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Premise: Variation in seed traits is common within and among populations of plant species and often has ecological and evolutionary implications. However, due to the time‐consuming nature of manual seed measurements and the level of variability in imaging techniques, quantifying and interpreting the extent of seed variation can be challenging. Methods: We developed a standardized high‐throughput technique to measure seed number, as well as individual seed area and color, using a derived empirical scale to constrain area in Arabidopsis thaliana, Brassica rapa, and Mimulus guttatus. We develop a specific rational model using seed area measured at various spatial scales relative to the pixel count, observing the asymptotic value of the seed area as the modeled number of pixels approaches infinity. Results: We found that our model has high reliability in estimating seed traits and efficiently processes large numbers of images, facilitating the quantification of seed traits in studies with large sample sizes. Discussion: This technique facilitates consistency between imaging sessions and standardizes the measurement of seed traits. These novel advances allow researchers to directly and reliably measure seed traits, which will enable tests of the ecological and evolutionary causes of their variation. [ABSTRACT FROM AUTHOR]

Reproductive timing is a key life‐history trait that impacts the pool of available mates, the environment experienced during flowering, and the expression of other traits through genetic covariation. Selection on phenology, and its consequences on other life‐history traits, has considerable implications in the context of ongoing climate change and shifting growing seasons. To test this, we grew field‐collected seed from the wildflower Mimulus guttatus in a greenhouse to assess the standing genetic variation for flowering time and covariation with other traits. We then created full‐sib families through phenological assortative mating and grew offspring in three photoperiod treatments representing seasonal variation in daylength. We find substantial quantitative genetic variation for the onset of flowering time, which covaried with vegetative traits. The assortatively‐mated offspring varied in their critical photoperiod by over two hours, so that families differed in their probability of flowering across treatments Allocation to flowering and vegetative growth changed across the daylength treatments, with consistent direction and magnitude of covariation among flowering time and other traits. Our results suggest that future studies of flowering time evolution should consider the joint evolution of correlated traits and shifting seasonal selection to understand how environmental variation influences life histories. Reproductive timing is a key life‐history trait that affects the pool of available mates, the environment experienced during flowering, and the expression of other traits through genetic covariation. We found a broad distribution of heritable variation in flowering time and correlated traits, providing the potential for assortative mating. Next we grew assortatively mated offspring in daylengths representing seasonal variation and found the probability and timing of flowering changed across daylengths, with consistent direction and magnitude of traits correlations. [ABSTRACT FROM AUTHOR]

Information about a gene sometimes can be deduced by examining the impact of its mutation on phenotype. However, the genome-scale utility of the method is limited because, for nearly all model organisms, the majority of mutations result in little or no observable phenotypic impact. The cause of this is often attributed to robustness or redundancy within the genome, but that is only one plausible hypothesis. We examined a standard set of phenotypic traits, and applied statistical methods commonly used in the study of natural variants to an engineered mutant strain collection representing disruptions in 180 of the 192 ABC transporters within the bacterium Myxococcus xanthus. These strains display continuous variation in their phenotypic distributions, with a small number of "outlier" strains at both phenotypic extremes, and the majority within a confidence interval about the mean that always includes wild type. Correlation analysis reveals substantial pleiotropy, indicating that the traits do not represent independent variables. The traits measured in this study co-cluster with expression profiles, thereby demonstrating that these changes in phenotype correspond to changes at the molecular level, and therefore can be indirectly connected to changes in the genome. However, the continuous distributions, the pleiotropy, and the placement of wild type always within the confidence interval all indicate that this standard set of M. xanthus phenotypic assays is measuring a narrow range of partially overlapping traits that do not directly reflect fitness. This is likely a significant cause of the observed small phenotypic impact from mutation, and is unrelated to robustness and redundancy. [ABSTRACT FROM AUTHOR]

Species with extensive ranges experience highly variable environments with respect to temperature, light and soil moisture. Synchronizing the transition from vegetative to floral growth is important to employ favorable conditions for reproduction. Optimal timing of this transition might be different for semelparous annual plants and iteroparous perennial plants., We studied variation in the critical photoperiod necessary for floral induction and the requirement for a period of cold-chilling (vernalization) in 46 populations of annuals and perennials in the Mimulus guttatus species complex. We then examined critical photoperiod and vernalization QTLs in growth chambers using F2 progeny from annual and perennial parents that differed in their requirements for flowering., We identify extensive variation in critical photoperiod, with most annual populations requiring substantially shorter day lengths to initiate flowering than perennial populations. We discover a novel type of vernalization requirement in perennial populations that is contingent on plants experiencing short days first. QTL analyses identify two large-effect QTLs which influence critical photoperiod. In two separate vernalization experiments we discover each set of crosses contain different large-effect QTLs for vernalization., Mimulus guttatus harbors extensive variation in critical photoperiod and vernalization that may be a consequence of local adaptation. [ABSTRACT FROM AUTHOR]

Differential natural selection acting on populations in contrasting environments often results in adaptive divergence in multivariate phenotypes. Multivariate trait divergence across populations could be caused by selection on pleiotropic alleles or through many independent loci with trait-specific effects. Here, we assess patterns of association between a suite of traits contributing to life history divergence in the common monkey flower, Mimulus guttatus, and examine the genetic architecture underlying these correlations. A common garden survey of 74 populations representing annual and perennial strategies from across the native range revealed strong correlations between vegetative and reproductive traits. To determine whether these multitrait patterns arise from pleiotropic or independent loci, we mapped QTLs using an approach combining high-throughput sequencing with bulk segregant analysis on a cross between populations with divergent life histories. We find extensive pleiotropy for QTLs related to flowering time and stolon production, a key feature of the perennial strategy. Candidate genes related to axillary meristem development colocalize with the QTLs in a manner consistent with either pleiotropic or independent QTL effects. Further, these results are analogous to previous work showing pleiotropy-mediated genetic correlations within a single population of M. guttatus experiencing heterogeneous selection. Our findings of strong multivariate trait associations and pleiotropic QTLs suggest that patterns of genetic variation may determine the trajectory of adaptive divergence., (© 2014 John Wiley & Sons Ltd.)