EMBL's European Bioinformatics Institute (EMBL-EBI) in 2023.

The European Molecular Biology Laboratory's European Bioinformatics Institute (EMBL-EBI) is one of the world's leading sources of public biomolecular data. Based at the Wellcome Genome Campus in Hinxton, UK, EMBL-EBI is one of six sites of the European Molecular Biology Laboratory (EMBL), Europe's only intergovernmental life sciences organisation. This overview summarises the latest developments in the services provided by EMBL-EBI data resources to scientific communities globally. These developments aim to ensure EMBL-EBI resources meet the current and future needs of these scientific communities, accelerating the impact of open biological data for all.

Roast: a tool for reference-free optimization of supertranscriptome assemblies.

BACKGROUND: Transcriptomic studies involving organisms for which reference genomes are not available typically start by generating de novo transcriptome or supertranscriptome assembly from the raw RNA-seq reads. Assembling a supertranscriptome is, however, a challenging task due to significantly varying abundance of mRNA transcripts, alternative splicing, and sequencing errors. As a result, popular de novo supertranscriptome assembly tools generate assemblies containing contigs that are partially-assembled, fragmented, false chimeras or have local mis-assemblies leading to decreased assembly accuracy. Commonly available tools for assembly improvement rely primarily on running BLAST using closely related species making their accuracy and reliability conditioned on the availability of the data for closely related organisms. RESULTS: We present ROAST, a tool for optimization of supertranscriptome assemblies that uses paired-end RNA-seq data from Illumina sequencing platform to iteratively identify and fix assembly errors solely using the error signatures generated by RNA-seq alignment tools including soft-clips, unexpected expression coverage, and reads with mates unmapped or mapped on a different contig to identify and fix various supertranscriptome assembly errors without performing BLAST searches against other organisms. Evaluation results using simulated as well as real datasets show that ROAST significantly improves assembly quality by identifying and fixing various assembly errors. CONCLUSION: ROAST provides a reference-free approach to optimizing supertranscriptome assemblies highlighting its utility in refining de novo supertranscriptome assemblies of non-model organisms.

Thermal stress accelerates Arabidopsis thaliana mutation rate.

Mutations are the source of both genetic diversity and mutational load. However, the effects of increasing environmental temperature on plant mutation rates and relative impact on specific mutational classes (e.g., insertion/deletion [indel] vs. single nucleotide variant [SNV]) are unknown. This topic is important because of the poorly defined effects of anthropogenic global temperature rise on biological systems. Here, we show the impact of temperature increase on Arabidopsis thaliana mutation, studying whole genome profiles of mutation accumulation (MA) lineages grown for 11 successive generations at 29°C. Whereas growth of A. thaliana at standard temperature (ST; 23°C) is associated with a mutation rate of 7 × 10-9 base substitutions per site per generation, growth at stressful high temperature (HT; 29°C) is highly mutagenic, increasing the mutation rate to 12 × 10-9 SNV frequency is approximately two- to threefold higher at HT than at ST, and HT-growth causes an ∼19- to 23-fold increase in indel frequency, resulting in a disproportionate increase in indels (vs. SNVs). Most HT-induced indels are 1-2 bp in size and particularly affect homopolymeric or dinucleotide A or T stretch regions of the genome. HT-induced indels occur disproportionately in nucleosome-free regions, suggesting that much HT-induced mutational damage occurs during cell-cycle phases when genomic DNA is packaged into nucleosomes. We conclude that stressful experimental temperature increases accelerate plant mutation rates and particularly accelerate the rate of indel mutation. Increasing environmental temperatures are thus likely to have significant mutagenic consequences for plants growing in the wild and may, in particular, add detrimentally to mutational load.

DNA mismatch repair preferentially protects genes from mutation.

Mutation is the source of genetic variation and fuels biological evolution. Many mutations first arise as DNA replication errors. These errors subsequently evade correction by cellular DNA repair, for example, by the well-known DNA mismatch repair (MMR) mechanism. Here, we determine the genome-wide effects of MMR on mutation. We first identify almost 9000 mutations accumulated over five generations in eight MMR-deficient mutation accumulation (MA) lines of the model plant species, Arabidopsis thaliana We then show that MMR deficiency greatly increases the frequency of both smaller-scale insertions and deletions (indels) and of single-nucleotide variant (SNV) mutations. Most indels involve A or T nucleotides and occur preferentially in homopolymeric (poly A or poly T) genomic stretches. In addition, we find that the likelihood of occurrence of indels in homopolymeric stretches is strongly related to stretch length, and that this relationship causes ultrahigh localized mutation rates in specific homopolymeric stretch regions. For SNVs, we show that MMR deficiency both increases their frequency and changes their molecular mutational spectrum, causing further enhancement of the GC to AT bias characteristic of organisms with normal MMR function. Our final genome-wide analyses show that MMR deficiency disproportionately increases the numbers of SNVs in genes, rather than in nongenic regions of the genome. This latter observation indicates that MMR preferentially protects genes from mutation and has important consequences for understanding the evolution of genomes during both natural selection and human tumor growth.

Environmentally responsive genome-wide accumulation of de novo Arabidopsis thaliana mutations and epimutations.

Evolution is fueled by phenotypic diversity, which is in turn due to underlying heritable genetic (and potentially epigenetic) variation. While environmental factors are well known to influence the accumulation of novel variation in microorganisms and human cancer cells, the extent to which the natural environment influences the accumulation of novel variation in plants is relatively unknown. Here we use whole-genome and whole-methylome sequencing to test if a specific environmental stress (high-salinity soil) changes the frequency and molecular profile of accumulated mutations and epimutations (changes in cytosine methylation status) in mutation accumulation (MA) lineages of Arabidopsis thaliana. We first show that stressed lineages accumulate ∼100% more mutations, and that these mutations exhibit a distinctive molecular mutational spectrum (specific increases in relative frequency of transversion and insertion/deletion [indel] mutations). We next show that stressed lineages accumulate ∼45% more differentially methylated cytosine positions (DMPs) at CG sites (CG-DMPs) than controls, and also show that while many (∼75%) of these CG-DMPs are inherited, some can be lost in subsequent generations. Finally, we show that stress-associated CG-DMPs arise more frequently in genic than in nongenic regions of the genome. We suggest that commonly encountered natural environmental stresses can accelerate the accumulation and change the profiles of novel inherited variants in plants. Our findings are significant because stress exposure is common among plants in the wild, and they suggest that environmental factors may significantly alter the rates and patterns of incidence of the inherited novel variants that fuel plant evolution.

ROS-mediated vascular homeostatic control of root-to-shoot soil Na delivery in Arabidopsis.

Sodium (Na) is ubiquitous in soils, and is transported to plant shoots via transpiration through xylem elements in the vascular tissue. However, excess Na is damaging. Accordingly, control of xylem-sap Na concentration is important for maintenance of shoot Na homeostasis, especially under Na stress conditions. Here we report that shoot Na homeostasis of Arabidopsis thaliana plants grown in saline soils is conferred by reactive oxygen species (ROS) regulation of xylem-sap Na concentrations. We show that lack of A. thaliana respiratory burst oxidase protein F (AtrbohF; an NADPH oxidase catalysing ROS production) causes hypersensitivity of shoots to soil salinity. Lack of AtrbohF-dependent salinity-induced vascular ROS accumulation leads to increased Na concentrations in root vasculature cells and in xylem sap, thus causing delivery of damaging amounts of Na to the shoot. We also show that the excess shoot Na delivery caused by lack of AtrbohF is dependent upon transpiration. We conclude that AtrbohF increases ROS levels in wild-type root vasculature in response to raised soil salinity, thereby limiting Na concentrations in xylem sap, and in turn protecting shoot cells from transpiration-dependent delivery of excess Na.

Genome-wide analysis of mutations in mutant lineages selected following fast-neutron irradiation mutagenesis of Arabidopsis thaliana.

Ionizing radiation has long been known to induce heritable mutagenic change in DNA sequence. However, the genome-wide effect of radiation is not well understood. Here we report the molecular properties and frequency of mutations in phenotypically selected mutant lines isolated following exposure of the genetic model flowering plant Arabidopsis thaliana to fast neutrons (FNs). Previous studies suggested that FNs predominantly induce deletions longer than a kilobase in A. thaliana. However, we found a higher frequency of single base substitution than deletion mutations. While the overall frequency and molecular spectrum of fast-neutron (FN)-induced single base substitutions differed substantially from those of "background" mutations arising spontaneously in laboratory-grown plants, G:C>A:T transitions were favored in both. We found that FN-induced G:C>A:T transitions were concentrated at pyrimidine dinucleotide sites, suggesting that FNs promote the formation of mutational covalent linkages between adjacent pyrimidine residues. In addition, we found that FNs induced more single base than large deletions, and that these single base deletions were possibly caused by replication slippage. Our observations provide an initial picture of the genome-wide molecular profile of mutations induced in A. thaliana by FN irradiation and are particularly informative of the nature and extent of genome-wide mutation in lines selected on the basis of mutant phenotypes from FN-mutagenized A. thaliana populations.

Patterns of homoeologous gene expression shown by RNA sequencing in hexaploid bread wheat.

BACKGROUND: Bread wheat (Triticum aestivum) has a large, complex and hexaploid genome consisting of A, B and D homoeologous chromosome sets. Therefore each wheat gene potentially exists as a trio of A, B and D homoeoloci, each of which may contribute differentially to wheat phenotypes. We describe a novel approach combining wheat cytogenetic resources (chromosome substitution 'nullisomic-tetrasomic' lines) with next generation deep sequencing of gene transcripts (RNA-Seq), to directly and accurately identify homoeologue-specific single nucleotide variants and quantify the relative contribution of individual homoeoloci to gene expression. RESULTS: We discover, based on a sample comprising ~5-10% of the total wheat gene content, that at least 45% of wheat genes are expressed from all three distinct homoeoloci. Most of these genes show strikingly biased expression patterns in which expression is dominated by a single homoeolocus. The remaining ~55% of wheat genes are expressed from either one or two homoeoloci only, through a combination of extensive transcriptional silencing and homoeolocus loss. CONCLUSIONS: We conclude that wheat is tending towards functional diploidy, through a variety of mechanisms causing single homoeoloci to become the predominant source of gene transcripts. This discovery has profound consequences for wheat breeding and our understanding of wheat evolution.

Microarray-based ultra-high resolution discovery of genomic deletion mutations.

BACKGROUND: Oligonucleotide microarray-based comparative genomic hybridization (CGH) offers an attractive possible route for the rapid and cost-effective genome-wide discovery of deletion mutations. CGH typically involves comparison of the hybridization intensities of genomic DNA samples with microarray chip representations of entire genomes, and has widespread potential application in experimental research and medical diagnostics. However, the power to detect small deletions is low. RESULTS: Here we use a graduated series of Arabidopsis thaliana genomic deletion mutations (of sizes ranging from 4 bp to ~5 kb) to optimize CGH-based genomic deletion detection. We show that the power to detect smaller deletions (4, 28 and 104 bp) depends upon oligonucleotide density (essentially the number of genome-representative oligonucleotides on the microarray chip), and determine the oligonucleotide spacings necessary to guarantee detection of deletions of specified size. CONCLUSIONS: Our findings will enhance a wide range of research and clinical applications, and in particular will aid in the discovery of genomic deletions in the absence of a priori knowledge of their existence.

HANDS: a tool for genome-wide discovery of subgenome-specific base-identity in polyploids.

BACKGROUND: The analysis of polyploid genomes is problematic because homeologous subgenome sequences are closely related. This relatedness makes it difficult to assign individual sequences to the specific subgenome from which they are derived, and hinders the development of polyploid whole genome assemblies. RESULTS: We here present a next-generation sequencing (NGS)-based approach for assignment of subgenome-specific base-identity at sites containing homeolog-specific polymorphisms (HSPs): 'HSP base Assignment using NGS data through Diploid Similarity' (HANDS). We show that HANDS correctly predicts subgenome-specific base-identity at >90% of assayed HSPs in the hexaploid bread wheat (Triticum aestivum) transcriptome, thus providing a substantial increase in accuracy versus previous methods for homeolog-specific base assignment. CONCLUSION: We conclude that HANDS enables rapid and accurate genome-wide discovery of homeolog-specific base-identity, a capability having multiple applications in polyploid genomics.

Comparative analysis of metabolic networks provides insight into the evolution of plant pathogenic and nonpathogenic lifestyles in Pseudomonas.

Plant pathogenic pseudomonads such as Pseudomonas syringae colonize plant surfaces and tissues and have been reported to be nutritionally specialized relative to nonpathogenic pseudomonads. We performed comparative analyses of metabolic networks reconstructed from genome sequence data in order to investigate the hypothesis that P. syringae has evolved to be metabolically specialized for a plant pathogenic lifestyle. We used the metabolic network comparison tool Rahnuma and complementary bioinformatic analyses to compare the distribution of 1,299 metabolic reactions across nine genome-sequenced strains of Pseudomonas, including three strains of P. syringae. The two pathogenic Pseudomonas species analyzed, P. syringae and the opportunistic human pathogen P. aeruginosa, each displayed a high level of intraspecies metabolic similarity compared with nonpathogenic Pseudomonas. The three P. syringae strains lacked a significant number of reactions predicted to be present in all other Pseudomonas strains analyzed, which is consistent with the hypothesis that P. syringae is adapted for growth in a nutritionally constrained environment. Pathway predictions demonstrated that some of the differences detected in metabolic network comparisons could account for differences in amino acid assimilation ability reported in experimental analyses. Parsimony analysis and reaction neighborhood approaches were used to model the evolution of metabolic networks and amino acid assimilation pathways in pseudomonads. Both methods supported a model of Pseudomonas evolution in which the common ancestor of P. syringae had experienced a significant number of deletion events relative to other nonpathogenic pseudomonads. We discuss how the characteristic metabolic features of P. syringae could reflect adaptation to a pathogenic lifestyle.

A Bayesian approach to the evolution of metabolic networks on a phylogeny.

The availability of genomes of many closely related bacteria with diverse metabolic capabilities offers the possibility of tracing metabolic evolution on a phylogeny relating the genomes to understand the evolutionary processes and constraints that affect the evolution of metabolic networks. Using simple (independent loss/gain of reactions) or complex (incorporating dependencies among reactions) stochastic models of metabolic evolution, it is possible to study how metabolic networks evolve over time. Here, we describe a model that takes the reaction neighborhood into account when modeling metabolic evolution. The model also allows estimation of the strength of the neighborhood effect during the course of evolution. We present Gibbs samplers for sampling networks at the internal node of a phylogeny and for estimating the parameters of evolution over a phylogeny without exploring the whole search space by iteratively sampling from the conditional distributions of the internal networks and parameters. The samplers are used to estimate the parameters of evolution of metabolic networks of bacteria in the genus Pseudomonas and to infer the metabolic networks of the ancestral pseudomonads. The results suggest that pathway maps that are conserved across the Pseudomonas phylogeny have a stronger neighborhood structure than those which have a variable distribution of reactions across the phylogeny, and that some Pseudomonas lineages are going through genome reduction resulting in the loss of a number of reactions from their metabolic networks.

Kinome-Wide RNAi Screen Uncovers Role of Ballchen in Maintenance of Gene Activation by Trithorax Group in Drosophila.

Polycomb group (PcG) and trithorax group (trxG) proteins are evolutionary conserved factors that contribute to cell fate determination and maintenance of cellular identities during development of multicellular organisms. The PcG maintains heritable patterns of gene silencing while trxG acts as anti-silencing factors by conserving activation of cell type specific genes. Genetic and molecular analysis has revealed extensive details about how different PcG and trxG complexes antagonize each other to maintain cell fates, however, the cellular signaling components that contribute to the preservation of gene expression by PcG/trxG remain elusive. Here, we report an ex vivo kinome-wide RNAi screen in Drosophila aimed at identifying cell signaling genes that facilitate trxG in counteracting PcG mediated repression. From the list of trxG candidates, Ballchen (BALL), a histone kinase known to phosphorylate histone H2A at threonine 119 (H2AT119p), was characterized as a trxG regulator. The ball mutant exhibits strong genetic interactions with Polycomb (Pc) and trithorax (trx) mutants and loss of BALL affects expression of trxG target genes. BALL co-localizes with Trithorax on chromatin and depletion of BALL results in increased H2AK118 ubiquitination, a histone mark central to PcG mediated gene silencing. Moreover, BALL was found to substantially associate with known TRX binding sites across the genome. Genome wide distribution of BALL also overlaps with H3K4me3 and H3K27ac at actively transcribed genes. We propose that BALL mediated signaling positively contributes to the maintenance of gene activation by trxG in counteracting the repressive effect of PcG.

A stochastic model for the evolution of metabolic networks with neighbor dependence.

MOTIVATION: Most current research in network evolution focuses on networks that follow a Duplication Attachment model where the network is only allowed to grow. The evolution of metabolic networks, however, is characterized by gain as well as loss of reactions. It would be desirable to have a biologically relevant model of network evolution that could be used to calculate the likelihood of homologous metabolic networks. RESULTS: We describe metabolic network evolution as a discrete space continuous time Markov process and introduce a neighbor-dependent model for the evolution of metabolic networks where the rates with which reactions are added or removed depend on the fraction of neighboring reactions present in the network. We also present a Gibbs sampler for estimating the parameters of evolution without exploring the whole search space by iteratively sampling from the conditional distributions of the paths and parameters. A Metropolis-Hastings algorithm for sampling paths between two networks and calculating the likelihood of evolution is also presented. The sampler is used to estimate the parameters of evolution of metabolic networks in the genus Pseudomonas. AVAILABILITY: An implementation of the Gibbs sampler in Java is available at http://www.stats.ox.ac.uk/ approximately mithani/networkGibbs/. SUPPLEMENTARY INFORMATION: Supplementary data are available at the Bioinformatics online.

Rahnuma: hypergraph-based tool for metabolic pathway prediction and network comparison.

SUMMARY: We present a tool called Rahnuma for prediction and analysis of metabolic pathways and comparison of metabolic networks. Rahnuma represents metabolic networks as hypergraphs and computes all possible pathways between two or more metabolites. It provides an intuitive way to answer biological ques- tions focusing on differences between organisms or the evolution of different species by allowing pathway-based metabolic network comparisons at an organism as well as at a phylogenetic level. AVAILABILITY: Rahnuma is available online at http://portal.stats.ox.ac.uk:8080/rahnuma/.

MAPPS: A Web-Based Tool for Metabolic Pathway Prediction and Network Analysis in the Postgenomic Era.

Comparative and evolutionary analyses of metabolic networks have a wide range of applications, ranging from research into metabolic evolution through to practical applications in drug development, synthetic biology, and biodegradation. We present MAPPS: Metabolic network Analysis and Pathway Prediction Server (https://mapps.lums.edu.pk), a web-based tool to study functions and evolution of metabolic networks using traditional and 'omics data sets. MAPPS provides diverse functionalities including an interactive interface, graphical visualization of results, pathway prediction and network comparison, identification of potential drug targets, in silico metabolic engineering, host-microbe interactions, and ancestral network building. Importantly, MAPPS also allows users to upload custom data, thus enabling metabolic analyses on draft and custom genomes, and has an 'omics pipeline to filter pathway results, making it relevant in today's postgenomic era.

A cell-based high-throughput screen identifies inhibitors that overcome P-glycoprotein (Pgp)-mediated multidrug resistance.

Multidrug resistance (MDR) to chemotherapeutic drugs remains one of the major impediments to the treatment of cancer. Discovery and development of drugs that can prevent and reverse the acquisition of multidrug resistance constitute a foremost challenge in cancer therapeutics. In this work, we screened a library of 1,127 compounds with known targets for their ability to overcome Pgp-mediated multidrug resistance in cancer cell lines. We identified four compounds (CHIR-124, Elesclomol, Tyrphostin-9 and Brefeldin A) that inhibited the growth of two pairs of parental and Pgp-overexpressing multidrug-resistant cell lines with similar potency irrespective of their Pgp status. Mechanistically, CHIR-124 (a potent inhibitor of Chk1 kinase) inhibited Pgp activity in both multidrug-resistant cell lines (KB-V1 and A2780-Pac-Res) as determined through cell-based Pgp-efflux assays. Other three inhibitors on the contrary, were effective in Pgp-overexpressing resistant cells without increasing the cellular accumulation of a Pgp substrate, indicating that they overcome resistance by avoiding efflux through Pgp. None of these compounds modulated the expression of Pgp in resistant cell lines. PIK-75, a PI3 Kinase inhibitor, was also determined to inhibit Pgp activity, despite being equally potent in only one of the two pairs of resistant and parental cell lines. Strong binding of both CHIR-124 and PIK-75 to Pgp was predicted through docking studies and both compounds inhibited Pgp in a biochemical assay. The inhibition of Pgp causes accumulation of these compounds in the cells where they can modulate the function of their target proteins and thereby inhibit cell proliferation. In conclusion, we have identified compounds with various cellular targets that overcome multidrug resistance in Pgp-overexpressing cell lines through mechanisms that include Pgp inhibition and efflux evasion. These compounds, therefore, can avoid challenges associated with the co-administration of Pgp inhibitors with chemotherapeutic or targeted drugs such as additive toxicities and differing pharmacokinetic properties.

Transcriptomic analysis reveals differential gene expression, alternative splicing, and novel exons during mouse trophoblast stem cell differentiation.

BACKGROUND: Differentiation of mouse trophoblast stem cells (TSCs) to trophoblast giant cells (TGCs) has been widely used as a model system to study placental development and function. While several differentially expressed genes, including regulators of TSC differentiation, have been identified, a comprehensive analysis of the global expression of genes and splice variants in the two cell types has not been reported. RESULTS: Here, we report ~ 7800 differentially expressed genes in TGCs compared to TSCs which include regulators of the cell cycle, apoptosis, cytoskeleton, cell mobility, embryo implantation, metabolism, and various signaling pathways. We show that several mitotic proteins, including Aurora A kinase, were downregulated in TGCs and that the activity of Aurora A kinase is required for the maintenance of TSCs. We also identify hitherto undiscovered, cell-type specific alternative splicing events in 31 genes in the two cell types. Finally, we also report 19 novel exons in 12 genes which are expressed in both TSCs and TGCs. CONCLUSIONS: Overall, our results uncover several potential regulators of TSC differentiation and TGC function, thereby providing a valuable resource for developmental and molecular biologists interested in the study of stem cell differentiation and embryonic development.

Genome-wide RNAi screen in Drosophila reveals Enok as a novel trithorax group regulator.

BACKGROUND: Polycomb group (PcG) and trithorax group (trxG) proteins contribute to the specialization of cell types by maintaining differential gene expression patterns. Initially discovered as positive regulators of HOX genes in forward genetic screens, trxG counteracts PcG-mediated repression of cell type-specific genes. Despite decades of extensive analysis, molecular understanding of trxG action and regulation are still punctuated by many unknowns. This study aimed at discovering novel factors that elicit an anti-silencing effect to facilitate trxG-mediated gene activation. RESULTS: We have developed a cell-based reporter system and performed a genome-wide RNAi screen to discover novel factors involved in trxG-mediated gene regulation in Drosophila. We identified more than 200 genes affecting the reporter in a manner similar to trxG genes. From the list of top candidates, we have characterized Enoki mushroom (Enok), a known histone acetyltransferase, as an important regulator of trxG in Drosophila. Mutants of enok strongly suppressed extra sex comb phenotype of Pc mutants and enhanced homeotic transformations associated with trx mutations. Enok colocalizes with both TRX and PC at chromatin. Moreover, depletion of Enok specifically resulted in an increased enrichment of PC and consequently silencing of trxG targets. This downregulation of trxG targets was also accompanied by a decreased occupancy of RNA-Pol-II in the gene body, correlating with an increased stalling at the transcription start sites of these genes. We propose that Enok facilitates trxG-mediated maintenance of gene activation by specifically counteracting PcG-mediated repression. CONCLUSION: Our ex vivo approach led to identification of new trxG candidate genes that warrant further investigation. Presence of chromatin modifiers as well as known members of trxG and their interactors in the genome-wide RNAi screen validated our reverse genetics approach. Genetic and molecular characterization of Enok revealed a hitherto unknown interplay between Enok and PcG/trxG system. We conclude that histone acetylation by Enok positively impacts the maintenance of trxG-regulated gene activation by inhibiting PRC1-mediated transcriptional repression.

HANDS2: accurate assignment of homoeallelic base-identity in allopolyploids despite missing data.

Characterization of homoeallelic base-identity in allopolyploids is difficult since homeologous subgenomes are closely related and becomes further challenging if diploid-progenitor data is missing. We present HANDS2, a next-generation sequencing-based tool that enables highly accurate (>90%) genome-wide discovery of homeolog-specific base-identity in allopolyploids even in the absence of a diploid-progenitor. We applied HANDS2 to the transcriptomes of various cruciferous plants belonging to genus Brassica. Our results suggest that the three C genomes in Brassica are more similar to each other than the three A genomes, and provide important insights into the relationships between various Brassica tetraploids and their diploid-progenitors at a single-base resolution.