Genetic architecture of flowering-time variation in Arabidopsis thaliana

Local climate and vernalization sensitivity predict the latitudinal patterns of flowering onset in the crop wild relative Linum bienne Mill

BACKGROUND AND AIMS

The timing of flowering onset is often correlated with latitude, indicative of climatic gradients. Flowering onset in temperate species commonly requires exposure to cold temperatures, known as vernalization. Hence, population differentiation of flowering onset with latitude might reflect adaptation to the local climatic conditions experienced by populations.

METHODS

Within its western range, seeds from Linum bienne populations (the wild relative of cultivated Linum usitatissimum) were used to describe the latitudinal differentiation of flowering onset to determine its association with the local climate of the population. A vernalization experiment including different crop cultivars was used to determine how vernalization accelerates flowering onset, in addition to the vernalization sensitivity response among populations and cultivars. Additionally, genetic differentiation of L. bienne populations along the latitudinal range was scrutinized using microsatellite markers.

KEY RESULTS

Flowering onset varied with latitude of origin, with southern populations flowering earlier than their northern counterparts. Vernalization reduced the number of days to flowering onset, but vernalization sensitivity was greater in northern populations compared with southern ones. Conversely, vernalization delayed flowering onset in the crop, exhibiting less variation in sensitivity. In L. bienne, both flowering onset and vernalization sensitivity were better predicted by the local climate of the population than by latitude itself. Microsatellite data unveiled genetic differentiation of populations, forming two groups geographically partitioned along latitude.

CONCLUSIONS

The consistent finding of latitudinal variation across experiments suggests that both flowering onset and vernalization sensitivity in L. bienne populations are under genetic regulation and might depend on climatic cues at the place of origin. The association with climatic gradients along latitude suggests that the climate experienced locally drives population differentiation of the flowering onset and vernalization sensitivity patterns. The genetic population structure suggests that past population history could have influenced the flowering initiation patterns detected, which deserves further work.

Flowering time: From physiology, through genetics to mechanism

Plant species have evolved different requirements for environmental/endogenous cues to induce flowering. Originally, these varying requirements were thought to reflect the action of different molecular mechanisms. Thinking changed when genetic and molecular analysis in Arabidopsis thaliana revealed that a network of environmental and endogenous signaling input pathways converge to regulate a common set of "floral pathway integrators." Variation in the predominance of the different input pathways within a network can generate the diversity of requirements observed in different species. Many genes identified by flowering time mutants were found to encode general developmental and gene regulators, with their targets having a specific flowering function. Studies of natural variation in flowering were more successful at identifying genes acting as nodes in the network central to adaptation and domestication. Attention has now turned to mechanistic dissection of flowering time gene function and how that has changed during adaptation. This will inform breeding strategies for climate-proof crops and help define which genes act as critical flowering nodes in many other species.

Genetic Architecture of Flowering Time Differs Between Populations With Contrasting Demographic and Selective Histories

Understanding the evolutionary factors that impact the genetic architecture of traits is a central goal of evolutionary genetics. Here, we investigate how quantitative trait variation accumulated over time in populations that colonized a novel environment. We compare the genetic architecture of flowering time in Arabidopsis populations from the drought-prone Cape Verde Islands and their closest outgroup population from North Africa. We find that trait polygenicity is severely reduced in the island populations compared to the continental North African population. Further, trait architectures and reconstructed allelic histories best fit a model of strong directional selection in the islands in accord with a Fisher-Orr adaptive walk. Consistent with this, we find that large-effect variants that disrupt major flowering time genes (FRI and FLC) arose first, followed by smaller effect variants, including ATX2 L125F, which is associated with a 4-day reduction in flowering time. The most recently arising flowering time-associated loci are not known to be directly involved in flowering time, consistent with an omnigenic signature developing as the population approaches its trait optimum. Surprisingly, we find no effect in the natural population of EDI-Cvi-0 (CRY2 V367M), an allele for which an effect was previously validated by introgression into a Eurasian line. Instead, our results suggest the previously observed effect of the EDI-Cvi-0 allele on flowering time likely depends on genetic background, due to an epistatic interaction. Altogether, our results provide an empirical example of the effects demographic history and selection has on trait architecture.

Forecasting trait responses in novel environments to aid seed provenancing under climate change

Revegetation projects face the major challenge of sourcing optimal plant material. This is often done with limited information about plant performance and increasingly requires factoring resilience to climate change. Functional traits can be used as quantitative indices of plant performance and guide seed provenancing, but trait values expected under novel conditions are often unknown. To support climate-resilient provenancing efforts, we develop a trait prediction model that integrates the effect of genetic variation with fine-scale temperature variation. We train our model on multiple field plantings of Arabidopsis thaliana and predict two relevant fitness traits-days-to-bolting and fecundity-across the species' European range. Prediction accuracy was high for days-to-bolting and moderate for fecundity, with the majority of trait variation explained by temperature differences between plantings. Projection under future climate predicted a decline in fecundity, although this response was heterogeneous across the range. In response, we identified novel genotypes that could be introduced to genetically offset the fitness decay. Our study highlights the value of predictive models to aid seed provenancing and improve the success of revegetation projects.

Preadapted to adapt: underpinnings of adaptive plasticity revealed by the downy brome genome

Bromus tectorum L. is arguably the most successful invasive weed in the world. It has fundamentally altered arid ecosystems of the western United States, where it now found on an excess of 20 million hectares. Invasion success is related to avoidance of abiotic stress and human management. Early flowering is a heritable trait utilized by B. tectorum, enabling the species to temporally monopolize limited resources and outcompete the native plant community. Thus, understanding the genetic underpinning of flowering time is critical for the design of integrated management strategies. To study flowering time traits in B. tectorum, we assembled a chromosome scale reference genome for B. tectorum. To assess the utility of the assembled genome, 121 diverse B. tectorum accessions are phenotyped and subjected to a genome wide association study (GWAS). Candidate genes, representing homologs of genes that have been previously associated with plant height or flowering phenology traits in related species are located near QTLs we identified. This study uses a high-resolution GWAS to identify reproductive phenology genes in a weedy species and represents a considerable step forward in understanding the mechanisms underlying genetic plasticity in one of the most successful invasive weed species.

An efficient genomic prediction method without the direct inverse of the genomic relationship matrix

GBLUP, the most widely used genomic prediction (GP) method, consumes large and increasing amounts of computational resources as the training population size increases due to the inverse of the genomic relationship matrix (GRM). Therefore, in this study, we developed a new genomic prediction method (RHEPCG) that avoids the direct inverse of the GRM by combining randomized Haseman-Elston (HE) regression (RHE-reg) and a preconditioned conjugate gradient (PCG). The simulation results demonstrate that RHEPCG, in most cases, not only achieves similar predictive accuracy with GBLUP but also significantly reduces computational time. As for the real data, RHEPCG shows similar or better predictive accuracy for seven traits of the Arabidopsis thaliana F2 population and four traits of the Sorghum bicolor RIL population compared with GBLUP. This indicates that RHEPCG is a practical alternative to GBLUP and has better computational efficiency.

Co-expression pan-network reveals genes involved in complex traits within maize pan-genome

BACKGROUND

With the advances in the high throughput next generation sequencing technologies, genome-wide association studies (GWAS) have identified a large set of variants associated with complex phenotypic traits at a very fine scale. Despite the progress in GWAS, identification of genotype-phenotype relationship remains challenging in maize due to its nature with dozens of variants controlling the same trait. As the causal variations results in the change in expression, gene expression analyses carry a pivotal role in unraveling the transcriptional regulatory mechanisms behind the phenotypes.

RESULTS

To address these challenges, we incorporated the gene expression and GWAS-driven traits to extend the knowledge of genotype-phenotype relationships and transcriptional regulatory mechanisms behind the phenotypes. We constructed a large collection of gene co-expression networks and identified more than 2 million co-expressing gene pairs in the GWAS-driven pan-network which contains all the gene-pairs in individual genomes of the nested association mapping (NAM) population. We defined four sub-categories for the pan-network: (1) core-network contains the highest represented ~ 1% of the gene-pairs, (2) near-core network contains the next highest represented 1-5% of the gene-pairs, (3) private-network contains ~ 50% of the gene pairs that are unique to individual genomes, and (4) the dispensable-network contains the remaining 50-95% of the gene-pairs in the maize pan-genome. Strikingly, the private-network contained almost all the genes in the pan-network but lacked half of the interactions. We performed gene ontology (GO) enrichment analysis for the pan-, core-, and private- networks and compared the contributions of variants overlapping with genes and promoters to the GWAS-driven pan-network.

CONCLUSIONS

Gene co-expression networks revealed meaningful information about groups of co-regulated genes that play a central role in regulatory processes. Pan-network approach enabled us to visualize the global view of the gene regulatory network for the studied system that could not be well inferred by the core-network alone.

Genetic variation in reproductive timing in a long-lived herbaceous perennial

PREMISE

Reproductive fitness of individual plants depends on the timing of flowering, especially in mate-limited populations, such as those in fragmented habitats. When flowering time traits are associated with differential reproductive success, the narrow-sense heritability (h² ) of traits will determine how rapidly trait means evolve in response to selection. Heritability of flowering time is documented in many annual plants. However, estimating h² of flowering time in perennials presents additional methodological challenges, often including paternity assignment and trait expression over multiple years.

METHODS

We evaluated the h² of onset and duration of flowering using offspring-midparent regressions and restricted maximum likelihood methods in an experimental population of an iterocarpic, perennial, herbaceous plant, Echinacea angustifolia, growing in natural conditions. We assessed the flowering time of the parental cohort in 2005 and 2006; the offspring in 2014 through 2017. We also examined the effects of the paternity assignment from Cervus and MasterBayes on estimates of h² .

RESULTS

We found substantial h² for onset and duration of flowering. We also observed variation in estimates among years. The most reliable estimates for both traits fell in the range of 0.1-0.17. We found evidence of a genotype by year interaction for onset of flowering and strong evidence that genotypes are consistent in their duration of flowering across years.

CONCLUSIONS

Substantial heritabilities in this population imply the capacity for a response to natural selection, while also suggesting the potential for differential contributions to adaptive evolution among seasons.

A Pleiotropic Flowering Time QTL Exhibits Gene-by-Environment Interaction for Fitness in a Perennial Grass

Appropriate flowering time is a crucial adaptation impacting fitness in natural plant populations. Although the genetic basis of flowering variation has been extensively studied, its mechanisms in nonmodel organisms and its adaptive value in the field are still poorly understood. Here, we report new insights into the genetic basis of flowering time and its effect on fitness in Panicum hallii, a native perennial grass. Genetic mapping in populations derived from inland and coastal ecotypes identified flowering time quantitative trait loci (QTL) and many exhibited extensive QTL-by-environment interactions. Patterns of segregation within recombinant hybrids provide strong support for directional selection driving ecotypic divergence in flowering time. A major QTL on chromosome 5 (q-FT5) was detected in all experiments. Fine-mapping and expression studies identified a gene with orthology to a rice FLOWERING LOCUS T-like 9 (PhFTL9) as the candidate underlying q-FT5. We used a reciprocal transplant experiment to test for local adaptation and the specific impact of q-FT5 on performance. We did not observe local adaptation in terms of fitness tradeoffs when contrasting ecotypes in home versus away habitats. However, we observed that the coastal allele of q-FT5 conferred a fitness advantage only in its local habitat but not at the inland site. Sequence analyses identified an excess of low-frequency polymorphisms at the PhFTL9 promoter in the inland lineage, suggesting a role for either selection or population expansion on promoter evolution. Together, our findings demonstrate the genetic basis of flowering variation in a perennial grass and provide evidence for conditional neutrality underlying flowering time divergence.

Genome-wide identification and characterization of AP2/ERF gene superfamily during flower development in Actinidia eriantha

Background

As one of the largest transcription factor families in plants, AP2/ERF gene superfamily plays important roles in plant growth, development, fruit ripening and biotic and abiotic stress responses. Despite the great progress has been made in kiwifruit genomic studies, little research has been conducted on the AP2/ERF genes of kiwifruit. The increasing kiwifruit genome resources allowed us to reveal the tissue expression profiles of AP2/ERF genes in kiwifruit on a genome-wide basis.

Results

In present study, a total of 158 AP2/ERF genes in A. eriantha were identified. All genes can be mapped on the 29 chromosomes. Phylogenetic analysis divided them into four main subfamilies based on the complete protein sequences. Additionally, our results revealed that the same subfamilies contained similar gene structures and conserved motifs. Ka/Ks calculation indicated that AP2/ERF gene family was undergoing a strong purifying selection and the evolutionary rates were slow. RNA-seq showed that the AP2/ERF genes were expressed differently in different flower development stages and 56 genes were considered as DEGs among three contrasts. Moreover, qRT-PCR suggested partial genes showed significant expressions as well, suggesting they could be key regulators in flower development in A. eriantha. In addition, two genes (AeAP2/ERF061, AeAP2/ERF067) had abundant transcription level based on transcriptomes, implying that they may play a crucial role in plant flower development regulation and flower tissue forming.

Conclusions

We identified AP2/ERF genes and demonstrated their gene structures, conserved motifs, and phylogeny relationships of AP2/ERF genes in two related species of kiwifruit, A. eriantha and A. chinensis, and their potential roles in flower development in A. eriantha. Such information would lay the foundation for further functional identification of AP2/ERF genes involved in kiwifruit flower development.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08871-4.

MicroRNA miR394 regulates flowering time in Arabidopsis thaliana

miR394 regulates Arabidopsis flowering time in a LCR-independent manner. Arabidopsis plants harboring mutations in theMIR394 genes exhibit early flowering, lower expression of floral repressor FLC and higher expression of floral integrators FT and SOC1. Plant development occurs throughout its entire life cycle and involves a phase transition between vegetative and reproductive phases, leading to the flowering process, fruit formation and ultimately seed production. It has been shown that the microRNA394 (miR394) regulates the accumulation of the transcript coding for LEAF CURLING RESPONSIVENESS, a member of a family of F-Box proteins. The miR394 pathway regulates several processes including leaf morphology and development of the shoot apical meristem during embryogenesis, as well as having been assigned a role in the response to biotic and abiotic stress in Arabidopsis thaliana and other species. Here, we characterized plants harboring mutations in MIR394 precursor genes and demonstrate that mir394a mir394b double mutants display an early flowering phenotype which correlates with a lower expression of FLOWERING LOCUS C earlier in development and higher expression of the floral integrators FLOWERING LOCUS T and SUPPRESSOR OF OVEREXPRESSION OF CONSTANS 1. Consequently, mutant plants produce fewer branches and exhibit lower seed production. Our work reveals previously unknown developmental aspects regulated by the miR394 pathway, in an LCR-independent manner, contributing to the characterization of the multiple roles of this versatile plant regulatory miRNA.

GWAS and bulked segregant analysis reveal the Loci controlling growth habit-related traits in cultivated Peanut (Arachis hypogaea L.)

Background

Peanut (Arachis hypogaea L.) is a grain legume crop that originated from South America and is now grown around the world. Peanut growth habit affects the variety’s adaptability, planting patterns, mechanized harvesting, disease resistance, and yield. The objective of this study was to map the quantitative trait locus (QTL) associated with peanut growth habit-related traits by combining the genome-wide association analysis (GWAS) and bulked segregant analysis sequencing (BSA-seq) methods.

Results

GWAS was performed with 17,223 single nucleotide polymorphisms (SNPs) in 103 accessions of the U.S. mini core collection genotyped using an Affymetrix version 2.0 SNP array. With a total of 12,342 high-quality polymorphic SNPs, the 90 suggestive and significant SNPs associated with lateral branch angle (LBA), main stem height (MSH), lateral branch height (LBL), extent radius (ER), and the index of plant type (IOPT) were identified. These SNPs were distributed among 15 chromosomes. A total of 597 associated candidate genes may have important roles in biological processes, hormone signaling, growth, and development. BSA-seq coupled with specific length amplified fragment sequencing (SLAF-seq) method was used to find the association with LBA, an important trait of the peanut growth habit. A 4.08 Mb genomic region on B05 was associated with LBA. Based on the linkage disequilibrium (LD) decay distance, we narrowed down and confirmed the region within the 160 kb region (144,193,467–144,513,467) on B05. Four candidate genes in this region were involved in plant growth. The expression levels of Araip.E64SW detected by qRT-PCR showed significant difference between ‘Jihua 5’ and ‘M130’.

Conclusions

In this study, the SNP (AX-147,251,085 and AX-144,353,467) associated with LBA by GWAS was overlapped with the results in BSA-seq through combined analysis of GWAS and BSA-seq. Based on LD decay distance, the genome range related to LBA on B05 was shortened to 144,193,467–144,513,467. Three candidate genes related to F-box family proteins (Araip.E64SW, Araip.YG1LK, and Araip.JJ6RA) and one candidate gene related to PPP family proteins (Araip.YU281) may be involved in plant growth and development in this genome region. The expression analysis revealed that Araip.E64SW was involved in peanut growth habits. These candidate genes will provide molecular targets in marker-assisted selection for peanut growth habits.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08640-3.

Parallel reduction in flowering time from de novo mutations enable evolutionary rescue in colonizing lineages

Understanding how populations adapt to abrupt environmental change is necessary to predict responses to future challenges, but identifying specific adaptive variants, quantifying their responses to selection and reconstructing their detailed histories is challenging in natural populations. Here, we use Arabidopsis from the Cape Verde Islands as a model to investigate the mechanisms of adaptation after a sudden shift to a more arid climate. We find genome-wide evidence of adaptation after a multivariate change in selection pressures. In particular, time to flowering is reduced in parallel across islands, substantially increasing fitness. This change is mediated by convergent de novo loss of function of two core flowering time genes: FRI on one island and FLC on the other. Evolutionary reconstructions reveal a case where expansion of the new populations coincided with the emergence and proliferation of these variants, consistent with models of rapid adaptation and evolutionary rescue.

Detailing how populations adapted to environmental change is needed to predict future responses, but identifying adaptive variants and detailing their fitness effects is rare. Here, the authors show that parallel loss of FRI and FLC function reduces time to flowering and drives adaptation in a drought prone environment.

Time outweighs the effect of host developmental stage on microbial community composition

Thousands of microbial taxa in the soil form symbioses with host plants, and due to their contribution to plant performance, these microbes are often considered an extension of the host genome. Given microbial effects on host performance, it is important to understand factors that govern microbial community assembly. Host developmental stage could affect rhizosphere microbial diversity while, alternatively, microbial assemblages could change simply as a consequence of time and the opportunity for microbial succession. Previous studies suggest that rhizosphere microbial assemblages shift across plant developmental stages, but time since germination is confounded with developmental stage. We asked how elapsed time and potential microbial succession relative to host development affected microbial diversity in the rhizosphere using monogenic flowering-time mutants of Arabidopsis thaliana. Under our experimental design, different developmental stages were present among host genotypes after the same amount of time following germination, e.g. at 76 days following germination some host genotypes were flowering while others were fruiting or senescing. We found that elapsed time was a strong predictor of microbial diversity whereas there were few differences among developmental stages. Our results support the idea that time and, likely, microbial succession more strongly affect microbial community assembly than host developmental stage.

Natural variation in plant telomere length is associated with flowering time

Telomeres are highly repetitive DNA sequences found at the ends of chromosomes that protect the chromosomes from deterioration duringcell division. Here, using whole-genome re-sequencing and terminal restriction fragment assays, we found substantial natural intraspecific variation in telomere length in Arabidopsis thaliana, rice (Oryza sativa), and maize (Zea mays). Genome-wide association study (GWAS) mapping in A. thaliana identified 13 regions with GWAS-significant associations underlying telomere length variation, including a region that harbors the telomerase reverse transcriptase (TERT) gene. Population genomic analysis provided evidence for a selective sweep at the TERT region associated with longer telomeres. We found that telomere length is negatively correlated with flowering time variation not only in A. thaliana, but also in maize and rice, indicating a link between life-history traits and chromosome integrity. Our results point to several possible reasons for this correlation, including the possibility that longer telomeres may be more adaptive in plants that have faster developmental rates (and therefore flower earlier). Our work suggests that chromosomal structure itself might be an adaptive trait associated with plant life-history strategies.

Polygenic Adaptation: Integrating Population Genetics and Gene Regulatory Networks

The adaptation of populations to local environments often relies on the selection of optimal values for polygenic traits. Here, we first summarize the results obtained from different quantitative genetics and population genetics models, about the genetic architecture of polygenic traits and their response to directional selection. We then highlight the contribution of systems biology to the understanding of the molecular bases of polygenic traits and the evolution of gene regulatory networks involved in these traits. Finally, we discuss the need for a unifying framework merging the fields of population genetics, quantitative genetics and systems biology to better understand the molecular bases of polygenic traits adaptation.

Genetic architecture affecting maize agronomic traits identified by variance heterogeneity association mapping

Conventional genome-wide association studies (GWAS) focused on the phenotypic mean differences (mGWAS) but often ignored genetic variants influencing differences in the variance between genotypes. In this study, we performed variance heterogeneity GWAS (vGWAS) analysis for 13 previously measured agronomic traits in a maize population. We discovered a total of 129 significant SNPs. We demonstrated that the genetic loci influencing mean differences and variance heterogeneity formed distinct groups, suggesting that breeders were able to independently select for phenotype mean and variance values. Moreover, vGWAS served as a tractable approach to effectively identify 214 epistatic interaction pairs. In addition, we documented four agronomic traits with decreasing phenotype variance during modern maize breeding history and identified the potential genetic variants influencing this process. In summary, we discovered additional non-additive effects contributing to missing heritability and valuable genetic variants used for breeding varieties with desired phenotypic variance.

Natural variation in stress response induced by low CO2 in Arabidopsis thaliana

Variation in atmospheric carbon dioxide (CO₂) concentration can dictate plant growth and development and shape plant evolution. For paired populations of 31 Arabidopsis accessions, respectively, grown under 100 or 380 ppm CO₂, we compared phenotypic traits related to vegetative growth and flowering time. Four accessions showed the least variation in measured growth traits between 100 ppm CO₂ and 380 ppm CO₂ conditions, though all accessions exhibited a dwarf stature with reduced biomass under low CO₂. Our comparison of accessions also incorporated the altitude (indicated in meters) above sea level at which they were originally collected. Notably, An-1 (50 m), Est (50 m), Ws-0 (150 m), and Ler-0 (600 m) showed the least differences (lower decrease or increase) between treatments in flowering time, rosette leaf number, specific leaf weight, stomatal density, and less negative δ¹³C values. When variations for all traits and seedset were considered together, Ws-0 exhibited the least change between treatments. Our results showed that physiological and phenotypic responses to low CO₂ varied among these accessions and did not correlate linearly with altitude, thus suggesting that slower growth or smaller stature under ambient CO₂ may potentially belie a fitness advantage for sustainable growth under low CO₂ availability.

Multiple Loci Control Variation in Plasticity to Foliar Shade Throughout Development in Arabidopsis thaliana

The shade avoidance response is a set of developmental changes exhibited by plants to avoid shading by competitors, and is an important model of adaptive plant plasticity. While the mechanisms of sensing shading by other plants are well-known and appear conserved across plants, less is known about the developmental mechanisms that result in the diverse array of morphological and phenological responses to shading. This is particularly true for traits that appear later in plant development. Here we use a nested association mapping (NAM) population of Arabidopsis thaliana to decipher the genetic architecture of the shade avoidance response in late-vegetative and reproductive plants. We focused on four traits: bolting time, rosette size, inflorescence growth rate, and inflorescence size, found plasticity in each trait in response to shade, and detected 17 total QTL; at least one of which is a novel locus not previously identified for shade responses in Arabidopsis. Using path analysis, we dissected each colocalizing QTL into direct effects on each trait and indirect effects transmitted through direct effects on earlier developmental traits. Doing this separately for each of the seven NAM populations in each environment, we discovered considerable heterogeneity among the QTL effects across populations, suggesting allelic series at multiple QTL or interactions between QTL and the genetic background or the environment. Our results provide insight into the development and variation in shade avoidance responses in Arabidopsis, and emphasize the value of directly modeling the relationships among traits when studying the genetics of complex developmental syndromes.

Temperature-Dependent Alternative Splicing of Precursor mRNAs and Its Biological Significance: A Review Focused on Post-Transcriptional Regulation of a Cold Shock Protein Gene in Hibernating Mammals

Multiple mRNA isoforms are often generated during processing such as alternative splicing of precursor mRNAs (pre-mRNA), resulting in a diversity of generated proteins. Alternative splicing is an essential mechanism for the functional complexity of eukaryotes. Temperature, which is involved in all life activities at various levels, is one of regulatory factors for controlling patterns of alternative splicing. Temperature-dependent alternative splicing is associated with various phenotypes such as flowering and circadian clock in plants and sex determination in poikilothermic animals. In some specific situations, temperature-dependent alternative splicing can be evoked even in homothermal animals. For example, the splicing pattern of mRNA for a cold shock protein, cold-inducible RNA-binding protein (CIRP or CIRBP), is changed in response to a marked drop in body temperature during hibernation of hamsters. In this review, we describe the current knowledge about mechanisms and functions of temperature-dependent alternative splicing in plants and animals. Then we discuss the physiological significance of hypothermia-induced alternative splicing of a cold shock protein gene in hibernating and non-hibernating animals.

Ten Years of the Maize Nested Association Mapping Population: Impact, Limitations, and Future Directions

It has been just over a decade since the release of the maize (Zea mays) Nested Association Mapping (NAM) population. The NAM population has been and continues to be an invaluable resource for the maize genetics community and has yielded insights into the genetic architecture of complex traits. The parental lines have become some of the most well-characterized maize germplasm, and their de novo assemblies were recently made publicly available. As we enter an exciting new stage in maize genomics, this retrospective will summarize the design and intentions behind the NAM population; its application, the discoveries it has enabled, and its influence in other systems; and use the past decade of hindsight to consider whether and how it will remain useful in a new age of genomics.

Evaluating Population Genomic Candidate Genes Underlying Flowering Time in Arabidopsis thaliana Using T-DNA Insertion Lines

Population genomic scans have emerged as a powerful tool to detect regions of the genome that are potential targets of selection. Despite the success of genomic scans in identifying novel lists of loci potentially underlying adaptation, few studies proceed to validate the function of these candidate genes. In this study, we used transfer-DNA (T-DNA) insertion lines to evaluate the effects of 27 candidate genes on flowering time in North American accessions of Arabidopsis thaliana. We compared the flowering time of T-DNA insertion lines that knock out the function of a candidate gene obtained from population genomic studies to a wild type under long- and short-day conditions. We also did the same for a collection of randomly chosen genes that had not been identified as candidates. We validated the well-known effect of long-day conditions in accelerating flowering time and found that gene disruption caused by insertional mutagenesis tends to delay flowering. Surprisingly, we found that knockouts in random genes were just as likely to produce significant phenotypic effects as knockouts in candidate genes. T-DNA insertions at a handful of candidate genes that had previously been identified as outlier loci showed significant delays in flowering time under both long and short days, suggesting that they are promising candidates for future investigation.

Synchronization of senescence and desynchronization of flowering in Arabidopsis thaliana

In a recent publication, we proposed that adjusting lifespan in order to synchronize senescence is important for timing of reproduction, and we quantified the synchrony of reproductive timing relative to germination timing. Here, in a second sequential seeding experiment (SSE), the germination timing of Arabidopsis thaliana accessions was manipulated and plants were then grown under two different temperature regimes. Life stage traits of plants in each temperature regime were analysed and it was evaluated whether the cohorts were grouped according to age and/or environmental conditions. While flowering-related traits showed desynchrony among cohorts, striking synchrony in the timing of senescence among cohorts for each group was found. A quantitative trait locus (QTL) analysis using a genotyped population of 'Cvi/Ler' recombinant inbred lines (RILs) was then conducted. Novel and known loci were assigned to flowering and senescence timing. However, senescence synchrony resulted in low variation in senescence time and weak QTL detection for flowering termination. Overlapping flowering and senescence genes with loci affecting either of those traits were found and suggest a potential interdependency of reproductive traits.

Mapping QTLs for 15 morpho-metric traits in Arabidopsis thaliana using Col-0 × Don-0 population

Genome wide quantitative trait loci (QTL) mapping was conducted in Arabidopsis thaliana using F₂ mapping population (Col-0 × Don-0) and SNPs markers. A total of five linkage groups were obtained with number of SNPs varying from 45 to 59 per linkage group. The composite interval mapping detected a total of 36 QTLs for 15 traits and the number of QTLs ranged from one (root length, root dry biomass, cauline leaf width, number of internodes and internode distance) to seven (for bolting days). The range of phenotypic variance explained (PVE) and logarithm of the odds ratio of these 36 QTLs was found be 0.19-38.17% and 3.0-6.26 respectively. Further, the epistatic interaction detected one main effect QTL and four epistatic QTLs. Five major QTLs viz. Qbd.nbri.4.3, Qfd.nbri.4.2, Qrdm.nbri.5.1, Qncl.nbri.2.2, Qtd.nbri.4.1 with PVE > 15.0% might be useful for fine mapping to identify genes associated with respective traits, and also for development of specialized population through marker assisted selection. The identification of additive and dominant effect QTLs and desirable alleles of each of above mentioned traits would also be important for future research.

Evolutionary processes from the perspective of flowering time diversity

Although it is well appreciated that genetic studies of flowering time regulation have led to fundamental advances in the fields of molecular and developmental biology, the ways in which genetic studies of flowering time diversity have enriched the field of evolutionary biology have received less attention despite often being equally profound. Because flowering time is a complex, environmentally responsive trait that has critical impacts on plant fitness, crop yield, and reproductive isolation, research into the genetic architecture and molecular basis of its evolution continues to yield novel insights into our understanding of domestication, adaptation, and speciation. For instance, recent studies of flowering time variation have reconstructed how, when, and where polygenic evolution of phenotypic plasticity proceeded from standing variation and de novo mutations; shown how antagonistic pleiotropy and temporally varying selection maintain polymorphisms in natural populations; and provided important case studies of how assortative mating can evolve and facilitate speciation with gene flow. In addition, functional studies have built detailed regulatory networks for this trait in diverse taxa, leading to new knowledge about how and why developmental pathways are rewired and elaborated through evolutionary time.

Variance heterogeneity genome-wide mapping for cadmium in bread wheat reveals novel genomic loci and epistatic interactions

Genome-wide association mapping identifies quantitative trait loci (QTL) that influence the mean differences between the marker genotypes for a given trait. While most loci influence the mean value of a trait, certain loci, known as variance heterogeneity QTL (vQTL) determine the variability of the trait instead of the mean trait value (mQTL). In the present study, we performed a variance heterogeneity genome-wide association study (vGWAS) for grain cadmium (Cd) concentration in bread wheat. We used double generalized linear model and hierarchical generalized linear model to identify vQTL associated with grain Cd. We identified novel vQTL regions on chromosomes 2A and 2B that contribute to the Cd variation and loci that affect both mean and variance heterogeneity (mvQTL) on chromosome 5A. In addition, our results demonstrated the presence of epistatic interactions between vQTL and mvQTL, which could explain variance heterogeneity. Overall, we provide novel insights into the genetic architecture of grain Cd concentration and report the first application of vGWAS in wheat. Moreover, our findings indicated that epistasis is an important mechanism underlying natural variation for grain Cd concentration.

Gene Expression Modularity Reveals Footprints of Polygenic Adaptation in Theobroma cacao

Separating footprints of adaptation from demography is challenging. When selection has acted on a single locus with major effect, this issue can be alleviated through signatures left by selective sweeps. However, as adaptation is often driven by small allele frequency shifts at many loci, studies focusing on single genes are able to identify only a small portion of genomic variants responsible for adaptation. In face of this challenge, we utilize coexpression information to search for signals of polygenetic adaptation in Theobroma cacao, a tropical tree species that is the source of chocolate. Using transcriptomics and a weighted correlation network analysis, we group genes with similar expression patterns into functional modules. We then ask whether modules enriched for specific biological processes exhibit cumulative effects of differential selection in the form of high FST and dXY between populations. Indeed, modules putatively involved in protein modification, flowering, and water transport show signs of polygenic adaptation even though individual genes that are members of those groups do not bear strong signatures of selection. Modeling of demography, background selection, and the effects of genomic features reveal that these patterns are unlikely to arise by chance. We also find that specific modules are enriched for signals of strong or relaxed purifying selection, with one module bearing signs of adaptive differentiation and an excess of deleterious mutations. Our results provide insight into polygenic adaptation and contribute to understanding of population structure, demographic history, and genome evolution in T. cacao.

In the presence of population structure: From genomics to candidate genes underlying local adaptation

Understanding the genomic signatures, genes, and traits underlying local adaptation of organisms to heterogeneous environments is of central importance to the field evolutionary biology. To identify loci underlying local adaptation, models that combine allelic and environmental variation while controlling for the effects of population structure have emerged as the method of choice. Despite being evaluated in simulation studies, there has not been a thorough investigation of empirical evidence supporting local adaptation across these alleles. To evaluate these methods, we use 875 Arabidopsis thaliana Eurasian accessions and two mixed models (GEMMA and LFMM) to identify candidate SNPs underlying local adaptation to climate. Subsequently, to assess evidence of local adaptation and function among significant SNPs, we examine allele frequency differentiation and recent selection across Eurasian populations, in addition to their distribution along quantitative trait loci (QTL) explaining fitness variation between Italy and Sweden populations and cis-regulatory/nonsynonymous sites showing significant selective constraint. Our results indicate that significant LFMM/GEMMA SNPs show low allele frequency differentiation and linkage disequilibrium across locally adapted Italy and Sweden populations, in addition to a poor association with fitness QTL peaks (highest logarithm of odds score). Furthermore, when examining derived allele frequencies across the Eurasian range, we find that these SNPs are enriched in low-frequency variants that show very large climatic differentiation but low levels of linkage disequilibrium. These results suggest that their enrichment along putative functional sites most likely represents deleterious variation that is independent of local adaptation. Among all the genomic signatures examined, only SNPs showing high absolute allele frequency differentiation (AFD) and linkage disequilibrium (LD) between Italy and Sweden populations showed a strong association with fitness QTL peaks and were enriched along selectively constrained cis-regulatory/nonsynonymous sites. Using these SNPs, we find strong evidence linking flowering time, freezing tolerance, and the abscisic-acid pathway to local adaptation.

In the presence of population structure: From genomics to candidate genes underlying local adaptation

Understanding the genomic signatures, genes, and traits underlying local adaptation of organisms to heterogeneous environments is of central importance to the field evolutionary biology. To identify loci underlying local adaptation, models that combine allelic and environmental variation while controlling for the effects of population structure have emerged as the method of choice. Despite being evaluated in simulation studies, there has not been a thorough investigation of empirical evidence supporting local adaptation across these alleles. To evaluate these methods, we use 875 Arabidopsis thaliana Eurasian accessions and two mixed models (GEMMA and LFMM) to identify candidate SNPs underlying local adaptation to climate. Subsequently, to assess evidence of local adaptation and function among significant SNPs, we examine allele frequency differentiation and recent selection across Eurasian populations, in addition to their distribution along quantitative trait loci (QTL) explaining fitness variation between Italy and Sweden populations and cis-regulatory/nonsynonymous sites showing significant selective constraint. Our results indicate that significant LFMM/GEMMA SNPs show low allele frequency differentiation and linkage disequilibrium across locally adapted Italy and Sweden populations, in addition to a poor association with fitness QTL peaks (highest logarithm of odds score). Furthermore, when examining derived allele frequencies across the Eurasian range, we find that these SNPs are enriched in low-frequency variants that show very large climatic differentiation but low levels of linkage disequilibrium. These results suggest that their enrichment along putative functional sites most likely represents deleterious variation that is independent of local adaptation. Among all the genomic signatures examined, only SNPs showing high absolute allele frequency differentiation (AFD) and linkage disequilibrium (LD) between Italy and Sweden populations showed a strong association with fitness QTL peaks and were enriched along selectively constrained cis-regulatory/nonsynonymous sites. Using these SNPs, we find strong evidence linking flowering time, freezing tolerance, and the abscisic-acid pathway to local adaptation.

Assessing by Modeling the Consequences of Increased Recombination in Recurrent Selection of Oryza sativa and Brassica rapa

Meiotic recombination generates genetic diversity but in most species the number of crossovers per meiosis is limited. Previous modeling studies showed that increasing recombination can enhance response to selection. However, such studies did not assume a specific method of modifying recombination. Our objective was to test whether two methods used to increase recombination in plants could increase genetic gain in a population undergoing recurrent selection such as in genomic selection programs. The first method, in Oryza sativa, used a mutant of anti-crossover genes, increasing global recombination without affecting the recombination landscape shape. The second one used the ploidy level of a cross between Brassica rapa and Brassica napus, increasing recombination especially in pericentromeric regions. Our modeling framework used these recombination landscapes and sampled quantitative trait loci positions from the actual gene distributions. We simulated selection programs with initially a cross between two inbred lines, for two species. Increased recombination enhanced the response to selection. The amount of enhancement in the cumulative gain largely depended on the species and the number of quantitative trait loci (2, 10, 20, 50, 200 or 1000 per chromosome). Genetic gains were increased up to 30% after 20 generations. Furthermore, increasing recombination in cold regions was the most effective: the gain was larger by 25% with the first method and 34% with the second one in B. rapa, and 12% compared to 16% in O. sativa In summary, increased recombination enhances the genetic gain in long-term selection programs, with visible effects after four to five generations.

Standard Deviations: The Biological Bases of Transmission Ratio Distortion

The rule of Mendelian inheritance is remarkably robust, but deviations from the equal transmission of alternative alleles at a locus [a.k.a. transmission ratio distortion (TRD)] are also commonly observed in genetic mapping populations. Such TRD reveals locus-specific selection acting at some point between the diploid heterozygous parents and progeny genotyping and therefore can provide novel insight into otherwise-hidden genetic and evolutionary processes. Most of the classic selfish genetic elements were discovered through their biasing of transmission, but many unselfish evolutionary and developmental processes can also generate TRD. In this review, we describe methodologies for detecting TRD in mapping populations, detail the arenas and genetic interactions that shape TRD during plant and animal reproduction, and summarize patterns of TRD from across the genetic mapping literature. Finally, we point to new experimental approaches that can accelerate both detection of TRD and characterization of the underlying genetic mechanisms.

Statistical tests for detecting variance effects in quantitative trait studies

Motivation

Identifying variants, both discrete and continuous, that are associated with quantitative traits, or QTs, is the primary focus of quantitative genetics. Most current methods are limited to identifying mean effects, or associations between genotype or covariates and the mean value of a quantitative trait. It is possible, however, that a variant may affect the variance of the quantitative trait in lieu of, or in addition to, affecting the trait mean. Here, we develop a general methodology to identify covariates with variance effects on a quantitative trait using a Bayesian heteroskedastic linear regression model (BTH). We compare BTH with existing methods to detect variance effects across a large range of simulations drawn from scenarios common to the analysis of quantitative traits.

Results

We find that BTH and a double generalized linear model (dglm) outperform classical tests used for detecting variance effects in recent genomic studies. We show BTH and dglm are less likely to generate spurious discoveries through simulations and application to identifying methylation variance QTs and expression variance QTs. We identify four variance effects of sex in the Cardiovascular and Pharmacogenetics study. Our work is the first to offer a comprehensive view of variance identifying methodology. We identify shortcomings in previously used methodology and provide a more conservative and robust alternative. We extend variance effect analysis to a wide array of covariates that enables a new statistical dimension in the study of sex and age specific quantitative trait effects.

Availability and implementation

https://github.com/b2du/bth.

Supplementary information

Supplementary data are available at Bioinformatics online.

Inflorescence shoot elongation, but not flower primordia formation, is photoperiodically regulated in Arabidopsis lyrata

BACKGROUND AND AIMS

Photoperiod contains information about the progress of seasons. Plants use the changing photoperiod as a cue for the correct timing of important life history events, including flowering. Here the effect of photoperiod on flowering in four Arabidopsis lyrata populations originating from different latitudes was studied, as well as expression levels of candidate genes for governing the between-population differences.

METHODS

Flowering of plants from four A. lyrata populations was studied in three different photoperiods after vernalization. Flowering development was separated into three steps: flower primordia formation, inflorescence shoot elongation and opening of the first flower. Circadian expression rhythms of the A. lyrata homologues of GIGANTEA (GI), FLAVIN-BINDING, KELCH REPEAT, F-BOX 1 (FKF1), CONSTANS (CO) and FLOWERING LOCUS T (FT) were studied in three of the populations in the intermediate (14 h) photoperiod treatment.

KEY RESULTS

Most plants in all populations formed visible flower primordia during vernalization. Further inflorescence development after vernalization was strongly inhibited by short days in the northern European population (latitude 61°N), only slightly in the central European population (49°N) and not at all in the North American populations (36°N and 42°N). In the 14 h daylength, where all plants from the three southernmost populations but only 60 % of the northernmost population flowered, the circadian expression rhythm of the A. lyrata FT was only detected in the southern populations, suggesting differentiation in the critical daylength for activation of the long-day pathway. However, circadian expression rhythms of A. lyrata GI, FKF1 and CO were similar between populations.

CONCLUSIONS

The results indicate that in A. lyrata, transition to flowering can occur through pathways independent of long days, but elongation of inflorescences is photoperiodically regulated.

A Polygenic Genetic Architecture of Flowering Time in the Worldwide Arabidopsis thaliana Population

Here, we report an empirical study of the polygenic basis underlying the evolution of complex traits. Flowering time variation measured at 10 and 16°C in the 1,001-genomes Arabidopsis thaliana collection of natural accessions were used as a model. The polygenic architecture of flowering time was defined as the 48 loci that were significantly associated with flowering time-at 10 and/or 16°C and/or their difference-in this population. Contributions from alleles at flowering time associated loci to global and local adaptation were explored by evaluating their distribution across genetically and geographically defined subpopulations across the native range of the species. The dynamics in the genetic architecture of flowering time in response to temperature was evaluated by estimating how the effects of these loci on flowering changed with growth temperature. Overall, the genetic basis of flowering time was stable-about 2/3 of the flowering time loci had similar effects at 10°C and 16°C-but many loci were involved in gene by temperature interactions. Globally present alleles, mostly of moderate effect, contributed to the differences in flowering times between the subpopulations via subtle changes in allele frequencies. More extreme local adaptations were, on several occasions, due to regional alleles with relatively large effects, and their linkage disequilibrium-patterns suggest coevolution of functionally connected alleles within local populations. Overall, these findings provide a significant contribution to our understanding about the possible modes of global and local evolution of a complex adaptive trait in A. thaliana.

Molecular markers based on sequence variation in BoFLC1.C9 for characterizing early- and late-flowering cabbage genotypes

BACKGROUND

Cabbage (Brassica oleracea var. capitata) is popular worldwide for consumption as a leafy vegetable. Premature flowering is triggered by low temperature, and deteriorates quality of cabbage as vegetable. In general, growers prefer late-flowering varieties to assure good quality compact head. Here, we report BoFLC1.C9 as a gene with clear sequence variation between cabbage lines with different flowering times, and proposed as molecular marker to characterize early- and late-flowering cabbage lines.

RESULTS

We identified sequence variation of 67 bp insertions in intron 2, which were contributed in flowering time variation between two inbred lines through rapid down-regulation of the BoFLC1.C9 gene in early-flowering line compared to late-flowering one upon vernalization. One set of primer 'F7R7' proposed as marker, of which was explained with 83 and 80% of flowering time variation in 141 F₂ individuals and 20 commercial lines, respectively.

CONCLUSIONS

This F7R7 marker could be used as genetic tools to characterize flowering time variation and to select as well to develop early- and late-flowering cabbage cultivars.

The complex genetic architecture of shoot growth natural variation in Arabidopsis thaliana

One of the main outcomes of quantitative genetics approaches to natural variation is to reveal the genetic architecture underlying the phenotypic space. Complex genetic architectures are described as including numerous loci (or alleles) with small-effect and/or low-frequency in the populations, interactions with the genetic background, environment or age. Linkage or association mapping strategies will be more or less sensitive to this complexity, so that we still have an unclear picture of its extent. By combining high-throughput phenotyping under two environmental conditions with classical QTL mapping approaches in multiple Arabidopsis thaliana segregating populations as well as advanced near isogenic lines construction and survey, we have attempted to improve our understanding of quantitative phenotypic variation. Integrative traits such as those related to vegetative growth used in this work (highlighting either cumulative growth, growth rate or morphology) all showed complex and dynamic genetic architecture with respect to the segregating population and condition. The more resolutive our mapping approach, the more complexity we uncover, with several instances of QTLs visible in near isogenic lines but not detected with the initial QTL mapping, indicating that our phenotyping accuracy was less limiting than the mapping resolution with respect to the underlying genetic architecture. In an ultimate approach to resolve this complexity, we intensified our phenotyping effort to target specifically a 3Mb-region known to segregate for a major quantitative trait gene, using a series of selected lines recombined every 100kb. We discovered that at least 3 other independent QTLs had remained hidden in this region, some with trait- or condition-specific effects, or opposite allelic effects. If we were to extrapolate the figures obtained on this specific region in this particular cross to the genome- and species-scale, we would predict hundreds of causative loci of detectable phenotypic effect controlling these growth-related phenotypes.

Translating Flowering Time From Arabidopsis thaliana to Brassicaceae and Asteraceae Crop Species

Flowering and seed set are essential for plant species to survive, hence plants need to adapt to highly variable environments to flower in the most favorable conditions. Endogenous cues such as plant age and hormones coordinate with the environmental cues like temperature and day length to determine optimal time for the transition from vegetative to reproductive growth. In a breeding context, controlling flowering time would help to speed up the production of new hybrids and produce high yield throughout the year. The flowering time genetic network is extensively studied in the plant model species Arabidopsis thaliana, however this knowledge is still limited in most crops. This article reviews evidence of conservation and divergence of flowering time regulation in A. thaliana with its related crop species in the Brassicaceae and with more distant vegetable crops within the Asteraceae family. Despite the overall conservation of most flowering time pathways in these families, many genes controlling this trait remain elusive, and the function of most Arabidopsis homologs in these crops are yet to be determined. However, the knowledge gathered so far in both model and crop species can be already exploited in vegetable crop breeding for flowering time control.

Ambient Temperature-Responsive Mechanisms Coordinate Regulation of Flowering Time

In plants, environmental conditions such as temperature affect survival, growth, and fitness, particularly during key stages such as seedling growth and reproduction. To survive and thrive in changing conditions, plants have evolved adaptive responses that tightly regulate developmental processes such as hypocotyl elongation and flowering time in response to environmental temperature changes. Increases in temperature, coupled with increasing fluctuations in local climate and weather, severely affect our agricultural systems; therefore, understanding the mechanisms by which plants perceive and respond to temperature is critical for agricultural sustainability. In this review, we summarize recent findings on the molecular mechanisms of ambient temperature perception as well as possible temperature sensing components in plants. Based on recent publications, we highlight several temperature response mechanisms, including the deposition and eviction of histone variants, DNA methylation, alternative splicing, protein degradation, and protein localization. We discuss roles of each proposed temperature-sensing mechanism that affects plant development, with an emphasis on flowering time. Studies of plant ambient temperature responses are advancing rapidly, and this review provides insights for future research aimed at understanding the mechanisms of temperature perception and responses in plants.

Synchronisation of Arabidopsis flowering time and whole-plant senescence in seasonal environments

Synchronisation of flowering phenology has often been observed between individuals within plant species. We expected that a critical role of flowering-time control under natural conditions is a phenological synchronisation. However, no studies have quantified the level of synchronisation of reproductive timing relative to germination timing under natural conditions. In a sequential seeding experiment (SSE) in which we manipulated the germination timing of Arabidopsis thaliana accessions, we developed a quantification index to evaluate reproductive synchrony in annual plants. In the SSE, we identified a novel phenomenon of reproductive synchrony: senescence synchrony. The role of vernalisation in realising flowering synchrony between plants of different ages under natural conditions was demonstrated by synchronisation and de-synchronisation of flowering initiation in vernalisation-sensitive and less-vernalisation-sensitive accessions, respectively. We also observed up-regulation of senescence-related genes at corresponding times. The approach we developed in this study provides a set of concepts and procedures that can be used to study reproductive synchrony experimentally under natural conditions.

Genetic basis and evolution of rapid cycling in railway populations of tetraploid Arabidopsis arenosa

Spatially structured plant populations with diverse adaptations provide powerful models to investigate evolution. Human-generated ruderal habitats are abundant and low-competition, but are challenging for plants not adapted to them. Ruderal habitats also sometimes form networked corridors (e.g. roadsides and railways) that allow rapid long-distance spread of successfully adapted variants. Here we use transcriptomic and genomic analyses, coupled with genetic mapping and transgenic follow-up, to understand the evolution of rapid cycling during adaptation to railway sites in autotetraploid Arabidopsis arenosa. We focus mostly on a hybrid population that is likely a secondary colonist of a railway site. These mountain railway plants are phenotypically similar to their cosmopolitan cousins. We thus hypothesized that colonization primarily involved the flow of adaptive alleles from the cosmopolitan railway variant. But our data shows that it is not that simple: while there is evidence of selection having acted on introgressed alleles, selection also acted on rare standing variation, and new mutations may also contribute. Among the genes we show have allelic divergence with functional relevance to flowering time are known regulators of flowering, including FLC and CONSTANS. Prior implications of these genes in weediness and rapid cycling supports the idea that these are “evolutionary hotspots” for these traits. We also find that one of two alleles of CONSTANS under selection in the secondary colonist was selected from rare standing variation in mountain populations, while the other was introgressed from the cosmopolitan railway populations. The latter allele likely arose in diploid populations over 700km away, highlighting how ruderal populations could act as allele conduits and thus influence local adaptation.

Array of MADS-Box Genes: Facilitator for Rapid Adaptation?

In a world of global warming, the question emerges whether all plants have suitable mechanisms to keep pace with the rapidly changing environment. Most previous studies have focused on either the ability of plants to rapidly acclimatize via physiological and developmental plasticity, or long-term adaptation over thousands of years. However, we wonder whether plants can also adapt to changes in the environment within only a few generations. We hypothesize that rapidly evolving clusters of tandemly duplicated developmental control genes represent a source for fast adaptation. Specifically, we propose that a tandem cluster of FLC-like MADS-box genes involved in the transition to flowering in Arabidopsis functions as a facilitator for rapid adaptation to changes in ambient temperature.

A new genomic prediction method with additive-dominance effects in the least-squares framework

In our previous work, we proposed a genomic prediction method combing identical-by-state-based Haseman-Elston regression and best linear prediction with additive variance component only (HEBLP|A herein), the most essential component of genetic variation. Since the dominance effects contribute significantly in heterosis, it is desirable to incorporate the HEBLP with dominance variance component that is expected to enhance the predictive accuracy as we move to the further development: HEBLP|AD, a paralleled implementation of genomic prediction compared with genomic best linear unbiased prediction (GBLUP). The simulation results indicated that when the dominance effects contributed to a large proportion of genetic variation, HEBLP|AD and GBLUP|AD, having similar accuracy, both outperformed HEBLP|A; but when the dominance variation was none or little, HEBLP|A, HEBLP|AD, and GBLUP|AD had similar predictability. The analysis of real data from Arabidopsis thaliana F2 population also demonstrated the latter situation. In summary, HEBLP|AD performed stable whether a trait was controlled by dominance effects or not.

Prediction of Complex Traits: Robust Alternatives to Best Linear Unbiased Prediction

A widely used method for prediction of complex traits in animal and plant breeding is “genomic best linear unbiased prediction” (GBLUP). In a quantitative genetics setting, BLUP is a linear regression of phenotypes on a pedigree or on a genomic relationship matrix, depending on the type of input information available. Normality of the distributions of random effects and of model residuals is not required for BLUP but a Gaussian assumption is made implicitly. A potential downside is that Gaussian linear regressions are sensitive to outliers, genetic or environmental in origin. We present simple (relative to a fully Bayesian analysis) to implement robust alternatives to BLUP using a linear model with residual t or Laplace distributions instead of a Gaussian one, and evaluate the methods with milk yield records on Italian Brown Swiss cattle, grain yield data in inbred wheat lines, and using three traits measured on accessions of Arabidopsis thaliana. The methods do not use Markov chain Monte Carlo sampling and model hyper-parameters, viewed here as regularization “knobs,” are tuned via some cross-validation. Uncertainty of predictions are evaluated by employing bootstrapping or by random reconstruction of training and testing sets. It was found (e.g., test-day milk yield in cows, flowering time and FRIGIDA expression in Arabidopsis) that the best predictions were often those obtained with the robust methods. The results obtained are encouraging and stimulate further investigation and generalization.

UV-B radiation delays flowering time through changes in the PRC2 complex activity and miR156 levels in Arabidopsis thaliana

UV-B is a high-energy component of the solar radiation perceived by the plant and induces a number of modifications in plant growth and development, including changes in flowering time. However, the molecular mechanisms underlying these changes are largely unknown. In the present work, we demonstrate that Arabidopsis plants grown under white light supplemented with UV-B show a delay in flowering time, and this developmental reprogramming is mediated by the UVR8 photoreceptor. Using a combination of gene expression analyses and UV-B irradiation of different flowering mutants, we gained insight into the pathways involved in the observed flowering time delay in UV-B-exposed Arabidopsis plants. We provide evidence that UV-B light downregulates the expression of MSI1 and CLF, two of the components of the polycomb repressive complex 2, which in consequence drives a decrease in H3K27me3 histone methylation of MIR156 and FLC genes. Modification in the expression of several flowering time genes as a consequence of the decrease in the polycomb repressive complex 2 activity was also determined. UV-B exposure of flowering mutants supports the involvement of this complex in the observed delay in flowering time, mostly through the age pathway.

Parallel Evolution of Common Allelic Variants Confers Flowering Diversity in Capsella rubella

Flowering time is an adaptive life history trait. Capsella rubella, a close relative of Arabidopsis thaliana and a young species, displays extensive variation for flowering time but low standing genetic variation due to an extreme bottleneck event, providing an excellent opportunity to understand how phenotypic diversity can occur with a limited initial gene pool. Here, we demonstrate that common allelic variation and parallel evolution at the FLC locus confer variation in flowering time in C. rubella. We show that two overlapping deletions in the 5' untranslated region (UTR) of C. rubella FLC, which are associated with local changes in chromatin conformation and histone modifications, reduce its expression levels and promote flowering. We further show that these two pervasive variants originated independently in natural C. rubella populations after speciation and spread to an intermediate frequency, suggesting a role of this parallel cis-regulatory change in adaptive evolution. Our results provide an example of how parallel mutations in the same 5' UTR region can shape phenotypic evolution in plants.

Comparison of the Relative Potential for Epigenetic and Genetic Variation To Contribute to Trait Stability

The theoretical ability of epigenetic variation to influence the heritable variation of complex traits is gaining traction in the study of adaptation. This theory posits that epigenetic marks can control adaptive phenotypes but the relative potential of epigenetic variation in comparison to genetic variation in these traits is not presently understood. To compare the potential of epigenetic and genetic variation in adaptive traits, we analyzed the influence of DNA methylation variation on the accumulation of chemical defense compounds glucosinolates from the order Brassicales. Several decades of work on glucosinolates has generated extensive knowledge about their synthesis, regulation, genetic variation and contribution to fitness establishing this pathway as a model pathway for complex adaptive traits. Using high-throughput phenotyping with a randomized block design of ddm1 derived Arabidopsis thaliana epigenetic Recombinant Inbred Lines, we measured the correlation between DNA methylation variation and mean glucosinolate variation and within line stochastic variation. Using this information, we identified epigenetic Quantitative Trait Loci that contained specific Differentially Methylated Regions associated with glucosinolate traits. This showed that variation in DNA methylation correlates both with levels and variance of glucosinolates and flowering time with trait-specific loci. By conducting a meta-analysis comparing the results to different genetically variable populations, we conclude that the influence of DNA methylation variation on these adaptive traits is much lower than the corresponding impact of standing genetic variation. As such, selective pressure on these traits should mainly affect standing genetic variation to lead to adaptation.

Biomass increase under zinc deficiency caused by delay of early flowering in Arabidopsis

Plants generally produce more biomass when all nutrients are available in sufficient amounts. In addition to environmental constraints, genetic and developmental factors, such as the transition from vegetative to reproductive growth, restrict maximal biomass yield. Here, we report the peculiar observation that a subset of Arabidopsis thaliana accessions produced larger shoot rosette diameters when grown in zinc (Zn)-deficient conditions, compared with Zn-sufficient conditions. This was associated with early flowering that restricted the leaf length under Zn sufficiency. Zinc deficiency repressed the expression of FLOWERING LOCUS T (FT), which encodes a major regulator of flowering. Repression or loss of FT increased the rosette diameter via a delay of the transition to flowering, a longer phase of leaf growth, and an increased leaf number. The transition to flowering reduced, but did not terminate, the proliferation of established leaves. The size of individual leaf mesophyll cells was not affected by Zn deficiency or by loss of FT, indicating that the larger rosette diameter was caused by maintained proliferation of vegetative tissue. As a consequence, early-flowering accessions under Zn deficiency grew to have larger rosette diameters due to a delay of flowering, which explains the unusual increase of vegetative biomass under nutrient deficiency.

A multilocus association analysis method integrating phenotype and expression data reveals multiple novel associations to flowering time variation in wild-collected Arabidopsis thaliana

The adaptation to a new habitat often results in a confounding between genomewide genotype and beneficial alleles. When the confounding is strong, or the allelic effects is weak, it is a major statistical challenge to detect the adaptive polymorphisms. We describe a novel approach to dissect polygenic traits in natural populations. First, candidate adaptive loci are identified by screening for loci directly associated with the adaptive trait or the expression of genes known to affect it. Then, a multilocus genetic architecture is inferred using a backward elimination association analysis across all candidate loci with an adaptive false discovery rate-based threshold. Effects of population stratification are controlled by accounting for genomic kinship in both steps of the analysis and also by simultaneously testing all candidate loci in the multilocus model. We illustrate the method by exploring the polygenic basis of an important adaptive trait, flowering time in Arabidopsis thaliana, using public data from the 1,001 genomes project. We revealed associations between 33 (29) loci and flowering time at 10 (16)°C in this collection of natural accessions, where standard genomewide association analysis methods detected five (3) loci. The 33 (29) loci explained approximately 55.1 (48.7)% of the total phenotypic variance of the respective traits. Our work illustrates how the genetic basis of highly polygenic adaptive traits in natural populations can be explored in much greater detail using new multilocus mapping approaches taking advantage of prior biological information, genome and transcriptome data.

A Predictive Model for Time-to-Flowering in the Common Bean Based on QTL and Environmental Variables

The common bean is a tropical facultative short-day legume that is now grown in tropical and temperate zones. This observation underscores how domestication and modern breeding can change the adaptive phenology of a species. A key adaptive trait is the optimal timing of the transition from the vegetative to the reproductive stage. This trait is responsive to genetically controlled signal transduction pathways and local climatic cues. A comprehensive characterization of this trait can be started by assessing the quantitative contribution of the genetic and environmental factors, and their interactions. This study aimed to locate significant QTL (G) and environmental (E) factors controlling time-to-flower in the common bean, and to identify and measure G × E interactions. Phenotypic data were collected from a biparental [Andean × Mesoamerican] recombinant inbred population (F_11:14, 188 genotypes) grown at five environmentally distinct sites. QTL analysis using a dense linkage map revealed 12 QTL, five of which showed significant interactions with the environment. Dissection of G × E interactions using a linear mixed-effect model revealed that temperature, solar radiation, and photoperiod play major roles in controlling common bean flowering time directly, and indirectly by modifying the effect of certain QTL. The model predicts flowering time across five sites with an adjusted r-square of 0.89 and root-mean square error of 2.52 d. The model provides the means to disentangle the environmental dependencies of complex traits, and presents an opportunity to identify in silico QTL allele combinations that could yield desired phenotypes under different climatic conditions.