The pattern of polymorphism in Arabidopsis thaliana

Transcriptome-referenced association study provides insights into the regulation of oil and fatty acid biosynthesis in Torreya grandis kernel

INTRODUCTION

Torreya grandis is a gymnosperm belonging to Taxodiaceae. As an economically important tree, its kernels are edible and rich in oil with high unsaturated fatty acids, such as sciadonic acid. However, the kernels from different T. grandis landraces exhibit fatty acid and oil content variations.

OBJECTIVES

As a gymnosperm, does T. grandis have special regulation mechanisms for oil biosynthesis? The aim of this study was to dissect the genetic architecture of fatty acid and oil content and the underlying mechanism in T. grandis.

METHODS

We constructed a high integrity reference sequence of expressed regions of the genome in T. grandis and performed transcriptome-referenced association study (TRAS) for 10 fatty acid and oil traits of kernels in the 170 diverse T. grandis landraces. To confirm the TRAS result, we performed functional validation and molecular biology experiments for oil significantly associated genes.

RESULTS

We identified 41 SNPs from 34 transcripts significantly associated with 7 traits by TRAS (-log10 (P) greater than 6.0). Results showed that LOB domain-containing protein 40 (LBD40) and surfeit locus protein 1 (SURF1) may be indirectly involved in the regulation of oil and sciadonic acid biosynthesis, respectively. Moreover, overexpression of TgLBD40 significantly increased seed oil content. The nonsynonymous variant in the TgLBD40 coding region discovered by TRAS could alter the oil content in plants. Pearson's correlation analysis and dual-luciferase assay indicated that TgLBD40 positively enhanced oil accumulation by affecting oil biosynthesis pathway genes, such as TgDGAT1.

CONCLUSION

Our study provides new insights into the genetic basis of oil biosynthesis in T. grandis and demonstrates that integrating RNA sequencing and TRAS is a powerful strategy to perform association study independent of a reference genome for dissecting important traits in T. grandis.

Previously unmeasured genetic diversity explains part of Lewontin's paradox in a k-mer-based meta-analysis of 112 plant species

At the molecular level, most evolution is expected to be neutral. A key prediction of this expectation is that the level of genetic diversity in a population should scale with population size. However, as was noted by Richard Lewontin in 1974 and reaffirmed by later studies, the slope of the population size-diversity relationship in nature is much weaker than expected under neutral theory. We hypothesize that one contributor to this paradox is that current methods relying on single nucleotide polymorphisms (SNPs) called from aligning short reads to a reference genome underestimate levels of genetic diversity in many species. To test this idea, we calculated nucleotide diversity ( π ) and k-mer-based metrics of genetic diversity across 112 plant species, amounting to over 205 terabases of DNA sequencing data from 27,488 individual plants. We then compared how these different metrics correlated with proxies of population size that account for both range size and population density variation across species. We found that our population size proxies scaled anywhere from about 3 to over 20 times faster with k-mer diversity than nucleotide diversity after adjusting for evolutionary history, mating system, life cycle habit, cultivation status, and invasiveness. The relationship between k-mer diversity and population size proxies also remains significant after correcting for genome size, whereas the analogous relationship for nucleotide diversity does not. These results suggest that variation not captured by common SNP-based analyses explains part of Lewontin's paradox in plants.

High allelic diversity in Arabidopsis NLRs is associated with distinct genomic features

Plants rely on Nucleotide-binding, Leucine-rich repeat Receptors (NLRs) for pathogen recognition. Highly variable NLRs (hvNLRs) show remarkable intraspecies diversity, while their low-variability paralogs (non-hvNLRs) are conserved between ecotypes. At a population level, hvNLRs provide new pathogen-recognition specificities, but the association between allelic diversity and genomic and epigenomic features has not been established. Our investigation of NLRs in Arabidopsis Col-0 has revealed that hvNLRs show higher expression, less gene body cytosine methylation, and closer proximity to transposable elements than non-hvNLRs. hvNLRs show elevated synonymous and nonsynonymous nucleotide diversity and are in chromatin states associated with an increased probability of mutation. Diversifying selection maintains variability at a subset of codons of hvNLRs, while purifying selection maintains conservation at non-hvNLRs. How these features are established and maintained, and whether they contribute to the observed diversity of hvNLRs is key to understanding the evolution of plant innate immune receptors.

Genetic adaptations in the population history of Arabidopsis thaliana

A population encounters a variety of environmental stresses, so the full source of its resilience can only be captured by collecting all the signatures of adaptation to the selection of the local environment in its population history. Based on the multiomic data of Arabidopsis thaliana, we constructed a database of phenotypic adaptations (p-adaptations) and gene expression (e-adaptations) adaptations in the population. Through the enrichment analysis of the identified adaptations, we inferred a likely scenario of adaptation that is consistent with the biological evidence from experimental work. We analyzed the dynamics of the allele frequencies at the 23,880 QTLs of 174 traits and 8,618 eQTLs of 1,829 genes with respect to the total SNPs in the genomes and identified 650 p-adaptations and 3,925 e-adaptations [false discovery rate (FDR) = 0.05]. The population underwent large-scale p-adaptations and e-adaptations along 4 lineages. Extremely cold winters and short summers prolonged seed dormancy and expanded the root system architecture. Low temperatures prolonged the growing season, and low light intensity required the increased chloroplast activity. The subtropical and humid environment enhanced phytohormone signaling pathways in response to the biotic and abiotic stresses. Exposure to heavy metals selected alleles for lower heavy metal uptake from soil, lower growth rate, lower resistance to bacteria, and higher expression of photosynthetic genes were selected. The p-adaptations are directly interpretable, while the coadapted gene expressions reflect the physiological requirements for the adaptation. The integration of this information characterizes when and where the population has experienced environmental stress and how the population responded at the molecular level.

Metabolome plasticity in 241 Arabidopsis thaliana accessions reveals evolutionary cold adaptation processes

Acclimation and adaptation of metabolism to a changing environment are key processes for plant survival and reproductive success. In the present study, 241 natural accessions of Arabidopsis (Arabidopsis thaliana) were grown under two different temperature regimes, 16 °C and 6 °C, and growth parameters were recorded, together with metabolite profiles, to investigate the natural genome × environment effects on metabolome variation. The plasticity of metabolism, which was captured by metabolic distance measures, varied considerably between accessions. Both relative growth rates and metabolic distances were predictable by the underlying natural genetic variation of accessions. Applying machine learning methods, climatic variables of the original growth habitats were tested for their predictive power of natural metabolic variation among accessions. We found specifically habitat temperature during the first quarter of the year to be the best predictor of the plasticity of primary metabolism, indicating habitat temperature as the causal driver of evolutionary cold adaptation processes. Analyses of epigenome- and genome-wide associations revealed accession-specific differential DNA-methylation levels as potentially linked to the metabolome and identified FUMARASE2 as strongly associated with cold adaptation in Arabidopsis accessions. These findings were supported by calculations of the biochemical Jacobian matrix based on variance and covariance of metabolomics data, which revealed that growth under low temperatures most substantially affects the accession-specific plasticity of fumarate and sugar metabolism. Our findings indicate that the plasticity of metabolic regulation is predictable from the genome and epigenome and driven evolutionarily by Arabidopsis growth habitats.

A low-coverage 3' RNA-seq to detect homeolog expression in polyploid wheat

Although allopolyploid species are common among natural and crop species, it is not easy to distinguish duplicated genes, known as homeologs, during their genomic analysis. Yet, cost-efficient RNA sequencing (RNA-seq) is to be developed for large-scale transcriptomic studies such as time-series analysis and genome-wide association studies in allopolyploids. In this study, we employed a 3' RNA-seq utilizing 3' untranslated regions (UTRs) containing frequent mutations among homeologous genes, compared to coding sequence. Among the 3' RNA-seq protocols, we examined a low-cost method Lasy-Seq using an allohexaploid bread wheat, Triticum aestivum. HISAT2 showed the best performance for 3' RNA-seq with the least mapping errors and quick computational time. The number of detected homeologs was further improved by extending 1 kb of the 3' UTR annotation. Differentially expressed genes in response to mild cold treatment detected by the 3' RNA-seq were verified with high-coverage conventional RNA-seq, although the latter detected more differentially expressed genes. Finally, downsampling showed that even a 2 million sequencing depth can still detect more than half of expressed homeologs identifiable by the conventional 32 million reads. These data demonstrate that this low-cost 3' RNA-seq facilitates large-scale transcriptomic studies of allohexaploid wheat and indicate the potential application to other allopolyploid species.

Genomic diversity landscapes in outcrossing and selfing Caenorhabditis nematodes

Caenorhabditis nematodes form an excellent model for studying how the mode of reproduction affects genetic diversity, as some species reproduce via outcrossing whereas others can self-fertilize. Currently, chromosome-level patterns of diversity and recombination are only available for self-reproducing Caenorhabditis, making the generality of genomic patterns across the genus unclear given the profound potential influence of reproductive mode. Here we present a whole-genome diversity landscape, coupled with a new genetic map, for the outcrossing nematode C. remanei. We demonstrate that the genomic distribution of recombination in C. remanei, like the model nematode C. elegans, shows high recombination rates on chromosome arms and low rates toward the central regions. Patterns of genetic variation across the genome are also similar between these species, but differ dramatically in scale, being tenfold greater for C. remanei. Historical reconstructions of variation in effective population size over the past million generations echo this difference in polymorphism. Evolutionary simulations demonstrate how selection, recombination, mutation, and selfing shape variation along the genome, and that multiple drivers can produce patterns similar to those observed in natural populations. The results illustrate how genome organization and selection play a crucial role in shaping the genomic pattern of diversity whereas demographic processes scale the level of diversity across the genome as a whole.

Convergent evolution of plant pattern recognition receptors sensing cysteine-rich patterns from three microbial kingdoms

The Arabidopsis thaliana Receptor-Like Protein RLP30 contributes to immunity against the fungal pathogen Sclerotinia sclerotiorum. Here we identify the RLP30-ligand as a small cysteine-rich protein (SCP) that occurs in many fungi and oomycetes and is also recognized by the Nicotiana benthamiana RLP RE02. However, RLP30 and RE02 share little sequence similarity and respond to different parts of the native/folded protein. Moreover, some Brassicaceae other than Arabidopsis also respond to a linear SCP peptide instead of the folded protein, suggesting that SCP is an eminent immune target that led to the convergent evolution of distinct immune receptors in plants. Surprisingly, RLP30 shows a second ligand specificity for a SCP-nonhomologous protein secreted by bacterial Pseudomonads. RLP30 expression in N. tabacum results in quantitatively lower susceptibility to bacterial, fungal and oomycete pathogens, thus demonstrating that detection of immunogenic patterns by Arabidopsis RLP30 is involved in defense against pathogens from three microbial kingdoms.

Weaker selection on genes with treatment-specific expression consistent with a limit on plasticity evolution in Arabidopsis thaliana

Differential gene expression between environments often underlies phenotypic plasticity. However, environment-specific expression patterns are hypothesized to relax selection on genes, and thus limit plasticity evolution. We collated over 27 terabases of RNA-sequencing data on Arabidopsis thaliana from over 300 peer-reviewed studies and 200 treatment conditions to investigate this hypothesis. Consistent with relaxed selection, genes with more treatment-specific expression have higher levels of nucleotide diversity and divergence at nonsynonymous sites but lack stronger signals of positive selection. This result persisted even after controlling for expression level, gene length, GC content, the tissue specificity of expression, and technical variation between studies. Overall, our investigation supports the existence of a hypothesized trade-off between the environment specificity of a gene's expression and the strength of selection on said gene in A. thaliana. Future studies should leverage multiple genome-scale datasets to tease apart the contributions of many variables in limiting plasticity evolution.

Limitations and advantages of using metabolite-based genome-wide association studies: focus on fruit quality traits

In the last decades, linkage mapping has help in the location of metabolite quantitative trait loci (QTL) in many species; however, this approach shows some limitations. Recently, thanks to the most recent advanced in high-throughput genotyping technologies like next-generation sequencing, metabolite genome-wide association study (mGWAS) has been proposed a powerful tool to identify the genetic variants in polygenic agrinomic traits. Fruit flavor is a complex interaction of aroma volatiles and taste being sugar and acid ratio key parameter for flavor acceptance. Here, we review recent progress of mGWAS in pinpoint gene polymorphisms related to flavor-related metabolites in fruits. Despite clear successes in discovering novel genes or regions associated with metabolite accumulation affecting sensory attributes in fruits, GWAS incurs in several limitations summarized in this review. In addition, in our own work, we performed mGWAS on 194 Citrus grandis accessions to investigate the genetic control of individual primary and lipid metabolites in ripe fruit. We have identified a total of 667 associations for 14 primary metabolites including amino acids, sugars, and organic acids, and 768 associations corresponding to 47 lipids. Furthermore, candidate genes related to important metabolites related to fruit quality such as sugars, organic acids and lipids were discovered.

Genome-wide association study reveals WRKY42 as a novel plant transcription factor that influences oviposition preference of Pieris butterflies

Insect herbivores are amongst the most destructive plant pests, damaging both naturally occurring and domesticated plants. As sessile organisms, plants make use of structural and chemical barriers to counteract herbivores. However, over 75% of herbivorous insect species are well adapted to their host's defenses and these specialists are generally difficult to ward off. By actively antagonizing the number of insect eggs deposited on plants, future damage by the herbivore's offspring can be limited. Therefore, it is important to understand which plant traits influence attractiveness for oviposition, especially for specialist insects that are well adapted to their host plants. In this study, we investigated the oviposition preference of Pieris butterflies (Lepidoptera: Pieridae) by offering them the choice between 350 different naturally occurring Arabidopsis accessions. Using a genome-wide association study of the oviposition data and subsequent fine mapping with full genome sequences of 164 accessions, we identified WRKY42 and AOC1 as candidate genes that are associated with the oviposition preference observed for Pieris butterflies. Host plant choice assays with Arabidopsis genotypes impaired in WRKY42 or AOC1 function confirmed a clear role for WRKY42 in oviposition preference of female Pieris butterflies, while for AOC1 the effect was mild. In contrast, WRKY42-impaired plants, which were preferred for oviposition by butterflies, negatively impacted offspring performance. These findings exemplify that plant genotype can have opposite effects on oviposition preference and caterpillar performance. This knowledge can be used for breeding trap crops or crops that are unattractive for oviposition by pest insects.

Fine mapping of meiotic crossovers in Brassica oleracea reveals patterns and variations depending on direction and combination of crosses

Meiotic recombination is crucial for assuring proper segregation of parental chromosomes and generation of novel allelic combinations. As this process is tightly regulated, identifying factors influencing rate, and distribution of meiotic crossovers (COs) is of major importance, notably for plant breeding programs. However, high-resolution recombination maps are sparse in most crops including the Brassica genus and knowledge about intraspecific variation and sex differences is lacking. Here, we report fine-scale resolution recombination landscapes for 10 female and 10 male crosses in Brassica oleracea, by analyzing progenies of five large four-way-cross populations from two reciprocally crossed F1s per population. Parents are highly diverse inbred lines representing major crops, including broccoli, cauliflower, cabbage, kohlrabi, and kale. We produced approximately 4.56T Illumina data from 1248 progenies and identified 15 353 CO across the 10 reciprocal crosses, 51.13% of which being mapped to <10 kb. We revealed fairly similar Mb-scale recombination landscapes among all cross combinations and between the sexes, and provided evidence that these landscapes are largely independent of sequence divergence. We evidenced strong influence of gene density and large structural variations on CO formation in B. oleracea. Moreover, we found extensive variations in CO number depending on the direction and combination of the initial parents crossed with, for the first time, a striking interdependency between these factors. These data improve our current knowledge on meiotic recombination and are important for Brassica breeders.

Single nucleotide polymorphism (SNP) markers for genetic diversity and population structure study in Ethiopian barley (Hordeum vulgare L.) germplasm

BACKGROUND

High-density single nucleotide polymorphisms (SNPs) are the most abundant and robust form of genetic variants and hence make highly favorable markers to determine the genetic diversity and relationship, enhancing the selection of breeding materials and the discovery of novel genes associated with economically important traits. In this study, a total of 105 barley genotypes were sampled from various agro-ecologies of Ethiopia and genotyped using 10 K single nucleotide polymorphism (SNP) markers. The refined dataset was used to assess genetic diversity and population structure.

RESULTS

The average gene diversity was 0.253, polymorphism information content (PIC) of 0.216, and minor allelic frequency (MAF) of 0.118 this revealed a high genetic variation in barley genotypes. The genetic differentiation also showed the existence of variations, ranging from 0.019 to 0.117, indicating moderate genetic differentiation between barley populations. Analysis of molecular variance (AMOVA) revealed that 46.43% and 52.85% of the total genetic variation occurred within the accessions and populations, respectively. The heat map, principal components and population structure analysis further confirm the presence of four distinct clusters.

CONCLUSIONS

This study confirmed that there is substantial genetic variation among the different barley genotypes. This information is useful in genomics, genetics and barley breeding.

AGO1 and HSP90 buffer different genetic variants in Arabidopsis thaliana

Argonaute 1 (AGO1), the principal protein component of microRNA-mediated regulation, plays a key role in plant growth and development. AGO1 physically interacts with the chaperone HSP90, which buffers cryptic genetic variation in plants and animals. We sought to determine whether genetic perturbation of AGO1 in Arabidopsis thaliana would also reveal cryptic genetic variation, and if so, whether AGO1-dependent loci overlap with those dependent on HSP90. To address these questions, we introgressed a hypomorphic mutant allele of AGO1 into a set of mapping lines derived from the commonly used Arabidopsis strains Col-0 and Ler. Although we identified several cases in which AGO1 buffered genetic variation, none of the AGO1-dependent loci overlapped with those buffered by HSP90 for the traits assayed. We focused on 1 buffered locus where AGO1 perturbation uncoupled the traits days to flowering and rosette leaf number, which are otherwise closely correlated. Using a bulk segregant approach, we identified a nonfunctional Ler hua2 mutant allele as the causal AGO1-buffered polymorphism. Introduction of a nonfunctional hua2 allele into a Col-0 ago1 mutant background recapitulated the Ler-dependent ago1 phenotype, implying that coupling of these traits involves different molecular players in these closely related strains. Taken together, our findings demonstrate that even though AGO1 and HSP90 buffer genetic variation in the same traits, these robustness regulators interact epistatically with different genetic loci, suggesting that higher-order epistasis is uncommon. Plain Language Summary Argonaute 1 (AGO1), a key player in plant development, interacts with the chaperone HSP90, which buffers environmental and genetic variation. We found that AGO1 buffers environmental and genetic variation in the same traits; however, AGO1-dependent and HSP90-dependent loci do not overlap. Detailed analysis of a buffered locus found that a nonfunctional HUA2 allele decouples days to flowering and rosette leaf number in an AGO1-dependent manner, suggesting that the AGO1-dependent buffering acts at the network level.

Population Genetic Considerations Regarding Evidence for Biased Mutation Rates in Arabidopsis thaliana

It has recently been proposed that lower mutation rates in gene bodies compared with upstream and downstream sequences in Arabidopsis thaliana are the result of an "adaptive" modification of the rate of beneficial and deleterious mutations in these functional regions. This claim was based both on analyses of mutation accumulation lines and on population genomics data. Here, we show that several questionable assumptions were used in the population genomics analyses. In particular, we demonstrate that the difference between gene bodies and less selectively constrained sequences in the magnitude of Tajima's D can in principle be explained by the presence of sites subject to purifying selection and does not require lower mutation rates in regions experiencing selective constraints.

Mapping Genetic Variation in Arabidopsis in Response to Plant Growth-Promoting Bacterium Azoarcus olearius DQS-4T

Plant growth-promoting bacteria (PGPB) can enhance plant health by facilitating nutrient uptake, nitrogen fixation, protection from pathogens, stress tolerance and/or boosting plant productivity. The genetic determinants that drive the plant-bacteria association remain understudied. To identify genetic loci highly correlated with traits responsive to PGPB, we performed a genome-wide association study (GWAS) using an Arabidopsis thaliana population treated with Azoarcus olearius DQS-4^T. Phenotypically, the 305 Arabidopsis accessions tested responded differently to bacterial treatment by improving, inhibiting, or not affecting root system or shoot traits. GWA mapping analysis identified several predicted loci associated with primary root length or root fresh weight. Two statistical analyses were performed to narrow down potential gene candidates followed by haplotype block analysis, resulting in the identification of 11 loci associated with the responsiveness of Arabidopsis root fresh weight to bacterial inoculation. Our results showed considerable variation in the ability of plants to respond to inoculation by A. olearius DQS-4^T while revealing considerable complexity regarding statistically associated loci with the growth traits measured. This investigation is a promising starting point for sustainable breeding strategies for future cropping practices that may employ beneficial microbes and/or modifications of the root microbiome.

Population Genomic Analyses Suggest a Hybrid Origin, Cryptic Sexuality, and Decay of Genes Regulating Seed Development for the Putatively Strictly Asexual Kingdonia uniflora (Circaeasteraceae, Ranunculales)

Asexual lineages are perceived to be short-lived on evolutionary timescales. Hence, reports for exceptional cases of putative 'ancient asexuals' usually raise questions about the persistence of such species. So far, there have been few studies to solve the mystery in plants. The monotypic Kingdonia dating to the early Eocene, contains only K. uniflora that has no known definitive evidence for sexual reproduction nor records for having congeneric sexual species, raising the possibility that the species has persisted under strict asexuality for a long period of time. Here, we analyze whole genome polymorphism and divergence in K. uniflora. Our results show that K. uniflora is characterized by high allelic heterozygosity and elevated π_N/π_S ratio, in line with theoretical expectations under asexual evolution. Allele frequency spectrum analysis reveals the origin of asexuality in K. uniflora occurred prior to lineage differentiation of the species. Although divergence within K. uniflora individuals exceeds that between populations, the topologies of the two haplotype trees, however, fail to match each other, indicating long-term asexuality is unlikely to account for the high allele divergence and K. uniflora may have a recent hybrid origin. Phi-test shows a statistical probability of recombination for the conflicting phylogenetic signals revealed by the split network, suggesting K. uniflora engages in undetected sexual reproduction. Detection of elevated genetic differentiation and premature stop codons (in some populations) in genes regulating seed development indicates mutational degradation of sexuality-specific genes in K. uniflora. This study unfolds the origin and persistence mechanism of a plant lineage that has been known to reproduce asexually and presents the genomic consequences of lack of sexuality.

The effect of DNA polymorphisms and natural variation on crossover hotspot activity in Arabidopsis hybrids

In hybrid organisms, genetically divergent homologous chromosomes pair and recombine during meiosis; however, the effect of specific types of polymorphisms on crossover is poorly understood. Here, to analyze this in Arabidopsis, we develop the seed-typing method that enables the massively parallel fine-mapping of crossovers by sequencing. We show that structural variants, observed in one of the generated intervals, do not change crossover frequency unless they are located directly within crossover hotspots. Both natural and Cas9-induced deletions result in lower hotspot activity but are not compensated by increases in immediately adjacent hotspots. To examine the effect of single nucleotide polymorphisms on crossover formation, we analyze hotspot activity in mismatch detection-deficient msh2 mutants. Surprisingly, polymorphic hotspots show reduced activity in msh2. In lines where only the hotspot-containing interval is heterozygous, crossover numbers increase above those in the inbred (homozygous). We conclude that MSH2 shapes crossover distribution by stimulating hotspot activity at polymorphic regions.

Polymorphisms in alternative oxidase genes from ecotypes of Arabidopsis and rice revealed an environment-induced linkage to altitude and rainfall

We investigated SNPs in alternative oxidase (AOX) genes and their connection to ecotype origins (climate, altitude, and rainfall) by using genomic data sets of Arabidopsis and rice populations from 1190 and 90 ecotypes, respectively. Parameters were defined to detect non-synonymous SNPs in the AOX ORF, which revealed amino acid (AA) changes in AOX1c, AOX1d, and AOX2 from Arabidopsis and AOX1c from rice in comparison to AOX references from Columbia-0 and Japonica ecotypes, respectively. Among these AA changes, Arabidopsis AOX1c_A161E&G165R and AOX1c_R242S revealed a link to high rainfall and high altitude, respectively, while all other changes in Arabidopsis and rice AOX was connected to high altitude and rainfall. Comparative 3D modeling showed that all mutant AOX presented structural differences in relation to the respective references. Molecular docking analysis uncovered lower binding affinity values between AOX and the substrate ubiquinol for most of the identified structures compared to their reference, indicating better enzyme-substrate binding affinities. Thus, our in silico data suggest that the majority of the AA changes found in the available ecotypes will confer better enzyme-subtract interactions and thus indicate environment-related, more efficient AOX activity.

Conditional GWAS of non-CG transposon methylation in Arabidopsis thaliana reveals major polymorphisms in five genes

Genome-wide association studies (GWAS) have revealed that the striking natural variation for DNA CHH-methylation (mCHH; H is A, T, or C) of transposons has oligogenic architecture involving major alleles at a handful of known methylation regulators. Here we use a conditional GWAS approach to show that CHG-methylation (mCHG) has a similar genetic architecture—once mCHH is statistically controlled for. We identify five key trans-regulators that appear to modulate mCHG levels, and show that they interact with a previously identified modifier of mCHH in regulating natural transposon mobilization.

DNA methylation is an epigenetic mark common across eukaryotes. It is associated with transcriptional silencing, in particular of transposable elements. Multiple elements, including epigenetic inheritance, shape DNA methylation patterns, and the complexity makes it challenging to dissect the regulation. Our work on the 1001 Arabidopsis Epigenomes project led to the unexpected discovery that much of the natural variation for CHH methylation (mCHH; H is A, T, or C) on transposable elements could be attributed to allelic variation in three genes known to be involved in epigenetic regulation. However, our analysis of methylation in other sequence contexts (mCHG and mCG) revealed no genetic regulator.

Here we show that if mCHG variation is analyzed while taking mCHH into account, mCHG is also strongly influenced by allelic variation in a small number of genes with known or highly plausible direct roles in epigenetic regulation. The presence of common allelic variation of large effect is suggestive of some form of local adaptation. The nature of this adaptation remains obscure, but we present further evidence that allelic variation regulating DNA methylation influences transposon mobilization.

Uncovering natural variation in root system architecture and growth dynamics using a robotics-assisted phenomics platform

The plant kingdom contains a stunning array of complex morphologies easily observed above-ground, but more challenging to visualize below-ground. Understanding the magnitude of diversity in root distribution within the soil, termed root system architecture (RSA), is fundamental in determining how this trait contributes to species adaptation in local environments. Roots are the interface between the soil environment and the shoot system and therefore play a key role in anchorage, resource uptake, and stress resilience. Previously, we presented the GLO-Roots (Growth and Luminescence Observatory for Roots) system to study the RSA of soil-grown Arabidopsis thaliana plants from germination to maturity (Rellán-Álvarez et al., 2015). In this study, we present the automation of GLO-Roots using robotics and the development of image analysis pipelines in order to examine the temporal dynamic regulation of RSA and the broader natural variation of RSA in Arabidopsis, over time. These datasets describe the developmental dynamics of two independent panels of accessions and reveal highly complex and polygenic RSA traits that show significant correlation with climate variables of the accessions’ respective origins.

The megabase-scale crossover landscape is largely independent of sequence divergence

Meiotic recombination frequency varies along chromosomes and strongly correlates with sequence divergence. However, the causal relationship between recombination landscapes and polymorphisms is unclear. Here, we characterize the genome-wide recombination landscape in the quasi-absence of polymorphisms, using Arabidopsis thaliana homozygous inbred lines in which a few hundred genetic markers were introduced through mutagenesis. We find that megabase-scale recombination landscapes in inbred lines are strikingly similar to the recombination landscapes in hybrids, with the notable exception of heterozygous large rearrangements where recombination is prevented locally. In addition, the megabase-scale recombination landscape can be largely explained by chromatin features. Our results show that polymorphisms are not a major determinant of the shape of the megabase-scale recombination landscape but rather favour alternative models in which recombination and chromatin shape sequence divergence across the genome.

The frequency of recombination varies along chromosomes and highly correlates with sequence divergence. Here, the authors show that polymorphisms are not a major determinant of the megabase-scale recombination landscape in Arabidopsis, which is rather determined by chromatin accessibility and DNA methylation.

Genomic Differentiation and Demographic Histories of Two Closely Related Salicaceae Species

Populus alba (P. alba) and Populus davidiana (P. davidiana) are important plant species for answering a variety of issues on species evolution due to their wide distribution and ability to adapt to a variety of environments and climates. Even though P. alba and P. davidiana belong to ecologically and economically important forest trees in the Northern Hemisphere, little is known about their genomic landscape and genome divergence during speciation. We re-sequenced 20 and 19 members of P. davidiana and P. alba, respectively, and found that the Dxy value between P. alba and P. davidiana was 0.2658, whereas the F _ST values were 0.2988, indicating that the genetic divergence was fairly clear. Populus davidiana and P. alba diverged from the ancestor in the middle Pleistocene, c. 0.80 Ma (95% HPD: 0.79-0.81 Ma). The population sizes of P. davidiana increased ~20,000 years ago after a considerable long-term decline following divergence. However, after differentiation, the effective population size of P. alba expanded slightly before experiencing a long-term bottleneck effect. According to the expectation of allopatric speciation, we found a significant number of genomic differentiation sites in both species' speciation events, and the majority of these genomic differentiation regions can be attributed to neutral evolutionary processes. Nevertheless, the regions with extreme divergence exist in abundance, indicating that natural selection has had an impact. Positive selection can be found in highly differentiated regions, while long-term balancing selection traits can be easily observed in low differentiated regions. According to these findings, climate differences over the Quaternary, as well as variance in linked selection and recombination, all contributed significantly to genomic divergence during allopatric speciation of the two aspens.

Comparative Analysis and Structural Modeling of Elaeis oleifera FAD2, a Fatty Acid Desaturase Involved in Unsaturated Fatty Acid Composition of American Oil Palm

Simple Summary

Palm oil has become the world’s most important vegetable oil in terms of production quantity, and its overall demand is exponentially growing with the global population. The fatty acid composition and particularly the oleic/linoleic acid ratio are major factors influencing palm oil quality. In this study, we focused on FAD2, a fatty acid desaturase enzyme involved in the desaturation and conversion of oleic acid to linoleic acid in Elaeis oleifera, identified through in silico annotation analysis. Our phylogenetic and comparative studies revealed two SNP markers, SNP278 and SNP851, significantly correlated with the oleic/linoleic acid contents. Our study provides fundamental insights into the mechanism of fatty acids synthesis in oil palm and could support the application of molecular biology techniques to enhance the enzymatic activity and substrate affinity of EoFAD2.

Abstract

American oil palm (Elaeis oleifera) is an important source of dietary oil that could fulfill the increasing worldwide demand for cooking oil. Therefore, improving its production is crucial and could be realized through breeding and genetic engineering approaches aiming to obtain high-yielding varieties with improved oil content and quality. The fatty acid composition and particularly the oleic/linoleic acid ratio are major factors influencing oil quality. Our work focused on a fatty acid desaturase (FAD) enzyme involved in the desaturation and conversion of oleic acid to linoleic acid. Following the in silico identification and annotation of Elaeis oleifera FAD2, its molecular and structural features characterization was performed to better understand the mechanistic bases of its enzymatic activity. EoFAD2 is 1173 nucleotides long and encodes a protein of 390 amino acids that shares similarities with other FADs. Interestingly, the phylogenetic study showed three distinguished groups where EoFAD2 clustered among monocotyledonous taxa. EoFAD2 is a membrane-bound protein with five transmembrane domains presumably located in the endoplasmic reticulum. The homodimer organization model of EoFAD2 enzyme and substrates and respective substrate-binding residues were predicted and described. Moreover, the comparison between 24 FAD2 sequences from different species generated two interesting single-nucleotide polymorphisms (SNPs) associated with the oleic/linoleic acid contents.

Genotyping-by-sequencing-based identification of Arabidopsis pattern recognition receptor RLP32 recognizing proteobacterial translation initiation factor IF1

Activation of plant pattern-triggered immunity (PTI) relies on the recognition of microbe-derived structures, termed patterns, through plant-encoded surface-resident pattern recognition receptors (PRRs). We show that proteobacterial translation initiation factor 1 (IF1) triggers PTI in Arabidopsis thaliana and related Brassicaceae species. Unlike for most other immunogenic patterns, IF1 elicitor activity cannot be assigned to a small peptide epitope, suggesting that tertiary fold features are required for IF1 receptor activation. We have deployed natural variation in IF1 sensitivity to identify Arabidopsis leucine-rich repeat (LRR) receptor-like protein 32 (RLP32) as IF1 receptor using a restriction site-associated DNA sequencing approach. RLP32 confers IF1 sensitivity to rlp32 mutants, IF1-insensitive Arabidopsis accessions and IF1-insensitive Nicotiana benthamiana, binds IF1 specifically and forms complexes with LRR receptor kinases SOBIR1 and BAK1 to mediate signaling. Similar to other PRRs, RLP32 confers resistance to Pseudomonas syringae, highlighting an unexpectedly complex array of bacterial pattern sensors within a single plant species.

Pattern-triggered immunity is activated by recognition of microbe-derived structures by host pattern recognition receptors. Here the authors use a genotype-by sequencing approach to show that bacterial translation initiation factor 1 triggers PTI in Arabidopsis thaliana after recognition by the RLP32 receptor.

Species-specific partial gene duplication in Arabidopsis thaliana evolved novel phenotypic effects on morphological traits under strong positive selection

Gene duplication is increasingly recognized as an important mechanism for the origination of new genes, as revealed by comparative genomic analysis. However, how new duplicate genes contribute to phenotypic evolution remains largely unknown, especially in plants. Here, we identified the new gene EXOV, derived from a partial gene duplication of its parental gene EXOVL in Arabidopsis thaliana. EXOV is a species-specific gene that originated within the last 3.5 million years and shows strong signals of positive selection. Unexpectedly, RNA-sequencing analyses revealed that, despite its young age, EXOV has acquired many novel direct and indirect interactions in which the parental gene does not engage. This observation is consistent with the high, selection-driven substitution rate of its encoded protein, in contrast to the slowly evolving EXOVL, suggesting an important role for EXOV in phenotypic evolution. We observed significant differentiation of morphological changes for all phenotypes assessed in genome-edited and T-DNA insertional single mutants and in double T-DNA insertion mutants in EXOV and EXOVL. We discovered a substantial divergence of phenotypic effects by principal component analyses, suggesting neofunctionalization of the new gene. These results reveal a young gene that plays critical roles in biological processes that underlie morphological evolution in A. thaliana.

Evolutionary systems biology reveals patterns of rice adaptation to drought-prone agro-ecosystems

Rice (Oryza sativa) was domesticated around 10,000 years ago and has developed into a staple for half of humanity. The crop evolved and is currently grown in stably wet and intermittently dry agro-ecosystems, but patterns of adaptation to differences in water availability remain poorly understood. While previous field studies have evaluated plant developmental adaptations to water deficit, adaptive variation in functional and hydraulic components, particularly in relation to gene expression, has received less attention. Here, we take an evolutionary systems biology approach to characterize adaptive drought resistance traits across roots and shoots. We find that rice harbors heritable variation in molecular, physiological, and morphological traits that is linked to higher fitness under drought. We identify modules of co-expressed genes that are associated with adaptive drought avoidance and tolerance mechanisms. These expression modules showed evidence of polygenic adaptation in rice subgroups harboring accessions that evolved in drought-prone agro-ecosystems. Fitness-linked expression patterns allowed us to identify the drought-adaptive nature of optimizing photosynthesis and interactions with arbuscular mycorrhizal fungi. Taken together, our study provides an unprecedented, integrative view of rice adaptation to water-limited field conditions.

Contrasting gene-level signatures of selection with reproductive fitness

Selection leaves signatures in the DNA sequence of genes, with many test statistics devised to detect its action. While these statistics are frequently used to support hypotheses about the adaptive significance of particular genes, the effect these genes have on reproductive fitness is rarely quantified experimentally. Consequently, it is unclear how gene-level signatures of selection are associated with empirical estimates of gene effect on fitness. Eukaryotic datasets that permit this comparison are very limited. Using the model plant Arabidopsis thaliana, for which these resources are available, we calculated seven gene-level substitution and polymorphism-based statistics commonly used to infer selection (dN/dS, NI, DOS, Tajima's D, Fu and Li's D*, Fay and Wu's H, and Zeng's E) and, using knockout lines, compared these to gene-level estimates of effect on fitness. We found that consistent with expectations, essential genes were more likely to be classified as negatively selected. By contrast, using 379 Arabidopsis genes for which data was available, we found no evidence that genes predicted to be positively selected had a significantly different effect on fitness than genes evolving more neutrally. We discuss these results in the context of the analytic challenges posed by Arabidopsis, one of the only systems in which this study could be conducted, and advocate for examination in additional systems. These results are relevant to the evaluation of genome-wide studies across species where experimental fitness data is unavailable, as well as highlighting an increasing need for the latter.

Quinoa genome assembly employing genomic variation for guided scaffolding

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.

Genetic melting pot and importance of long-distance dispersal indicated in the Gladiolus imbricatus L. populations in the Polish Carpathians

The genetic diversity in 11 populations of Gladiolus imbricatus in five mountain ranges, including the Tatra, Pieniny, Gorce, Beskid Niski (Western Carpathians) and Bieszczady Mts (Eastern Carpathians), was studied with inter-simple sequence repeat (ISSR) markers. The species is a perennial plant occurring in open and semi-open sites of anthropogenic origin (meadows and forest margins). We checked a hypothesis on the microrefugial character of the plant populations in the Pieniny Mts, a small calcareous Carpathian range of complicated relief that has never been glaciated. Plant populations in the Tatra and Pieniny Mts had the highest genetic diversity indices, pointing to their long-term persistence. The refugial vs. the non-refugial mountain ranges accounted for a relatively high value of total genetic variation [analysis of molecular variance (AMOVA), 14.12%, p = 0.003]. One of the Pieniny populations was of hybridogenous origin and shared genetic stock with the Tatra population, indicating there is a local genetic melting pot. A weak genetic structuring of populations among particular regions was found (AMOVA, 4.5%, p > 0.05). This could be an effect of the frequent short-distance and sporadic long-distance gene flow. The dispersal of diaspores between the remote populations in the Western Carpathians and Eastern Carpathians could be affected by the historical transportation of flocks of sheep from the Tatra to Bieszczady Mts.

The rate and molecular spectrum of mutation are selectively maintained in yeast

What determines the rate (μ) and molecular spectrum of mutation is a fundamental question. The prevailing hypothesis asserts that natural selection against deleterious mutations has pushed μ to the minimum achievable in the presence of genetic drift, or the drift barrier. Here we show that, contrasting this hypothesis, μ substantially exceeds the drift barrier in diverse organisms. Random mutation accumulation (MA) in yeast frequently reduces μ, and deleting the newly discovered mutator gene PSP2 nearly halves μ. These results, along with a comparison between the MA and natural yeast strains, demonstrate that μ is maintained above the drift barrier by stabilizing selection. Similar comparisons show that the mutation spectrum such as the universal AT mutational bias is not intrinsic but has been selectively preserved. These findings blur the separation of mutation from selection as distinct evolutionary forces but open the door to alleviating mutagenesis in various organisms by genome editing.

How natural selection shapes the rate and molecular spectrum of mutations is debated. Yeast mutation accumulation experiments identify a gene promoting mutagenesis and show stabilizing selection maintaining the mutation rate above the drift barrier. Selection also preserves the mutation spectrum.

Meta-Analysis Identifies Pleiotropic Loci Controlling Phenotypic Trade-offs in Sorghum

Community association populations are composed of phenotypically and genetically diverse accessions. Once these populations are genotyped, the resulting marker data can be reused by different groups investigating the genetic basis of different traits. Because the same genotypes are observed and scored for a wide range of traits in different environments, these populations represent a unique resource to investigate pleiotropy. Here we assembled a set of 234 separate trait datasets for the Sorghum Association Panel, a group of 406 sorghum genotypes widely employed by the sorghum genetics community. Comparison of genome wide association studies conducted with two independently generated marker sets for this population demonstrate that existing genetic marker sets do not saturate the genome and likely capture only 35-43% of potentially detectable loci controlling variation for traits scored in this population. While limited evidence for pleiotropy was apparent in cross-GWAS comparisons, a multivariate adaptive shrinkage approach recovered both known pleiotropic effects of existing loci and new pleiotropic effects, particularly significant impacts of known dwarfing genes on root architecture. In addition, we identified new loci with pleiotropic effects consistent with known trade-offs in sorghum development. These results demonstrate the potential for mining existing trait datasets from widely used community association populations to enable new discoveries from existing trait datasets as new, denser genetic marker datasets are generated for existing community association populations.

Cis-regulatory evolution spotlights species differences in the adaptive potential of gene expression plasticity

Phenotypic plasticity is the variation in phenotype that a single genotype can produce in different environments and, as such, is an important component of individual fitness. However, whether the effect of new mutations, and hence evolution, depends on the direction of plasticity remains controversial. Here, we identify the cis-acting modifications that have reshaped gene expression in response to dehydration stress in three Arabidopsis species. Our study shows that the direction of effects of most cis-regulatory variants differentiating the response between A. thaliana and the sister species A. lyrata and A. halleri depends on the direction of pre-existing plasticity in gene expression. A comparison of the rate of cis-acting variant accumulation in each lineage indicates that the selective forces driving adaptive evolution in gene expression favors regulatory changes that magnify the stress response in A. lyrata. The evolutionary constraints measured on the amino-acid sequence of these genes support this interpretation. In contrast, regulatory changes that mitigate the plastic response to stress evolved more frequently in A. halleri. Our results demonstrate that pre-existing plasticity may be a stepping stone for adaptation, but its selective remodeling differs between lineages.

Anno genominis XX: 20 years of Arabidopsis genomics

Twenty years ago, the Arabidopsis thaliana genome sequence was published. This was an important moment as it was the first sequenced plant genome and explicitly brought plant science into the genomics era. At the time, this was not only an outstanding technological achievement, but it was characterized by a superb global collaboration. The Arabidopsis genome was the seed for plant genomic research. Here, we review the development of numerous resources based on the genome that have enabled discoveries across plant species, which has enhanced our understanding of how plants function and interact with their environments.

Gene body methylation is under selection in Arabidopsis thaliana

In plants, mammals and insects, some genes are methylated in the CG dinucleotide context, a phenomenon called gene body methylation (gbM). It has been controversial whether this phenomenon has any functional role. Here, we took advantage of the availability of 876 leaf methylomes in Arabidopsis thaliana to characterize the population frequency of methylation at the gene level and to estimate the site-frequency spectrum of allelic states. Using a population genetics model specifically designed for epigenetic data, we found that genes with ancestral gbM are under significant selection to remain methylated. Conversely, ancestrally unmethylated genes were under selection to remain unmethylated. Repeating the analyses at the level of individual cytosines confirmed these results. Estimated selection coefficients were small, on the order of 4 N_es = 1.4, which is similar to the magnitude of selection acting on codon usage. We also estimated that A. thaliana is losing gbM threefold more rapidly than gaining it, which could be due to a recent reduction in the efficacy of selection after a switch to selfing. Finally, we investigated the potential function of gbM through its link with gene expression. Across genes with polymorphic methylation states, the expression of gene body methylated alleles was consistently and significantly higher than unmethylated alleles. Although it is difficult to disentangle genetic from epigenetic effects, our work suggests that gbM has a small but measurable effect on fitness, perhaps due to its association to a phenotype-like gene expression.

1,135 ionomes reveal the global pattern of leaf and seed mineral nutrient and trace element diversity in Arabidopsis thaliana

Soil is a heterogeneous reservoir of essential elements needed for plant growth and development. Plants have evolved mechanisms to balance their nutritional needs based on availability of nutrients. This has led to genetically based variation in the elemental composition, the 'ionome', of plants, both within and between species. We explore this natural variation using a panel of wild-collected, geographically widespread Arabidopsis thaliana accessions from the 1001 Genomes Project including over 1,135 accessions, and the 19 parental accessions of the Multi-parent Advanced Generation Inter-Cross (MAGIC) panel, all with full-genome sequences available. We present an experimental design pipeline for high-throughput ionomic screenings and analyses with improved normalisation procedures to account for errors and variability in conditions often encountered in large-scale, high-throughput data collection. We report quantification of the complete leaf and seed ionome of the entire collection using this pipeline and a digital tool, Ion Explorer, to interact with the dataset. We describe the pattern of natural ionomic variation across the A. thaliana species and identify several accessions with extreme ionomic profiles. It forms a valuable resource for exploratory genetic mapping studies to identify genes underlying natural variation in leaf and seed ionome and genetic adaptation of plants to soil conditions.

Drivers of linkage disequilibrium across a species' geographic range

While linkage disequilibrium (LD) is an important parameter in genetics and evolutionary biology, the drivers of LD remain elusive. Using whole-genome sequences from across a species’ range, we assessed the impact of demographic history and mating system on LD. Both range expansion and a shift from outcrossing to selfing in North American Arabidopsis lyrata were associated with increased average genome-wide LD. Our results indicate that range expansion increases short-distance LD at the farthest range edges by about the same amount as a shift to selfing. However, the extent over which LD in genic regions unfolds was shorter for range expansion compared to selfing. Linkage among putatively neutral variants and between neutral and deleterious variants increased to a similar degree with range expansion, providing support that genome-wide LD was positively associated with mutational load. As a consequence, LD combined with mutational load may decelerate range expansions and set range limits. Finally, a small number of genes were identified as LD outliers, suggesting that they experience selection by either of the two demographic processes. These included genes involved in flowering and photoperiod for range expansion, and the self-incompatibility locus for mating system.

Nearby genomic variants are often co-inherited because of limited recombination. The extent of non-random association of alleles at different loci is called linkage disequilibrium (LD) and is commonly used in genomic analyses, for example to detect regions under selection or to determine effective population size. Here we reversed testing and addressed how demographic history may affect LD within a species. Using genomic data from more than a thousand individuals of North American Arabidopsis lyrata from across the entire species’ range, we quantified the effect of postglacial range expansion and a shift in mating system from outcrossing to selfing on LD. We show that both factors lead to increased LD, and that the maximal effect of range expansion is comparable with a shift in mating system to selfing. Heightened LD involves deleterious mutations, and therefore, LD can also serve as an indicator of mutation accumulation. Furthermore, we provide evidence that some genes experienced stronger increases in LD possibly due to selection associated with the two demographic changes. Our results provide a novel and broad view on the evolutionary factors shaping LD that may also apply to the very many species that underwent postglacial range expansion.

Naturally occurring circadian rhythm variation associated with clock gene loci in Swedish Arabidopsis accessions

Circadian clocks have evolved to resonate with external day and night cycles. However, these entrainment signals are not consistent everywhere and vary with latitude, climate and seasonality. This leads to divergent selection for clocks which are locally adapted. To investigate the genetic basis for this circadian variation, we used a delayed fluorescence imaging assay to screen 191 naturally occurring Swedish Arabidopsis accessions for their circadian phenotypes. We demonstrate that the period length co-varies with both geography and population sub-structure. Several candidate loci linked to period, phase and relative amplitude error (RAE) were revealed by genome-wide association mapping and candidate genes were investigated using TDNA mutants. We show that natural variation in a single non-synonymous substitution within COR28 is associated with a long-period and late-flowering phenotype similar to that seen in TDNA knock-out mutants. COR28 is a known coordinator of flowering time, freezing tolerance and the circadian clock; all of which may form selective pressure gradients across Sweden. We demonstrate the effect of the COR28-58S SNP in increasing period length through a co-segregation analysis. Finally, we show that period phenotypic tails remain diverged under lower temperatures and follow a distinctive "arrow-shaped" trend indicative of selection for a cold-biased temperature compensation response.

Evolution of Conserved Noncoding Sequences in Arabidopsis thaliana

Recent pangenome studies have revealed a large fraction of the gene content within a species exhibits presence-absence variation (PAV). However, coding regions alone provide an incomplete assessment of functional genomic sequence variation at the species level. Little to no attention has been paid to noncoding regulatory regions in pangenome studies, though these sequences directly modulate gene expression and phenotype. To uncover regulatory genetic variation, we generated chromosome-scale genome assemblies for thirty Arabidopsis thaliana accessions from multiple distinct habitats and characterized species level variation in Conserved Noncoding Sequences (CNS). Our analyses uncovered not only PAV and positional variation (PosV) but that diversity in CNS is nonrandom, with variants shared across different accessions. Using evolutionary analyses and chromatin accessibility data, we provide further evidence supporting roles for conserved and variable CNS in gene regulation. Additionally, our data suggests that transposable elements contribute to CNS variation. Characterizing species-level diversity in all functional genomic sequences may later uncover previously unknown mechanistic links between genotype and phenotype.

Model-based genotype and ancestry estimation for potential hybrids with mixed-ploidy

Non-random mating among individuals can lead to spatial clustering of genetically similar individuals and population stratification. This deviation from panmixia is commonly observed in natural populations. Consequently, individuals can have parentage in single populations or involving hybridization between differentiated populations. Accounting for this mixture and structure is important when mapping the genetics of traits and learning about the formative evolutionary processes that shape genetic variation among individuals and populations. Stratified genetic relatedness among individuals is commonly quantified using estimates of ancestry that are derived from a statistical model. Development of these models for polyploid and mixed-ploidy individuals and populations has lagged behind those for diploids. Here, we extend and test a hierarchical Bayesian model, called entropy, which can use low-depth sequence data to estimate genotype and ancestry parameters in autopolyploid and mixed-ploidy individuals (including sex chromosomes and autosomes within individuals). Our analysis of simulated data illustrated the trade-off between sequencing depth and genome coverage and found lower error associated with low-depth sequencing across a larger fraction of the genome than with high-depth sequencing across a smaller fraction of the genome. The model has high accuracy and sensitivity as verified with simulated data and through analysis of admixture among populations of diploid and tetraploid Arabidopsis arenosa.

A natural diversity screen in Arabidopsis thaliana reveals determinants for HopZ1a recognition in the ZAR1-ZED1 immune complex

Pathogen pressure on hosts can lead to the evolution of genes regulating the innate immune response. By characterizing naturally occurring polymorphisms in immune receptors, we can better understand the molecular determinants of pathogen recognition. ZAR1 is an ancient Arabidopsis thaliana NLR (Nucleotide-binding [NB] Leucine-rich-repeat [LRR] Receptor) that recognizes multiple secreted effector proteins from the pathogenic bacteria Pseudomonas syringae and Xanthomonas campestris through its interaction with receptor-like cytoplasmic kinases (RLCKs). ZAR1 was first identified for its role in recognizing P. syringae effector HopZ1a, through its interaction with the RLCK ZED1. To identify additional determinants of HopZ1a recognition, we performed a computational screen for ecotypes from the 1001 Genomes project that were likely to lack HopZ1a recognition, and tested ~300 ecotypes. We identified ecotypes containing polymorphisms in ZAR1 and ZED1. Using our previously established Nicotiana benthamiana transient assay and Arabidopsis ecotypes, we tested for the effect of naturally occurring polymorphisms on ZAR1 interactions and the immune response. We identified key residues in the NB or LRR domain of ZAR1 that impact the interaction with ZED1. We demonstrate that natural diversity combined with functional assays can help define the molecular determinants and interactions necessary to regulate immune induction in response to pathogens.

Demography and Natural Selection Have Shaped Genetic Variation in the Widely Distributed Conifer Norway Spruce (Picea abies)

Under the neutral theory, species with larger effective population size are expected to harbor higher genetic diversity. However, across a wide variety of organisms, the range of genetic diversity is orders of magnitude more narrow than the range of effective population size. This observation has become known as Lewontin’s paradox and although aspects of this phenomenon have been extensively studied, the underlying causes for the paradox remain unclear. Norway spruce (Picea abies) is a widely distributed conifer species across the northern hemisphere, and it consequently plays a major role in European forestry. Here, we use whole-genome resequencing data from 35 individuals to perform population genomic analyses in P. abies in an effort to understand what drives genome-wide patterns of variation in this species. Despite having a very wide geographic distribution and an corresponding enormous current population size, our analyses find that genetic diversity of P. abies is low across a number of populations (π = 0.0049 in Central-Europe, π = 0.0063 in Sweden-Norway, π = 0.0063 in Finland). To assess the reasons for the low levels of genetic diversity, we infer the demographic history of the species and find that it is characterized by several reoccurring bottlenecks with concomitant decreases in effective population size can, at least partly, provide an explanation for low polymorphism we observe in P. abies. Further analyses suggest that recurrent natural selection, both purifying and positive selection, can also contribute to the loss of genetic diversity in Norway spruce by reducing genetic diversity at linked sites. Finally, the overall low mutation rates seen in conifers can also help explain the low genetic diversity maintained in Norway spruce.

Molecular variation in a functionally divergent homolog of FCA regulates flowering time in Arabidopsis thaliana

The identification and functional characterization of natural variants in plants are essential for understanding phenotypic adaptation. Here we identify a molecular variation in At2g47310 that contributes to the natural variation in flowering time in Arabidopsis thaliana accessions. This gene, which we term SISTER of FCA (SSF), functions in an antagonistic manner to its close homolog FCA. Genome-wide association analysis screens two major haplotypes of SSF associated with the natural variation in FLC expression, and a single polymorphism, SSF-N414D, is identified as a main contributor. The SSF414N protein variant interacts more strongly with CUL1, a component of the E3 ubiquitination complex, than the SSF414D form, mediating differences in SSF protein degradation and FLC expression. FCA and SSF appear to have arisen through gene duplication after dicot-monocot divergence, with the SSF-N414D polymorphism emerging relatively recently within A. thaliana. This work provides a good example for deciphering the functional importance of natural polymorphisms in different organisms.

Natural variation represents valuable source for gene discovery. Here, the authors show that a homolog of Flowering Control Locus A (FCA) functions in an antagonistic manner to FCA in regulating Arabidopsis flowering time through interacting with CUL1-E3 and modulating FLC expression.

Genomic Prediction Informed by Biological Processes Expands Our Understanding of the Genetic Architecture Underlying Free Amino Acid Traits in Dry Arabidopsis Seeds

Plant growth, development, and nutritional quality depends upon amino acid homeostasis, especially in seeds. However, our understanding of the underlying genetics influencing amino acid content and composition remains limited, with only a few candidate genes and quantitative trait loci identified to date. Improved knowledge of the genetics and biological processes that determine amino acid levels will enable researchers to use this information for plant breeding and biological discovery. Toward this goal, we used genomic prediction to identify biological processes that are associated with, and therefore potentially influence, free amino acid (FAA) composition in seeds of the model plant Arabidopsis thaliana. Markers were split into categories based on metabolic pathway annotations and fit using a genomic partitioning model to evaluate the influence of each pathway on heritability explained, model fit, and predictive ability. Selected pathways included processes known to influence FAA composition, albeit to an unknown degree, and spanned four categories: amino acid, core, specialized, and protein metabolism. Using this approach, we identified associations for pathways containing known variants for FAA traits, in addition to finding new trait-pathway associations. Markers related to amino acid metabolism, which are directly involved in FAA regulation, improved predictive ability for branched chain amino acids and histidine. The use of genomic partitioning also revealed patterns across biochemical families, in which serine-derived FAAs were associated with protein related annotations and aromatic FAAs were associated with specialized metabolic pathways. Taken together, these findings provide evidence that genomic partitioning is a viable strategy to uncover the relative contributions of biological processes to FAA traits in seeds, offering a promising framework to guide hypothesis testing and narrow the search space for candidate genes.

Genomic Landscape of Mutational Biases in the Pacific Oyster Crassostrea gigas

Mutation is a driving force of evolution that has been shaped by natural selection and is universally biased. Previous studies determined genome-wide mutational patterns for several species and investigated the heterogeneity of mutational patterns at fine-scale levels. However, little evidence of the heterogeneity of mutation rates over large genomic regions was shown. Hence, the mutational patterns of different large-scale genomic regions and their association with selective pressures still need to be explored. As the second most species-rich animal phylum, little is known about the mutational patterns in Mollusca, especially oysters. In this study, the mutational bias patterns are characterized by using whole-genome resequencing data in the Crassostrea gigas genome. I studied the genome-wide relative rates of the pair mutations and found that the predominant mutation is GC -> AT, irrespective of the genomic regions. This analysis reveals that mutational biases were associated with gene expression levels across the C. gigas genome. Genes with higher expression levels and breadth expression patterns, longer coding length, and more exon numbers had relatively higher GC -> AT rates. I also found that genes with larger dN/dS values had relatively higher GC -> AT rates. This work represents the first comprehensive research on the mutational biases in Mollusca species. Here, I comprehensively investigated the relationships between mutational biases with some intrinsic genetic factors and evolutionary indicators and proposed that selective pressures are important forces shaping the mutational biases across the C. gigas genome.

Leaf chlorosis in Arabidopsis thaliana hybrids is associated with transgenerational decline and imbalanced ribosome number

The interaction of two parental genomes can result in negative outcomes in offspring, also known as hybrid incompatibility. We have previously reported a case in which two recessively interacting alleles result in hybrid chlorosis in Arabidopsis thaliana. A DEAD-box RNA helicase 18 (AtRH18) was identified to be necessary for chlorosis. In this study, we use a sophisticated genetic approach to investigate genes underlying hybrid chlorosis. Sequence comparisons, DNA methylation inhibitor drug treatment and segregation analysis were used to investigate the epigenetic regulation of hybrid chlorosis. Relative rRNA numbers were quantified using real-time quantitative PCR. We confirmed the causality of AtRH18 and provided evidence for the involvement of the promoter region of AtRH18 in the hybrid chlorosis. Furthermore, AtMOM1 from the second parent was identified as the likely candidate gene on chromosome 1. Chlorotic hybrids displayed transgenerational decline in chlorosis, and DNA demethylation experiment restored chlorophyll levels in chlorotic hybrids. Quantification of rRNA indicated that hybrid chlorosis was associated with an imbalance in the ratio of cytosolic and plastid ribosomes. Our findings highlight that the epigenetic regulation of AtRH18 causes hybrid breakdown and provide novel information about the role of AtRH18 in plant development.

MSH2 shapes the meiotic crossover landscape in relation to interhomolog polymorphism in Arabidopsis

During meiosis, DNA double-strand breaks undergo interhomolog repair to yield crossovers between homologous chromosomes. To investigate how interhomolog sequence polymorphism affects crossovers, we sequenced multiple recombinant populations of the model plant Arabidopsis thaliana. Crossovers were elevated in the diverse pericentromeric regions, showing a local preference for polymorphic regions. We provide evidence that crossover association with elevated diversity is mediated via the Class I crossover formation pathway, although very high levels of diversity suppress crossovers. Interhomolog polymorphism causes mismatches in recombining molecules, which can be detected by MutS homolog (MSH) mismatch repair protein heterodimers. Therefore, we mapped crossovers in a msh2 mutant, defective in mismatch recognition, using multiple hybrid backgrounds. Although total crossover numbers were unchanged in msh2 mutants, recombination was remodelled from the diverse pericentromeres towards the less-polymorphic sub-telomeric regions. Juxtaposition of megabase heterozygous and homozygous regions causes crossover remodelling towards the heterozygous regions in wild type Arabidopsis, but not in msh2 mutants. Immunostaining showed that MSH2 protein accumulates on meiotic chromosomes during prophase I, consistent with MSH2 regulating meiotic recombination. Our results reveal a pro-crossover role for MSH2 in regions of higher sequence diversity in A. thaliana.

A Peptide Pair Coordinates Regular Ovule Initiation Patterns with Seed Number and Fruit Size

Ovule development in Arabidopsis thaliana involves pattern formation, which ensures that ovules are regularly arranged in the pistils to reduce competition for nutrients and space. Mechanisms underlying pattern formation in plants, such as phyllotaxis, flower morphogenesis, or lateral root initiation, have been extensively studied, and genes controlling the initiation of ovules have been identified. However, the fundamental patterning mechanism that determines the spacing of ovule anlagen within the placenta remained unexplored. Using natural variation analysis combined with quantitative trait locus analysis, we found that the spacing of ovules in the developing gynoecium and fruits is controlled by two secreted peptides, EPFL2 and EPFL9 (also known as Stomagen), and their receptors from the ERECTA (ER) family that act from the carpel wall and the placental tissue. We found that a signaling pathway controlled by EPFL9 acting from the carpel wall through the LRR-receptor kinases ER, ERL1, and ERL2 promotes fruit growth. Regular spacing of ovules depends on EPFL2 expression in the carpel wall and in the inter-ovule spaces, where it acts through ERL1 and ERL2. Loss of EPFL2 signaling results in shorter gynoecia and fruits and irregular spacing of ovules or even ovule twinning. We propose that the EPFL2 signaling module evolved to control the initiation and regular, equidistant spacing of ovule primordia, which may serve to minimize competition between seeds or facilitate equal resource allocation. Together, EPFL2 and EPFL9 help to coordinate ovule patterning and thereby seed number with gynoecium and fruit growth through a set of shared receptors.

Estimating the genome-wide contribution of selection to temporal allele frequency change

Rapid phenotypic adaptation is often observed in natural populations and selection experiments. However, detecting the genome-wide impact of this selection is difficult since adaptation often proceeds from standing variation and selection on polygenic traits, both of which may leave faint genomic signals indistinguishable from a noisy background of genetic drift. One promising signal comes from the genome-wide covariance between allele frequency changes observable from temporal genomic data (e.g., evolve-and-resequence studies). These temporal covariances reflect how heritable fitness variation in the population leads changes in allele frequencies at one time point to be predictive of the changes at later time points, as alleles are indirectly selected due to remaining associations with selected alleles. Since genetic drift does not lead to temporal covariance, we can use these covariances to estimate what fraction of the variation in allele frequency change through time is driven by linked selection. Here, we reanalyze three selection experiments to quantify the effects of linked selection over short timescales using covariance among time points and across replicates. We estimate that at least 17 to 37% of allele frequency change is driven by selection in these experiments. Against this background of positive genome-wide temporal covariances, we also identify signals of negative temporal covariance corresponding to reversals in the direction of selection for a reasonable proportion of loci over the time course of a selection experiment. Overall, we find that in the three studies we analyzed, linked selection has a large impact on short-term allele frequency dynamics that is readily distinguishable from genetic drift.