Pollen competitive ability in maize: within population variability and response to selection

Summary Male gametophytic selection can play a special role in the evolution of higher plant populations. The main assumption — gametophytic-sporophytic gene expression of a large portion of a plant's genes — has been proven by a number of studies. Population analyses have revealed a large amount of variability for male gametophytic fitness. However, the data available do not prove that at least a portion of this variability is due to postmeiotic gene expression. This paper reports the analysis of a synthetic population of maize based on a gametophytic selection experiment, carried out according to a recurrent scheme. After two cycles of selection, the response was evaluated for gametophytic and sporophytic traits. A parameter representing pollen viability and time to germination, although showing a large amount of genetic variability, was not affected by gametophytic selection, indicating that this variability is largely sporophytically controlled. Pollen tube growth rate was significantly affected by gametophytic selection: 21.6% of the genetical variability was released by selection. Correlated response for sporophytic traits was observed for mean kernel weight: 15.67% of the variability was released. The results are a direct demonstration that pollen competitive ability due to pollen tube growth rate and kernel development are controlled, to a considerable extent, by genes expressed in both tissues. They also indicate that gametophytic selection in higher plants can produce a higher evolution rate than sporophytic selection; it can thus serve to regulate the amount of genetic variability in the populations by removing a large amount of the genetic load produced by recombination.     

Prediction of response with overlapping generations accounting for multistage selection

Summary A generalization of Hill's equations predicting response to selection is developed that accounts for multiple stage selection in either or both sexes. The method accounts for the flow of genes for animals selected at later stages. This allows for the use of genetic gains from later stages, which explains the reduction in variance due to previous selection. Genetic gains from different selection differentials in each reproductive pathway are incorporated into the equations. The asymptotic response to a single cycle of selection is shown to agree with classical selection theory.The method is applied to a dairy progeny testing scheme representative of an artificial insemination organization in the USA. Two models were compared: (1) the first model accounted for two-stage selection of males, the first stage being based on pedigree information and the second stage on both pedigree and progeny test information; and (2) the second model assumed single-stage male selection. Selection was based on milk volume, milk fat, and milk protein yields. The predicted asymptotic rates for a single cycle of selection were overestimated by 6% and the cumulative response to continuous selection over 20 years was overestimated by 8% by assuming singlestage male selection.Journal Paper No. J14146 of the Iowa Agriculture and Home Economics Experiment Station, Ames, Iowa; Project No. 1053     

Predicting long-term response to selection

Lande's equation for predicting the response of trait means to a shift in optimal trait values is tested using a stochastic simulation model. The simulated population is finite, and each individual has a finite number of loci. Therefore, selection may cause allele frequencies and distributions to change over time. Since the equation assumes constant genetic parameters, the degree to which such allelic changes affect predictions can be examined. Predictions are based only on information available at generation zero of directional selection. The quality of the predictions depends on the nature of allelic distributions in the original population. If allelic effects are approximately normally distributed, as assumed in Lande's Gaussian approximation to the continuum-of-alleles model, the predictions are very accurate, despite small changes in the G matrix. If allelic effects have a leptokurtic distribution, as is likely in Turelli's 'house-of-cards' approximation, the equation underestimates the rate of response and correlated response, and overestimates the time required for the trait means to reach their equilibrium values. Models with biallelic loci have limits as to the amount of trait divergence possible, since only two allelic values are available at each of a finite set of loci. If the new optimal trait values lie within these limits, predictions are good, if not, singularity in the G matrix results in suboptimal equilibria, despite the presence of genetic variance for each individual trait.     

Identification of positive selection in disease response genes within members of the Poaceae

Millions of years of coevolution between plants and pathogens can leave footprints on their genomes and genes involved on this interaction are expected to show patterns of positive selection in which novel, beneficial alleles are rapidly fixed within the population. Using information about upregulated genes in maize during Colletotrichum graminicola infection and resources available in the Phytozome database, we looked for evidence of positive selection in the Poaceae lineage, acting on protein coding sequences related with plant defense. We found six genes with evidence of positive selection and another eight with sites showing episodic selection. Some of them have already been described as evolving under positive selection, but others are reported here for the first time including genes encoding isocitrate lyase, dehydrogenases, a multidrug transporter, a protein containing a putative leucine-rich repeat and other proteins with unknown functions. Mapping positively selected residues onto the predicted 3-D structure of proteins showed that most of them are located on the surface, where proteins are in contact with other molecules. We present here a set of Poaceae genes that are likely to be involved in plant defense mechanisms and have evidence of positive selection. These genes are excellent candidates for future functional validation.     

Forward and reverse response to artificial selection

Summary The effect of t generations of reverse selection after t generations of forward selection can be described by expressing the change in the metric mean resulting from reverse selection (R) interms ofthe change in the metric mean due to the previous forward selection (x). An additive model of artificial selection in a population of effective size N with no natural selection has been considered.If reverse selection is continued for as many generations as the previous forward selection (t=t), then the ratio R/x equals 1 – F where F is the inbreeding coefficient for a neutral locus at generation t and is estimated as [1–(1–1/2N)^t]. The result of a single generation of reverse selection (t=1) following t generations of forward selection can be described in terms of the ratio NR₁/Dx where R₁ is the response to the first generation of reverse selection. The value of NR₁/x is expected to be (1–F) /2F.For any period of reverse selection following any period of forward selection, the value of R/x never exceeds t /t, and tends to decrease exponentially from this value as t increases.     

The incidental response to uniform natural selection

When populations are exposed to novel conditions of growth, they often become adapted to a similar extent, and at the same time, evolve some degree of impairment in their original environment. They may also come to vary widely with respect to characters which are uncorrelated with fitness, as the result of chance genetic associations among the founders, when these are a small sample from a large and variable ancestral population. I report an experiment in which 240 replicate lines of the unicellular chlorophyte Chlamydomonas were derived from primarily photoautotrophic ancestors and cultured as heterotrophs in the dark. All adapted to the dark and were impaired in the light after several hundred generations of culture. They also displayed a wide range of colony morphologies that were uncorrelated with fitness. This incidental response to selection probably arose through random variation in the initial composition of the lines. The differences between closely related species or varieties may likewise arise, in similar circumstances, by sampling error rather than natural selection.     

Sequence variations within protein families are linearly related to structural variations

It is commonly believed that similarities between the sequences of two proteins infer similarities between their structures. Sequence alignments reliably recognize pairs of protein of similar structures provided that the percentage sequence identity between their two sequences is sufficiently high. This distinction, however, is statistically less reliable when the percentage sequence identity is lower than 30% and little is known then about the detailed relationship between the two measures of similarity. Here, we investigate the inverse correlation between structural similarity and sequence similarity on 12 protein structure families. We define the structure similarity between two proteins as the cRMS distance between their structures. The sequence similarity for a pair of proteins is measured as the mean distance between the sequences in the subsets of sequence space compatible with their structures. We obtain an approximation of the sequence space compatible with a protein by designing a collection of protein sequences both stable and specific to the structure of that protein. Using these measures of sequence and structure similarities, we find that structural changes within a protein family are linearly related to changes in sequence similarity.     

Multilevel selection 1: Quantitative genetics of inheritance and response to selection

Interaction among individuals is universal, both in animals and in plants, and substantially affects evolution of natural populations and responses to artificial selection in agriculture. Although quantitative genetics has successfully been applied to many traits, it does not provide a general theory accounting for interaction among individuals and selection acting on multiple levels. Consequently, current quantitative genetic theory fails to explain why some traits do not respond to selection among individuals, but respond greatly to selection among groups. Understanding the full impacts of heritable interactions on the outcomes of selection requires a quantitative genetic framework including all levels of selection and relatedness. Here we present such a framework and provide expressions for the response to selection. Results show that interaction among individuals may create substantial heritable variation, which is hidden to classical analyses. Selection acting on higher levels of organization captures this hidden variation and therefore always yields positive response, whereas individual selection may yield response in the opposite direction. Our work provides testable predictions of response to multilevel selection and reduces to classical theory in the absence of interaction. Statistical methodology provided elsewhere enables empirical application of our work to both natural and domestic populations.     

An interval estimation of expected response to selection

Summary A method is presented here for obtaining an interval estimate of expected response to selection based on results of a progeny test experiment. The structure of the constructed confidence limits is then examined for the influence of the numbers of lines and replicates on the precision of predicting the expected response to selection.     

Localization of protein-binding sites within families of proteins

We address the question of whether or not the positions of protein-binding sites on homologous protein structures are conserved irrespective of the identities of their binding partners. First, for each domain family in the Structural Classification of Proteins (SCOP), protein-binding sites are extracted from our comprehensive database of structurally defined binary domain interactions (PIBASE). Second, the binding sites within each family are superposed using a structural alignment of its members. Finally, the degree of localization of binding sites within each family is quantified by comparing it with localization expected by chance. We found that 72% of the 1847 SCOP domain families in PIBASE have binding sites with localization values greater than expected by chance. Moreover, 554 (30%) of these families have localizations that are statistically significant (i.e., more than four standard deviations away from the mean expected by chance). In contrast, only 144 (8%) families have significantly low localization. The absence of a significant correlation of the binding site localization with the average sequence and structural conservations in a family suggests that localization can be helpful for describing the functional diversity of protein-protein interactions, complementing measures of sequence and structural conservation. Consideration of the binding site localization may also result in spatial restraints for the modeling of protein assembly structures.     

Prevalence of Helicobacter pylori CagA-producing strains within families

During prophylactic examination of blood sera taken from the members of 59 families by the enzyme immunoassay, antibodies to H. pylori and CagA protein were determined. As shown in this study, the children of non-infected mothers proved to be infected in 6.3% of cases and the children of infected mothers, in 72.1% of cases (p < 0.001). The children of non-infected fathers were H. pylori-positive in 71.4% and those of infected fathers, in 58.4% of cases. The CagA status was found to coincide in mothers and their children (p = 0.01), but not in fathers and their children. These data indicate that children acquire H. pylori infection from the members of their family, mainly from their mothers.     

Computational analysis of ligand relationships within target families

Computational tools for the large-scale analysis and prediction of ligand-target interactions and the identification of small molecules having different selectivity profiles within target protein families complement research in chemical genetics and chemogenomics. For computational analysis and design, such tasks require a departure from the traditional focus on single targets, hit identification, and lead optimization. Recently, studies have been reported that profile compounds in silico against arrays of targets or systematically map ligand-target space. In order to identify small molecular probes that are suitable for chemical genetics applications, molecular diversity needs to be viewed in a way that partly differs from principles guiding conventional library design.     

Phylogenetic relationships within cation transporter families of Arabidopsis

Uptake and translocation of cationic nutrients play essential roles in physiological processes including plant growth, nutrition, signal transduction, and development. Approximately 5% of the Arabidopsis genome appears to encode membrane transport proteins. These proteins are classified in 46 unique families containing approximately 880 members. In addition, several hundred putative transporters have not yet been assigned to families. In this paper, we have analyzed the phylogenetic relationships of over 150 cation transport proteins. This analysis has focused on cation transporter gene families for which initial characterizations have been achieved for individual members, including potassium transporters and channels, sodium transporters, calcium antiporters, cyclic nucleotide-gated channels, cation diffusion facilitator proteins, natural resistance-associated macrophage proteins (NRAMP), and Zn-regulated transporter Fe-regulated transporter-like proteins. Phylogenetic trees of each family define the evolutionary relationships of the members to each other. These families contain numerous members, indicating diverse functions in vivo. Closely related isoforms and separate subfamilies exist within many of these gene families, indicating possible redundancies and specialized functions. To facilitate their further study, the PlantsT database (http://plantst.sdsc.edu) has been created that includes alignments of the analyzed cation transporters and their chromosomal locations.     

Conservation and divergence in multigene families: alternatives to selection and drift

It is generally assumed that conservation and divergence of DNA signify function (selection) and no function (drift), respectively. This assumption is based on the view that a mutation is a unique event on a single chromosome, the fate of which depends on selection or drift. Knowledge of the rates, units and biases of widespread mechanisms of non-reciprocal DNA exchange, in particular within multigene families, provides alternative explanations for conservation and divergence, notwithstanding biological function. Such mechanisms of DNA turnover cause continual fluctuations in the copy-number of variant genes in an individual and, hence, promote the gradual and cohesive spread of a variant gene throughout a family (homogenization) and throughout a population (fixation). The dual processes (molecular drive) of homogenization and fixation are inextricably linked. Data are presented of the expected stages of transition in the spread of variant repeats by molecular drive in some non-genic families of DNA, seemingly not under the influence of selection. When a molecularly driven change in a given gene family is accompanied by the coevolution (mediated by selection) of other DNA, RNA or protein molecules that interact with the gene family then biological function is observed to be maintained despite sequence divergence. Conversely, the mechanics of DNA turnover and a turnover bias in favour of ancestral sequences can dramatically retard the rate of sequence change, in the absence of function. Examples of the maintenance of function by molecular coevolution and conservation of sequences in the absence of function, are drawn mainly from the rDNA multigene family.