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It was used the following multivariate statistical model:. Contrasts of orthogonal and multivariate means were performed to compare groups of treatment means to verify differences between the levels of heterozygosity tested, namely: C 1 : Homozygous lineages x segregant and mutant populations; C 2 : M 2 vs. M 7 ; C 7 : segregant populations x mutant populations C 8 : F 4 vs. The canonical discriminant analysis CCP was used to detect the response variables with greater canonical weight for the differentiation of heterozygosity levels.
CCPs are interpreted as follows: i positive values indicate the effect of separation between heterozygosity levels. Characters with higher CCP values show greater weight in the differentiation between the levels of heterozygosity; ii negative values can be interpreted similarly, but with opposite direction of the effect, so that the negative values reduce the response of the variable under study HAIR et al.
The multivariate analysis of variance showed significant difference for the vectors of the average generation factor nested to the population Table 1. This fact shows that the mechanisms associated with genetic variability artificial hybridization and induced mutation caused genetic changes in populations over the segregating generations, which allowed the optimization of genetic gain in beans. The analysis of variance is the first step of the tests that discriminate genotypes.
It provides important information about the existence of different genotypic constitutions. Agronomy Journal, v. Variables are often equally important or inter relate, thus establishing a structure of interest for research. The multivariate variance analysis identifies the co variation existing between the response variables HAIR et al. Therefore, understanding both the relationship and the effect of each variable under study can be fundamental for the biological sciences BERTINI et al.
Acta Scientiarum. Agronomy, v. Diallel analysis of combining ability and heterosis for yield and yield components in rice by using positive loci. Revista Ceres, v. The identification of these genotypes based on one character alone often leads to the failure of a plant variety in the market, especially when characters such as color, shape and size of the grains are not considered.
In Table 2 it was observed significant difference between homozygous lineages, mutant populations and other segregating contrast C 1.
The use of mutagenic agent and artificial hybridization increased the occurrence of heterozygous loci, which led to genetic variability in populations. A breeding program seeks balance between the traits studied so that the plant may have an ideotype that maximizes grain yield, taking into account the other traits associated BAENZIGER et al.
Improving lives: 50 years of crop breeding, genetics, and cytology C Crop Science, v. Efficiency of plant breeding. It is extremely important to bring together the trait pursued and the other associated traits. For example, there must be genetic variability for the trait SD, since a significant increase in the number of vegetables may not be supported by a plant that does not present increased stem diameter as well ROCHA et al.
Biotemas, v. On the other hand, the linear comparison C 2 inherent to the early mutant generations showed no significant difference Table 2. The first mutant generation presented changes in the mean populations.
These changes remained in subsequent mutant generations without causing significant differences between the mean vectors. In general, it is observed a strong prevalence of macromutation compared to micromutation. Macromutations led to changes in population averages, even in the first mutant generations. Mutation breeding.
Plant breeding. Significant difference was observed in the comparison C 3 Table 2. The physical mutagenic agent was efficient to cause consistent changes in both allele and genotypic frequencies of the traits COIMBRA et al.
Doses de raio gama na cultura da aveia: estatura de planta. These traits show narrow genetic variability in the populations studied. Rocha et al. There was significant difference in the linear comparison involved between the mutant population M 4 and other mutant populations C 4. Significant differences can also be found in contrast C 5 between M 5 vs. For each population r and He were estimated.
Successively, in the following steps b, c and d while the number of different alleles increases, He also increases in populations at both sides. However, in populations at the right side, since the alleles are equally frequent in all steps, He reaches the maximum values, while in the populations at left side, the new alleles show low frequencies rare alleles and He increases little by little.
Finally, in the step e He reaches the maximum value although all alleles are rare because of they show the same frequency. Hence, the estimation of He is highly dependent on allele frequencies and its value will be determined in a greater extent by the presence of alleles at high frequency which usually show high probability to be proportionally maintained when population reduce its size.
Changes in number of alleles NA and expected heterozygosity He as consequence of population size reduction. Changes in allelic richness r and expected heterozygosity He in small populations with increasing in number of different alleles: two, three, four, five and ten a, b, c, d and e, respectively. The effects of changes in population size on genetic diversity estimators considering different gene flow levels were studied in the present chapter by means of simulations A-C vs.
B-D, respectively. As expected, reductions in r and He values were obtained between large and small populations. In case that r and He are used for detecting genetic diversity reduction, r is more sensitive than He to detect genetic diversity reduction independently gene flow levels Table 3. The effects of gene flow levels on genetic diversity estimators considering different population sizes were studied in the present chapter by means of simulations A-C vs. In large populations, r is more sensitive than He to detect genetic diversity reduction as consequence of low gene flow level.
On the other hand, in small populations He is more sensitive than r to detect genetic diversity reduction as consequence of low gene flow level Table 4.
Gene flow is a microevolutionary process that maintain the genetic exchange among local populations increasing population genetic diversity [ 21 ]. Gene flow can be quantified by the parameter m , which describes the movement of each gamete or individual independently of population size [ 22 ].
As microevolutionary process, gene flow counteracts the genetic drift effect and the balance between gene flow and genetic drift determine genetic diversity levels for neutral alleles. Genetic diversity is the basis for local adaptation and genetic drift could be understood as a threat for biodiversity because of it causes genetic diversity loss in natural populations.
Current climate change and fragmentation of natural populations as consequence of anthropic impacts are calling to urgent collective and interdisciplinary actions from researchers. The study of genetic diversity levels is especially important for the management of endangered and valuable species. The focus in conservation biology is the maintenance of genetic diversity because of inbreeding and reduction in reproductive fitness is often associated with loss of genetic diversity [ 12 ].
Although the International Union for Conservation of Nature IUCN recognizes the need to conserve genetic diversity as one of three global conservation priorities [ 23 ] the genetic factors are not currently considered to assign the conservation status of species [ 24 ]. The comprehensive quantification of genetic diversity levels demand the estimation of r and He because of the sensitiveness of both estimators depends on allele multiplicity and frequencies. In this way, the estimation of r and He is recommended for genetics studies in populations that inhabit disturbed environments.
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Downloaded: Abstract Genetic diversity comprises the total of genetic variability contained in a population and it represents the fundamental component of changes since it determines the microevolutionary potential of populations. Keywords allelic richness computational simulations gene diversity molecular markers population genetics. That is, if we were to read along the DNA sequence that mom gave you and the DNA sequence that dad gave you, we would find absolutely, positively no differences in that gene or in the region of the gene that we're concerned about.
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