A pan-genome of 69 Arabidopsis thaliana accessions reveals a conserved genome structure throughout the global species range.

Although originally primarily a system for functional biology, Arabidopsis thaliana has, owing to its broad geographical distribution and adaptation to diverse environments, developed into a powerful model in population genomics. Here we present chromosome-level genome assemblies of 69 accessions from a global species range. We found that genomic colinearity is very conserved, even among geographically and genetically distant accessions. Along chromosome arms, megabase-scale rearrangements are rare and typically present only in a single accession. This indicates that the karyotype is quasi-fixed and that rearrangements in chromosome arms are counter-selected. Centromeric regions display higher structural dynamics, and divergences in core centromeres account for most of the genome size variations. Pan-genome analyses uncovered 32,986 distinct gene families, 60% being present in all accessions and 40% appearing to be dispensable, including 18% private to a single accession, indicating unexplored genic diversity. These 69 new Arabidopsis thaliana genome assemblies will empower future genetic research.

Corrigendum: Investigating genetic diversity within the most abundant and prevalent non-pathogenic leaf-associated bacteria interacting with Arabidopsis thaliana in natural habitats.

[This corrects the article DOI: 10.3389/fmicb.2022.984832.].

First whole genome assembly and annotation of a European common bean cultivar using PacBio HiFi and Iso-Seq data.

Common bean (Phaseolus vulgaris L.) is the most important grain legume for direct human consumption worldwide. Flageolet bean originates from France and presents typical organoleptic properties, including the remarkable feature of having small pale green colored seeds. Here, we report the whole-genome data, assembly and annotation of the flageolet bean accession 'Flavert'. High molecular weight DNA and RNA were extracted and subjected to long-read sequencing using PacBio Sequel II platform. The genome consisted of 566,238,753 bp assembled in 13 molecules, including 11 chromosomes plus the mitochondrial and chloroplastic genomes. Annotation predicted 29,549 protein coding genes and 6,958 non-coding RNA. This high-quality genome (99.2% BUSCO completeness) represents a valuable data set for further genomic and genetic studies on common bean and more generally on legumes. To our knowledge, this is the first whole-genome sequence of a common bean accession originating from Europe.

An atypical NLR gene confers bacterial wilt susceptibility in Arabidopsis.

Quantitative disease resistance (QDR) remains the most prevalent form of plant resistance in crop fields and wild habitats. Genome-wide association studies (GWAS) have proved to be successful in deciphering the quantitative genetic basis of complex traits such as QDR. To unravel the genetics of QDR to the devastating worldwide bacterial pathogen Ralstonia solanacearum, we performed a GWAS by challenging a highly polymorphic local mapping population of Arabidopsis thaliana with four R. solanacearum type III effector (T3E) mutants, identified as key pathogenicity determinants after a first screen on an A. thaliana core collection of 25 accessions. Although most quantitative trait loci (QTLs) were highly specific to the identity of the T3E mutant (ripAC, ripAG, ripAQ, and ripU), we finely mapped a common QTL located on a cluster of nucleotide-binding domain and leucine-rich repeat (NLR) genes that exhibited structural variation. We functionally validated one of these NLRs as a susceptibility factor in response to R. solanacearum, named it Bacterial Wilt Susceptibility 1 (BWS1), and cloned two alleles that conferred contrasting levels of QDR. Further characterization indicated that expression of BWS1 leads to suppression of immunity triggered by different R. solanacearum effectors. In addition, we showed a direct interaction between BWS1 and RipAC T3E, and BWS1 and SUPPRESSOR OF G2 ALLELE OF skp1 (SGT1b), the latter interaction being suppressed by RipAC. Together, our results highlight a putative role for BWS1 as a quantitative susceptibility factor directly targeted by the T3E RipAC, mediating negative regulation of the SGT1-dependent immune response.

The genomics of linkage drag in inbred lines of sunflower.

Crop wild relatives represent valuable sources of alleles for crop improvement, including adaptation to climate change and emerging diseases. However, introgressions from wild relatives might have deleterious effects on desirable traits, including yield, due to linkage drag. Here, we analyzed the genomic and phenotypic impacts of wild introgressions in inbred lines of cultivated sunflower to estimate the impacts of linkage drag. First, we generated reference sequences for seven cultivated and one wild sunflower genotype, as well as improved assemblies for two additional cultivars. Next, relying on previously generated sequences from wild donor species, we identified introgressions in the cultivated reference sequences, as well as the sequence and structural variants they contain. We then used a ridge-regression best linear unbiased prediction (BLUP) model to test the effects of the introgressions on phenotypic traits in the cultivated sunflower association mapping population. We found that introgression has introduced substantial sequence and structural variation into the cultivated sunflower gene pool, including >3,000 new genes. While introgressions reduced genetic load at protein-coding sequences, they mostly had negative impacts on yield and quality traits. Introgressions found at high frequency in the cultivated gene pool had larger effects than low-frequency introgressions, suggesting that the former likely were targeted by artificial selection. Also, introgressions from more distantly related species were more likely to be maladaptive than those from the wild progenitor of cultivated sunflower. Thus, breeding efforts should focus, as far as possible, on closely related and fully compatible wild relatives.

Investigating genetic diversity within the most abundant and prevalent non-pathogenic leaf-associated bacteria interacting with Arabidopsis thaliana in natural habitats.

Microbiota modulates plant health and appears as a promising lever to develop innovative, sustainable and eco-friendly agro-ecosystems. Key patterns of microbiota assemblages in plants have been revealed by an extensive number of studies based on taxonomic profiling by metabarcoding. However, understanding the functionality of microbiota is still in its infancy and relies on reductionist approaches primarily based on the establishment of representative microbial collections. In Arabidopsis thaliana, most of these microbial collections include one strain per OTU isolated from a limited number of habitats, thereby neglecting the ecological potential of genetic diversity within microbial species. With this study, we aimed at estimating the extent of genetic variation between strains within the most abundant and prevalent leaf-associated non-pathogenic bacterial species in A. thaliana located south-west of France. By combining a culture-based collection approach consisting of the isolation of more than 7,000 bacterial colonies with an informative-driven approach, we isolated 35 pure strains from eight non-pathogenic bacterial species. We detected significant intra-specific genetic variation at the genomic level and for growth rate in synthetic media. In addition, significant host genetic variation was detected in response to most bacterial strains in in vitro conditions, albeit dependent on the developmental stage at which plants were inoculated, with the presence of both negative and positive responses on plant growth. Our study provides new genetic and genomic resources for a better understanding of the plant-microbe ecological interactions at the microbiota level. We also highlight the need of considering genetic variation in both non-pathogenic bacterial species and A. thaliana to decipher the genetic and molecular mechanisms involved in the ecologically relevant dialog between hosts and leaf microbiota.

Low-Input High-Molecular-Weight DNA Extraction for Long-Read Sequencing From Plants of Diverse Families.

Long-read DNA sequencing technologies require high molecular weight (HMW) DNA of adequate purity and integrity, which can be difficult to isolate from plant material. Plant leaves usually contain high levels of carbohydrates and secondary metabolites that can impact DNA purity, affecting downstream applications. Several protocols and kits are available for HMW DNA extraction, but they usually require a high amount of input material and often lead to substantial DNA fragmentation, making sequencing suboptimal in terms of read length and data yield. We here describe a protocol for plant HMW DNA extraction from low input material (0.1 g) which is easy to follow and quick (2.5 h). This method successfully enabled us to extract HMW from four species from different families (Orchidaceae, Poaceae, Brassicaceae, Asteraceae). In the case of recalcitrant species, we show that an additional purification step is sufficient to deliver a clean DNA sample. We demonstrate the suitability of our protocol for long-read sequencing on the Oxford Nanopore Technologies PromethION® platform, with and without the use of a short fragment depletion kit.

APOK3, a pollen killer antidote in Arabidopsis thaliana.

The principles of heredity state that the two alleles carried by a heterozygote are equally transmitted to the progeny. However, genomic regions that escape this rule have been reported in many organisms. It is notably the case of genetic loci referred to as gamete killers, where one allele enhances its transmission by causing the death of the gametes that do not carry it. Gamete killers are of great interest, particularly to understand mechanisms of evolution and speciation. Although being common in plants, only a few, all in rice, have so far been deciphered to the causal genes. Here, we studied a pollen killer found in hybrids between two accessions of Arabidopsis thaliana. Exploring natural variation, we observed this pollen killer in many crosses within the species. Genetic analyses revealed that three genetically linked elements are necessary for pollen killer activity. Using mutants, we showed that this pollen killer works according to a poison-antidote model, where the poison kills pollen grains not producing the antidote. We identified the gene encoding the antidote, a chimeric protein addressed to mitochondria. De novo genomic sequencing in 12 natural variants with different behaviors regarding the pollen killer revealed a hyper variable locus, with important structural variations particularly in killer genotypes, where the antidote gene recently underwent duplications. Our results strongly suggest that the gene has newly evolved within A. thaliana. Finally, we identified in the protein sequence polymorphisms related to its antidote activity.

Adaptation to Plant Communities across the Genome of Arabidopsis thaliana.

Despite the importance of plant-plant interactions on plant community dynamics and crop yield, our understanding of the adaptive genetics underlying these interactions is still limited and deserves to be investigated in the context of complex and diffuse interactions occurring in plant assemblages. Here, based on 145 natural populations of Arabidopsis thaliana located in south-west of France and characterized for plant communities, we conducted a Genome-Environment Association analysis to finely map adaptive genomic regions of A. thaliana associated with plant community descriptors. To control for correlated abiotic environment effects, we also characterized the populations for a set of biologically meaningful climate and soil variables. A nonnegligible fraction of top single nucleotide polymorphisms was associated with both plant community descriptors and abiotic variables, highlighting the importance of considering the actual abiotic drivers of plant communities to disentangle genetic variants for biotic adaptation from genetic variants for abiotic adaptation. The adaptive loci associated with species abundance were highly dependent on the identity of the neighboring species suggesting a high degree of biotic specialization of A. thaliana to members of its plant interaction network. Moreover, the identification of adaptive loci associated with α-diversity and composition of plant communities supports the ability of A. thaliana to interact simultaneously with multiple plant neighbors, which in turn can help to understand the role of community-wide selection. Altogether, our study highlights that dissecting the genetic basis underlying plant-plant interactions at a regional scale while controlling for abiotic confounding factors can help understanding the adaptive mechanisms modulating natural plant assemblages.

Whole-genome landscape of Medicago truncatula symbiotic genes.

Advances in deciphering the functional architecture of eukaryotic genomes have been facilitated by recent breakthroughs in sequencing technologies, enabling a more comprehensive representation of genes and repeat elements in genome sequence assemblies, as well as more sensitive and tissue-specific analyses of gene expression. Here we show that PacBio sequencing has led to a substantially improved genome assembly of Medicago truncatula A17, a legume model species notable for endosymbiosis studies1, and has enabled the identification of genome rearrangements between genotypes at a near-base-pair resolution. Annotation of the new M. truncatula genome sequence has allowed for a thorough analysis of transposable elements and their dynamics, as well as the identification of new players involved in symbiotic nodule development, in particular 1,037 upregulated long non-coding RNAs (lncRNAs). We have also discovered that a substantial proportion (~35% and 38%, respectively) of the genes upregulated in nodules or expressed in the nodule differentiation zone colocalize in genomic clusters (270 and 211, respectively), here termed symbiotic islands. These islands contain numerous expressed lncRNA genes and display differentially both DNA methylation and histone marks. Epigenetic regulations and lncRNAs are therefore attractive candidate elements for the orchestration of symbiotic gene expression in the M. truncatula genome.

In situ relationships between microbiota and potential pathobiota in Arabidopsis thaliana.

A current challenge in microbial pathogenesis is to identify biological control agents that may prevent and/or limit host invasion by microbial pathogens. In natura, hosts are often infected by multiple pathogens. However, most of the current studies have been performed under laboratory controlled conditions and by taking into account the interaction between a single commensal species and a single pathogenic species. The next step is therefore to explore the relationships between host-microbial communities (microbiota) and microbial members with potential pathogenic behavior (pathobiota) in a realistic ecological context. In the present study, we investigated such relationships within root-associated and leaf-associated bacterial communities of 163 ecologically contrasted Arabidopsis thaliana populations sampled across two seasons in southwest of France. In agreement with the theory of the invasion paradox, we observed a significant humped-back relationship between microbiota and pathobiota α-diversity that was robust between both seasons and plant organs. In most populations, we also observed a strong dynamics of microbiota composition between seasons. Accordingly, the potential pathobiota composition was explained by combinations of season-specific microbiota operational taxonomic units. This result suggests that the potential biomarkers controlling pathogen's invasion are highly dynamic.

The sunflower genome provides insights into oil metabolism, flowering and Asterid evolution.

The domesticated sunflower, Helianthus annuus L., is a global oil crop that has promise for climate change adaptation, because it can maintain stable yields across a wide variety of environmental conditions, including drought. Even greater resilience is achievable through the mining of resistance alleles from compatible wild sunflower relatives, including numerous extremophile species. Here we report a high-quality reference for the sunflower genome (3.6 gigabases), together with extensive transcriptomic data from vegetative and floral organs. The genome mostly consists of highly similar, related sequences and required single-molecule real-time sequencing technologies for successful assembly. Genome analyses enabled the reconstruction of the evolutionary history of the Asterids, further establishing the existence of a whole-genome triplication at the base of the Asterids II clade and a sunflower-specific whole-genome duplication around 29 million years ago. An integrative approach combining quantitative genetics, expression and diversity data permitted development of comprehensive gene networks for two major breeding traits, flowering time and oil metabolism, and revealed new candidate genes in these networks. We found that the genomic architecture of flowering time has been shaped by the most recent whole-genome duplication, which suggests that ancient paralogues can remain in the same regulatory networks for dozens of millions of years. This genome represents a cornerstone for future research programs aiming to exploit genetic diversity to improve biotic and abiotic stress resistance and oil production, while also considering agricultural constraints and human nutritional needs.

Genetic control of plasticity of oil yield for combined abiotic stresses using a joint approach of crop modelling and genome-wide association.

Understanding the genetic basis of phenotypic plasticity is crucial for predicting and managing climate change effects on wild plants and crops. Here, we combined crop modelling and quantitative genetics to study the genetic control of oil yield plasticity for multiple abiotic stresses in sunflower. First, we developed stress indicators to characterize 14 environments for three abiotic stresses (cold, drought and nitrogen) using the SUNFLO crop model and phenotypic variations of three commercial varieties. The computed plant stress indicators better explain yield variation than descriptors at the climatic or crop levels. In those environments, we observed oil yield of 317 sunflower hybrids and regressed it with three selected stress indicators. The slopes of cold stress norm reaction were used as plasticity phenotypes in the following genome-wide association study. Among the 65 534 tested Single Nucleotide Polymorphisms (SNPs), we identified nine quantitative trait loci controlling oil yield plasticity to cold stress. Associated single nucleotide polymorphisms are localized in genes previously shown to be involved in cold stress responses: oligopeptide transporters, lipid transfer protein, cystatin, alternative oxidase or root development. This novel approach opens new perspectives to identify genomic regions involved in genotype-by-environment interaction of a complex traits to multiple stresses in realistic natural or agronomical conditions.

Extraction of high-molecular-weight genomic DNA for long-read sequencing of single molecules.

De novo sequencing of complex genomes is one of the main challenges for researchers seeking high-quality reference sequences. Many de novo assemblies are based on short reads, producing fragmented genome sequences. Third-generation sequencing, with read lengths >10 kb, will improve the assembly of complex genomes, but these techniques require high-molecular-weight genomic DNA (gDNA), and gDNA extraction protocols used for obtaining smaller fragments for short-read sequencing are not suitable for this purpose. Methods of preparing gDNA for bacterial artificial chromosome (BAC) libraries could be adapted, but these approaches are time-consuming, and commercial kits for these methods are expensive. Here, we present a protocol for rapid, inexpensive extraction of high-molecular-weight gDNA from bacteria, plants, and animals. Our technique was validated using sunflower leaf samples, producing a mean read length of 12.6 kb and a maximum read length of 80 kb.

A biomarker based on gene expression indicates plant water status in controlled and natural environments.

Plant or soil water status is required in many scientific fields to understand plant responses to drought. Because the transcriptomic response to abiotic conditions, such as water deficit, reflects plant water status, genomic tools could be used to develop a new type of molecular biomarker. Using the sunflower (Helianthus annuus L.) as a model species to study the transcriptomic response to water deficit both in greenhouse and field conditions, we specifically identified three genes that showed an expression pattern highly correlated to plant water status as estimated by the pre-dawn leaf water potential, fraction of transpirable soil water, soil water content or fraction of total soil water in controlled conditions. We developed a generalized linear model to estimate these classical water status indicators from the expression levels of the three selected genes under controlled conditions. This estimation was independent of the four tested genotypes and the stage (pre- or post-flowering) of the plant. We further validated this gene expression biomarker under field conditions for four genotypes in three different trials, over a large range of water status, and we were able to correct their expression values for a large diurnal sampling period.