Genome-wide association mapping of flowering time in Arabidopsis thaliana in nature: genetics for underlying components and reaction norms across two successive years

Leveraging Automated Machine Learning for Environmental Data-Driven Genetic Analysis and Genomic Prediction in Maize Hybrids

Genotype, environment, and genotype-by-environment (G×E) interactions play a critical role in shaping crop phenotypes. Here, a large-scale, multi-environment hybrid maize dataset is used to construct and validate an automated machine learning framework that integrates environmental and genomic data for improved accuracy and efficiency in genetic analyses and genomic predictions. Dimensionality-reduced environmental parameters (RD_EPs) aligned with developmental stages are applied to establish linear relationships between RD_EPs and traits to assess the influence of environment on phenotype. Genome-wide association study identifies 539 phenotypic plasticity trait-associated markers (PP-TAMs), 223 environmental stability TAMs (Main-TAMs), and 92 G×E-TAMs, revealing distinct genetic bases for PP and G×E interactions. Training genomic prediction models with both TAMs and RD_EPs increase prediction accuracy by 14.02% to 28.42% over that of genome-wide marker approaches. These results demonstrate the potential of utilizing environmental data for improving genetic analysis and genomic selection, offering a scalable approach for developing climate-adaptive maize varieties.

Adaptive significance of flowering time variation across natural seasonal environments in Arabidopsis thaliana

The relevance of flowering time variation and plasticity to climate adaptation requires a comprehensive empirical assessment. We investigated natural selection and the genetic architecture of flowering time in Arabidopsis through field experiments in Europe across multiple sites and seasons. We estimated selection for flowering time, plasticity and canalization. Loci associated with flowering time, plasticity and canalization by genome-wide association studies were tested for a geographic signature of climate adaptation. Selection favored early flowering and increased canalization, except at the northernmost site, but was rarely detected for plasticity. Genome-wide association studies revealed significant associations with flowering traits and supported a substantial polygenic inheritance. Alleles associated with late flowering, including functional FRIGIDA variants, were more common in regions experiencing high annual temperature variation. Flowering time plasticity to fall vs spring and summer environments was associated with GIGANTEA SUPPRESSOR 5, which promotes early flowering under decreasing day length and temperature. The finding that late flowering genotypes and alleles are associated with climate is evidence for past adaptation. Real-time phenotypic selection analysis, however, reveals pervasive contemporary selection for rapid flowering in agricultural settings across most of the species range. The response to this selection may involve genetic shifts in environmental cuing compared to the ancestral state.

SNP- and Haplotype-Based GWAS of Flowering-Related Traits in Brassica napus

Traits related to flowering time are the most promising agronomic traits that directly impact the seed yield and oil quality of rapeseed (Brassica napus L.). Developing early flowering and maturity rapeseed varieties is an important breeding objective in B. napus. Many studies have reported on days to flowering, but few have reported on budding, bolting, and the interval between bolting and DTF. Therefore, elucidating the genetic architecture of QTLs and genes regulating flowering time, we presented an integrated investigation on SNP and haplotype-based genome-wide association study of 373 diverse B. napus germplasm, which were genotyped by the 60K SNP array and were phenotyped in the four environments. The results showed that a total of 15 and 37 QTLs were detected from SNP and haplotype-based GWAS, respectively. Among them, seven QTL clusters were identified by haplotype-based GWAS. Moreover, three and eight environmentally stable QTLs were detected by SNP-GWAS and haplotype-based GWAS, respectively. By integrating the above two approaches and by co-localizing the four traits, ten (10) genomic regions were under selection on chromosomes A03, A07, A08, A10, C06, C07, and C08. Interestingly, the genomic regions FT.A07.1, FT.A08, FT.C06, and FT.C07 were identified as novel. In these ten regions, a total of 197 genes controlling FT were detected, of which 14 highly expressed DEGs were orthologous to 13 Arabidopsis thaliana genes after integration with transcriptome results. In a nutshell, the above results uncovered the genetic architecture of important agronomic traits related to flowering time and provided a basis for multiple molecular marker-trait associations in B. napus.

Plasticity of rosette size in response to nitrogen availability is controlled by an RCC1-family protein

Nitrogen (N) is fundamental to plant growth, development and yield. Genes underlying N utilization and assimilation are well-characterized, but mechanisms underpinning plasticity of different phenotypes in response to N remain elusive. Here, using Arabidopsis thaliana accessions, we dissected the genetic architecture of plasticity in early and late rosette diameter, flowering time and yield, in response to three levels of N in the soil. Furthermore, we found that the plasticity in levels of primary metabolites were related with the plasticities of the studied traits. Genome-wide association analysis identified three significant associations for phenotypic plasticity, one for early rosette diameter and two for flowering time. We confirmed that the gene At1g19880, hereafter named as PLASTICITY OF ROSETTE TO NITROGEN 1 (PROTON1), encoding for a regulator of chromatin condensation 1 (RCC1) family protein, conferred plasticity of rosette diameter in response to N. Treatment of PROTON1 T-DNA line with salt implied that the reduced plasticity of early rosette diameter was not a general growth response to stress. We further showed that plasticities of growth and flowering-related traits differed between environmental cues, indicating decoupled genetic programs regulating these traits. Our findings provide a prospective to identify genes that stabilize performance under fluctuating environments.

A complex network of additive and epistatic quantitative trait loci underlies natural variation of Arabidopsis thaliana quantitative disease resistance to Ralstonia solanacearum under heat stress

Plant immunity is often negatively impacted by heat stress. However, the underlying molecular mechanisms remain poorly characterized. Based on a genome-wide association mapping approach, this study aims to identify in Arabidopsis thaliana the genetic bases of robust resistance mechanisms to the devastating pathogen Ralstonia solanacearum under heat stress. A local mapping population was phenotyped against the R. solanacearum GMI1000 strain at 27 and 30 °C. To obtain a precise description of the genetic architecture underlying natural variation of quantitative disease resistance (QDR), we applied a genome-wide local score analysis. Alongside an extensive genetic variation found in this local population at both temperatures, we observed a playful dynamics of quantitative trait loci along the infection stages. In addition, a complex genetic network of interacting loci could be detected at 30 °C. As a first step to investigate the underlying molecular mechanisms, the atypical meiotic cyclin SOLO DANCERS gene was validated by a reverse genetic approach as involved in QDR to R. solanacearum at 30 °C. In the context of climate change, the complex genetic architecture underlying QDR under heat stress in a local mapping population revealed candidate genes with diverse molecular functions.

HpaP Sequesters HrpJ, an Essential Component of Ralstonia solanacearum Virulence That Triggers Necrosis in Arabidopsis

The Gram-negative bacterium Ralstonia solanacearum, the causal agent of bacterial wilt, is a worldwide major crop pathogen whose virulence strongly relies on a type III secretion system (T3SS). This extracellular apparatus allows the translocation of proteins, called type III effectors (T3Es), directly into the host cells. To date, very few data are available in plant-pathogenic bacteria concerning the role played by type III secretion (T3S) regulators at the posttranslational level. We have demonstrated that HpaP, a putative T3S substrate specificity switch protein of R. solanacearum, controls T3E secretion. To better understand the role of HpaP on T3S control, we analyzed the secretomes of the GMI1000 wild-type strain as well as the hpaP mutant using a mass spectrometry experiment (liquid chromatography tandem mass spectrometry). The secretomes of both strains appeared to be very similar and highlighted the modulation of the secretion of few type III substrates. Interestingly, only one type III-associated protein, HrpJ, was identified as specifically secreted by the hpaP mutant. HrpJ appeared to be an essential component of the T3SS, essential for T3S and pathogenicity. We further showed that HrpJ is specifically translocated in planta by the hpaP mutant and that HrpJ can physically interact with HpaP. Moreover, confocal microscopy experiments demonstrated a cytoplasmic localization for HrpJ once in planta. When injected into Arabidopsis thaliana leaves, HrpJ is able to trigger a necrosis on 16 natural accessions. A genome-wide association mapping revealed a major association peak with 12 highly significant single-nucleotide polymorphisms located on a plant acyl-transferase.

PIF transcription factors link a neighbor threat cue to accelerated reproduction in Arabidopsis

Changes in light quality indicative of competition for this essential resource influence plant growth and developmental transitions; however, little is known about neighbor proximity-induced acceleration of reproduction. Phytochrome B (phyB) senses light cues from plant competitors, ultimately leading to the expression of the floral inducers FLOWERING LOCUS T (FT) and TWIN SISTER of FT (TSF). Here we show that PHYTOCHROME INTERACTING FACTORs 4, 5 and 7 (PIF4, PIF5 and PIF7) mediate neighbor proximity-induced flowering, with PIF7 playing a prominent role. These transcriptional regulators act directly downstream of phyB to promote expression of FT and TSF. Neighbor proximity enhances PIF accumulation towards the end of the day, coinciding with enhanced floral inducer expression. We present evidence supporting direct PIF-regulated TSF expression. The relevance of our findings is illustrated by the prior identification of FT, TSF and PIF4 as loci underlying flowering time regulation in natural conditions.

Crop genome-wide association study: a harvest of biological relevance

With the advent of rapid genotyping and next-generation sequencing technologies, genome-wide association study (GWAS) has become a routine strategy for decoding genotype-phenotype associations in many species. More than 1000 such studies over the last decade have revealed substantial genotype-phenotype associations in crops and provided unparalleled opportunities to probe functional genomics. Beyond the many 'hits' obtained, this review summarizes recent efforts to increase our understanding of the genetic architecture of complex traits by focusing on non-main effects including epistasis, pleiotropy, and phenotypic plasticity. We also discuss how these achievements and the remaining gaps in our knowledge will guide future studies. Synthetic association is highlighted as leading to false causality, which is prevalent but largely underestimated. Furthermore, validation evidence is appealing for future GWAS, especially in the context of emerging genome-editing technologies.

Determining the evolutionary forces shaping G × E

Contents Summary 31 I. Introduction 31 II. The maintenance of genetic variation for plasticity 32 III. Why is there environmental variation for genetic effects? 33 IV. Conclusions 35 Acknowledgements 35 References 35 SUMMARY: Phenotypic plasticity is common in nature, yet we lack a comprehensive understanding of the evolutionary forces that shape genetic variation for plasticity. This endeavor is especially important because variation for plasticity will result in genotype-by-environment interactions (G × E), a crucial component of variation in quantitative traits. Here, I review our understanding of the evolutionary forces shaping G × E, focusing specifically on: what evolutionary forces maintain variation for plasticity; and what forces maintain different genetic architectures across environments. My specific goal is to show that genomic data can be leveraged to explain the maintenance of G × E by contrasting patterns of genetic variation for plasticity with neutral expectations.

On the post-glacial spread of human commensal Arabidopsis thaliana

Recent work has shown that Arabidopsis thaliana contains genetic groups originating from different ice age refugia, with one particular group comprising over 95% of the current worldwide population. In Europe, relicts of other groups can be found in local populations along the Mediterranean Sea. Here we provide evidence that these 'relicts' occupied post-glacial Eurasia first and were later replaced by the invading 'non-relicts', which expanded through the east-west axis of Eurasia, leaving traces of admixture in the north and south of the species range. The non-relict expansion was likely associated with human activity and led to a demographic replacement similar to what occurred in humans. Introgressed genomic regions from relicts are associated with flowering time and enriched for genes associated with environmental conditions, such as root cap development or metal ion trans-membrane transport, which suggest that admixture with locally adapted relicts helped the non-relicts colonize new habitats.

Genetic architecture of plant stress resistance: multi-trait genome-wide association mapping

Plants are exposed to combinations of various biotic and abiotic stresses, but stress responses are usually investigated for single stresses only. Here, we investigated the genetic architecture underlying plant responses to 11 single stresses and several of their combinations by phenotyping 350 Arabidopsis thaliana accessions. A set of 214 000 single nucleotide polymorphisms (SNPs) was screened for marker-trait associations in genome-wide association (GWA) analyses using tailored multi-trait mixed models. Stress responses that share phytohormonal signaling pathways also share genetic architecture underlying these responses. After removing the effects of general robustness, for the 30 most significant SNPs, average quantitative trait locus (QTL) effect sizes were larger for dual stresses than for single stresses. Plants appear to deploy broad-spectrum defensive mechanisms influencing multiple traits in response to combined stresses. Association analyses identified QTLs with contrasting and with similar responses to biotic vs abiotic stresses, and below-ground vs above-ground stresses. Our approach allowed for an unprecedented comprehensive genetic analysis of how plants deal with a wide spectrum of stress conditions.

Genotypes, Networks, Phenotypes: Moving Toward Plant Systems Genetics

One of the central goals in biology is to understand how and how much of the phenotype of an organism is encoded in its genome. Although many genes that are crucial for organismal processes have been identified, much less is known about the genetic bases underlying quantitative phenotypic differences in natural populations. We discuss the fundamental gap between the large body of knowledge generated over the past decades by experimental genetics in the laboratory and what is needed to understand the genotype-to-phenotype problem on a broader scale. We argue that systems genetics, a combination of systems biology and the study of natural variation using quantitative genetics, will help to address this problem. We present major advances in these two mostly disconnected areas that have increased our understanding of the developmental processes of flowering time control and root growth. We conclude by illustrating and discussing the efforts that have been made toward systems genetics specifically in plants.

Population Genomics for Understanding Adaptation in Wild Plant Species

Darwin's theory of evolution by natural selection is the foundation of modern biology. However, it has proven remarkably difficult to demonstrate at the genetic, genomic, and population level exactly how wild species adapt to their natural environments. We discuss how one can use large sets of multiple genome sequences from wild populations to understand adaptation, with an emphasis on the small herbaceous plant Arabidopsis thaliana. We present motivation for such studies; summarize progress in describing whole-genome, species-wide sequence variation; and then discuss what insights have emerged from these resources, either based on sequence information alone or in combination with phenotypic data. We conclude with thoughts on opportunities with other plant species and the impact of expected progress in sequencing technology and genome engineering for studying adaptation in nature.

"Missing" G x E Variation Controls Flowering Time in Arabidopsis thaliana

Understanding how genetic variation interacts with the environment is essential for understanding adaptation. In particular, the life cycle of plants is tightly coordinated with local environmental signals through complex interactions with the genetic variation (G x E). The mechanistic basis for G x E is almost completely unknown. We collected flowering time data for 173 natural inbred lines of Arabidopsis thaliana from Sweden under two growth temperatures (10°C and 16°C), and observed massive G x E variation. To identify the genetic polymorphisms underlying this variation, we conducted genome-wide scans using both SNPs and local variance components. The SNP-based scan identified several variants that had common effects in both environments, but found no trace of G x E effects, whereas the scan using local variance components found both. Furthermore, the G x E effects appears to be concentrated in a small fraction of the genome (0.5%). Our conclusion is that G x E effects in this study are mostly due to large numbers of allele or haplotypes at a small number of loci, many of which correspond to previously identified flowering time genes.

From phenotypes to causal sequences: using genome wide association studies to dissect the sequence basis for variation of plant development

Tremendous natural variation of growth and development exists within species. Uncovering the molecular mechanisms that tune growth and development promises to shed light on a broad set of biological issues including genotype to phenotype relations, regulatory mechanisms of biological processes and evolutionary questions. Recent progress in sequencing and data processing capabilities has enabled Genome Wide Association Studies (GWASs) to identify DNA sequence polymorphisms that underlie the variation of biological traits. In the last years, GWASs have proven powerful in revealing the complex genetic bases of many phenotypes in various plant species. Here we highlight successful recent GWASs that uncovered mechanistic and sequence bases of trait variation related to plant growth and development and discuss important considerations for conducting successful GWASs.

Genome-wide association mapping identifies a new arsenate reductase enzyme critical for limiting arsenic accumulation in plants

Inorganic arsenic is a carcinogen, and its ingestion through foods such as rice presents a significant risk to human health. Plants chemically reduce arsenate to arsenite. Using genome-wide association (GWA) mapping of loci controlling natural variation in arsenic accumulation in Arabidopsis thaliana allowed us to identify the arsenate reductase required for this reduction, which we named High Arsenic Content 1 (HAC1). Complementation verified the identity of HAC1, and expression in Escherichia coli lacking a functional arsenate reductase confirmed the arsenate reductase activity of HAC1. The HAC1 protein accumulates in the epidermis, the outer cell layer of the root, and also in the pericycle cells surrounding the central vascular tissue. Plants lacking HAC1 lose their ability to efflux arsenite from roots, leading to both increased transport of arsenic into the central vascular tissue and on into the shoot. HAC1 therefore functions to reduce arsenate to arsenite in the outer cell layer of the root, facilitating efflux of arsenic as arsenite back into the soil to limit both its accumulation in the root and transport to the shoot. Arsenate reduction by HAC1 in the pericycle may play a role in limiting arsenic loading into the xylem. Loss of HAC1-encoded arsenic reduction leads to a significant increase in arsenic accumulation in shoots, causing an increased sensitivity to arsenate toxicity. We also confirmed the previous observation that the ACR2 arsenate reductase in A. thaliana plays no detectable role in arsenic metabolism. Furthermore, ACR2 does not interact epistatically with HAC1, since arsenic metabolism in the acr2 hac1 double mutant is disrupted in an identical manner to that described for the hac1 single mutant. Our identification of HAC1 and its associated natural variation provides an important new resource for the development of low arsenic-containing food such as rice.

Genotype×environment interaction QTL mapping in plants: lessons from Arabidopsis

Plant growth and development are influenced by the genetic composition of the plant (G), the environment (E), and the interaction between them (G×E). To produce suitable genotypes for multiple environments, G×E should be accounted for and assessed in plant-breeding programs. Here, we review the genetic basis of G×E and its consequence for quantitative trait loci (QTL) mapping in biparental and genome-wide association (GWA) mapping populations. We also consider the implications of G×E for understanding plant fitness trade-offs and evolutionary ecology.