Simulations in Evolution. III. Randomness as a Generator of Opportunities

In Neo‐Darwinism, variation and natural selection are the two evolutionary mechanisms which propel biological evolution. Our previous reports presented a histogram model to simulate the evolution of populations of individuals classified into bins according to an unspecified, quantifiable phenotypic character, and whose number in each bin changed generation after generation under the influence of fitness, while the total population was maintained constant. The histogram model also allowed Shannon entropy (SE) to be monitored continuously as the information content of the total population decreased or increased. Here, a simple Perl (Practical Extraction and Reporting Language) application was developed to carry out these computations, with the critical feature of an added random factor in the percent of individuals whose offspring moved to a vicinal bin. The results of the simulations demonstrate that the random factor mimicking variation increased considerably the range of values covered by Shannon entropy, especially when the percentage of changed offspring was high. This increase in information content is interpreted as facilitated adaptability of the population.     

The development of a bin mapping population and the selective mapping of 103 markers in the diploid Fragaria reference map.

We have identified a set of plants (the bin set) to permit "selective" or "bin" mapping using the diploid strawberry mapping population FV x FN, derived from the F2 cross F. vesca 815 x F. nubicola 601, which has been used to develop the Fragaria reference map. The bin set consists of 8 plants: the F. vesca 815 parent, the F1 hybrid individual, and 6 seedlings of the F2 population. This bin set divides the 578 cM of the diploid Fragaria genome into 46 bins, the largest mapping bin being 26 cM in length and the average bin size being 12.6 cM. To validate the FV x FN bin set, we used it to locate 103 loci into bins on the FV x FN map. These loci comprised 61 previously described SSRs, 38 new SSRs developed in this investigation from Fragaria x ananassa genomic DNA, EST and gene sequences, and 4 ripening-related genes developed for Prunus. The 103 markers were located to bins on all 7 linkage groups of the Fragaria map and a new mapping bin was identified with the novel markers, demonstrating that the map covers the majority of the diploid Fragaria genome and that the 6 bin-set seedlings selected were appropriate for bin mapping using this progeny.     

Genetic Mapping and Genomic Selection Using Recombination Breakpoint Data

The correct models for quantitative trait locus mapping are the ones that simultaneously include all significant genetic effects. Such models are difficult to handle for high marker density. Improving statistical methods for high-dimensional data appears to have reached a plateau. Alternative approaches must be explored to break the bottleneck of genomic data analysis. The fact that all markers are located in a few chromosomes of the genome leads to linkage disequilibrium among markers. This suggests that dimension reduction can also be achieved through data manipulation. High-density markers are used to infer recombination breakpoints, which then facilitate construction of bins. The bins are treated as new synthetic markers. The number of bins is always a manageable number, on the order of a few thousand. Using the bin data of a recombinant inbred line population of rice, we demonstrated genetic mapping, using all bins in a simultaneous manner. To facilitate genomic selection, we developed a method to create user-defined (artificial) bins, in which breakpoints are allowed within bins. Using eight traits of rice, we showed that artificial bin data analysis often improves the predictability compared with natural bin data analysis. Of the eight traits, three showed high predictability, two had intermediate predictability, and two had low predictability. A binary trait with a known gene had predictability near perfect. Genetic mapping using bin data points to a new direction of genomic data analysis.     

Two Tests of Y Chromosomal Variation in Male Fertility of Drosophila Melanogaster

Deficiency mapping with Y autosome translocations has shown that the Y chromosome of Drosophila melanogaster carries genes that are essential to male fertility. While the qualitative behavior of these lesions provides important insight into the physiological importance of the Y chromosome, quantitative variation in effects on male fertility among extant Y chromosomes in natural populations may have a significant effect on the evolution of the Y chromosome. Here a series of 36 Y chromosome replacement lines were tested in two ways designed to detect subtle variation in effects on male fertility and total male fitness. The first test involved crossing males from the 36 lines to an excess of females in an attempt to measure differences in male mating success (virility) and male fecundity. The second test challenged males bearing each of the 36 Y chromosomes to competition in populations with males bearing a standard, phenotypically marked (BsY) chromosome. These tests indicated that the Y chromosome lines did not differ significantly in either male fertility or total fitness, but that interactions with autosomes approached significance. A deterministic population genetic model was developed allowing Y autosome interaction in fertility, and it is shown that, consistent with the experimental observations, this model cannot protect Y-linked polymorphism.     

Considerations for measuring genetic variation and population structure with multilocus fingerprinting

Multilocus DNA fingerprinting provides a cost-effective means to rapidly assay genetic variation at many loci. While this makes the technique particularly attractive for studies of evolution and conservation biology, fingerprint data can be difficult to interpret. Measurement errors inherent with the technique force investigators to group similar-sized alleles (bands) into discrete bins before estimating genetic parameters. If too little error is accounted for in this process homologous alleles will not be grouped in a common bin, whereas overestimated error can produce bins with homoplasic alleles. We used simulations and empirical data for two frog species ( Rana luteiventris and Hyla regilla ) to demonstrate that mean band-sharing ( S¯_xy ) and heterozygosity ( H ¯_E) are a function of both bin width and band profile complexity (i.e. number and distribution of bands). These estimators are also sensitive to the number of lanes included in the analysis when bin width is wide and a floating bin algorithm is employed. Multilocus estimates of H ¯_E were highly correlated with S¯_xy and thus provide no additional information about genetic variation. Estimates of population subdivision ( F ^ and Φ^_ST) appeared robust to changes in bin size. We also examined the issue of statistical independence for band-sharing data when comparisons are made among all samples. This analysis indicated that the covariance between band-sharing statistics was very small and not statistically different from zero. We recommend that sensitivity analyses for bin size be used to improve confidence in the biological interpretation of multilocus fingerprints, and that the covariance structure for band-sharing statistics be examined.     

Mapping with a few plants: using selective mapping for microsatellite saturation of the Prunus reference map

The concept of selective (or bin) mapping is used here for the first time, using as an example the Prunus reference map constructed with an almond x peach F2 population. On the basis of this map, a set of six plants that jointly defined 65 possible different genotypes for the codominant markers mapped on it was selected. Sixty-three of these joint genotypes corresponded to a single chromosomal region (a bin) of the Prunus genome, and the two remaining corresponded to two bins each. The 67 bins defined by these six plants had a 7.8-cM average length and a maximum individual length of 24.7 cM. Using a unit of analysis composed of these six plants, their F1 hybrid parent, and one of the parents of the hybrid, we mapped 264 microsatellite (or simple-sequence repeat, SSR) markers from 401 different microsatellite primer pairs. Bin mapping proved to be a fast and economic strategy that could be used for further map saturation, the addition of valuable markers (such as those based on microsatellites or ESTs), and giving a wider scope to, and a more efficient use of, reference mapping populations.     

基于染色体片段导入系发掘抗玉米丝黑穗病主效QTL

选用抗玉米丝黑穗病自交系Mo17和SH15为供体,与受体感病自交系黄早四和昌7-2构建回交群体(BC3F1\BC4F2),通过田间人工接种玉米丝黑穗病原菌鉴定抗病性表现,评价群体抗病性。研究结果显示黄早四×(黄早四×Mo17)BC4F2群体发病率明显高于BC3F1群体;两个BC4F2黄早四×(黄早四×Mo17)和昌7-2×(昌7-2×SH15)群体的发病率差异较大。采用SSR标记分析抗病株的供体染色体导入片段,发现随着回交次数的增多,导入片段数量减少,但不同回交群体中供体导入片段数目明显不同。通过连锁不平衡分析,在染色体2.09和3.04区段发掘和验证2个抗玉米丝黑穗病主效QTL,连锁标记分别为umc2077和phio53或bnlg1965。本文研究结果为抗丝黑穗病基因精细定位和分子聚合育种提供了信息和材料。     

Chi-square distance kernel of the gaits for the diagnosis of Parkinson's disease

In this paper, a new approach for the diagnosis of the subjects with Parkinson's disease (PD) from the healthy control subjects is proposed. This method uses the measurements of gait signals using the ground reaction forces under usual walking of the subjects. These measurements were computed using 8 sensors placed underneath of each foot. The absolute value of the difference between the force measurements were calculated for each sensor at each time and these signals went through a short-time Fourier transform (STFT) and several features were extracted from the spectrum of the signals. The histogram of these features was computed and the bin selection was performed using the feature discriminant ratio (FDR) method. Then the chi-square distance between the reduced histograms was computed and it formed a kernel for support vector machines (SVMs) for classification. The results on 93 subjects with PD and 73 healthy control subjects show that the proposed approach obtains an accuracy of 91.20% for the diagnosis of the PD using gait signals.     

An infinitesimal model for quantitative trait genomic value prediction

We developed a marker based infinitesimal model for quantitative trait analysis. In contrast to the classical infinitesimal model, we now have new information about the segregation of every individual locus of the entire genome. Under this new model, we propose that the genetic effect of an individual locus is a function of the genome location (a continuous quantity). The overall genetic value of an individual is the weighted integral of the genetic effect function along the genome. Numerical integration is performed to find the integral, which requires partitioning the entire genome into a finite number of bins. Each bin may contain many markers. The integral is approximated by the weighted sum of all the bin effects. We now turn the problem of marker analysis into bin analysis so that the model dimension has decreased from a virtual infinity to a finite number of bins. This new approach can efficiently handle virtually unlimited number of markers without marker selection. The marker based infinitesimal model requires high linkage disequilibrium of all markers within a bin. For populations with low or no linkage disequilibrium, we develop an adaptive infinitesimal model. Both the original and the adaptive models are tested using simulated data as well as beef cattle data. The simulated data analysis shows that there is always an optimal number of bins at which the predictability of the bin model is much greater than the original marker analysis. Result of the beef cattle data analysis indicates that the bin model can increase the predictability from 10% (multiple marker analysis) to 33% (multiple bin analysis). The marker based infinitesimal model paves a way towards the solution of genetic mapping and genomic selection using the whole genome sequence data.     

Identifying genomic regions for fine-mapping using genome scan meta-analysis (GSMA) to identify the minimum regions of maximum significance (MRMS) across populations

In order to detect linkage of the simulated complex disease Kofendrerd Personality Disorder across studies from multiple populations, we performed a genome scan meta-analysis (GSMA). Using the 7-cM microsatellite map, nonparametric multipoint linkage analyses were performed separately on each of the four simulated populations independently to determine p-values. The genome of each population was divided into 20-cM bin regions, and each bin was rank-ordered based on the most significant linkage p-value for that population in that region. The bin ranks were then averaged across all four studies to determine the most significant 20-cM regions over all studies. Statistical significance of the averaged bin ranks was determined from a normal distribution of randomly assigned rank averages. To narrow the region of interest for fine-mapping, the meta-analysis was repeated two additional times, with each of the 20-cM bins offset by 7 cM and 13 cM, respectively, creating regions of overlap with the original method. The 6-7 cM shared regions, where the highest averaged 20-cM bins from each of the three offsets overlap, designated the minimum region of maximum significance (MRMS). Application of the GSMA-MRMS method revealed genome wide significance (p-values refer to the average rank assigned to the bin) at regions including or adjacent to all of the simulated disease loci: chromosome 1 (p < 0.0001 for 160-167 cM, including D1), chromosome 3 (p-value < 0.0000001 for 287-294 cM, including D2), chromosome 5 (p-value < 0.001 for 0-7 cM, including D3), and chromosome 9 (p-value < 0.05 for 7-14 cM, the region adjacent to D4). This GSMA analysis approach demonstrates the power of linkage meta-analysis to detect multiple genes simultaneously for a complex disorder. The MRMS method enhances this powerful tool to focus on more localized regions of linkage.     

A count-dependent filter for smoothing flow cytometric histograms

An adaptive count-dependent algorithm for smoothing statistically limited histograms has been developed. It considers both the spatial frequency limitations of the measurement system (described by the measurement system point spread function) and the reliability of the measured data (indicated by the effective number of counts influencing each channel of the histogram. Windows for smoothing flow cytometric histograms are derived from an assumed Gaussian-shaped point spread function (PSF) with a constant coefficient of variation. The windows are developed by scaling the variances of the Gaussian functions inversely with the statistical reliability of the data contained in each channel of the measured histogram. The reliability of this data is determined by taking the square root of the number of counts influencing the value tabulated for each channel. Using the algorithm, a smoothed version of the measured histogram may be developed from a linear sum of the products of the individual scaled Gaussian functions and the original measured histogram. Data are presented demonstrating the advantages of count-dependent smoothing over non-count-dependent smoothing using synthesized DNA histograms as a function of sample size.     

VARIABLE SELECTION ON EUROSTA'S GALL SIZE,I: THE EXTENT AND NATURE OF VARIATION IN PHENOTYPIC SELECTION

Natural fluctuations in environmental conditions are likely to induce variation in the intensity or direction of natural selection. A long-term study of the insect, Eurosta solidaginins Fitch (Diptera; Tephritidae), which induces stem galls on the perennial herb Solidago altissima (Asteraceae) was performed to explore the patterns of variation in phenotypic selection. The intensity of selection imposed by parasitoids and predators on gallmaking larvae, for gall size, was measured across 16 populations over the course of 4 generations, for a total of 64 population-generations. Directional selection was quantified by i, the selection intensity, and variance selection by j‘, a measure of the intensity of selection on phenotypic variance. Size-dependent attack by parasitoids caused upward directional selection (mean i_p = 0.42; SE = 0.023), while size-dependent bird attack favored larvae that induced smaller galls (mean i_b = -0.07; SE = 0.013. The mean net directional selection intensity was 0.35 (SE = 0.030), which indicates that insects inducing larger galls are generally favored by selection. The opposing patterns of size-dependent attack resulted in stabilizing selection in half the population generations, with an overall average. j‘ of -0.11 (SE = 0.078). The magnitude of directional selection was strongly influenced by the population mean gall size and weakly by the optimal gall size. The intensity of variance selection was strongly influenced by the shape of the fitness function, with sigmoidal and Gaussian-like shapes causing greater depletion of phenotypic variance.     

Rarity in large data sets: Singletons,modal values and the location of the species abundance distribution

Species abundance data in 12 large data sets, holding 10 × 10³ to 125 × 10⁶ individuals in 350 to 10 × 10³ samples, were studied. Samples and subsets, for instance the summarized data of samples over years, and whole sets were analysed. Two methods of the binning of data, assigning abundance values to classes for histograms, have been applied in the past: bins of equal size and bins of exponentially increasing size (‘octaves’). A hump in a histogram with exponential bins does not represent a mode of primary, non-transformed abundance values, but of log transformed abundance values. A proper interpretation of the hump is given. Moreover, the extrapolation to the left of a histogram with exponential bins, below an abundance of unity, lifting a ‘veil’, hiding species present in the community but absent from the sample, is rejected. The literature is confusing at these points and, as a result, prevents a proper view on the species abundance distribution. Applying bins of equal size, modal values equalled or approached unity. The number of singletons increased with sample size in some data sets but decreased in others. However, singletons remain present in large samples, subsets or sets, in agreement with the results on modal values. The relatively high number of singletons in small samples is no artefact of undersampling. The mode at unity, that is at the left end of the species abundance distribution, independent of scale (sample, subset or set), is an important statistical property of the species abundance distribution. Our results may have implications for theory development in community ecology: the selection and/or development of an accurate species abundance model, and, connected to this, the formulation of improved assembly rules, and the selection and/or development of more precise species richness estimators.     

Toward a marker-dense meiotic map of the potato genome: lessons from linkage group I

Segregation data were obtained for 1260 potato linkage group I-specific AFLP loci from a heterozygous diploid potato population. Analytical tools that identified potential typing errors and/or inconsistencies in the data and that assembled cosegregating markers into bins were applied. Bins contain multiple-marker data sets with an identical segregation pattern, which is defined as the bin signature. The bin signatures were used to construct a skeleton bin map that was based solely on observed recombination events. Markers that did not match any of the bin signatures exactly (and that were excluded from the calculation of the skeleton bin map) were placed on the map by maximum likelihood. The resulting maternal and paternal maps consisted of 95 and 101 bins, respectively. Markers derived from EcoRI/MseI, PstI/MseI, and SacI/MseI primer combinations showed different genetic distributions. Approximately three-fourths of the markers placed into a bin were considered to fit well on the basis of an estimated residual "error rate" of 0-3%. However, twice as many PstI-based markers fit badly, suggesting that parental PstI-site methylation patterns had changed in the population. Recombination frequencies were highly variable across the map. Inert, presumably centromeric, regions caused extensive marker clustering while recombination hotspots (or regions identical by descent) resulted in empty bins, despite the level of marker saturation.     

Analysis of DNA synthesis rate of cultured cells from flow cytometric data

The rate of DNA synthesis along S phase is estimated from flow cytometric histograms on the basis of a mathematical model of a cell population. In the absence of loss, the model expresses the population kinetics in terms of DNA synthesis rate, S-phase influx, and population size. A single histogram is sufficient to determine the DNA synthesis rate when the population is in balanced exponential growth. Two suitably chosen histograms are necessary if the S-phase influx is exponential in a time interval longer than the S-phase duration. The analysis procedure was tested on published autoradiographic data and applied to three cultured cell lines (CM-S, 3LL, and M14 cells) that show various patterns of DNA distribution. In each case the cell-cycle fractions, the DNA synthesis rate, and the S-phase duration were obtained.     

Surprising Differences in the Variability of Y Chromosomes in African and Cosmopolitan Populations of Drosophila melanogaster

The nonrecombining Drosophila melanogaster Y chromosome is heterochromatic and has few genes. Despite these limitations, there remains ample opportunity for natural selection to act on the genes that are vital for male fertility and on Y factors that modulate gene expression elsewhere in the genome. Y chromosomes of many organisms have low levels of nucleotide variability, but a formal survey of D. melanogaster Y chromosome variation had yet to be performed. Here we surveyed Y-linked variation in six populations of D. melanogaster spread across the globe. We find surprisingly low levels of variability in African relative to Cosmopolitan (i.e., non-African) populations. While the low levels of Cosmopolitan Y chromosome polymorphism can be explained by the demographic histories of these populations, the staggeringly low polymorphism of African Y chromosomes cannot be explained by demographic history. An explanation that is entirely consistent with the data is that the Y chromosomes of Zimbabwe and Uganda populations have experienced recent selective sweeps. Interestingly, the Zimbabwe and Uganda Y chromosomes differ: in Zimbabwe, a European Y chromosome appears to have swept through the population.     

Mitochondrial DNA diversity, population structure, and gender association in the gynodioecious plant Silene vulgaris

A highly variable mitochondrial DNA (mtDNA) restriction fragment length polymorphism (RFLP) locus is used to assess the population structure of mitochondrial genomes in the gynodioecious plant Silene vulgaris at two spatial scales. Thirteen mtDNA haplotypes were identified within 250 individuals from 18 populations in a 20-km diameter region of western Virginia. The population structure of these mtDNA haplotypes was estimated as thetaST = 0.574 (+/- 0.066 SE) and, surprisingly, genetic differentiation among populations was negatively correlated with geographic distance (Mantel r = -0.246, P < 0.002). Additionally, mtDNA haplotypes were spatially clumped at the scale of meters within one population. Gender in S. vulgaris is determined by an interaction between autosomal male fertility restorers and cytoplasmic male sterility (CMS) factors, and seed fitness is affected by an interaction between gender and population sex ratio; thus, selection acting on gender could influence the distribution of mtDNA RFLP haplotypes. The sex ratio (females:hermaphrodites) varied among mtDNA haplotypes across the entire metapopulation, possibly because the haplotypes were in linkage disequilibrium with different CMS factors. The gender associated with some of the most common haplotypes varied among populations, suggesting that there is also population structure in male fertility restorer genes. In comparison with reports of mtDNA variation from other published studies, we found that S. vulgaris exhibits a large number of mtDNA haplotypes relative to that observed in other species.     

Comparison of aeration and spinosad for suppressing insects in stored wheat

Field studies were conducted from July 2002 to January 2003 for evaluating the effects of controlled aeration and a commercial biological insecticide, spinosad, in suppressing insect populations in stored wheat. Six cylindrical steel bins were filled with newly harvested (2002 crop year) hard red winter wheat on 9 and 10 July 2002. Each bin contained 30.7 metric tons (1,100 bu) of wheat. Wheat in two bins was left untreated (control), whereas wheat in two bins was treated with spinosad, and in another two bins was subjected to aeration by using aeration controllers. Spinosad was applied to wheat at the time of bin filling to obtain a rate of 1 mg ([AI])/kg. Aeration controllers were set to run the fans when ambient air temperature fell below 23.9, 18.3, and 7.2 degrees C for the first, second, and third cooling cycles, respectively. We added 400 adults each of the rusty grain beetle, Cryptolestes ferrugineus (Stephens); lesser grain borer, Rhyzopertha dominica (F.); and red flour beetle, Tribolium castaneum (Herbst), to the grain at monthly intervals between July and October 2002. Insect density in the bins was estimated monthly by taking 3-kg grain samples from 21 locations within each bin by using a pneumatic grain sampler. No live T. castaneum or C. ferrugineus and very low densities of R. dominica (<0.008 adults per kilogram) were found in wheat treated with spinosad during the 6-mo sampling period. Density of C. ferrugineus and T. castaneum in aerated bins did not exceed two adults per kilogram (the Federal Grain Inspection Service standard for infested wheat), whereas R. dominica increased to 12 adults per kilogram in November 2002, which subsequently decreased to three adults per kilogram in January 2003. In the untreated (control) bins, R. dominica density increased faster than that of C. ferrugineus or T. castaneum. Density of R. dominica peaked at 58 adults per kilogram in October 2002 and decreased subsequently, whereas T. castaneum density was 10 adults per kilogram in October 2002 but increased to 78 adults per kilogram in January 2003. Density of C. ferrugineus increased steadily during the 6-mo study period and was highest (six adults per kilogram) in January 2003. This is the first report comparing the field efficacy of spinosad and aeration in managing insects in farm bins. Our results suggest that spinosad is very effective in suppressing R. dominica, C. ferrugineus, and T. castaneum populations in stored wheat.