compartments. The presence of 117 RefProt and two AltProt variants was described, along with their possible implications in the different physiological/pathological characteristics. To identify the possible involvement of AltProts in cellular processes, cross-linking-MS (XL-MS) was performed in each cell line to identify AltProt-RefProt interactions. This approach revealed an interaction between POLD3 and the AltProt IP_183088, which after molecular docking, was placed between POLD3-POLD2 binding sites, highlighting its possibility of the involvement in DNA replication and repair.

Humans↗

PubMed2026

Comparative phylogenomics and transcriptional regulatory networks of AQPs, HSPs, and LEA proteins in salt-stressed Portulaca oleracea.

Soil salinization severely threatens global food security, necessitating systematic investigations of halophytes like Portulaca oleracea to decode the molecular mechanisms of environmental resilience. Utilizing an integrated framework of deep learning-based genome annotation (58,817 predicted genes; 96.5% BUSCO completeness), multi-tissue RNA-Seq, phylogenomics, and gene regulatory network (GRN) inference, the synergistic orchestration of 78 aquaporins (AQPs), 525 heat shock proteins (HSPs), and 119 late embryogenesis abundant (LEA) proteins was elucidated. The active transcriptome, encompassing 39,065 expressed loci, revealed a systemic growth-defense trade-off. Tissues displayed distinct adaptive mechanisms: leaves modulated intracellular water balance via specialized AQPs, whereas adult roots maintained proteostasis through robust HSP20/HSP70 induction. Phylogenomic clustering across 154 species demonstrated that salinity tolerance constitutes an evolutionary mosaic, identifying 81 halophyte-exclusive orthogroups and 1129 species-specific clusters. Comparative topology across six independent GRNs (4.2M-5.3 M edges) unmasked a highly modular transcriptional reprogramming strategy governed by a core apparatus of 22 stress-exclusive regulators, with functional enrichment heavily prioritizing protein dimerization and chromatin remodeling. Theoretically, the distinct convergence of Trihelix transcription factors with guard cell differentiation pathways offers a candidate transcriptomic framework to explain the plant's characteristic C4-CAM photosynthetic plasticity under severe osmotic pressure. Practically, these evolutionary blueprints and specific master switches transcend single-gene transgenic limitations. Utilizing these root-sustained and stress-inducible targets under localized promoters provides a naturally optimized, network-level precision engineering roadmap to transfer robust, compartmentalized halotolerance to sensitive glycophytic crops.

Gene Regulatory Networks↗

PubMed2026

Genome-wide epigenomic atlas and multi-omics responses of Eriocheir sinensis to natural extreme heat.

BACKGROUND: Global climate warming has led to increasingly frequent and prolonged extreme summer heat events, posing severe environmental challenges to aquaculture systems. Extreme summer heat can disrupt the performance of pond-cultured ectotherms. The Chinese mitten crab (Eriocheir sinensis) is an economically important freshwater crustacean, but coordinated molecular differences following contrasting natural summers remain incompletely characterized. RESULTS: We performed a comprehensive multi-omics analysis integrating meteorological monitoring, mRNA/lncRNA transcriptomics, small-RNA profiling of miRNAs, DNA methylomics, and LC-MS metabolomics in E. sinensis populations collected from Yancheng, China, between 2020 and 2024. Across the ten farms, survival was significantly lower in 2024, whereas yield and the proportion of large individuals showed nonsignificant downward trends. Gene-set analyses showed negative enrichment of cellular heat-response, protein-folding, oxidative-phosphorylation, and mitochondrial ATP-production terms in the 2024 cohort at the time of sampling. The integrated transcript annotation contained 72,240 lncRNAs and 63,833 mRNAs, and CpG was the predominant methylation context. Differential methylation analysis identified 73 regions and 185 cytosines, with hypomethylated events predominating within the significant subset. Metabolomic profiles differed between annual cohorts and mapped to carbohydrate, lipid, and amino-acid pathways. Cross-omics integration prioritized eight candidate genes-ADCY9, UNC79, UBN1, IFT52, ACO2, LOC126986070, LOC127001126, and LOC126997895-and qPCR reproduced the reported directions of expression for selected RNAs. CONCLUSION: This study provides the first integrative multi-omics framework for understanding chronic heat adaptation in E. sinensis. By linking transcriptomic, epigenomic, and metabolic remodeling, we elucidate the molecular mechanisms underlying energy imbalance, epigenetic reprogramming, and immune dysregulation during prolonged thermal stress. These findings offer valuable insights and genomic resources for breeding heat-tolerant crab strains and improving aquaculture resilience under ongoing climate change.

DNA methylation↗

PubMed2026

Distinct molecular responses to acute cold exposure revealed by comparative transcriptomic and metabolomic profiling in the bay scallop Argopecten irradians.

Acute cold stress can elicit distinct molecular responses even when bay scallop populations show similar phenotypic outcomes. We compared a seventh-generation fast-growing bay scallop line (BS) with a commercial control population (CC) during a 72-h acute cold exposure at -1 ± 0.3 °C. RNA-seq was used as the discovery layer, representative BS cold-responsive genes were evaluated by qRT-PCR, and paired LC-MS profiles provided a comparative metabolic layer. At baseline, 138 genes differed between BS and CC; after cold exposure, 134 of these baseline differences disappeared and 61 of 65 cold-state differences newly emerged. BS showed a larger transcriptomic response magnitude than CC, with 1129 cold-responsive genes compared with 28 genes in CC, and this ordering remained robust across multiple sensitivity analyses. Survival after 72 h was identical in BS and CC (83/90, 92.2% in each population). Biochemical responses were time-dependent and marker-specific: CAT, LZM, T-SOD and T-AOC showed population-by-time interactions, whereas GSH-Px and MDA did not, and the 72-h differences were not consistently favourable to BS. Metabolomic cold effects were strongly concordant between populations, and no feature showed a significant population-by-cold interaction. Features putatively assigned to arachidonic acid metabolism were enriched, but this provider-annotated pathway signal remains exploratory because authentic-standard confirmation was not performed. These findings indicate population-specific differences in molecular responsiveness but do not establish superior cold tolerance in BS.

Animals↗

PubMed2000

Genomic exploration of the hemiascomycetous yeasts: 4. The genome of Saccharomyces cerevisiae revisited.

Since its completion more than 4 years ago, the sequence of Saccharomyces cerevisiae has been extensively used and studied. The original sequence has received a few corrections, and the identification of genes has been completed, thanks in particular to transcriptome analyses and to specialized studies on introns, tRNA genes, transposons or multigene families. In order to undertake the extensive comparative sequence analysis of this program, we have entirely revisited the S. cerevisiae sequence using the same criteria for all 16 chromosomes and taking into account publicly available annotations for genes and elements that cannot be predicted. Comparison with the other yeast species of this program indicates the existence of 50 novel genes in segments previously considered as 'intergenic' and suggests extensions for 26 of the previously annotated genes.

Ascomycota↗

PubMed2025

Microbiology Galaxy Lab: The first community-driven gateway for reproducible and FAIR analysis of microbial data.

The explosion of microbial omics data has outpaced the ability of many researchers to analyze it, with complex tools and limited computational resources creating barriers to discovery. To address this gap, we present the Microbiology Galaxy Lab: a free, globally accessible, community-supported platform that combines state-of-the-art analytical power with user-friendly accessibility. Supported by the Galaxy and global microbiology communities, this platform integrates over 315 tool suites and 115 curated workflows, enabling comprehensive metabarcoding, (meta)genomic, (meta)transcriptomic, and (meta)proteomic data analysis within a FAIR-aligned environment. It also supports research in the health and infectious disease sectors, as well as in environmental microbiology. The platform's utility is exemplified through various use cases, including antimicrobial resistance tracking, biomarker prediction, microbiome classification, and functional annotation of key microbes. Built on reproducibility and community engagement, it supports creation, sharing, and updating of best-practice workflows. Over 35 tutorials and learning paths empower scientists, fostering an ecosystem that keeps resources at the forefront of microbial science. The Microbiology Galaxy Lab enables collective analysis, democratising research, thereby accelerating discovery across the global microbiology community (microbiology.usegalaxy.org, .eu, .org.au, .fr).

Journal Article↗

PubMed2026

Morphological, Physiological and Transcriptomic Changes in Response to Water Deficit Stress in Brassica napus L.

Yield losses due to water-deficit (WD) conditions, especially during the reproductive stages of plant development, pose a significant threat to global canola (Brassica napus L.) production. Therefore, it is critical to investigate traits contributing to improved productivity under increased WD conditions. Here we present phenotypic, physiological and transcriptomic changes in response to WD across contrasting canola accessions exhibiting variation in drought resistance-related traits. WD significantly reduced shoot biomass, plant height, harvest index, leaf water content, photosynthetic CO2 assimilation rate, intrinsic water-use efficiency and carbon isotope discrimination. WD caused 49 to 100% of the seed yield reduction: the minimum seed yield reduction (49.66%) was observed in a doubled-haploid (DH) line, 06-5101.137, while the maximum yield reduction (94.1 to 100%) occurred in the late-flowering DH lines (06.5101.088 and 06-5101.306). Seed yield showed a positive correlation (r = 0.29 to 0.95) with shoot biomass and harvest index, leaf water content, photosynthetic CO2 assimilation rate, intrinsic water use efficiency and carbon isotope discrimination. However, it showed negative correlations with days to flower, leaf specific weight, root length, root biomass (r = -0.04 to -0.79) across water treatments. The specific leaf transcriptome analysis of the two parental lines of DH population that exhibit variation for effective water use under well-watered and water-deficient conditions revealed different categories of differentially expressed genes (DEGs): WD-responsive DEGs in BC1329 parental line (1116) and BC9102 (1205) with 754 and 853 DEGs unique to BC1329 and BC9102, respectively, WD-responsive DEGs (906), genotype-dependent DEGs (8465) and genotype × treatment interaction DEGs (353). DEG annotations revealed that the WD-treatment-affected genes were involved in stress responses and growth and development. We further located 235 DEGs within the QTL regions underlying agronomic and physiological performance. Our study provides a conceptual framework for the morphological, physiological and molecular determinants involved in water-use efficiency. Seedlings' traits with high heritability values, such as shoot biomass, leaf weight, leaf water content and Δ13C, serve as proxies for trait-based selection for improved seed yield under both water-limited and non-water-limited conditions.

Brassica napus↗

PubMed2002

The Gene Resource Locator: gene locus maps for transcriptome analysis.

Since the advent of the draft human genome sequence there has been growing interest in transcriptome analysis based on genomic data. The Gene Resource Locator (GRL) assembles gene maps that include information on gene-expression patterns, cis-elements in regulatory regions and alternatively spliced transcripts. The database was constructed using customized software, and currently contains 2.2 million alignments (exon-intron structures). The alignments have been annotated and integrated into a system that encompasses approximately 90 000 EST loci sharing common exons, 8091 alternatively spliced transcript groups, 10 801 expression-profile groups, 8066 candidate regulatory regions in full-length cDNAs, and 1 million SNP loci. We have used Flash technology to build a dynamic web viewer that facilitates browsing through the millions of alignments. All of the information is available through the World Wide Web at the Gene Resource Locator web site (http://grl.gi.k.u-tokyo.ac.jp).

Alternative Splicing↗