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.

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.

The genome of Lactuca saligna, a wild relative of lettuce, provides insight into non-host resistance to the downy mildew Bremia lactucae.

Lactuca saligna L. is a wild relative of cultivated lettuce (Lactuca sativa L.), with which it is partially interfertile. Hybrid progeny suffer from hybrid incompatibility (HI), resulting in reduced fertility and distorted transmission ratios. Lactuca saligna displays broad-spectrum resistance against lettuce downy mildew caused by Bremia lactucae Regel and is considered a non-host species. This phenomenon of resistance in L. saligna is called non-host resistance (NHR). One possible mechanism behind this NHR is through the plant-pathogen interaction triggered by pathogen recognition receptors, including nucleotide-binding leucine-rich repeat (NLR) proteins and receptor-like kinases (RLKs). We report a chromosome-level genome assembly of L. saligna (accession CGN05327), leading to the identification of two large paracentric inversions (>50 Mb) between L. saligna and L. sativa. Genome-wide searches delineated the major resistance clusters as regions enriched in NLRs and RLKs. Three of the enriched regions co-locate with previously identified NHR intervals. RNA-seq analysis of Bremia-infected lettuce identified several differentially expressed RLKs in NHR regions. Three tandem wall-associated kinase-encoding genes (WAKs) in the NHR8 interval display particularly high expression changes at an early stage of infection. We propose RLKs as strong candidates for determinants of the NHR phenotype of L. saligna.

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.

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.