The genome sequence of Hirschfeldia incana, a new Brassicaceae model to improve photosynthetic light-use efficiency.

Photosynthesis is a key process in sustaining plant and human life. Improving the photosynthetic capacity of agricultural crops is an attractive means to increase their yields. While the core mechanisms of photosynthesis are highly conserved in C3 plants, these mechanisms are very flexible, allowing considerable diversity in photosynthetic properties. Among this diversity is the maintenance of high photosynthetic light-use efficiency at high irradiance as identified in a small number of exceptional C3 species. Hirschfeldia incana, a member of the Brassicaceae family, is such an exceptional species, and because it is easy to grow, it is an excellent model for studying the genetic and physiological basis of this trait. Here, we present a reference genome of H. incana and confirm its high photosynthetic light-use efficiency. While H. incana has the highest photosynthetic rates found so far in the Brassicaceae, the light-saturated assimilation rates of closely related Brassica rapa and Brassica nigra are also high. The H. incana genome has extensively diversified from that of B. rapa and B. nigra through large chromosomal rearrangements, species-specific transposon activity, and differential retention of duplicated genes. Duplicated genes in H. incana, B. rapa, and B. nigra that are involved in photosynthesis and/or photoprotection show a positive correlation between copy number and gene expression, providing leads into the mechanisms underlying the high photosynthetic efficiency of these species. Our work demonstrates that the H. incana genome serves as a valuable resource for studying the evolution of high photosynthetic light-use efficiency and enhancing photosynthetic rates in crop species.

PanTools v3: functional annotation, classification and phylogenomics.

SUMMARY: The ever-increasing number of sequenced genomes necessitates the development of pangenomic approaches for comparative genomics. Introduced in 2016, PanTools is a platform that allows pangenome construction, homology grouping and pangenomic read mapping. The use of graph database technology makes PanTools versatile, applicable from small viral genomes like SARS-CoV-2 up to large plant or animal genomes like tomato or human. Here, we present our third major update to PanTools that enables the integration of functional annotations and provides both gene-level analyses and phylogenetics. AVAILABILITY AND IMPLEMENTATION: PanTools is implemented in Java 8 and released under the GNU GPLv3 license. Software and documentation are available at https://git.wur.nl/bioinformatics/pantools. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Genetic mechanisms underlying increased microalgal thermotolerance, maximal growth rate, and yield on light following adaptive laboratory evolution.

BACKGROUND: Adaptive laboratory evolution (ALE) is a powerful method for strain optimization towards abiotic stress factors and for identifying adaptation mechanisms. In this study, the green microalga Picochlorum sp. BPE23 was cultured under supra-optimal temperature to force genetic adaptation. The robustness and adaptive capacity of Picochlorum strains turned them into an emerging model for evolutionary studies on abiotic stressors such as temperature, salinity, and light. RESULTS: Mutant strains showed an expanded maximal growth temperature of 44.6 °C, whereas the maximal growth temperature of the wild-type strain was 42 °C. Moreover, at the optimal growth temperature of 38 °C, the biomass yield on light was 22.3% higher, and the maximal growth rate was 70.5% higher than the wild type. Genome sequencing and transcriptome analysis were performed to elucidate the mechanisms behind the improved phenotype. A de novo assembled phased reference genome allowed the identification of 21 genic mutations involved in various processes. Moreover, approximately half of the genome contigs were found to be duplicated or even triplicated in all mutants, suggesting a causal role in adaptation. CONCLUSIONS: The developed tools and mutant strains provide a strong framework from whereupon Picochlorum sp. BPE23 can be further developed. Moreover, the extensive strain characterization provides evidence of how microalgae evolve to supra-optimal temperature and to photobioreactor growth conditions. With this study, microalgal evolutionary mechanisms were identified by combining ALE with genome sequencing.

The Pectobacterium pangenome, with a focus on Pectobacterium brasiliense, shows a robust core and extensive exchange of genes from a shared gene pool.

BACKGROUND: Bacterial plant pathogens of the Pectobacterium genus are responsible for a wide spectrum of diseases in plants, including important crops such as potato, tomato, lettuce, and banana. Investigation of the genetic diversity underlying virulence and host specificity can be performed at genome level by using a comprehensive comparative approach called pangenomics. A pangenomic approach, using newly developed functionalities in PanTools, was applied to analyze the complex phylogeny of the Pectobacterium genus. We specifically used the pangenome to investigate genetic differences between virulent and avirulent strains of P. brasiliense, a potato blackleg causing species dominantly present in Western Europe. RESULTS: Here we generated a multilevel pangenome for Pectobacterium, comprising 197 strains across 19 species, including type strains, with a focus on P. brasiliense. The extensive phylogenetic analysis of the Pectobacterium genus showed robust distinct clades, with most detail provided by 452,388 parsimony-informative single-nucleotide polymorphisms identified in single-copy orthologs. The average Pectobacterium genome consists of 47% core genes, 1% unique genes, and 52% accessory genes. Using the pangenome, we zoomed in on differences between virulent and avirulent P. brasiliense strains and identified 86 genes associated to virulent strains. We found that the organization of genes is highly structured and linked with gene conservation, function, and transcriptional orientation. CONCLUSION: The pangenome analysis demonstrates that evolution in Pectobacteria is a highly dynamic process, including gene acquisitions partly in clusters, genome rearrangements, and loss of genes. Pectobacterium species are typically not characterized by a set of species-specific genes, but instead present themselves using new gene combinations from the shared gene pool. A multilevel pangenomic approach, fusing DNA, protein, biological function, taxonomic group, and phenotypes, facilitates studies in a flexible taxonomic context.

Comparative genomics of the nonlegume Parasponia reveals insights into evolution of nitrogen-fixing rhizobium symbioses.

Nodules harboring nitrogen-fixing rhizobia are a well-known trait of legumes, but nodules also occur in other plant lineages, with rhizobia or the actinomycete Frankia as microsymbiont. It is generally assumed that nodulation evolved independently multiple times. However, molecular-genetic support for this hypothesis is lacking, as the genetic changes underlying nodule evolution remain elusive. We conducted genetic and comparative genomics studies by using Parasponia species (Cannabaceae), the only nonlegumes that can establish nitrogen-fixing nodules with rhizobium. Intergeneric crosses between Parasponia andersonii and its nonnodulating relative Trema tomentosa demonstrated that nodule organogenesis, but not intracellular infection, is a dominant genetic trait. Comparative transcriptomics of P. andersonii and the legume Medicago truncatula revealed utilization of at least 290 orthologous symbiosis genes in nodules. Among these are key genes that, in legumes, are essential for nodulation, including NODULE INCEPTION (NIN) and RHIZOBIUM-DIRECTED POLAR GROWTH (RPG). Comparative analysis of genomes from three Parasponia species and related nonnodulating plant species show evidence of parallel loss in nonnodulating species of putative orthologs of NIN, RPG, and NOD FACTOR PERCEPTION Parallel loss of these symbiosis genes indicates that these nonnodulating lineages lost the potential to nodulate. Taken together, our results challenge the view that nodulation evolved in parallel and raises the possibility that nodulation originated ∼100 Mya in a common ancestor of all nodulating plant species, but was subsequently lost in many descendant lineages. This will have profound implications for translational approaches aimed at engineering nitrogen-fixing nodules in crop plants.

GeneNoteBook, a collaborative notebook for comparative genomics.

SUMMARY: Analysis and comparison of genomic and transcriptomic datasets have become standard procedures in biological research. However, for non-model organisms no efficient tools exist to visually work with multiple genomes and their metadata, and to annotate such data in a collaborative way. Here we present GeneNoteBook: a web based collaborative notebook for comparative genomics. GeneNoteBook allows experimental and computational researchers to query, browse, visualize and curate bioinformatic analysis results for multiple genomes. GeneNoteBook is particularly suitable for the analysis of non-model organisms, as it allows for comparing newly sequenced genomes to those of model organisms. AVAILABILITY AND IMPLEMENTATION: GeneNoteBook is implemented as a node.js web application and depends on MongoDB and NCBI BLAST. Source code is available at https://github.com/genenotebook/genenotebook. Additionally, GeneNoteBook can be installed through Bioconda and as a Docker image. Full installation instructions and online documentation are available at https://genenotebook.github.io. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Hecaton: reliably detecting copy number variation in plant genomes using short read sequencing data.

BACKGROUND: Copy number variation (CNV) is thought to actively contribute to adaptive evolution of plant species. While many computational algorithms are available to detect copy number variation from whole genome sequencing datasets, the typical complexity of plant data likely introduces false positive calls. RESULTS: To enable reliable and comprehensive detection of CNV in plant genomes, we developed Hecaton, a novel computational workflow tailored to plants, that integrates calls from multiple state-of-the-art algorithms through a machine-learning approach. In this paper, we demonstrate that Hecaton outperforms current methods when applied to short read sequencing data of Arabidopsis thaliana, rice, maize, and tomato. Moreover, it correctly detects dispersed duplications, a type of CNV commonly found in plant species, in contrast to several state-of-the-art tools that erroneously represent this type of CNV as overlapping deletions and tandem duplications. Finally, Hecaton scales well in terms of memory usage and running time when applied to short read datasets of domesticated and wild tomato accessions. CONCLUSIONS: Hecaton provides a robust method to detect CNV in plants. We expect it to be of immediate interest to both applied and fundamental research on the relationship between genotype and phenotype in plants.

NCBI-compliant genome submissions: tips and tricks to save time and money.

Genome sequences nowadays play a central role in molecular biology and bioinformatics. These sequences are shared with the scientific community through sequence databases. The sequence repositories of the International Nucleotide Sequence Database Collaboration (INSDC, comprising GenBank, ENA and DDBJ) are the largest in the world. Preparing an annotated sequence in such a way that it will be accepted by the database is challenging because many validation criteria apply. In our opinion, it is an undesirable situation that researchers who want to submit their sequence need either a lot of experience or help from partners to get the job done. To save valuable time and money, we list a number of recommendations for people who want to submit an annotated genome to a sequence database, as well as for tool developers, who could help to ease the process.

Efficient inference of homologs in large eukaryotic pan-proteomes.

BACKGROUND: Identification of homologous genes is fundamental to comparative genomics, functional genomics and phylogenomics. Extensive public homology databases are of great value for investigating homology but need to be continually updated to incorporate new sequences. As new sequences are rapidly being generated, there is a need for efficient standalone tools to detect homologs in novel data. RESULTS: To address this, we present a fast method for detecting homology groups across a large number of individuals and/or species. We adopted a k-mer based approach which considerably reduces the number of pairwise protein alignments without sacrificing sensitivity. We demonstrate accuracy, scalability, efficiency and applicability of the presented method for detecting homology in large proteomes of bacteria, fungi, plants and Metazoa. CONCLUSIONS: We clearly observed the trade-off between recall and precision in our homology inference. Favoring recall or precision strongly depends on the application. The clustering behavior of our program can be optimized for particular applications by altering a few key parameters. The program is available for public use at https://github.com/sheikhizadeh/pantools as an extension to our pan-genomic analysis tool, PanTools.

Coping with living in the soil: the genome of the parthenogenetic springtail Folsomia candida.

BACKGROUND: Folsomia candida is a model in soil biology, belonging to the family of Isotomidae, subclass Collembola. It reproduces parthenogenetically in the presence of Wolbachia, and exhibits remarkable physiological adaptations to stress. To better understand these features and adaptations to life in the soil, we studied its genome in the context of its parthenogenetic lifestyle. RESULTS: We applied Pacific Bioscience sequencing and assembly to generate a reference genome for F. candida of 221.7 Mbp, comprising only 162 scaffolds. The complete genome of its endosymbiont Wolbachia, was also assembled and turned out to be the largest strain identified so far. Substantial gene family expansions and lineage-specific gene clusters were linked to stress response. A large number of genes (809) were acquired by horizontal gene transfer. A substantial fraction of these genes are involved in lignocellulose degradation. Also, the presence of genes involved in antibiotic biosynthesis was confirmed. Intra-genomic rearrangements of collinear gene clusters were observed, of which 11 were organized as palindromes. The Hox gene cluster of F. candida showed major rearrangements compared to arthropod consensus cluster, resulting in a disorganized cluster. CONCLUSIONS: The expansion of stress response gene families suggests that stress defense was important to facilitate colonization of soils. The large number of HGT genes related to lignocellulose degradation could be beneficial to unlock carbohydrate sources in soil, especially those contained in decaying plant and fungal organic matter. Intra- as well as inter-scaffold duplications of gene clusters may be a consequence of its parthenogenetic lifestyle. This high quality genome will be instrumental for evolutionary biologists investigating deep phylogenetic lineages among arthropods and will provide the basis for a more mechanistic understanding in soil ecology and ecotoxicology.

Making the difference: integrating structural variation detection tools.

From prokaryotes to eukaryotes, phenotypic variation, adaptation and speciation has been associated with structural variation between genomes of individuals within the same species. Many computer algorithms detecting such variations (callers) have recently been developed, spurred by the advent of the next-generation sequencing technology. Such callers mainly exploit split-read mapping or paired-end read mapping. However, as different callers are geared towards different types of structural variation, there is still no single caller that can be considered a community standard; instead, increasingly the various callers are combined in integrated pipelines. In this article, we review a wide range of callers, discuss challenges in the integration step and present a survey of pipelines used in population genomics studies. Based on our findings, we provide general recommendations on how to set-up such pipelines. Finally, we present an outlook on future challenges in structural variation detection.

PanTools: representation, storage and exploration of pan-genomic data.

MOTIVATION: Next-generation sequencing technology is generating a wealth of highly similar genome sequences for many species, paving the way for a transition from single-genome to pan-genome analyses. Accordingly, genomics research is going to switch from reference-centric to pan-genomic approaches. We define the pan-genome as a comprehensive representation of multiple annotated genomes, facilitating analyses on the similarity and divergence of the constituent genomes at the nucleotide, gene and genome structure level. Current pan-genomic approaches do not thoroughly address scalability, functionality and usability. RESULTS: We introduce a generalized De Bruijn graph as a pan-genome representation, as well as an online algorithm to construct it. This representation is stored in a Neo4j graph database, which makes our approach scalable to large eukaryotic genomes. Besides the construction algorithm, our software package, called PanTools, currently provides functionality for annotating pan-genomes, adding sequences, grouping genes, retrieving gene sequences or genomic regions, reconstructing genomes and comparing and querying pan-genomes. We demonstrate the performance of the tool using datasets of 62 E. coli genomes, 93 yeast genomes and 19 Arabidopsis thaliana genomes. AVAILABILITY AND IMPLEMENTATION: The Java implementation of PanTools is publicly available at http://www.bif.wur.nl CONTACT: sandra.smit@wur.nl.

Enhancing faba bean (Vicia faba L.) genome resources.

Grain legume improvement is currently impeded by a lack of genomic resources. The paucity of genome information for faba bean can be attributed to the intrinsic difficulties of assembling/annotating its giant (~13 Gb) genome. In order to address this challenge, RNA-sequencing analysis was performed on faba bean (cv. Wizard) leaves. Read alignment to the faba bean reference transcriptome identified 16 300 high quality unigenes. In addition, Illumina paired-end sequencing was used to establish a baseline for genomic information assembly. Genomic reads were assembled de novo into contigs with a size range of 50-5000 bp. Over 85% of sequences did not align to known genes, of which ~10% could be aligned to known repetitive genetic elements. Over 26 000 of the reference transcriptome unigenes could be aligned to DNA-sequencing (DNA-seq) reads with high confidence. Moreover, this comparison identified 56 668 potential splice points in all identified unigenes. Sequence length data were extended at 461 putative loci through alignment of DNA-seq contigs to full-length, publicly available linkage marker sequences. Reads also yielded coverages of 3466× and 650× for the chloroplast and mitochondrial genomes, respectively. Inter- and intraspecies organelle genome comparisons established core legume organelle gene sets, and revealed polymorphic regions of faba bean organelle genomes.

Comparative genomics of Beauveria bassiana: uncovering signatures of virulence against mosquitoes.

BACKGROUND: Entomopathogenic fungi such as Beauveria bassiana are promising biological agents for control of malaria mosquitoes. Indeed, infection with B. bassiana reduces the lifespan of mosquitoes in the laboratory and in the field. Natural isolates of B. bassiana show up to 10-fold differences in virulence between the most and the least virulent isolate. In this study, we sequenced the genomes of five isolates representing the extremes of low/high virulence and three RNA libraries, and applied a genome comparison approach to uncover genetic mechanisms underpinning virulence. RESULTS: A high-quality, near-complete genome assembly was achieved for the highly virulent isolate Bb8028, which was compared to the assemblies of the four other isolates. Whole genome analysis showed a high level of genetic diversity between the five isolates (2.85-16.8 SNPs/kb), which grouped into two distinct phylogenetic clusters. Mating type gene analysis revealed the presence of either the MAT1-1-1 or the MAT1-2-1 gene. Moreover, a putative new MAT gene (MAT1-2-8) was detected in the MAT1-2 locus. Comparative genome analysis revealed that Bb8028 contains 163 genes exclusive for this isolate. These unique genes have a tendency to cluster in the genome and to be often located near the telomeres. Among the genes unique to Bb8028 are a Non-Ribosomal Peptide Synthetase (NRPS) secondary metabolite gene cluster, a polyketide synthase (PKS) gene, and five genes with homology to bacterial toxins. A survey of candidate virulence genes for B. bassiana is presented. CONCLUSIONS: Our results indicate several genes and molecular processes that may underpin virulence towards mosquitoes. Thus, the genome sequences of five isolates of B. bassiana provide a better understanding of the natural variation in virulence and will offer a major resource for future research on this important biological control agent.

Risk factors for tuberculosis smear non-conversion in Eden district, Western Cape, South Africa, 2007-2013: a retrospective cohort study.

BACKGROUND: Tuberculosis (TB) continues to be a major global health problem. While progress has been made to improve TB cure rates, South Africa's 76 % smear-positive pulmonary TB (PTB) case cure rate remains below the WHO target of 85 %. We report on the trends of TB smear non-conversion and their predictors at the end of an intensive phase of treatment, and how this impacted on treatment outcomes of smear-positive PTB cases in Eden District, Western Cape Province, South Africa. METHODS: Routinely collected, retrospective data of smear-positive PTB cases from the electronic TB register in Eden District between 2007 and 2013 was extracted. Non-conversion was defined as persistent sputum smear-positive PTB cases at the end of the two or three month intensive phase of treatment. Chi-square test for linear trend and simple linear regression analysis were used to analyse the change in percentages and slope of TB smear non-conversion rates over time. Risk factors for TB non-conversion, and their impact on treatment outcomes, were evaluated using logistic regression models. RESULTS: Of 12,742 total smear-positive PTB cases included in our study, 12.8 % (n = 1627) did not sputum smear convert; 13.3 % (1411 of 10,574) of new cases and 9.9 % (216 of 2168) of re-treatment cases. Although not statistically significant in either new or re-treatment cases, between 2007 and 2013, smear non-conversion decreased from 16.4 to 12.7 % (slope = -0.60; 95 % CI: -1.49 to 0.29; p = 0.142) in new cases, and from 11.3 to 10.8 % in re-treatment cases (slope = -0.29; 95 % CI: -1.06 to 0.48; p = 0.376). Male gender, HIV co-infection and a >2+ acid fast bacilli (AFB) smear grading at the start of TB treatment were independent risk factors for non-conversion (p < 0.001). Age was a risk factor for non-conversion in new cases, but not for re-treatment cases. Non-conversion was also associated with unsuccessful treatment outcomes (p < 0.01), including treatment default and treatment failure. CONCLUSIONS: Smear-positive PTB cases, especially men and those with identified risk factors for non-conversion, should be closely monitored throughout their treatment period. The South African TB control program should invest in patient adherence counselling and education to mitigate TB non-conversion risk factors, and to improve conversion and TB cure rates.

Exploring genetic variation in the tomato (Solanum section Lycopersicon) clade by whole-genome sequencing.

We explored genetic variation by sequencing a selection of 84 tomato accessions and related wild species representative of the Lycopersicon, Arcanum, Eriopersicon and Neolycopersicon groups, which has yielded a huge amount of precious data on sequence diversity in the tomato clade. Three new reference genomes were reconstructed to support our comparative genome analyses. Comparative sequence alignment revealed group-, species- and accession-specific polymorphisms, explaining characteristic fruit traits and growth habits in the various cultivars. Using gene models from the annotated Heinz 1706 reference genome, we observed differences in the ratio between non-synonymous and synonymous SNPs (dN/dS) in fruit diversification and plant growth genes compared to a random set of genes, indicating positive selection and differences in selection pressure between crop accessions and wild species. In wild species, the number of single-nucleotide polymorphisms (SNPs) exceeds 10 million, i.e. 20-fold higher than found in most of the crop accessions, indicating dramatic genetic erosion of crop and heirloom tomatoes. In addition, the highest levels of heterozygosity were found for allogamous self-incompatible wild species, while facultative and autogamous self-compatible species display a lower heterozygosity level. Using whole-genome SNP information for maximum-likelihood analysis, we achieved complete tree resolution, whereas maximum-likelihood trees based on SNPs from ten fruit and growth genes show incomplete resolution for the crop accessions, partly due to the effect of heterozygous SNPs. Finally, results suggest that phylogenetic relationships are correlated with habitat, indicating the occurrence of geographical races within these groups, which is of practical importance for Solanum genome evolution studies.

RNASTAR: an RNA STructural Alignment Repository that provides insight into the evolution of natural and artificial RNAs.

Automated RNA alignment algorithms often fail to recapture the essential conserved sites that are critical for function. To assist in the refinement of these algorithms, we manually curated a set of 148 alignments with a total of 9600 unique sequences, in which each alignment was backed by at least one crystal or NMR structure. These alignments included both naturally and artificially selected molecules. We used principles of isostericity to improve the alignments from an average of 83%-94% isosteric base pairs. We expect that this alignment collection will assist in a wide range of benchmarking efforts and provide new insight into evolutionary principles governing change in RNA structural motifs. The improved alignments have been contributed to the Rfam database.

PanVA: Pangenomic Variant Analysis.

Genomics researchers increasingly use multiple reference genomes to comprehensively explore genetic variants underlying differences in detectable characteristics between organisms. Pangenomes allow for an efficient data representation of multiple related genomes and their associated metadata. However, current visual analysis approaches for exploring these complex genotype-phenotype relationships are often based on single reference approaches or lack adequate support for interpreting the variants in the genomic context with heterogeneous (meta)data. This design study introduces PanVA, a visual analytics design for pangenomic variant analysis developed with the active participation of genomics researchers. The design uniquely combines tailored visual representations with interactions such as sorting, grouping, and aggregation, allowing users to navigate and explore different perspectives on complex genotype-phenotype relations. Through evaluation in the context of plants and pathogen research, we show that PanVA helps researchers explore variants in genes and generate hypotheses about their role in phenotypic variation.

Molecular characterization reveals no functional evidence for naturally occurring cross-kingdom RNA interference in the early stages of Botrytis cinerea-tomato interaction.

Plant immune responses are triggered during the interaction with pathogens. The fungus Botrytis cinerea has previously been reported to use small RNAs (sRNAs) as effector molecules capable of interfering with the host immune response. Conversely, a host plant produces sRNAs that may interfere with the infection mechanism of an intruder. We used high-throughput sequencing to identify sRNAs produced by B. cinerea and Solanum lycopersicum (tomato) during early phases of interaction and to examine the expression of their predicted mRNA targets in the other organism. A total of 7042 B. cinerea sRNAs were predicted to target 3185 mRNAs in tomato. Of the predicted tomato target genes, 163 were indeed transcriptionally down-regulated during the early phase of infection. Several experiments were performed to study a causal relation between the production of B. cinerea sRNAs and the down-regulation of predicted target genes in tomato. We generated B. cinerea mutants in which a transposon region was deleted that is the source of c.10% of the fungal sRNAs. Furthermore, mutants were generated in which both Dicer-like genes (Bcdcl1 and Bcdcl2) were deleted and these displayed a >99% reduction of transposon-derived sRNA production. Neither of these mutants was significantly reduced in virulence on any plant species tested. Our results reveal no evidence for any detectable role of B. cinerea sRNAs in the virulence of the fungus.

Genome assembly and analysis of Lactuca virosa: implications for lettuce breeding.

Lettuce (Lactuca sativa L.) is a leafy vegetable crop with ongoing breeding efforts related to quality, resilience, and innovative production systems. To breed resilient and resistant lettuce in the future, valuable genetic variation found in close relatives could be further exploited. Lactuca virosa (2x = 2n = 18), a wild relative assigned to the tertiary lettuce gene pool, has a much larger genome (3.7 Gbp) than Lactuca sativa (2.5 Gbp). It has been used in interspecific crosses and is a donor to modern crisphead lettuce cultivars. Here, we present a de novo reference assembly of L. virosa with high continuity and complete gene space. This assembly facilitated comparisons to the genome of L. sativa and to that of the wild species L. saligna, a representative of the secondary lettuce gene pool. To assess the diversity in gene content, we classified the genes of the 3 Lactuca species as core, accessory, and unique. In addition, we identified 3 interspecific chromosomal inversions compared to L. sativa, which each may cause recombination suppression and thus hamper future introgression breeding. Using 3-way comparisons in both reference-based and reference-free manners, we show that the proliferation of long-terminal repeat elements has driven the genome expansion of L. virosa. Further, we performed a genome-wide comparison of immune genes, nucleotide-binding leucine-rich repeat, and receptor-like kinases among Lactuca spp. and indicated the evolutionary patterns and mechanisms behind their expansions. These genome analyses greatly facilitate the understanding of genetic variation in L. virosa, which is beneficial for the breeding of improved lettuce varieties.