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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Persistence and plasticity in bacterial gene regulation

Organisms orchestrate cellular functions through transcription factor (TF) interactions with their target genes, although these regulatory relationships are largely unknown in most species. Here we report a high-throughput approach for characterizing TF-target gene interactions across species and its application to 354 TFs across 48 bacteria, generating 17,000 genome-wide binding maps. This dataset revealed themes of ancient conservation and rapid evolution of regulatory modules. We observed rewiring, where the TF sensing and regulatory role is maintained while the arrangement and identity of target genes diverges, in some cases encoding entirely new functions. We further integrated phenotypic information to define new functional regulatory modules and pathways. So, we identified 242 new TF DNA binding motifs, including a 70% increase of known Escherichia coli motifs and the first annotation in Pseudomonas simiae, revealing deep conservation in bacterial promoter architecture. Our method provides a versatile tool for functional characterization of genetic pathways in prokaryotes and eukaryotes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Signatures of Mollicutes-related endobacteria in publicly available Mucoromycota genomes

ABSTRACT Mucoromycota fungi and their Mollicutes-related endobacteria (MRE) are an ideal system for studying bacterial–fungal interactions and evolution due to the long-term and intimate nature of their interactions. However, methods for detecting MRE face specific challenges due to the poor representation of MRE in sequencing databases coupled with the high sequence divergence of their genomes, making traditional similarity searches unreliable. This has precluded estimations on the diversity of MRE associated with Mucoromycota. To determine the prevalence of previously undetected MRE in fungal genome sequences, we scanned 389 Mucoromycota genome assemblies available from the National Center for Biotechnology Information for the presence of MRE sequences using publicly available tools to map contigs from fungal assemblies to publicly available MRE genomes. We demonstrate a higher diversity of MRE genomes than previously described in Mucoromycota and a lack of cophylogeny between MRE and the majority of their fungal hosts. This supports the late invasion hypothesis regarding MRE acquisition across most of the examined fungal families. In contrast with other Mucoromycota lineages, MRE from the Gigasporaceae displayed some degree of cophylogeny with their hosts, which may indicate that horizontal transmission is restricted between members of this family or that transmission is strictly vertical. These results underscore the need for a refined process to capture sequencing data from potential fungal endosymbionts to discern their evolution and transmission. Screens of fungal genomes for MRE can help improve the quality of fungal genome assemblies while identifying new MRE lineages to further test hypotheses on their origin and evolution. IMPORTANCE Mollicutes-related endobacteria (MRE) are obligate intracellular bacteria found within Mucoromycota fungi. Despite their frequent detection, MRE roles in host functioning are still unknown. Comparative genomic investigations can improve our understanding of the impact of MRE on their fungal hosts by identifying similarities and differences in MRE genome evolution. However, MRE genomes have only been assembled from a small fraction of Mucoromycota hosts. Here, we demonstrate that MRE can be present yet undetected in publicly available Mucoromycota genome assemblies. We use these newfound sequences to assess the broader diversity of MRE and their phylogenetic relationships with respect to their hosts. We demonstrate that publicly available tools can be used to extract novel MRE sequences from assembled fungal genomes leading to insights on MRE evolution. This work contributes to a greater understanding of the fungal microbiome, which is crucial to improving knowledge on the dynamics and impacts of fungi in microbial ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Perspectives on ENCODE

The Encyclopedia of DNA Elements (ENCODE) Project launched in 2003 with the long-term goal of developing a comprehensive map of functional elements in the human genome. These included genes, biochemical regions associated with gene regulation (for example, transcription factor binding sites, open chromatin, and histone marks) and transcript isoforms. The marks serve as sites for candidate cis-regulatory elements (cCREs) that may serve functional roles in regulating gene expression. The project has been extended to model organisms, particularly the mouse. Finally, in the third phase of ENCODE, nearly a million and more than 300,000 cCRE annotations have been generated for human and mouse, respectively, and these have provided a valuable resource for the scientific community.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Developing an Evolutionary Baseline Model for Humans: Jointly Inferring Purifying Selection with Population History

Building evolutionarily appropriate baseline models for natural populations is not only important for answering fundamental questions in population genetics—including quantifying the relative contributions of adaptive versus nonadaptive processes—but also essential for identifying candidate loci experiencing relatively rare and episodic forms of selection (e.g., positive or balancing selection). Here, a baseline model was developed for a human population of West African ancestry, the Yoruba, comprising processes constantly operating on the genome (i.e., purifying and background selection, population size changes, recombination rate heterogeneity, and gene conversion). Specifically, to perform joint inference of selective effects with demography, an approximate Bayesian approach was employed that utilizes the decay of background selection effects around functional elements, taking into account genomic architecture. This approach inferred a recent 6-fold population growth together with a distribution of fitness effects that is skewed towards effectively neutral mutations. Importantly, these results further suggest that, although strong and/or frequent recurrent positive selection is inconsistent with observed data, weak to moderate positive selection is consistent but unidentifiable if rare.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Ecological Trait-Based Digital Categorization of Microbial Genomes for Denitrification Potential

Microorganisms encode proteins that function in the transformations of useful and harmful nitrogenous compounds in the global nitrogen cycle. The major transformations in the nitrogen cycle are nitrogen fixation, nitrification, denitrification, anaerobic ammonium oxidation, and ammonification. The focus of this report is the complex biogeochemical process of denitrification, which, in the complete form, consists of a series of four enzyme-catalyzed reduction reactions that transforms nitrate to nitrogen gas. Denitrification is a microbial strain-level ecological trait (characteristic), and denitrification potential (functional performance) can be inferred from trait rules that rely on the presence or absence of genes for denitrifying enzymes in microbial genomes. Despite the global significance of denitrification and associated large-scale genomic and scholarly data sources, there is lack of datasets and interactive computational tools for investigating microbial genomes according to denitrification trait rules. Therefore, our goal is to categorize archaeal and bacterial genomes by denitrification potential based on denitrification traits defined by rules of enzyme involvement in the denitrification reduction steps. We report the integration of datasets on genome, taxonomic lineage, ecosystem, and denitrifying enzymes to provide data investigations context for the denitrification potential of microbial strains. We constructed an ecosystem and taxonomic annotated denitrification potential dataset of 62,624 microbial genomes (866 archaea and 61,758 bacteria) that encode at least one of the twelve denitrifying enzymes in the four-step canonical denitrification pathway. Our four-digit binary-coding scheme categorized the microbial genomes to one of sixteen denitrification traits including complete denitrification traits assigned to 3280 genomes from 260 bacteria genera. The bacterial strains with complete denitrification potential pattern included Arcobacteraceae strains isolated or detected in diverse ecosystems including aquatic, human, plant, and Mollusca (shellfish). The dataset on microbial denitrification potential and associated interactive data investigations tools can serve as research resources for understanding the biochemical, molecular, and physiological aspects of microbial denitrification, among others. The microbial denitrification data resources produced in our research can also be useful for identifying microbial strains for synthetic denitrifying communities.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Simulating metagenomic stable isotope probing datasets with MetaSIPSim

DNA-stable isotope probing (DNA-SIP) links microorganisms to their in-situ function in diverse environmental samples. Combining DNA-SIP and metagenomics (metagenomic-SIP) allows us to link genomes from complex communities to their specific functions and improves the assembly and binning of these targeted genomes. However, empirical development of metagenomic-SIP methods is hindered by the complexity and cost of these studies. We developed a toolkit, ‘MetaSIPSim,’ to simulate sequencing read libraries for metagenomic-SIP experiments. MetaSIPSim is intended to generate datasets for method development and testing. To this end, we used MetaSIPSim generated data to demonstrate the advantages of metagenomic-SIP over a conventional shotgun metagenomic sequencing experiment. Through simulation we show that metagenomic-SIP improves the assembly and binning of isotopically labeled genomes relative to a conventional metagenomic approach. Improvements were dependent on experimental parameters and on sequencing depth. Community level G + C content impacted the assembly of labeled genomes and subsequent binning, where high community G + C generally reduced the benefits of metagenomic-SIP. Furthermore, when a high proportion of the community is isotopically labeled, the benefits of metagenomic-SIP decline. Finally, the choice of gradient fractions to sequence greatly influences method performance. Metagenomic-SIP is a valuable method for recovering isotopically labeled genomes from complex communities. We show that metagenomic-SIP performance depends on optimization of experimental parameters. MetaSIPSim allows for simulation of metagenomic-SIP datasets which facilitates the optimization and development of metagenomic-SIP experiments and analytical approaches for dealing with these data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Getting back to the grass roots: harnessing specialized metabolites for improved crop stress resilience

Roots remain understudied as the site of complex and important biological interactions mediating plant productivity. In grain and bioenergy crops, grass root specialized metabolites (GRSM) are central to key interactions, yet our basic knowledge of the chemical language remains fragmentary. Continued improvements in plant genome assembly and metabolomics are enabling large-scale advances in the discovery of specialized metabolic pathways as a means of regulating root-biotic interactions. Metabolomics, transcript coexpression analyses, forward genetic studies, gene synthesis and heterologous expression assays drive efficient pathway discoveries. Functional genetic variants identified through genome wide analyses, targeted CRISPR/Cas9 approaches, and both native and non-native overexpression studies critically inform novel strategies for bioengineering metabolic pathways to improve plant traits.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Programmable Gene Knockdown in Diverse Bacteria Using Mobile‐CRISPRi

Abstract Facile bacterial genome sequencing has unlocked a veritable treasure trove of novel genes awaiting functional exploration. To make the most of this opportunity requires powerful genetic tools that can target all genes in diverse bacteria. CRISPR interference (CRISPRi) is a programmable gene‐knockdown tool that uses an RNA‐protein complex comprised of a single guide RNA (sgRNA) and a catalytically inactive Cas9 nuclease (dCas9) to sterically block transcription of target genes. We previously developed a suite of modular CRISPRi systems that transfer by conjugation and integrate into the genomes of diverse bacteria, which we call Mobile‐CRISPRi. Here, we provide detailed protocols for the modification and transfer of Mobile‐CRISPRi vectors for the purpose of knocking down target genes in bacteria of interest. We further discuss strategies for optimizing Mobile‐CRISPRi knockdown, transfer, and integration. We cover the following basic protocols: sgRNA design, cloning new sgRNA spacers into Mobile‐CRISPRi vectors, Tn 7 transfer of Mobile‐CRISPRi to Gram‐negative bacteria, and ICE Bs1 transfer of Mobile‐CRISPRi to Bacillales. © 2020 The Authors. Basic Protocol 1 : sgRNA design Basic Protocol 2 : Cloning of new sgRNA spacers into Mobile‐CRISPRi vectors Basic Protocol 3 : Tn 7 transfer of Mobile‐CRISPRi to Gram‐negative bacteria Basic Protocol 4 : ICE Bs1 transfer of Mobile‐CRISPRi to Bacillales Support Protocol 1 : Quantification of CRISPRi repression using fluorescent reporters Support Protocol 2 : Testing for gene essentiality using CRISPRi spot assays on plates Support Protocol 3 : Transformation of E. coli by electroporation Support Protocol 4 : Transformation of CaCl 2 ‐competent E. coli

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Data from A Genetic Toolbox for Metabolic Engineering of Issatchenkia orientalis

The nonconventional yeast Issatchenkia orientalis can grow under highly acidic conditions and has been explored for production of various organic acids. However, its broader application is hampered by the lack of efficient genetic tools to enable sophisticated metabolic manipulations. We recently constructed an episomal plasmid based on the autonomously replicating sequence (ARS) from Saccharomyces cerevisiae (ScARS) in I. orientalis and developed a CRISPR/Cas9 system for multiplexed gene deletions. Here we report three additional genetic tools including: (1) identification of a 0.8 kb centromere-like (CEN-L) sequence from the I. orientalis genome by using bioinformatics and functional screening; (2) discovery and characterization of a set of constitutive promoters and terminators under different culture conditions by using RNA-Seq analysis and a fluorescent reporter; and (3) development of a rapid and efficient in vivo DNA assembly method in I. orientalis , which exhibited ~100% fidelity when assembling a 7 kb-plasmid from seven DNA fragments ranging from 0.7 kb to 1.7 kb. As proof of concept, we used these genetic tools to rapidly construct a functional xylose utilization pathway in I. orientalis .

Conversion↗
DOE OSTI2025

JGI-Trichoderma v1.0

There is a series of Python and bash scripts to parse genomics datasets used to evaluate the coevolution of gene families and the feature importance of gene families using an SVM classifier. - Cover analysis: takes a list of single-copy genes in a set of genomes, aligns and builds the gene trees to determine if two gene families have a signature of covariation with one another. It parses the files to run phykit cover script described here: https://jlsteenwyk.com/PhyKIT/usage/index.html - SVM-classifier: This Python script is an SVM-based genomic classifier designed for biological data analysis. It combines machine learning with feature selection to identify important genomic markers and classify biological samples. Core Functionality: The script uses Support Vector Machines from scikit-learn to classify genomic data, incorporating SelectKBest for automated feature selection and leave-one-out cross-validation for performance assessment. It operates in multiple modes: feature ranking, optimal combination discovery, and sample prediction. Primary Applications: Genomic sample classification and biomarker discovery Feature importance analysis in high-dimensional biological datasets Prediction of sample categories based on genomic profiles Research applications requiring robust classification of biological data Key Advantages: High-dimensional handling: SVMs excel with genomic data's typical high feature-to-sample ratios Integrated feature selection: Reduces noise and computational overhead while identifying key markers Probability estimation: Provides confidence scores essential for biological interpretation Validation robustness: Leave-one-out cross-validation ensures reliable performance metrics Operational flexibility: Multiple analysis modes support different research phases from exploration to prediction

Stecca Steindorff, Andrei [Lawrence Berkeley Natio↗
DOE OSTI2023

Comparative Genomic Analyses of Cellulolytic Machinery Reveal Two Nutritional Strategies of Marine Labyrinthulomycetes Protists

Labyrinthulomycetes are a group of ubiquitous and diverse unicellular Stramenopiles and have long been known for their vital role in ocean carbon cycling. However, their ecological function from the perspective of organic matter degradation remains poorly understood. This study reports high-quality genomes of two newly isolated Labyrinthulomycetes strains, namely, Botryochytrium sp. strain S-28 and Oblongichytrium sp. strain S-429, and provides molecular analysis of their ecological functions using comparative genomics and a biochemical assay. Our results suggest that Labyrinthulomycetes may occupy multiple ecological niches in marine ecosystems because of the significant differences in gene function among different genera. Certain strains could degrade wheat bran independently by secreting cellulase. The key glycoside hydrolase families (GH1, GH5, and GH9) related to cellulase and the functional domains of carbohydrate-active enzymes (CAZymes) were more enriched in their genomes. This group can actively participate in marine biochemical cycles as decomposers. In contrast, other strains that could not produce cellulase may thrive as “leftover scavengers” and act as a source of nutrients to the higher-trophic-level plankton. In addition, our findings emphasize the dual roles of endoglucanase, acting as both exo- and endoglucanases, in the process of cellulose degradation. Using genomic, biochemical, and phylogenetic analyses, our study provides a broader insight into the nutritional patterns and ecological functions of Labyrinthulomycetes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Integrated Proteomic and Glycoproteomic Characterization of Human High-Grade Serous Ovarian Carcinoma

Many gene products exhibit great structural heterogeneity because of an array of modifications. These modifications are not directly encoded in the genomic template but often affect the functionality of proteins. Protein glycosylation plays a vital role in proper protein functions. However, the analysis of glycoproteins has been challenging compared with other protein modifications, such as phosphorylation. Here, we perform an integrated proteomic and glycoproteomic analysis of 83 prospectively collected high-grade serous ovarian carcinoma (HGSC) and 23 non-tumor tissues. Integration of the expression data from global proteomics and glycoproteomics reveals tumor-specific glycosylation, uncovers different glycosylation associated with three tumor clusters, and identifies glycosylation enzymes that were correlated with the altered glycosylation. In addition to providing a valuable resource, these results provide insights into the potentialroles of glycosylation in the pathogenesis of HGSC, with the possibility of distinguishing pathological outcomes of ovarian tumors from non-tumors, as well as classifying tumor clusters.

Hu, Yingwei↗
DOE OSTI2022

Genome sequence, phylogenetic analysis, and structure-based annotation reveal metabolic potential of Chlorella sp. SLA-04

Algae are a broad class of photosynthetic eukaryotes that are phylogenetically and physiologically diverse. Most of the phylogenetic diversity has been inferred from 18S rDNA sequencing since there are only a few complete genomes available in public databases. Here we use ultra-long-read Nanopore sequencing to determine a gapless, telomere-to-telomere complete genome sequence of Chlorella sp. SLA-04, previously described as Chlorella sorokiniana SLA-04. Chlorella sp. SLA-04 is a green alga that grows to high cell density in a wide variety of environments - high and neutral pH, high and low alkalinity, and high and low salinity. SLA-04's ability to grow in high pH and high alkalinity media without external CO 2 supply is favorable for large-scale algal biomass production. Phylogenetic analysis performed using ribosomal DNA and conserved protein sequences consistently reveal that Chlorella sp. SLA-04 forms a distinct lineage from other strains of Chlorella sorokiniana. We complement traditional genome annotation methods with high throughput structural predictions and demonstrate that this approach expands functional prediction of the SLA-04 proteome. Genomic analysis of the SLA-04 genome identifies the genes capable of utilizing TCA cycle intermediates to replenish cytosolic acetyl-CoA pools for lipid production. We also identify a complete metabolic pathway for sphingolipid anabolism that may allow SLA-04 to readily adapt to changing environmental conditions and facilitate robust cultivation in mass production systems. Altogether, this work clarifies the phylogeny of Chlorella sp. SLA-04 within Trebouxiophyceae and demonstrates how structural predictions can be used to improve annotation beyond sequencebased methods.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Ecological and genomic responses of soil microbiomes to high-severity wildfire: linking community assembly to functional potential

Increasing wildfire severity, which is common throughout the western United States, can have deleterious effects on plant regeneration and large impacts on carbon (C) and nitrogen (N) cycling rates. Soil microbes are pivotal in facilitating these elemental cycles, so understanding the impact of increasing fire severity on soil microbial communities is critical. Here, we assess the long-term impact of high-severity fires on the soil microbiome. We find that high-severity wildfires result in a multi-decadal (>25 y) recovery of the soil microbiome mediated by concomitant differences in aboveground vegetation, soil chemistry, and microbial assembly processes. Our results depict a distinct taxonomic and functional successional pattern of increasing selection in post-fire soil microbial communities. Changes in microbiome composition corresponded with changes in microbial functional potential, specifically altered C metabolism and enhanced N cycling potential, which related to rates of potential decomposition and inorganic N availability, respectively. Based on metagenome-assembled genomes, we show that bacterial genomes enriched in our earliest site (4 y since fire) harbor distinct traits such as a robust stress response and a high potential to degrade pyrogenic, polyaromatic C that allow them to thrive in post-fire environments. Taken together, these results provide a biological basis for previously reported process rate measurements and explain the temporal dynamics of post-fire biogeochemistry, which ultimately constrains ecosystem recovery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

RNA language models predict mutations that improve RNA function

Structured RNA lies at the heart of many central biological processes, from gene expression to catalysis. RNA structure prediction is not yet possible due to a lack of high-quality reference data associated with organismal phenotypes that could inform RNA function. We present GARNET (Gtdb Acquired RNa with Environmental Temperatures), a new database for RNA structural and functional analysis anchored to the Genome Taxonomy Database (GTDB). GARNET links RNA sequences to experimental and predicted optimal growth temperatures of GTDB reference organisms. Using GARNET, we develop sequence- and structure-aware RNA generative models, with overlapping triplet tokenization providing optimal encoding for a GPT-like model. Leveraging hyperthermophilic RNAs in GARNET and these RNA generative models, we identify mutations in ribosomal RNA that confer increased thermostability to the Escherichia coli ribosome. The GTDB-derived data and deep learning models presented here provide a foundation for understanding the connections between RNA sequence, structure, and function.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Genome-resolved analysis of Serratia marcescens strain SMTT infers niche specialization as a hydrocarbon-degrader

Abstract Bacteria that are chronically exposed to high levels of pollutants demonstrate genomic and corresponding metabolic diversity that complement their strategies for adaptation to hydrocarbon-rich environments. Whole genome sequencing was carried out to infer functional traits of Serratia marcescens strain SMTT recovered from soil contaminated with crude oil. The genome size (Mb) was 5,013,981 with a total gene count of 4,842. Comparative analyses with carefully selected S. marcescens strains, 2 of which are associated with contaminated soil, show conservation of central metabolic pathways in addition to intra-specific genetic diversity and metabolic flexibility. Genome comparisons also indicated an enrichment of genes associated with multidrug resistance and efflux pumps for SMTT. The SMTT genome contained genes that enable the catabolism of aromatic compounds via the protocatechuate para-degradation pathway, in addition to meta-cleavage of catechol (meta-cleavage pathway II); gene enrichment for aromatic compound degradation was markedly higher for SMTT compared to the other S. marcescens strains analysed. Our data presents a valuable genetic inventory for future studies on strains of S. marcescens and provides insights into those genomic features of SMTT with industrial potential.

Genetics & Heredity↗
DOE OSTI2020

High-throughput mapping of the phage resistance landscape in E. coli

Bacteriophages (phages) are critical players in the dynamics and function of microbial communities and drive processes as diverse as global biogeochemical cycles and human health. Phages tend to be predators finely tuned to attack specific hosts, even down to the strain level, which in turn defend themselves using an array of mechanisms. However, to date, efforts to rapidly and comprehensively identify bacterial host factors important in phage infection and resistance have yet to be fully realized. Here, we globally map the host genetic determinants involved in resistance to 14 phylogenetically diverse double-stranded DNA phages using two model Escherichia coli strains (K-12 and BL21) with known sequence divergence to demonstrate strain-specific differences. Using genome-wide loss-of-function and gain-of-function genetic technologies, we are able to confirm previously described phage receptors as well as uncover a number of previously unknown host factors that confer resistance to one or more of these phages. We uncover differences in resistance factors that strongly align with the susceptibility of K-12 and BL21 to specific phage. We also identify both phage specific mechanisms, such as the unexpected role of cyclic-di-GMP in host sensitivity to phage N4, and more generic defenses, such as the overproduction of colanic acid capsular polysaccharide that defends against a wide array of phages. Our results indicate that host responses to phages can occur via diverse cellular mechanisms. Our systematic and high-throughput genetic workflow to characterize phage-host interaction determinants can be extended to diverse bacteria to generate datasets that allow predictive models of how phage-mediated selection will shape bacterial phenotype and evolution. The results of this study and future efforts to map the phage resistance landscape will lead to new insights into the coevolution of hosts and their phage, which can ultimately be used to design better phage therapeutic treatments and tools for precision microbiome engineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

A compendium of human gene functions derived from evolutionary modelling

A comprehensive, computable representation of the functional repertoire of all macromolecules encoded within the human genome is a foundational resource for biology and biomedical research. The Gene Ontology Consortium has been working towards this goal by generating a structured body of information about gene functions, which now includes experimental findings reported in more than 175,000 publications for human genes and genes in experimentally tractable model organisms 1,2 . Here, we describe the results of a large, international effort to integrate all of these findings to create a representation of human gene functions that is as complete and accurate as possible. Specifically, we apply an expert-curated, explicit evolutionary modelling approach to all human protein-coding genes. This approach integrates available experimental information across families of related genes into models that reconstruct the gain and loss of functional characteristics over evolutionary time. The models and the resulting set of 68,667 integrated gene functions cover approximately 82% of human protein-coding genes. The functional repertoire reveals a marked preponderance of molecular regulatory functions, and the models provide insights into the evolutionary origins of human gene functions. We show that our set of descriptions of functions can improve the widely used genomic technique of Gene Ontology enrichment analysis. The experimental evidence for each functional characteristic is recorded, thereby enabling the scientific community to help review and improve the resource, which we have made publicly available.

59 BASIC BIOLOGICAL SCIENCES↗