Adaptive Value of Phenological Traits in Stressful Environments: Predictions Based on Seed Production and Laboratory Natural Selection

Phenological traits often show variation within and among natural populations of annual plants. Nevertheless, the adaptive value of post-anthesis traits is seldom tested. In this study, we estimated the adaptive values of pre- and post-anthesis traits in two stressful environments (water stress and interspecific competition), using the selfing annual species Arabidopsis thaliana. By estimating seed production and by performing laboratory natural selection (LNS), we assessed the strength and nature (directional, disruptive and stabilizing) of selection acting on phenological traits in A. thaliana under the two tested stress conditions, each with four intensities. Both the type of stress and its intensity affected the strength and nature of selection, as did genetic constraints among phenological traits. Under water stress, both experimental approaches demonstrated directional selection for a shorter life cycle, although bolting time imposes a genetic constraint on the length of the interval between bolting and anthesis. Under interspecific competition, results from the two experimental approaches showed discrepancies. Estimation of seed production predicted directional selection toward early pre-anthesis traits and long post-anthesis periods. In contrast, the LNS approach suggested neutrality for all phenological traits. This study opens questions on adaptation in complex natural environment where many selective pressures act simultaneously

Environmental implications of gene flow from sugar beet to wild beet - current status and future research needs

Gene flow via seed or pollen is a basic biological process in plant evolution. The ecological and genetic consequences of gene flow depend on the amount and direction of gene flow as well as on the fitness of hybrids. The assessment of potential risks of transgenic plants should take into account the fact that conventional crops can often cross with wild plants. The precautionary approach in risk management of genetically modified plants (GMPs) may make it necessary to monitor significant wild and weed populations that might be affected by transgene escape. Gene flow is hard to control in wind-pollinated plants like beet (Beta vulgaris). In addition, wild beet populations potentially can undergo evolutionary changes which might expand their geographical distribution. Unintended products of cultivated beets pollinated by wild beets are weed beets that bolt and flower during their first year of planting. Weed beets cause yield losses and can delay harvest. Wild beets are important plant genetic resources and the preservation of wild beet diversity in Europe has been considered in biosafety research. We present here the methodology and research approaches that can be used for monitoring the geographical distribution and diversity of Beta populations. It has recently been shown that a century of gene flow from Beta vulgaris ssp. vulgaris has not altered the genetic diversity of wild Beta vulgaris L. ssp. maritima (L.) Arcang. in the Italian sugar beet seed production area. Future research should focus on the potential evolution of transgenic wild beet populations in comparison to these baseline data. Two monitoring models are presented describing how endpoints can be measured: (1) “Pre-post” crop commercialization against today's baseline and (2) “Parallel” to crop commercialization against GMP free reference areas/populations. Model 2 has the advantage of taking ongoing changes in genetic diversity and population dynamics into account. Model 1 is more applicable if gene flow is so strong that most areas/populations contain GMPs. Important traits that may change the ecology of populations are genes that confer tolerance to biotic and abiotic stress. An assessment of environmental effects can realistically only be based on endpoints and consequences of gene introgression, which may include economic values of biodiversity in littoral and other ecosystems containing wild beet. In general, there is still a great need to harmonize worldwide monitoring systems by the development of appropriate methods to evaluate the environmental impact of introgressed transgenes

Data from: Adaptive value of phenological traits in stressful environments: predictions based on seed production and laboratory natural selection

Phenological traits often show variation within and among natural populations of annual plants. Nevertheless, the adaptive value of post-anthesis traits is seldom tested. In this study, we estimated the adaptive values of pre- and post-anthesis traits in two stressful environments (water stress and interspecific competition), using the selfing annual species Arabidopsis thaliana. By estimating seed production and by performing laboratory natural selection (LNS), we assessed the strength and nature (directional, disruptive and stabilizing) of selection acting on phenological traits in A. thaliana under the two tested stress conditions, each with four intensities. Both the type of stress and its intensity affected the strength and nature of selection, as did genetic constraints among phenological traits. Under water stress, both experimental approaches demonstrated directional selection for a shorter life cycle, although bolting time imposes a genetic constraint on the length of the interval between bolting and anthesis. Under interspecific competition, results from the two experimental approaches showed discrepancies. Estimation of seed production predicted directional selection toward early pre-anthesis traits and long post-anthesis periods. In contrast, the LNS approach suggested neutrality for all phenological traits. This study opens questions on adaptation in complex natural environment where many selective pressures act simultaneously

FITNESS_estimation

FITNESS_estimatio

Phenotypic selection analysis with selection differentials (S), selection gradients (β), quadratic selection coefficients (γ) for phenological traits in each treatment.

<p>GERM: germination timing, BT: bolting time, INT: interval between bolting and anthesis, ANT: anthesis, FLO: flowering, RP: reproductive period duration, FRR: flowering-to-reproductive period ratio. Selection is stabilizing when γ<0 and disruptive when γ>0. Standard errors (SE) are in parentheses. Values in bold indicate significantly different selection coefficients compared to the ‘control’ treatment. Because ANT integrates BT and INT, ANT was not included in polynomial regressions.</p>*<p>0.05><i>P</i>>0.01,</p>**<p>0.01><i>P</i>>0.001,</p>***<p><i>P</i><0.001. NE: not estimated.</p

Correlations among phenological traits in five treatments.

<p>Within each treatment, phenotypic and genetic Pearson correlations are given above and below the diagonal, respectively. GERM: germination timing, BT: bolting time, INT: interval between bolting and anthesis, FLO: flowering, RP: reproductive period duration, FRR: flowering-to-reproductive period ratio. The correlations between RP or FRR and the other phenological traits were not computed for the two water stress treatments (see Material and Methods section).</p>*<p>0.05><i>P</i>>0.01,</p>**<p>0.01><i>P</i>>0.001,</p>***<p><i>P</i><0.001. NA: not available.</p

Genotypic selection analysis with selection differentials (S), selection gradients (β), quadratic selection coefficients (γ) for phenological traits in each treatment.

<p>GERM: germination timing, BT: bolting time, INT: interval between bolting and anthesis, ANT: anthesis, FLO: flowering, RP: reproductive period duration, FRR: flowering-to-reproductive period ratio. Selection was stabilizing when γ<0 and disruptive when γ>0. Standard errors (SE) are in parentheses. Values in bold indicate significantly different selection coefficients compared to the ‘control’ treatment. Because ANT integrates BT and INT, ANT was not included in polynomial regressions.</p>*<p>0.05><i>P</i>>0.01,</p>**<p>0.01><i>P</i>>0.001,</p>***<p><i>P</i><0.001. NE: not estimated.</p

Effect of water stress and competition on phenological traits and fitness.

<p>INT: interval between bolting and anthesis, ANT: anthesis, FLO: flowering, RP: reproductive period duration, FRR: flowering-to-reproductive period ratio, FITNESS: total silique length as a proxy of seed production. INT, FT, FP and RP are expressed in days. FITNESS is expressed in millimeters. Ctl: ‘control’ treatment. W−: ‘moderate water stress’ treatment. W+: ‘severe water stress’ treatment. C−: ‘moderate competition’ treatment. C+: ‘intense competition’ treatment. For each phenotypic trait, different letters indicate different phenotypic means among treatments after a Tukey's test of multiple comparisons of means (<i>P</i> = 0.05). Data are not available for RP and FRR in the two ‘water stress’ treatments (see Material and Methods).</p

Relationship between bolting time and fitness for each treatment at both phenotypic and genotypic levels.

<p>For illustration purposes, a polynomial regression including both linear and quadratic terms described either in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0032069#pone-0032069-t001" target="_blank">Table 1</a> (phenotypic level) or in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0032069#pone-0032069-t002" target="_blank">Table 2</a> (genotypic level) was first performed including all traits but bolting time. Then, a second polynomial regression including the linear and quadratic terms associated with bolting time was run on the residual fitness of the first polynomial regression. The black lines were drawn using the parameters from this second polynomial regression. BT: bolting time. BT is expressed in standardized values.</p