Fitness effects of mutation: testing genetic redundancy in Arabidopsis thaliana

Above and belowground phenotypic response to exogenous auxin across Arabidopsis thaliana mutants and natural accessions varies from seedling to reproductive maturity

Background

Plant hormones influence phenology, development, and function of above and belowground plant structures. In seedlings, auxin influences the initiation and development of lateral roots and root systems. How auxin-related genes influence root initiation at early life stages has been investigated from numerous perspectives. There is a gap in our understanding of how these genes influence root size through the life cycle and in mature plants. Across development, the influence of a particular gene on plant phenotypes is partly regulated by the addition of a poly-A tail to mRNA transcripts via alternative polyadenylation (APA). Auxin related genes have documented variation in APA, with auxin itself contributing to APA site switches. Studies of the influence of exogenous auxin on natural plant accessions and mutants of auxin pathway gene families exhibiting variation in APA are required for a more complete understanding of genotype by development by hormone interactions in whole plant and fitness traits.

Methods

We studied Arabidopsis thaliana homozygous mutant lines with inserts in auxin-related genes previously identified to exhibit variation in number of APA sites. Our growth chamber experiment included wildtype Col-0 controls, mutant lines, and natural accession phytometers. We applied exogenous auxin through the life cycle. We quantified belowground and aboveground phenotypes in 14 day old, 21 day old seedlings and plants at reproductive maturity. We contrasted root, rosette and flowering phenotypes across wildtype, auxin mutant, and natural accession lines, APA groups, hormone treatments, and life stages using general linear models.

Results

The root systems and rosettes of mutant lines in auxin related genes varied in response to auxin applications across life stages and varied between genotypes within life stages. In seedlings, exposure to auxin decreased size, but increased lateral root density, whereas at reproductive maturity, plants displayed greater aboveground mass and total root length. These differences may in part be due to a shift which delayed the reproductive stage when plants were treated with auxin. Root traits of auxin related mutants depended on the number of APA sites of mutant genes and the plant's developmental stage. Mutants with inserts in genes with many APA sites exhibited lower early seedling belowground biomass than those with few APA sites but only when exposed to exogenous auxin. As we observed different responses to exogenous auxin across the life cycle, we advocate for further studies of belowground traits and hormones at reproductive maturity. Studying phenotypic variation of genotypes across life stages and hormone environments will uncover additional shared patterns across traits, assisting efforts to potentially reach breeding targets and enhance our understanding of variation of genotypes in natural systems.

Artificial selection reveals complex genetic architecture of shoot branching and its response to nitrate supply in Arabidopsis

Quantitative traits may be controlled by many loci, many alleles at each locus, and subject to genotype-by-environment interactions, making them difficult to map. One example of such a complex trait is shoot branching in the model plant Arabidopsis, and its plasticity in response to nitrate. Here, we use artificial selection under contrasting nitrate supplies to dissect the genetic architecture of this complex trait, where loci identified by association mapping failed to explain heritability estimates. We found a consistent response to selection for high branching, with correlated responses in other traits such as plasticity and flowering time. Genome-wide scans for selection and simulations suggest that at least tens of loci control this trait, with a distinct genetic architecture between low and high nitrate treatments. While signals of selection could be detected in the populations selected for high branching on low nitrate, there was very little overlap in the regions selected in three independent populations. Thus the regulatory network controlling shoot branching can be tuned in different ways to give similar phenotypes.

Genome-Wide Analysis of the MADS-Box Gene Family in Holoparasitic Plants (Balanophora subcupularis and Balanophora fungosa var. globosa)

MADS-box is an important transcription factor family that is involved in the regulation of various stages of plant growth and development, especially flowering regulation and flower development. Being a holoparasitic plant, the body structure of Balanophoraceae has changed dramatically over time, and its vegetative and reproductive organs have been extensively modified, with rudimentary flower organs. Meanwhile, extraordinary gene losses have been identified in holoparasitic plants compared with autotrophs. Our study reveals that the MADS-box gene family contracted sharply in Balanophora subcupularis and Balanophora fungosa var. globosa, and some subfamilies were lost, exhibiting reduced redundancy in both. The genes that functioned in the transition from the vegetative to floral production stages suffered a significant loss, but the ABCE model genes remained intact. We further investigated genes related to flowering regulation in B. subcupularis and B. fungosa var. globosa, vernalization and autonomous ways of regulating flowering time remained comparatively integrated, while genes in photoperiod and circadian clock pathways were almost lost. Convergent gene loss in flowering regulation occurred in Balanophora and another holoparasitic plant Sapria himalayana (Rafflesiaceae). The genome-wide analysis of the MADS-box gene family in Balanophora species provides valuable information for understanding the classification, gene loss pattern, and flowering regulation mechanism of MADS-box gene family in parasitic plants.

High-throughput measurement of plant fitness traits with an object detection method using Faster R-CNN

Revealing the contributions of genes to plant phenotype is frequently challenging because loss-of-function effects may be subtle or masked by varying degrees of genetic redundancy. Such effects can potentially be detected by measuring plant fitness, which reflects the cumulative effects of genetic changes over the lifetime of a plant. However, fitness is challenging to measure accurately, particularly in species with high fecundity and relatively small propagule sizes such as Arabidopsis thaliana. An image segmentation-based method using the software ImageJ and an object detection-based method using the Faster Region-based Convolutional Neural Network (R-CNN) algorithm were used for measuring two Arabidopsis fitness traits: seed and fruit counts. The segmentation-based method was error-prone (correlation between true and predicted seed counts, r²  = 0.849) because seeds touching each other were undercounted. By contrast, the object detection-based algorithm yielded near perfect seed counts (r²  = 0.9996) and highly accurate fruit counts (r²  = 0.980). Comparing seed counts for wild-type and 12 mutant lines revealed fitness effects for three genes; fruit counts revealed the same effects for two genes. Our study provides analysis pipelines and models to facilitate the investigation of Arabidopsis fitness traits and demonstrates the importance of examining fitness traits when studying gene functions.

Contrasting gene-level signatures of selection with reproductive fitness

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

Macroscopic variation in Arabidopsis mutants despite stomatal uniformity across soil nutrient environments

Stomata are essential pores flanked by guard cells that control gas exchange in plants. We can utilize stomatal size and density measurements as a proxy for a plant's capacity for gas exchange. While stomatal responses to stressful environments are well studied; data are lacking in the responses across mutant genotypes of the same species in these trait and treatment interactions or genetic variation in phenotypic plasticity. We evaluated the effects of soil nutrient variation on macroscopic and stomatal traits of Arabidopsis thaliana T-DNA insertion mutants for which prior performance in a single benign growing condition were available. Nutrient-induced stress significantly impacted traits including plant biomass, height, fruit number, and leaf number which we denote as macroscopic traits. We found evidence that genotype by environment effects exist for macroscopic traits, yet total stomatal area variation, or "microscopic variation" across environments was modest. Divergence from the wildtype line varied by mutant background and these responses were variable among traits. These findings suggest that Arabidopsis employs a strategy of physiological compensation, sacrificing morphological traits to maintain stomatal production.

Comparisons within the Rice GA 2-Oxidase Gene Family Revealed Three Dominant Paralogs and a Functional Attenuated Gene that Led to the Identification of Four Amino Acid Variants Associated with GA Deactivation Capability

BACKGROUND

GA 2-oxidases (GA2oxs) are involved in regulating GA homeostasis in plants by inactivating bioactive GAs through 2β-hydroxylation. Rice GA2oxs are encoded by a family of 10 genes; some of them have been characterized, but no comprehensive comparisons for all these genes have been conducted.

RESULTS

Rice plants with nine functional GA2oxs were demonstrated in the present study, and these genes not only were differentially expressed but also revealed various capabilities for GA deactivation based on their height-reducing effects in transgenic plants. Compared to that of wild-type plants, the relative plant height (RPH) of transgenic plants was scored to estimate their reducing effects, and 8.3% to 59.5% RPH was observed. Phylogenetic analysis of class I GA2ox genes revealed two functionally distinct clades in the Poaceae. The OsGA2ox3, 4, and 8 genes belonging to clade A showed the most severe effect (8.3% to 8.7% RPH) on plant height reduction, whereas the OsGA2ox7 gene belonging to clade B showed the least severe effect (59.5% RPH). The clade A OsGA2ox3 gene contained two conserved C186/C194 amino acids that were crucial for enzymatic activity. In the present study, these amino acids were replaced with OsGA2ox7-conserved arginine (C186R) and proline (C194P), respectively, or simultaneously (C186R/C194P) to demonstrate their importance in planta. Another two amino acids, Q220 and Y274, conserved in OsGA2ox3 were substituted with glutamic acid (E) and phenylalanine (F), respectively, or simultaneously to show their significance in planta. In addition, through sequence divergence, RNA expression profile and GA deactivation capability analyses, we proposed that OsGA2ox1, OsGA2ox3 and OsGA2ox6 function as the predominant paralogs in each of their respective classes.

CONCLUSIONS

This study demonstrates rice has nine functional GA2oxs and the class I GA2ox genes are divided into two functionally distinct clades. Among them, the OsGA2ox7 of clade B is a functional attenuated gene and the OsGA2ox1, OsGA2ox3 and OsGA2ox6 are the three predominant paralogs in the family.

Predictive Models of Genetic Redundancy in Arabidopsis thaliana

Genetic redundancy refers to a situation where an individual with a loss-of-function mutation in one gene (single mutant) does not show an apparent phenotype until one or more paralogs are also knocked out (double/higher-order mutant). Previous studies have identified some characteristics common among redundant gene pairs, but a predictive model of genetic redundancy incorporating a wide variety of features derived from accumulating omics and mutant phenotype data is yet to be established. In addition, the relative importance of these features for genetic redundancy remains largely unclear. Here, we establish machine learning models for predicting whether a gene pair is likely redundant or not in the model plant Arabidopsis thaliana based on six feature categories: functional annotations, evolutionary conservation including duplication patterns and mechanisms, epigenetic marks, protein properties including posttranslational modifications, gene expression, and gene network properties. The definition of redundancy, data transformations, feature subsets, and machine learning algorithms used significantly affected model performance based on holdout, testing phenotype data. Among the most important features in predicting gene pairs as redundant were having a paralog(s) from recent duplication events, annotation as a transcription factor, downregulation during stress conditions, and having similar expression patterns under stress conditions. We also explored the potential reasons underlying mispredictions and limitations of our studies. This genetic redundancy model sheds light on characteristics that may contribute to long-term maintenance of paralogs, and will ultimately allow for more targeted generation of functionally informative double mutants, advancing functional genomic studies.

Fitness effects of mutation in natural populations of Arabidopsis thaliana reveal a complex influence of local adaptation

Little is empirically known about the contribution of mutations to fitness in natural environments. However, Fisher's Geometric Model (FGM) provides a conceptual foundation to consider the influence of the environment on mutational effects. To quantify mutational properties in the field, we established eight sets of MA lines (7-10 generations) derived from eight founders collected from natural populations of Arabidopsis thaliana from French and Swedish sites, representing the range margins of the species in Europe. We reciprocally planted the MA lines and their founders at French and Swedish sites, allowing us to test predictions of FGM under naturally occurring environmental conditions. The performance of the MA lines relative to each other and to their respective founders confirmed some and contradicted other predictions of the FGM: the contribution of mutation to fitness variance increased when the genotype was in an environment where its fitness was low, that is, in the away environment, but mutations were more likely to be beneficial when the genotype was in its home environment. Consequently, environmental context plays a large role in the contribution of mutations to the evolutionary process and local adaptation does not guarantee that a genotype is at or close to its optimum.

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.

Distributed phenomics with the unPAK project reveals the effects of mutations

Determining how genes are associated with traits in plants and other organisms is a major challenge in modern biology. The unPAK project - undergraduates phenotyping Arabidopsis knockouts - has generated phenotype data for thousands of non-lethal insertion mutation lines within a single Arabidopsis thaliana genomic background. The focal phenotypes examined by unPAK are complex macroscopic fitness-related traits, which have ecological, evolutionary and agricultural importance. These phenotypes are placed in the context of the wild-type and also natural accessions (phytometers), and standardized for environmental differences between assays. Data from the unPAK project are used to describe broad patterns in the phenotypic consequences of insertion mutation, and to identify individual mutant lines with distinct phenotypes as candidates for further study. Inclusion of undergraduate researchers is at the core of unPAK activities, and an important broader impact of the project is providing students an opportunity to obtain research experience.

Undergraduates Phenotyping Arabidopsis Knockouts in a Course-Based Undergraduate Research Experience: Exploring Plant Fitness and Vigor Using Quantitative Phenotyping Methods

We present a curriculum description, an initial student outcome investigation, and sample scientific results for a representative Course-Based Undergraduate Research Experience (CURE) that is part of the "Undergraduates Phenotyping Arabidopsis Knockouts" (unPAK) network. CUREs in the unPAK network characterize quantitative phenotypes of the model plant Arabidopsis from across environments to uncover connections between genotype and phenotype. Students in unPAK CUREs grow plants in a replicated block design and make quantitative measurements throughout the semester. This CURE enables students to answer plant science questions that draw from fields such as environmental science, genetics, ecology, and evolution. Findings indicate that this experience provides students with opportunities to make relevant scientific discoveries. Eighty percent of student datasets produced from the CURE met criteria for inclusion in the project database, indicative of student learning in data collection and analysis of quantitative plant traits. Student datasets uncovered novel effects of mutation on plant form. In addition, students' science self-efficacy increased as a result of course participation, and faculty feedback on course implementation was positive. We present unPAK as a new network that supports CUREs and research experiences focused on collecting biological data made publicly available to the scientific community. The unPAK CUREs can be tailored to address instructor interests or pedagogical needs while involving students in research investigating quantitative plant phenotypes.

Drought adaptation in Arabidopsis thaliana by extensive genetic loss-of-function

Interdisciplinary syntheses are needed to scale up discovery of the environmental drivers and molecular basis of adaptation in nature. Here we integrated novel approaches using whole genome sequences, satellite remote sensing, and transgenic experiments to study natural loss-of-function alleles associated with drought histories in wild Arabidopsis thaliana. The genes we identified exhibit population genetic signatures of parallel molecular evolution, selection for loss-of-function, and shared associations with flowering time phenotypes in directions consistent with longstanding adaptive hypotheses seven times more often than expected by chance. We then confirmed predicted phenotypes experimentally in transgenic knockout lines. These findings reveal the importance of drought timing to explain the evolution of alternative drought tolerance strategies and further challenge popular assumptions about the adaptive value of genetic loss-of-function in nature. These results also motivate improved species-wide sequencing efforts to better identify loss-of-function variants and inspire new opportunities for engineering climate resilience in crops.

Water shortages caused by droughts lead to crop losses that affect billions of people around the world each year. By discovering how wild plants adapt to drought, it may be possible to identify traits and genes that help to improve the growth of crop plants when water is scarce. It has been suggested that plants have adapted to droughts by flowering at times of the year when droughts are less likely to occur. For example, if droughts are more likely to happen in spring, the plants may delay flowering until the summer.

Arabidopsis thaliana is a small plant that is found across Eurasia, Africa and North America, including in areas that are prone to drought at different times of the year. Individual plants of the same species may carry different versions of the same gene (known as alleles). Some of these alleles may not work properly and are referred to as loss-of-function alleles. Monroe et al. investigated whether A. thaliana plants carry any loss-of-function alleles that are associated with droughts happening in the spring or summer, and whether they are linked to when those plants will flower.

Monroe et al. analyzed satellite images collected over the last 30 years to measure when droughts have occurred. Next, they searched genome sequences of Arabidopsis thaliana for alleles that might help the plants to adapt to droughts in the spring or summer. Combining the two approaches revealed that loss-of-function alleles associated with spring droughts were strongly predicted to be associated with the plants flowering later in the year. Similarly, loss-of-function alleles associated with summer droughts were predicted to be associated with the plants flowering earlier in the year.

These findings support the idea that plants can adapt to drought by changing when they produce flowers, and suggest that loss-of-function alleles play a major role in this process. New techniques for editing genes mean it is easier than ever to generate new loss-of-function alleles in specific genes. Therefore, the results presented by Monroe et al. may help researchers to develop new varieties of crop plants that are better adapted to droughts.

Next-generation metrics for monitoring genetic erosion within populations of conservation concern

Genetic erosion is a major threat to biodiversity because it can reduce fitness and ultimately contribute to the extinction of populations. Here, we explore the use of quantitative metrics to detect and monitor genetic erosion. Monitoring systems should not only characterize the mechanisms and drivers of genetic erosion (inbreeding, genetic drift, demographic instability, population fragmentation, introgressive hybridization, selection) but also its consequences (inbreeding and outbreeding depression, emergence of large-effect detrimental alleles, maladaptation and loss of adaptability). Technological advances in genomics now allow the production of data the can be measured by new metrics with improved precision, increased efficiency and the potential to discriminate between neutral diversity (shaped mainly by population size and gene flow) and functional/adaptive diversity (shaped mainly by selection), allowing the assessment of management-relevant genetic markers. The requirements of such studies in terms of sample size and marker density largely depend on the kind of population monitored, the questions to be answered and the metrics employed. We discuss prospects for the integration of this new information and metrics into conservation monitoring programmes.

RNA expression and disease tolerance are associated with a "keystone mutation" in the ochre sea star Pisaster ochraceus

An overdominant mutation in an intron of the elongation factor 1-α (EF1A) gene in the sea star Pisaster ochraceus has shown itself to mediate tolerance to "sea star wasting disease", a pandemic that has significantly reduced sea star populations on the Pacific coast of North America. Here we use RNA sequencing of healthy individuals to identify differences in constitutive expression of gene regions that may help explain this tolerance phenotype. Our results show that individuals carrying this mutation have lower expression at a large contingent of gene regions. Individuals without this mutation also appear to have a greater cellular response to temperature stress, which has been implicated in the outbreak of sea star wasting disease. Given the ecological significance of P. ochraceus, these results may be useful in predicting the evolutionary and demographic future for Pacific intertidal communities.