Spinach genomes reveal migration history and candidate genes for important crop traits.

Spinach (Spinacia oleracea) is an important leafy crop possessing notable economic value and health benefits. Current genomic resources include reference genomes and genome-wide association studies. However, the worldwide genetic relationships and the migration history of the crop remained uncertain, and genome-wide association studies have produced extensive gene lists related to agronomic traits. Here, we re-analysed the sequenced genomes of 305 cultivated and wild spinach accessions to unveil the phylogeny and history of cultivated spinach and to explore genetic variation in relation to phenotypes. In contrast to previous studies, we employed machine learning methods (based on Extreme Gradient Boosting, XGBoost) to detect variants that are collectively associated with agronomic traits. Variant-based cluster analyses revealed three primary spinach groups in the Middle East, Asia and Europe/US. Combining admixture analysis and allele-sharing statistics, migration routes of spinach from the Middle East to Europe and Asia are presented. Using XGBoost machine learning models we predict genomic variants influencing bolting time, flowering time, petiole color, and leaf surface texture and propose candidate genes for each trait. This study enhances our understanding of the history and phylogeny of domesticated spinach and provides valuable information on candidate genes for future genetic improvement of the crop.

Genomic basis of seed colour in quinoa inferred from variant patterns using extreme gradient boosting.

Quinoa is an agriculturally important crop species originally domesticated in the Andes of central South America. One of its most important phenotypic traits is seed colour. Seed colour variation is determined by contrasting abundance of betalains, a class of strong antioxidant and free radicals scavenging colour pigments only found in plants of the order Caryophyllales. However, the genetic basis for these pigments in seeds remains to be identified. Here we demonstrate the application of machine learning (extreme gradient boosting) to identify genetic variants predictive of seed colour. We show that extreme gradient boosting outperforms the classical genome-wide association approach. We provide re-sequencing and phenotypic data for 156 South American quinoa accessions and identify candidate genes potentially controlling betalain content in quinoa seeds. Genes identified include novel cytochrome P450 genes and known members of the betalain synthesis pathway, as well as genes annotated as being involved in seed development. Our work showcases the power of modern machine learning methods to extract biologically meaningful information from large sequencing data sets.

Genomic variation in the genus Beta based on 656 sequenced beet genomes.

Cultivated beets (Beta vulgaris ssp. vulgaris) constitute important crop plants, in particular sugar beet as an indispensable source of sucrose. Several species of wild beets of the genus Beta with distribution along the European Atlantic coast, Macaronesia, and throughout the Mediterranean area exist. Thorough characterization of beet genomes is required for straightforward access to genes promoting genetic resistance against biotic and abiotic stress. Analysing short-read data of 656 sequenced beet genomes, we identified 10 million variant positions in comparison to the sugar beet reference genome RefBeet-1.2. The main groups of species and subspecies were distinguishable based on shared variation, and the separation of sea beets (Beta vulgaris ssp. maritima) into a Mediterranean and an Atlantic subgroup as suggested by previous studies could be confirmed. Complementary approaches of variant-based clustering were employed based on PCA, genotype likelihoods, tree calculations, and admixture analysis. Outliers suggested the occurrence of inter(sub)specific hybridisation, independently confirmed by different analyses. Screens for regions under artificial selection in the sugar beet genome identified 15 Mbp of the genome as variation-poor, enriched for genes involved in shoot system development, stress response, and carbohydrate metabolism. The resources presented herein will be valuable for crop improvement and wild species monitoring and conservation efforts, and for studies on beet genealogy, population structure and population dynamics. Our study provides a wealth of data for in-depth analyses of further aspects of the beet genome towards a thorough understanding of the biology of this important complex of a crop species and its wild relatives.

Genome-environment associations along elevation gradients in two snowbed species of the North-Eastern Calcareous Alps.

BACKGROUND: Anthropogenic climate change leads to increasing temperatures and altered precipitation and snowmelt patterns, especially in alpine ecosystems. To understand species' responses to climate change, assessment of genetic structure and diversity is crucial as the basis for the evaluation of migration patterns, genetic adaptation potential as well as the identification of adaptive alleles. RESULTS: We studied genetic structure, diversity and genome-environment associations of two snowbed species endemic to the Eastern Alps with a large elevational range, Achillea clusiana Tausch and Campanula pulla L. Genotyping-by-sequencing was employed to assemble loci de novo, call variants and perform population genetic analyses. Populations of either species were distinguishable by mountain, and to some extent by elevation. We found evidence for gene flow between elevations. Results of genome-environment associations suggested similar selective pressures acting on both species, emanating mainly from precipitation and exposition rather than temperature. CONCLUSIONS: Given their genetic structure and amount of gene flow among populations the two study species are suitable to serve as a model for genetic monitoring of climate change adaptation along an elevation gradient. Consequences of climate change will predominantly manifest via changes in precipitation and, thus, duration of snow cover in the snowbeds and indirectly via shrub encroachment accompanied by increasing shading of snowbeds at lower range margins. Assembling genomes of the study species and studying larger sample sizes and time series will be necessary to functionally characterize and validate the herein identified genomic loci putatively involved in adaptive processes.

Putting hornets on the genomic map.

Hornets are the largest of the social wasps, and are important regulators of insect populations in their native ranges. Hornets are also very successful as invasive species, with often devastating economic, ecological and societal effects. Understanding why these wasps are such successful invaders is critical to managing future introductions and minimising impact on native biodiversity. Critical to the management toolkit is a comprehensive genomic resource for these insects. Here we provide the annotated genomes for two hornets, Vespa crabro and Vespa velutina. We compare their genomes with those of other social Hymenoptera, including the northern giant hornet Vespa mandarinia. The three hornet genomes show evidence of selection pressure on genes associated with reproduction, which might facilitate the transition into invasive ranges. Vespa crabro has experienced positive selection on the highest number of genes, including those putatively associated with molecular binding and olfactory systems. Caste-specific brain transcriptomic analysis also revealed 133 differentially expressed genes, some of which are associated with olfactory functions. This report provides a spring-board for advancing our understanding of the evolution and ecology of hornets, and opens up opportunities for using molecular methods in the future management of both native and invasive populations of these over-looked insects.

Storage media and RNA extraction approaches substantially influence the recovery and integrity of livestock fecal microbial RNA.

Background: There is growing interest in understanding gut microbiome dynamics, to increase the sustainability of livestock production systems and to better understand the dynamics that regulate antibiotic resistance genes (i.e., the resistome). High-throughput sequencing of RNA transcripts (RNA-seq) from microbial communities (metatranscriptome) allows an unprecedented opportunity to analyze the functional and taxonomical dynamics of the expressed microbiome and emerges as a highly informative approach. However, the isolation and preservation of high-quality RNA from livestock fecal samples remains highly challenging. This study aimed to determine the impact of the various sample storage and RNA extraction strategies on the recovery and integrity of microbial RNA extracted from selected livestock (chicken and pig) fecal samples. Methods: Fecal samples from pigs and chicken were collected from conventional slaughterhouses. Two different storage buffers were used at two different storage temperatures. The extraction of total RNA was done using four different commercially available kits and RNA integrity/quality and concentration were measured using a Bioanalyzer 2100 system with RNA 6000 Nano kit (Agilent, Santa Clara, CA, USA). In addition, RT-qPCR was used to assess bacterial RNA quality and the level of host RNA contamination. Results: The quantity and quality of RNA differed by sample type (i.e., either pig or chicken) and most significantly by the extraction kit, with differences in the extraction method resulting in the least variability in pig feces samples and the most variability in chicken feces. Considering a tradeoff between the RNA yield and the RNA integrity and at the same time minimizing the amount of host RNA in the sample, a combination of storing the fecal samples in RNALater at either 4 °C (for 24 h) or -80 °C (up to 2 weeks) with extraction with PM kit (RNEasy Power Microbiome Kit) had the best performance for both chicken and pig samples. Conclusion: Our findings provided a further emphasis on using a consistent methodology for sample storage, duration as well as a compatible RNA extraction approach. This is crucial as the impact of these technical steps can be potentially large compared with the real biological variability to be explained in microbiome and resistome studies.

Metatranscriptomic Analysis of the Chicken Gut Resistome Response to In-Feed Antibiotics and Natural Feed Additives.

The emergence of resistance against common antibiotics in the gut microbiota is a major issue for both human and livestock health. This highlights the need for understanding the impact of such application on the reservoir of antibiotic resistance genes in poultry gut and devising means to circumvent the potential resistome expansion. Phytogenic feed additives (PFAs) are potential natural alternative to antibiotic to improve animal health and performance, supposedly via positively affecting the gut microbial ecosystem, but there is little systematic information available. In this time-course study, we applied a shotgun meta-transcriptomics approach to investigate the impact of a PFA product as well as the commonly used antibiotic, zinc bacitracin either at AGP concentration or therapeutic concentration on the gut microbiome and resistome of broiler chickens raised for 35 days. Over the course of the trial, PFA treatments increased the abundance of Firmicutes such as Lactobacillus and resulted in a lower abundance of Escherichia, while the latter group increased significantly in the feces of chickens that received either AGP or AB doses of bacitracin. Tetracycline resistance and aminoglycoside resistance were the predominant antibiotic resistance gene (ARG) classes found, regardless of the treatment. PFA application resulted in a decrease in abundance of ARGs compared to those in the control group and other antibiotic treatment groups. In summary, the findings from this study demonstrate the potential of phytogenic feed additives could be an alternative to antibiotics in poultry farming, with the added benefit of counteracting antimicrobial resistance development.

Genotypic and phenotypic diversity among Komagataella species reveals a hidden pathway for xylose utilization.

BACKGROUND: The yeast genus Komagataella currently consists of seven methylotrophic species isolated from tree environments. Well-characterized strains of K. phaffii and K. pastoris are important hosts for biotechnological applications, but the potential of other species from the genus remains largely unexplored. In this study, we characterized 25 natural isolates from all seven described Komagataella species to identify interesting traits and provide a comprehensive overview of the genotypic and phenotypic diversity available within this genus. RESULTS: Growth tests on different carbon sources and in the presence of stressors at two different temperatures allowed us to identify strains with differences in tolerance to high pH, high temperature, and growth on xylose. As Komagataella species are generally not considered xylose-utilizing yeasts, xylose assimilation was characterized in detail. Growth assays, enzyme activity measurements and 13C labeling confirmed the ability of K. phaffii to utilize D-xylose via the oxidoreductase pathway. In addition, we performed long-read whole-genome sequencing to generate genome assemblies of all Komagataella species type strains and additional K. phaffii and K. pastoris isolates for comparative analysis. All sequenced genomes have a similar size and share 83-99% average sequence identity. Genome structure analysis showed that K. pastoris and K. ulmi share the same rearrangements in difference to K. phaffii, while the genome structure of K. kurtzmanii is similar to K. phaffii. The genomes of the other, more distant species showed a larger number of structural differences. Moreover, we used the newly assembled genomes to identify putative orthologs of important xylose-related genes in the different Komagataella species. CONCLUSIONS: By characterizing the phenotypes of 25 natural Komagataella isolates, we could identify strains with improved growth on different relevant carbon sources and stress conditions. Our data on the phenotypic and genotypic diversity will provide the basis for the use of so-far neglected Komagataella strains with interesting characteristics and the elucidation of the genetic determinants of improved growth and stress tolerance for targeted strain improvement.

Prediction of NB-LRR resistance genes based on full-length sequence homology.

The activation of plant immunity is mediated by resistance (R)-gene receptors, also known as nucleotide-binding leucine-rich repeat (NB-LRR) genes, which in turn trigger the authentic defense response. R-gene identification is a crucial goal for both classic and modern plant breeding strategies for disease resistance. The conventional method identifies NB-LRR genes using a protein motif/domain-based search (PDS) within an automatically predicted gene set of the respective genome assembly. PDS proved to be imprecise since repeat masking prior to automatic genome annotation unwittingly prevented comprehensive NB-LRR gene detection. Furthermore, R-genes have diversified in a species-specific manner, so that NB-LRR gene identification cannot be universally standardized. Here, we present the full-length Homology-based R-gene Prediction (HRP) method for the comprehensive identification and annotation of a genome's R-gene repertoire. Our method has substantially addressed the complex genomic organization of tomato (Solanum lycopersicum) NB-LRR gene loci, proving to be more performant than the well-established RenSeq approach. HRP efficiency was also tested on three differently assembled and annotated Beta sp. genomes. Indeed, HRP identified up to 45% more full-length NB-LRR genes compared to previous approaches. HRP also turned out to be a more refined strategy for R-gene allele mining, testified by the identification of hitherto undiscovered Fom-2 homologs in five Cucurbita sp. genomes. In summary, our high-performance method for full-length NB-LRR gene discovery will propel the identification of novel R-genes towards development of improved cultivars.

Genomic distances reveal relationships of wild and cultivated beets.

Cultivated beets (Beta vulgaris ssp. vulgaris), including sugar beet, rank among the most important crops. The wild ancestor of beet crops is the sea beet Beta vulgaris ssp. maritima. Species and subspecies of wild beets are readily crossable with cultivated beets and are thus available for crop improvement. To study genomic relationships in the genus Beta, we sequence and analyse 606 beet genomes, encompassing sugar beet, sea beet, B. v. adanensis, B. macrocarpa, and B. patula. We observe two genetically distinct groups of sea beets, one from the Atlantic coast and the other from the Mediterranean area. Genomic comparisons based on k-mers identify sea beets from Greece as the closest wild relatives of sugar beet, suggesting that domestication of the ancestors of sugar beet may be traced to this area. Our work provides comprehensive insight into the phylogeny of wild and cultivated beets and establishes a framework for classification of further accessions of unknown (sub-)species assignment.

Quinoa genome assembly employing genomic variation for guided scaffolding.

KEY MESSAGE: We propose to use the natural variation between individuals of a population for genome assembly scaffolding. In today's genome projects, multiple accessions get sequenced, leading to variant catalogs. Using such information to improve genome assemblies is attractive both cost-wise as well as scientifically, because the value of an assembly increases with its contiguity. We conclude that haplotype information is a valuable resource to group and order contigs toward the generation of pseudomolecules. Quinoa (Chenopodium quinoa) has been under cultivation in Latin America for more than 7500 years. Recently, quinoa has gained increasing attention due to its stress resistance and its nutritional value. We generated a novel quinoa genome assembly for the Bolivian accession CHEN125 using PacBio long-read sequencing data (assembly size 1.32 Gbp, initial N50 size 608 kbp). Next, we re-sequenced 50 quinoa accessions from Peru and Bolivia. This set of accessions differed at 4.4 million single-nucleotide variant (SNV) positions compared to CHEN125 (1.4 million SNV positions on average per accession). We show how to exploit variation in accessions that are distantly related to establish a genome-wide ordered set of contigs for guided scaffolding of a reference assembly. The method is based on detecting shared haplotypes and their expected continuity throughout the genome (i.e., the effect of linkage disequilibrium), as an extension of what is expected in mapping populations where only a few haplotypes are present. We test the approach using Arabidopsis thaliana data from different populations. After applying the method on our CHEN125 quinoa assembly we validated the results with mate-pairs, genetic markers, and another quinoa assembly originating from a Chilean cultivar. We show consistency between these information sources and the haplotype-based relations as determined by us and obtain an improved assembly with an N50 size of 1079 kbp and ordered contig groups of up to 39.7 Mbp. We conclude that haplotype information in distantly related individuals of the same species is a valuable resource to group and order contigs according to their adjacency in the genome toward the generation of pseudomolecules.

Assembly and characterization of the genome of chard (Beta vulgaris ssp. vulgaris var. cicla).

Chard (Beta vulgaris ssp. vulgaris var. cicla) is a member of one of four different cultigroups of beets. While the genome of sugar beet, the most prominent beet crop, has been studied extensively, molecular data on other beet cultivars is scant. Here, we present a genome assembly of chard, a vegetable crop grown for its fleshy leaves. We report a de novo genome assembly of 604 Mbp, slightly larger than sugar beet assemblies presented so far. About 57 % of the assembly was annotated as repetitive sequence, of which LTR retrotransposons were the most abundant. Based on the presence of conserved genes, the chard assembly was estimated to be at least 96 % complete regarding its gene space. We predicted 34,521 genes of which 27,582 genes were supported by evidence from transcriptomic sequencing reads, and 5503 of the evidence-supported genes had multiple isoforms. We compared the chard gene set with gene sets from sugar beet and two wild beets (i.e. Beta vulgaris ssp. maritima and Beta patula) to find orthology relationships and identified genome-wide syntenic regions between chard and sugar beet. Lastly, we determined genomic variants that distinguish sugar beet and chard. Assessing the variation distribution along the chard chromosomes, we found extensive haplotype sharing between the two cultivars. In summary, our work provides a foundation for the molecular analysis of Beta vulgaris cultigroups as a basis for chard genomics and to unravel the domestication history of beet crops.

Subgenome evolution in allotetraploid plants.

Polyploidization is a well-known speciation and adaptation mechanism. Traces of former polyploidization events were discovered within many genomes, and especially in plants. Allopolyploidization by interspecific hybridization between two species is common. Among hybrid plants, many are domesticated species of agricultural interest and many of their genomes and of their presumptive parents have been sequenced. Hybrid genomes remain challenging to analyse because of the presence of multiple subgenomes. The genomes of hybrids often undergo rearrangement and degradation over time. Based on 10 hybrid plant genomes from six different genera, with hybridization dating from 10,000 to 5 million years ago, we assessed subgenome degradation, subgenomic intermixing and biased subgenome fractionation. The restructuring of hybrid genomes does not proceed proportionally with the age of the hybrid. The oldest hybrids in our data set display completely different fates: whereas the subgenomes of the tobacco plant Nicotiana benthamiana are in an advanced stage of degradation, the subgenomes of quinoa (Chenopodium quinoa) are exceptionally well conserved by structure and sequence. We observed statistically significant biased subgenome fractionation in seven out of 10 hybrids, which had different ages and subgenomic intermixing levels. Hence, we conclude that no correlation exists between biased fractionation and subgenome intermixing. Lastly, domestication may encourage or hinder subgenome intermixing, depending on the evolutionary context. In summary, comparative analysis of hybrid genomes and their presumptive parents allowed us to determine commonalities and differences between their evolutionary fates. In order to facilitate the future analysis of further hybrid genomes, we automated the analysis steps within manticore, which is publicly available at https://github.com/MatteoSchiavinato/manticore.git.

Adaptive Evolution in Producing Microtiter Cultivations Generates Genetically Stable Escherichia coli Production Hosts for Continuous Bioprocessing.

The production of recombinant proteins usually reduces cell fitness and the growth rate of producing cells. The growth disadvantage favors faster-growing non-producer mutants. Therefore, continuous bioprocessing is hardly feasible in Escherichia coli due to the high escape rate. The stability of E. coli expression systems under long-term production conditions and how metabolic load triggered by recombinant gene expression influences the characteristics of mutations are investigated. Iterated fed-batch-like microbioreactor cultivations are conducted under production conditions. The easy-to-produce green fluorescent protein (GFP) and a challenging antigen-binding fragment (Fab) are used as model proteins, and BL21(DE3) and BL21Q strains as expression hosts. In comparative whole-genome sequencing analyses, mutations that allowed cells to grow unhindered despite recombinant protein production are identified. A T7 RNA polymerase expression system is only conditionally suitable for long-term cultivation under production conditions. Mutations leading to non-producers occur in either the T7 RNA polymerase gene or the T7 promoter. The host RNA polymerase-based BL21Q expression system remains stable in the production of GFP in long-term cultivations. For the production of Fab, mutations in lacI of the BL21Q derivatives have positive effects on long-term stability. The results indicate that adaptive evolution carried out with genome-integrated E. coli expression systems in microtiter cultivations under industrial-relevant production conditions is an efficient strain development tool for production hosts.

Comparative genome characterization of the periodontal pathogen Tannerella forsythia.

BACKGROUND: Tannerella forsythia is a bacterial pathogen implicated in periodontal disease. Numerous virulence-associated T. forsythia genes have been described, however, it is necessary to expand the knowledge on T. forsythia's genome structure and genetic repertoire to further elucidate its role within pathogenesis. Tannerella sp. BU063, a putative periodontal health-associated sister taxon and closest known relative to T. forsythia is available for comparative analyses. In the past, strain confusion involving the T. forsythia reference type strain ATCC 43037 led to discrepancies between results obtained from in silico analyses and wet-lab experimentation. RESULTS: We generated a substantially improved genome assembly of T. forsythia ATCC 43037 covering 99% of the genome in three sequences. Using annotated genomes of ten Tannerella strains we established a soft core genome encompassing 2108 genes, based on orthologs present in > = 80% of the strains analysed. We used a set of known and hypothetical virulence factors for comparisons in pathogenic strains and the putative periodontal health-associated isolate Tannerella sp. BU063 to identify candidate genes promoting T. forsythia's pathogenesis. Searching for pathogenicity islands we detected 38 candidate regions in the T. forsythia genome. Only four of these regions corresponded to previously described pathogenicity islands. While the general protein O-glycosylation gene cluster of T. forsythia ATCC 43037 has been described previously, genes required for the initiation of glycan synthesis are yet to be discovered. We found six putative glycosylation loci which were only partially conserved in other bacteria. Lastly, we performed a comparative analysis of translational bias in T. forsythia and Tannerella sp. BU063 and detected highly biased genes. CONCLUSIONS: We provide resources and important information on the genomes of Tannerella strains. Comparative analyses enabled us to assess the suitability of T. forsythia virulence factors as therapeutic targets and to suggest novel putative virulence factors. Further, we report on gene loci that should be addressed in the context of elucidating T. forsythia's protein O-glycosylation pathway. In summary, our work paves the way for further molecular dissection of T. forsythia biology in general and virulence of this species in particular.

Parental origin of the allotetraploid tobacco Nicotiana benthamiana.

Nicotiana section Suaveolentes is an almost all-Australian clade of allopolyploid tobacco species including the important plant model Nicotiana benthamiana. The homology relationships of this clade and its formation are not completely understood. To address this gap, we assessed phylogenies of all individual genes of N. benthamiana and the well studied N. tabacum (section Nicotiana) and their homologues in six diploid Nicotiana species. We generated sets of 44 424 and 65 457 phylogenetic trees of N. benthamiana and N. tabacum genes, respectively, each collectively called a phylome. Members of Nicotiana sections Noctiflorae and Sylvestres were represented as the species closest to N. benthamiana in most of the gene trees. Analyzing the gene trees of the phylome we: (i) dated the hybridization event giving rise to N. benthamiana to 4-5 MyA, and (ii) separated the subgenomes. We assigned 1.42 Gbp of the genome sequence to section Noctiflorae and 0.97 Gbp to section Sylvestres based on phylome analysis. In contrast, read mapping of the donor species did not succeed in separating the subgenomes of N. benthamiana. We show that the maternal progenitor of N. benthamiana was a member of section Noctiflorae, and confirm a member of section Sylvestres as paternal subgenome donor. We also demonstrate that the advanced stage of long-term genome diploidization in N. benthamiana is reflected in its subgenome organization. Taken together, our results underscore the usefulness of phylome analysis for subgenome characterization in hybrid species.

Benchmarking of long-read correction methods.

Third-generation sequencing technologies provided by Pacific Biosciences and Oxford Nanopore Technologies generate read lengths in the scale of kilobasepairs. However, these reads display high error rates, and correction steps are necessary to realize their great potential in genomics and transcriptomics. Here, we compare properties of PacBio and Nanopore data and assess correction methods by Canu, MARVEL and proovread in various combinations. We found total error rates of around 13% in the raw datasets. PacBio reads showed a high rate of insertions (around 8%) whereas Nanopore reads showed similar rates for substitutions, insertions and deletions of around 4% each. In data from both technologies the errors were uniformly distributed along reads apart from noisy 5' ends, and homopolymers appeared among the most over-represented kmers relative to a reference. Consensus correction using read overlaps reduced error rates to about 1% when using Canu or MARVEL after patching. The lowest error rate in Nanopore data (0.45%) was achieved by applying proovread on MARVEL-patched data including Illumina short-reads, and the lowest error rate in PacBio data (0.42%) was the result of Canu correction with minimap2 alignment after patching. Our study provides valuable insights and benchmarks regarding long-read data and correction methods.

Genome and transcriptome characterization of the glycoengineered Nicotiana benthamiana line ΔXT/FT.

BACKGROUND: The allotetraploid tobacco species Nicotiana benthamiana native to Australia has become a popular host for recombinant protein production. Although its usage grows every year, little is known on this plant's genomic and transcriptomic features. Most N. benthamiana accessions currently used in research lack proper documentation of their breeding history and provenance. One of these, the glycoengineered N. benthamiana line ΔXT/FT is increasingly used for the production of biopharmaceutical proteins. RESULTS: Based on an existing draft assembly of the N. benthamiana genome we predict 50,516 protein -encoding genes (62,216 transcripts) supported by expression data derived from 2.35 billion mRNA-seq reads. Using single-copy core genes we show high completeness of the predicted gene set. We functionally annotate more than two thirds of the gene set through sequence homology to genes from other Nicotiana species. We demonstrate that the expression profiles from leaf tissue of ΔXT/FT and its wild type progenitor only show minimal differences. We identify the transgene insertion sites in ΔXT/FT and show that one of the transgenes was inserted inside another predicted gene that most likely lost its function upon insertion. Based on publicly available mRNA-seq data, we confirm that the N. benthamiana accessions used by different research institutions most likely derive from a single source. CONCLUSIONS: This work provides gene annotation of the N. benthamiana genome, a genomic and transcriptomic characterization of a transgenic N. benthamiana line in comparison to its wild-type progenitor, and sheds light onto the relatedness of N. benthamiana accessions that are used in laboratories around the world.

Genomes of the wild beets Beta patula and Beta vulgaris ssp. maritima.

We present draft genome assemblies of Beta patula, a critically endangered wild beet endemic to the Madeira archipelago, and of the closely related Beta vulgaris ssp. maritima (sea beet). Evidence-based reference gene sets for B. patula and sea beet were generated, consisting of 25 127 and 27 662 genes, respectively. The genomes and gene sets of the two wild beets were compared with their cultivated sister taxon B. vulgaris ssp. vulgaris (sugar beet). Large syntenic regions were identified, and a display tool for automatic genome-wide synteny image generation was developed. Phylogenetic analysis based on 9861 genes showing 1:1:1 orthology supported the close relationship of B. patula to sea beet and sugar beet. A comparative analysis of the Rz2 locus, responsible for rhizomania resistance, suggested that the sequenced B. patula accession was rhizomania susceptible. Reference karyotypes for the two wild beets were established, and genomic rearrangements were detected. We consider our data as highly valuable and comprehensive resources for wild beet studies, B. patula conservation management, and sugar beet breeding research.