This chapter begins with a brief discussion on the different types of forests in the world, including their scope and importance. Then, the causes of variation in forests are outlined. A brief history of forest genetics is also provided. Finally, the importance of forest genetics in both natural and managed forests is discussed.
The neighbourhood model apportions offspring of individual mother plants to self-fertilization, outcrossing to males within a circumscribed area around the mother plant (the neighbourhood), and outcrossing to males outside the neighbourhood. Formerly the model was applied only to haploid pollen gametes in the offspring of conifers, but is extended so that it can be used with genotypic data from diploid offspring of both angiosperms and gymnosperms. In addition, it is shown that the mating parameters can be estimated without independent estimates of allele frequencies in the pollen pools outside the neighbourhood; thus the model might be applied effectively to natural populations exposed to unknown external pollen sources. Parameters of the neighbourhood mating model were estimated for a 10-year-old seed orchard population of the insect-pollinated tree, Eucalyptus regnans, in southeast Australia, which contained a mixture of two geographical provenances (Victoria and Tasmania). The mating patterns revealed were complex. Crosses between trees of the same provenance occurred three times more often than crosses between trees of different provenances. Levels of self-fertilization and patterns of mating within neighbourhoods were influenced by provenance origin, crop fecundity and orchard position (central vs. edge) of mother trees. Gene dispersal, however, was extensive, with approximately 50% of effective pollen gametes coming from males more than 40 m away from mother trees (average distance between neighbouring trees was 7.4 m). Thus, insect pollinators are efficient promoters of cross-fertilization in this orchard, with the result that the effective number of males mating with each female is large.
Estimating seed and pollen gene flow in plants on the basis of samples of naturally regenerated seedlings can provide much needed information about ''realized gene flow,'' but seems to be one of the greatest challenges in plant population biology. Traditional parentage methods, because of their inability to discriminate between male and female parentage of seedlings, unless supported by uniparentally inherited markers, are not capable of precisely describing seed and pollen aspects of gene flow realized in seedlings. Here, we describe a maximum-likelihood method for modeling female and male parentage in a local plant population on the basis of genotypic data from naturally established seedlings and when the location and genotypes of all potential parents within the population are known. The method models female and male reproductive success of individuals as a function of factors likely to influence reproductive success (e.g., distance of seed dispersal, distance between mates, and relative fecundity-i.e., female and male selection gradients). The method is designed to account for levels of seed and pollen gene flow into the local population from unsampled adults; therefore, it is well suited to isolated, but also wide-spread natural populations, where extensive seed and pollen dispersal complicates traditional parentage analyses. Computer simulations were performed to evaluate the utility and robustness of the model and estimation procedure and to assess how the exclusion power of genetic markers (isozymes or microsatellites) affects the accuracy of the parameter estimation. In addition, the method was applied to genotypic data collected in Scots pine (isozymes) and oak (microsatellites) populations to obtain preliminary estimates of long-distance seed and pollen gene flow and the patterns of local seed and pollen dispersal in these species.
Mutations in the p53 oncogene are extremely common in human cancers, and environmental exposure to mutagenic agents may play a role in the frequency and nature of the mutations. Differences in the patterns of p53 mutations have been observed for different tumor types. It is not trivial to determine if the differences observed in two mutational spectra are statistically significant. To this end, we present a computer program for comparison of two mutational spectra. The program runs on IBM-compatible personal computers and is freely available. The input for the program is a text file containing the number and nature of mutations observed in the two spectra. The output of the program is a P value, which indicates the probability that the two spectra are drawn from the same population. To demonstrate the program, the mutational spectra of single base substitutions in the p53 gene are compared in (i) bladder cancers from smokers and non-smokers, (ii) small-cell lung cancers, non-small-cell lung cancers and colon cancers and (iii) hepatocellular carcinomas from high- and low-aflatoxin exposure groups. p53 mutations differ in several important aspects from a typical mutational spectra experiment, where a homogeneous population of cells is treated with a specific mutagen and mutations at a specific locus are recovered by phenotypic selection. The means by which p53 mutations are recognized is by the appearance of a cancer, and this phenotype is very complex and varied.
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