Gene and lncRNA Profiling of ω3/ω6 Polyunsaturated Fatty Acid-Exposed Human Visceral Adipocytes Uncovers Different Responses in Healthy Lean, Obese and Colorectal Cancer-Affected Individuals.

Colorectal cancer (CRC) is a major life-threatening disease, being the third most common cancer and a leading cause of death worldwide. Enhanced adiposity, particularly visceral fat, is a major risk factor for CRC, and obesity-associated alterations in metabolic, inflammatory and immune profiles in visceral adipose tissue (VAT) strongly contribute to promoting or sustaining intestinal carcinogenesis. The role of diet and nutrition in obesity and CRC has been extensively demonstrated, and AT represents the main place where diet-induced signals are integrated. Among the factors introduced with diet and processed or enriched in AT, ω3/ω6 polyunsaturated fatty acids (PUFAs) are endowed with pro- or anti-inflammatory properties and have been shown to exert either promoting or protective roles in CRC. In this study, we investigated the impact of ex vivo exposure to the ω3 and ω6 PUFAs docosahexaenoic and arachidonic acids on VAT adipocyte whole transcription in healthy lean, obese and CRC-affected individuals. High-throughput sequencing of protein-coding and long non-coding RNAs allowed us to identify specific pathways and regulatory circuits controlled by PUFAs and highlighted an impaired responsiveness of obese and CRC-affected individuals as compared to the strong response observed in healthy lean subjects. This further supports the role of healthy diets and balanced ω3/ω6 PUFA intake in the primary prevention of obesity and cancer.

A mitochondrial NADPH-cholesterol axis regulates extracellular vesicle biogenesis to support hematopoietic stem cell fate.

Mitochondrial fatty acid oxidation (FAO) is essential for hematopoietic stem cell (HSC) self-renewal; however, the mechanism by which mitochondrial metabolism controls HSC fate remains unknown. Here, we show that within the hematopoietic lineage, HSCs have the largest mitochondrial NADPH pools, which are required for proper HSC cell fate and homeostasis. Bioinformatic analysis of the HSC transcriptome, biochemical assays, and genetic inactivation of FAO all indicate that FAO-generated NADPH fuels cholesterol synthesis in HSCs. Interference with FAO disturbs the segregation of mitochondrial NADPH toward corresponding daughter cells upon single HSC division. Importantly, we have found that the FAO-NADPH-cholesterol axis drives extracellular vesicle (EV) biogenesis and release in HSCs, while inhibition of EV signaling impairs HSC self-renewal. These data reveal the existence of a mitochondrial NADPH-cholesterol axis for EV biogenesis that is required for hematopoietic homeostasis and highlight the non-stochastic nature of HSC fate determination.

A pan-cancer landscape of pathogenic somatic copy number variations.

OBJECTIVE: Copy number variations (CNVs) play crucial roles in physiological and pathological processes, including cancer. However, the functional implications of somatic CNVs in tumor progression and evolution remain unclear. This study focuses on identifying CNV alterations with high pathogenic potential that drive and sustain tumorigenesis, distinguishing them from passenger alterations that accumulate during tumor growth. Our goal is to explore the variability of CNVs across different tumor types and infer their impact on tumor cell functions. METHODS: Starting from 7352 copy number profiles across 33 different cancer types, we infer the pathogenicity of each CNV and perform both intra- and inter-tumor analyses to predict the functional impact of different genomic patterns. We evaluate the actionability of genes belonging to altered regions and we correlate the presence of pathogenic regions with genome instability patterns and patients' survival. RESULTS: Our analysis uncovered large heterogeneity among different tumors suggesting in many cases distinct genetic drivers of tumorigenesis. Recurrent genomic alterations frequently coincide with dysfunctional homologous recombination pathways and negative regulation of the immune system. In certain tumors, the number of pathogenic CNVs emerged as a prognostic biomarker, highlighting their significance in cancer progression. CONCLUSION: This study contributes to elucidate the functional impact of pathogenic CNVs in tumor progression and sheds light on their potential as prognostic markers in specific cancer types.

signifinder enables the identification of tumor cell states and cancer expression signatures in bulk, single-cell and spatial transcriptomic data.

Over the last decade, many studies and some clinical trials have proposed gene expression signatures as a valuable tool for understanding cancer mechanisms, defining subtypes, monitoring patient prognosis, and therapy efficacy. However, technical and biological concerns about reproducibility have been raised. Technical reproducibility is a major concern: we currently lack a computational implementation of the proposed signatures, which would provide detailed signature definition and assure reproducibility, dissemination, and usability of the classifier. Another concern regards intratumor heterogeneity, which has never been addressed when studying these types of biomarkers using bulk transcriptomics. With the aim of providing a tool able to improve the reproducibility and usability of gene expression signatures, we propose signifinder, an R package that provides the infrastructure to collect, implement, and compare expression-based signatures from cancer literature. The included signatures cover a wide range of biological processes from metabolism and programmed cell death, to morphological changes, such as quantification of epithelial or mesenchymal-like status. Collected signatures can score tumor cell characteristics, such as the predicted response to therapy or the survival association, and can quantify microenvironmental information, including hypoxia and immune response activity. signifinder has been used to characterize tumor samples and to investigate intra-tumor heterogeneity, extending its application to single-cell and spatial transcriptomic data. Through these higher-resolution technologies, it has become increasingly apparent that the single-sample score assessment obtained by transcriptional signatures is conditioned by the phenotypic and genetic intratumor heterogeneity of tumor masses. Since the characteristics of the most abundant cell type or clone might not necessarily predict the properties of mixed populations, signature prediction efficacy is lowered, thus impeding effective clinical diagnostics. Through signifinder, we offer general principles for interpreting and comparing transcriptional signatures, as well as suggestions for additional signatures that would allow for more complete and robust data inferences. We consider signifinder a useful tool to pave the way for reproducibility and comparison of transcriptional signatures in oncology.

A comprehensive investigation of histotype-specific microRNA and their variants in Stage I epithelial ovarian cancers.

isomiRs, the sequence-variants of microRNA, are known to be tissue and cell type specific but their physiological role is largely unknown. In our study, we explored for the first time the expression of isomiRs across different Stage I epithelial ovarian cancer (EOC) histological subtypes, in order to shed new light on their biological role in tumor growth and progression. In a multicentric retrospective cohort of tumor biopsies (n = 215) we sequenced small RNAs finding 971 expressed miRNAs, 64% of which are isomiRs. Among them, 42 isomiRs showed a clear histotype specific pattern, confirming our previously identified miRNA markers (miR192/194 and miR30a-3p/5p for mucinous and clear cell subtypes, respectively) and uncovering new biomarkers for all the five subtypes. Using integrative models, we found that the 38% of these miRNA expression alterations is the result of copy number variations while the 17% of differential transcriptional activities. Our work represents the first attempt to characterize isomiRs expression in Stage I EOC within and across subtypes and to contextualize their alterations in the framework of the large genomic heterogeneity of this tumor.

Copy number alterations in stage I epithelial ovarian cancer highlight three genomic patterns associated with prognosis.

BACKGROUND: Stage I epithelial ovarian cancer (EOC) encompasses five histologically different subtypes of tumors confined to the ovaries with a generally favorable prognosis. Despite the intrinsic heterogeneity, all stage I EOCs are treated with complete resection and adjuvant therapy in most of the cases. Owing to the lack of robust prognostic markers, this often leads to overtreatment. Therefore, a better molecular characterization of stage I EOCs could improve the assessment of the risk of relapse and the refinement of optimal treatment options. MATERIALS AND METHODS: 205 stage I EOCs tumor biopsies with a median follow-up of eight years were gathered from two independent Italian tumor tissue collections, and the genome distribution of somatic copy number alterations (SCNAs) was investigated by shallow whole genome sequencing (sWGS) approach. RESULTS: Despite the variability in SCNAs distribution both across and within the histotypes, we were able to define three common genomic instability patterns, namely stable, unstable, and highly unstable. These patterns were based on the percentage of the genome affected by SCNAs and on their length. The genomic instability pattern was strongly predictive of patients' prognosis also with multivariate models including currently used clinico-pathological variables. CONCLUSIONS: The results obtained in this study support the idea that novel molecular markers, in this case genomic instability patterns, can anticipate the behavior of stage I EOC regardless of tumor subtype and provide valuable prognostic information. Thus, it might be propitious to extend the study of these genomic instability patterns to improve rational management of this disease.

Oxidative pentose phosphate pathway controls vascular mural cell coverage by regulating extracellular matrix composition.

Vascular mural cells (vMCs) play an essential role in the development and maturation of the vasculature by promoting vessel stabilization through their interactions with endothelial cells. Whether endothelial metabolism influences mural cell recruitment and differentiation is unknown. Here, we show that the oxidative pentose phosphate pathway (oxPPP) in endothelial cells is required for establishing vMC coverage of the dorsal aorta during early vertebrate development in zebrafish and mice. We demonstrate that laminar shear stress and blood flow maintain oxPPP activity, which in turn, promotes elastin expression in blood vessels through production of ribose-5-phosphate. Elastin is both necessary and sufficient to drive vMC recruitment and maintenance when the oxPPP is active. In summary, our work demonstrates that endothelial cell metabolism regulates blood vessel maturation by controlling vascular matrix composition and vMC recruitment.

Regional and temporal heterogeneity of epithelial ovarian cancer tumor biopsies: implications for therapeutic strategies.

Stage III/IV epithelial ovarian cancer (EOC) is a systemic disease. The clonal relationship among different tumor lesions at diagnosis (spatial heterogeneity) and how tumor clonal architecture evolves over time (temporal heterogeneity) have not yet been defined. Such knowledge would help to develop new target-based strategies, as biomarkers which can adjudge the success of therapeutic intervention should be independent of spatial and temporal heterogeneity. The work described in this paper addresses spatial and temporal heterogeneity in a cohort of 71 tumor biopsies using targeted NGS technology. These samples were taken from twelve high grade serous (HGS) and seven non HSG-EOC, both at the time of primary surgery when the tumor was naïve to chemotherapy and after chemotherapy. Matched tumor lesions growing in the ovary or at other anatomical sites show very different mutational landscapes with branched tumor evolution. Mutations in ATM, ATR,TGFB3,VCAM1 and COL3A1 genes were shared across all lesions. BRCA1 and BRCA2 genes were frequently mutated in synchronous lesions of non HGS-EOC. Relapsed disease seems to originate from resistant clones originally present at the time of primary surgery rather than from resistance acquired de novo during platinum based therapy. Overall the work suggests that EOC continues to evolve. More detailed mapping of genetic lesions is necessary to improve therapeutic strategies.

Summarizing RNA-Seq Data or Differentially Expressed Genes Using Gene Set, Network, or Pathway Analysis.

The main purpose of pathway or gene set analysis methods is to provide mechanistic insight into the large amount of data produced in high-throughput studies. These tools were developed for gene expression analyses, but they have been rapidly adopted by other high-throughput techniques, becoming one of the foremost tools of omics research.Currently, according to different biological questions and data, we can choose among a vast plethora of methods and databases. Here we use two published examples of RNAseq datasets to approach multiple analyses of gene sets, networks and pathways using freely available and frequently updated software. Finally, we conclude this chapter by presenting a survival pathway analysis of a multiomics dataset. During this overview of different methods, we focus on visualization, which is a fundamental but challenging step in this computational field.

Micro-RNA Quantification, Target Gene Identification, and Pathway Analysis.

RNA sequencing has become a powerful tool for profiling the expression level of small RNAs from both solid tissues and liquid biopsies. In conjunction with pathway analysis, it offers exciting possibilities for the identification of disease specific biomarkers. In this chapter, we describe a workflow for processing this type of sequencing data. We start by removing technical sequences (adapters) and by performing quality control, a critical task that is necessary to identify possible issues caused by sample preparation and library sequencing. We then describe read alignment and gene-level abundance estimation. Building on these results, we normalize expression profiles and compute differentially expressed microRNAs between sample groups of interest. We conclude by showing how to employ pathway analysis to identify molecular signatures corresponding to biological processes that are significantly altered by the action for microRNAs.

Integrated Transcriptome Analysis of Human Visceral Adipocytes Unravels Dysregulated microRNA-Long Non-coding RNA-mRNA Networks in Obesity and Colorectal Cancer.

Obesity, and the obesity-associated inflammation, represents a major risk factor for the development of chronic diseases, including colorectal cancer (CRC). Dysfunctional visceral adipose tissue (AT) is now recognized as key player in obesity-associated morbidities, although the biological processes underpinning the increased CRC risk in obese subjects are still a matter of debate. Recent findings have pointed to specific alterations in the expression pattern of non-coding RNAs (ncRNAs), such as microRNAs (miRNAs), and long non-coding RNAs (lncRNAs), as mechanisms underlying dysfunctional adipocyte phenotype in obesity. Nevertheless, the regulatory networks and interrelated processes relevant for adipocyte functions, that may contribute to a tumor-promoting microenvironment, are poorly known yet. To this end, based on RNA sequencing data, we identified lncRNAs and miRNAs, which are aberrantly expressed in visceral adipocytes from obese and CRC subjects, as compared to healthy lean control, and validated a panel of modulated ncRNAs by real-time qPCR. Furthermore, by combining the differentially expressed lncRNA and miRNA profiles with the transcriptome analysis dataset of adipocytes from lean and obese subjects affected or not by CRC, lncRNA-miRNA-mRNA adipocyte networks were defined for obese and CRC subjects. This analysis highlighted several ncRNAs modulation that are common to both obesity and CRC or unique of each disorder. Functional enrichment analysis of network-related mRNA targets, revealed dysregulated pathways associated with metabolic processes, lipid and energy metabolism, inflammation, and cancer. Moreover, adipocytes from obese subjects affected by CRC exhibited a higher complexity, in terms of number of genes, lncRNAs, miRNAs, and biological processes found to be dysregulated, providing evidence that the transcriptional and post-transcriptional program of adipocytes from CRC patients is deeply affected by obesity. Overall, this study adds further evidence for a central role of visceral adipocyte dysfunctions in the obesity-cancer relationship.

Expression profiles of PRKG1, SDF2L1 and PPP1R12A are predictive and prognostic factors for therapy response and survival in high-grade serous ovarian cancer.

High-grade serous ovarian cancer (HGS-EOCs) is generally sensitive to front-line platinum (Pt)-based chemotherapy although most patients at an advanced stage relapse with progressive resistant disease. Clinical or molecular data to identify primary resistant cases at diagnosis are not yet available. HGS-EOC biopsies from 105 Pt-sensitive (Pt-s) and 89 Pt-resistant (Pt-r) patients were retrospectively selected from two independent tumor tissue collections. Pathway analysis was done integrating miRNA and mRNA expression profiles. Signatures were further validated in silico on a cohort of 838 HGS-EOC cases from a published dataset. In all, 131 mRNAs and 5 miRNAs belonging to different functionally related molecular pathways distinguish Pt-s from Pt-r cases. Then, 17 out of 23 selected elements were validated by orthogonal approaches (SI signature). As resistance to Pt is associated with a short progression-free survival (PFS) and overall survival (OS), the prognostic role of the SI signature was assessed, and 14 genes associated with PFS and OS, in multivariate analyses (SII signature). The prognostic value of the SII signature was validated in a third extensive cohort. The expression profiles of SDF2L1, PPP1R12A and PRKG1 genes (SIII signature) served as independent prognostic biomarkers of Pt-response and survival. The study identified a prognostic molecular signature based on the combined expression profile of three genes which had never been associated with the clinical outcome of HGS-EOC. This may lead to early identification, at the time of diagnosis, of patients who would not greatly benefit from standard chemotherapy and are thus eligible for novel investigational approaches.

Transcriptional Characterization of Stage I Epithelial Ovarian Cancer: A Multicentric Study.

Stage I epithelial ovarian cancer (EOC) represents about 10% of all EOCs. It is characterized by a complex histopathological and molecular heterogeneity, and it is composed of five main histological subtypes (mucinous, endometrioid, clear cell and high, and low grade serous), which have peculiar genetic, molecular, and clinical characteristics. As it occurs less frequently than advanced-stage EOC, its molecular features have not been thoroughly investigated. In this study, using in silico approaches and gene expression data, on a multicentric cohort composed of 208 snap-frozen tumor biopsies, we explored the subtype-specific molecular alterations that regulate tumor aggressiveness in stage I EOC. We found that single genes rather than pathways are responsible for histotype specificities and that a cAMP-PKA-CREB1 signaling axis seems to play a central role in histotype differentiation. Moreover, our results indicate that immune response seems to be, at least in part, involved in histotype differences, as a higher immune-reactive behavior of serous and mucinous samples was observed with respect to other histotypes.

Individual Radiosensitivity in Oncological Patients: Linking Adverse Normal Tissue Reactions and Genetic Features.

Introduction: Adverse effects of radiotherapy (RT) significantly affect patient's quality of life (QOL). The possibility to identify patient-related factors that are associated with individual radiosensitivity would optimize adjuvant RT treatment, limiting the severity of normal tissue reactions, and improving patient's QOL. In this study, we analyzed the relationships between genetic features and toxicity grading manifested by RT patients looking for possible biomarkers of individual radiosensitivity. Methods: Early radiation toxicity was evaluated on 143 oncological patients according to the Common Terminology Criteria for Adverse Events (CTCAE). An individual radiosensitivity (IRS) index defining four classes of radiosensitivity (highly radiosensitive, radiosensitive, normal, and radioresistant) was determined by a G2-chromosomal assay on ex vivo irradiated, patient-derived blood samples. The expression level of 15 radioresponsive genes has been measured by quantitative real-time PCR at 24 h after the first RT fraction, in blood samples of a subset of 57 patients, representing the four IRS classes. Results: By applying univariate and multivariate statistical analyses, we found that fatigue was significantly associated with IRS index. Interestingly, associations were detected between clinical radiation toxicity and gene expression (ATM, CDKN1A, FDXR, SESN1, XPC, ZMAT3, and BCL2/BAX ratio) and between IRS index and gene expression (BBC3, FDXR, GADD45A, and BCL2/BAX). Conclusions: In this prospective cohort study we found that associations exist between normal tissue reactions and genetic features in RT-treated patients. Overall, our findings can contribute to the identification of biological markers to predict RT toxicity in normal tissues.

MOSClip: multi-omic and survival pathway analysis for the identification of survival associated gene and modules.

Survival analyses of gene expression data has been a useful and widely used approach in clinical applications. But, in complex diseases, such as cancer, the identification of survival-associated cell processes - rather than single genes - provides more informative results because the efficacy of survival prediction increases when multiple prognostic features are combined to enlarge the possibility of having druggable targets. Moreover, genome-wide screening in molecular medicine has rapidly grown, providing not only gene expression but also multi-omic measurements such as DNA mutations, methylation, expression, and copy number data. In cancer, virtually all these aberrations can contribute in synergy to pathological processes, and their measurements can improve a patient's outcome and help in diagnosis and treatment decisions. Here, we present MOSClip, an R package implementing a new topological pathway analysis tool able to integrate multi-omic data and look for survival-associated gene modules. MOSClip tests the survival association of dimensionality-reduced multi-omic data using multivariate models, providing graphical devices for management, browsing and interpretation of results. Using simulated data we evaluated MOSClip performance in terms of false positives and false negatives in different settings, while the TCGA ovarian cancer dataset is used as a case study to highlight MOSClip's potential.

Transcriptome Profiles of Human Visceral Adipocytes in Obesity and Colorectal Cancer Unravel the Effects of Body Mass Index and Polyunsaturated Fatty Acids on Genes and Biological Processes Related to Tumorigenesis.

Obesity, a low-grade inflammatory condition, represents a major risk factor for the development of several pathologies including colorectal cancer (CRC). Although the adipose tissue inflammatory state is now recognized as a key player in obesity-associated morbidities, the underlying biological processes are complex and not yet precisely defined. To this end, we analyzed transcriptome profiles of human visceral adipocytes from lean and obese subjects affected or not by CRC by RNA sequencing (n = 6 subjects/category), and validated selected modulated genes by real-time qPCR. We report that obesity and CRC, conditions characterized by the common denominator of inflammation, promote changes in the transcriptional program of adipocytes mostly involving pathways and biological processes linked to extracellular matrix remodeling, and metabolism of pyruvate, lipids and glucose. Interestingly, although the transcriptome of adipocytes shows several alterations that are common to both disorders, some modifications are unique under obesity (e.g., pathways associated with inflammation) and CRC (e.g., TGFß signaling and extracellular matrix remodeling) and are influenced by the body mass index (e.g., processes related to cell adhesion, angiogenesis, as well as metabolism). Indeed, cancer-induced transcriptional program is deeply affected by obesity, with adipocytes from obese individuals exhibiting a more complex response to the tumor. We also report that in vitro exposure of adipocytes to ω3 and ω6 polyunsaturated fatty acids (PUFA) endowed with either anti- or pro-inflammatory properties, respectively, modulates the expression of genes involved in processes potentially relevant to carcinogenesis, as assessed by real-time qPCR. All together our results suggest that genes involved in pyruvate, glucose and lipid metabolism, fibrosis and inflammation are central in the transcriptional reprogramming of adipocytes occurring in obese and CRC-affected individuals, as well as in their response to PUFA exposure. Moreover, our results indicate that the transcriptional program of adipocytes is strongly influenced by the BMI status in CRC subjects. The dysregulation of these interrelated processes relevant for adipocyte functions may contribute to create more favorable conditions to tumor establishment or favor tumor progression, thus linking obesity and colorectal cancer.

Multisite analysis of high-grade serous epithelial ovarian cancers identifies genomic regions of focal and recurrent copy number alteration in 3q26.2 and 8q24.3.

High-grade serous epithelial ovarian cancer (HGS-EOC) is a systemic disease, with marked intra and interpatient tumor heterogeneity. The issue of spatial and temporal heterogeneity has long been overlooked, hampering the possibility to identify those genomic alterations that persist, before and after therapy, in the genome of all tumor cells across the different anatomical districts. This knowledge is the first step to clarify those molecular determinants that characterize the tumor biology of HGS-EOC and their route toward malignancy. In our study, -omics data were generated from 79 snap frozen matched tumor biopsies, withdrawn before and after chemotherapy from 24 HGS-EOC patients, gathered together from independent cohorts. The landscape of somatic copy number alterations depicts a more homogenous and stable genomic portrait than the single nucleotide variant profile. Genomic identification of significant targets in cancer analysis identified two focal and minimal common regions (FMCRs) of amplification in the cytoband 3q26.2 (region α, 193 kb long) and 8q24.3 (region ß, 495 kb long). Analysis in two external databases confirmed regions α and ß are features of HGS-EOC. The MECOM gene is located in region α, and 15 genes are in region ß. No functional data are yet available for the genes in the ß region. In conclusion, we have identified for the first time two FMCRs of amplification in HGS-EOC, opening up a potential biological role in its etiopathogenesis.

metaGraphite-a new layer of pathway annotation to get metabolite networks.

MOTIVATION: Metabolomics is an emerging 'omics' science involving the characterization of metabolites and metabolism in biological systems. Few bioinformatic tools have been developed for the visualization, exploration and analysis of metabolomic data within the context of metabolic pathways: some of them became rapidly obsolete and are no longer supported, others are based on a single database. A systematic collection of existing annotations has the potential of considerably boosting the investigation and contextualization of metabolomic measurements. RESULTS: We have released a major update of our Bioconductor package graphite which explicitly tracks small molecules within pathway topologies and their interactions with proteins. The package gathers the information stored in eight major databases, oriented both at genes and at metabolites, across 14 different species. Depending on user preferences, all pathways can be retrieved as gene-only, gene metabolite or metabolite-only networks. AVAILABILITY AND IMPLEMENTATION: The new graphite version (1.24) is available on Bioconductor. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

KrillDB: A de novo transcriptome database for the Antarctic krill (Euphausia superba).

Antarctic krill (Euphausia superba) is a key species in the Southern Ocean with an estimated biomass between 100 and 500 million tonnes. Changes in krill population viability would have catastrophic effect on the Antarctic ecosystem. One looming threat due to elevated levels of anthropogenic atmospheric carbon dioxide (CO2) is ocean acidification (lowering of sea water pH by CO2 dissolving into the oceans). The genetics of Antarctic krill has long been of scientific interest for both for the analysis of population structure and analysis of functional genetics. However, the genetic resources available for the species are relatively modest. We have developed the most advanced genetic database on Euphausia superba, KrillDB, which includes comprehensive data sets of former and present transcriptome projects. In particular, we have built a de novo transcriptome assembly using more than 360 million Illumina sequence reads generated from larval krill including individuals subjected to different CO2 levels. The database gives access to: 1) the full list of assembled genes and transcripts; 2) their level of similarity to transcripts and proteins from other species; 3) the predicted protein domains contained within each transcript; 4) their predicted GO terms; 5) the level of expression of each transcript in the different larval stages and CO2 treatments. All references to external entities (sequences, domains, GO terms) are equipped with a link to the appropriate source database. Moreover, the software implements a full-text search engine that makes it possible to submit free-form queries. KrillDB represents the first large-scale attempt at classifying and annotating the full krill transcriptome. For this reason, we believe it will constitute a cornerstone of future approaches devoted to physiological and molecular study of this key species in the Southern Ocean food web.