A genetic and spatial Bayesian analysis of mastitis resistance

A nationwide health card recording system for dairy cattle was introduced in Norway in 1975 (the Norwegian Cattle Health Services). The data base holds information on mastitis occurrences on an individual cow basis. A reduction in mastitis frequency across the population is desired, and for this purpose risk factors are investigated. In this paper a Bayesian proportional hazards model is used for modelling the time to first veterinary treatment of clinical mastitis, including both genetic and environmental covariates. Sire effects were modelled as shared random components, and veterinary district was included as an environmental effect with prior spatial smoothing. A non-informative smoothing prior was assumed for the baseline hazard, and Markov chain Monte Carlo methods (MCMC) were used for inference. We propose a new measure of quality for sires, in terms of their posterior probability of being among the, say 10% best sires. The probability is an easily interpretable measure that can be directly used to rank sires. Estimating these complex probabilities is straightforward in an MCMC setting. The results indicate considerable differences between sires with regards to their daughters disease resistance. A regional effect was also discovered with the lowest risk of disease in the south-eastern parts of Norway.     

Familial breast/ovarian cancer and BRCA1/2 genetic screening: the role of immunohistochemistry as an additional method in the selection of patients.

Only 20-25% of families screened for BRCA1/2 mutations are found positive. Because only a positive result is informative, we studied the role of BRCA1/2 immunohistochemistry as an additional method for patient selection. From 53 high-risk-affected probands, 18 (34%) had available paraffin blocks of their tumors and were selected for this study. Mutation screening was done by conformation-sensitive gel electrophoresis and multiplex ligation-dependent probe amplification. For immunohistochemistry, 21 neoplastic specimens (15 breast carcinomas, 5 ovary neoplasms, and 1 rectal adenocarcinoma) were analyzed with BRCA1 (monoclonal antibody, Ab-1, oncogene) and BRCA2 (polyclonal antibody, Ab-2, oncogene) antibodies. Absence of the BRCA1 protein was confirmed in negative tumors by Western blotting. Seven patients were positive for BRCA1/2 mutations: 5 for BRCA1 and 2 for BRCA2. Four out of five positive patients had tumors negative for BRCA1 immunostaining, and the remaining 13 BRCA1-negative patients had positive BRCA1 immunostaining in all tumor samples. Sensitivity to predict for BRCA1 mutation carriers was 80%, and specificity was 100%, with a positive predictive value of 100% and a negative predictive value of 93%. This correlation was statistically significant (p=0.001). No correlation was observed for BRCA2. If larger studies confirm these results, high-risk patients with BRCA1-negative tumors should be screened first for this gene.     

THE EVOLUTION OF GENETIC CORRELATIONS: AN ANALYSIS OF PATTERNS

The genetic correlation is a central parameter of quantitative genetics, providing a measure of the rate at which traits respond to indirect selection (i.e., selection that does not act upon the traits under study, but some other trait with which they have genes in common). In this paper, I review the pattern of variation among four combinations of traits: life history × life history (L × L), morphological × morphological (M × M), life history × morphological (L × M), and behavioral × behavioral (B × B). A few other combinations were investigated, but insufficient data were obtained for separate analysis. A total of 1798 correlations, distributed over 51 different animal and plant species, were analyzed. The analysis was conducted at two levels: first by dividing the data set solely by trait combination, and second by blocking the data by trait combination and species. Because selection will tend to fix alleles that show positive correlations with fitness traits faster than those that are negative and because the latter are expected to arise more frequently by mutation, correlations between life-history traits are predicted to be more often negative than those between morphological traits. This prediction was supported, with the ranking in decreasing proportion of negative correlations being: L × L > L × M > B × B > M × M. The mean magnitude of the genetic correlation shows little variation among morphological and life-history combinations, and the distribution of values is remarkably flat. However, the estimated standard errors and the coefficient of variation (SE/r_G) are large, making it difficult to separate biological factors influencing the pattern of dispersion from experimental error. Analysis of the phenotypic and genetic correlations suggest that for the combinations M × M and L × M, but not L × L or B × B, the phenotypic correlation is an adequate estimate of the genetic correlation.     

Unequivocal determination of sire allele origin for multiallelic microsatellites when only the sire and progeny are genotyped

The effect of a segregating economic trait locus (ETL) can be detected with the aid of a linked genetic marker, if specific alleles of each locus are in association among the individuals genotyped for the genetic marker. For dairy cattle this can be achieved by application of the ‘granddaughter design’. If only the sires and their sons are genotyped for the genetic markers, then the allele origin of sons having the same genotypes as their sires cannot be determined. Seven sires and 101 sons were genotyped for five microsatellites. The mean frequency of heterozygous sires was 77%. The mean number of alleles per locus was 8.2. Frequency of informative sons per locus ranged from 60% to 80% with a mean of 72%. With highly polymorphic microsatellites, at least 60% more grandsire families can be included in the analysis, and the number of sons assayed can be reduced by 40%, as compared to diallelic markers.     

Influence of genetic architecture on contemporary local evolution in the soapberry bug,Jadera haematoloma: artificial selection on beak length

Little is known about the influence of genetic architecture on local adaptation. We investigated the genetic architecture of the rapid contemporary evolution of mouthparts, the flight polymorphism and life history traits in the soapberry bug Jadera haematoloma (Hemiptera) using laboratory selection. The mouthparts of these seed‐feeding bugs have adapted in 40–50 years by decreasing in length following novel natural selection induced by a host switch to the seeds of an introduced tree with smaller fruits than those of the native host vine. Laboratory selection on beak length in both an ancestral population feeding on the native host and a derived population feeding on the introduced host reveals genetic variance allowing a rapid response (heritabilities of 0.51–0.87) to selection for either longer or shorter beaks. This selection resulted in reverse evolution by restoring long beaks in the derived population and forward evolution by re‐creating short beaks in the ancestral bugs. There were strong genetic correlations (0.68–0.84) in both populations between beak lengths and the frequency of flight morphs, with short beaks associated with short wings. The results reveal a genetically interrelated set of adaptive multivariate traits including both beak length and flight morph. This suite of traits reflects host plant patchiness and seeding phenology. Weaker evidence suggests that egg mass and early egg production may be elements of the same suite. Reversible or forward evolution thus may occur in a broad set of genetically correlated multivariate traits undergoing rapid contemporary adaptation to altered local environments.     

Chloroplast DNA phylogeography of Fagus crenata (Fagaceae) in Japan

 CpDNA variation in Japanese beech, Fagus crenata (Fagaceae), was studied in 45 populations distributed throughout the species' range. Two cpDNA regions were sequenced: the non-coding region between the trnL (UAA) 5′exon and trnF (GAA), and the trnK region (including matK). Thirteen distinct cpDNA haplotypes were recognized and each haplotype was found to be geographically structured. Two major clades (I and II+III) were revealed in phylogenetic analyses among the haplotypes using F. sylvatica as an outgroup. The haplotypes of Clade I were distributed mainly along the Japan Sea side of the Japanese Archipelago, while those of Clade II+III occurred chiefly along the Pacific Ocean side. Consequently, the distribution of the two major cpDNA clades suggests that there were two migration routes in the history of F. crenata; one along the Japan Sea and the other along the Pacific Ocean side of the Japanese Islands. Received March 19, 2001 Accepted November 22, 2001     

Polymorphism of the SLB serologically defined (non-MHC) alloantigenic system in pigs

Six new antigenic specificities (designated SLB-2 to SLB-7) detectable with polyclonal reagents in the complement-dependent lymphocytotoxic test were determined in the SLB alloantigenic system of pigs. The SLB specificities (including the previously described SLB-1) are controlled by 13 alleles. An analysis of a further 121 double backcross matings (with 817 offspring) confirmed that the products of SLB alleles segregated independently of the SLA haplotypes (swine MHC). In addition, in 112 families of the same mating type (with 746 progeny) the map distance of the SLB locus and the highly polymorphic L blood group locus was found to be 7.82 centimorgans in the heterogametic sex and 12.57 centimorgans in the homogametic sex.     

pathmatrix: a geographical information system tool to compute effective distances among samples

pathmatrix is a tool used to compute matrices of effective geographical distances among samples using a least‐cost path algorithm. This program is dedicated to the study of the role of the environment on the spatial genetic structure of populations. Punctual locations (e.g. individuals) or zones encompassing sample data points (e.g. demes) are used in conjunction with a species‐specific friction map representing the cost of movement through the landscape. Matrices of effective distances can then be exported to population genetic software to test, for example, for isolation by distance. pathmatrix is an extension to the geographical information system (GIS) software arcview 3.x.     

EVOLUTION AND EXTINCTION IN A CHANGING ENVIRONMENT: A QUANTITATIVE-GENETIC ANALYSIS

Because of the ubiquity of genetic variation for quantitative traits, virtually all populations have some capacity to respond evolutionarily to selective challenges. However, natural selection imposes demographic costs on a population, and if these costs are sufficiently large, the likelihood of extinction will be high. We consider how the mean time to extinction depends on selective pressures (rate and stochasticity of environmental change, and strength of selection), population parameters (carrying capacity, and reproductive capacity), and genetics (rate of polygenic mutation). We assume that in a randomly mating, finite population subject to density-dependent population growth, individual fitness is determined by a single quantitative-genetic character under Gaussian stabilizing selection with the optimum phenotype exhibiting directional change, or random fluctuations, or both. The quantitative trait is determined by a finite number of freely recombining, mutationally equivalent, additive loci. The dynamics of evolution and extinction are investigated, assuming that the population is initially under mutation-selection-drift balance. Under this model, in a directionally changing environment, the mean phenotype lags behind the optimum, but on the average evolves parallel to it. The magnitude of the lag determines the vulnerability to extinction. In finite populations, stochastic variation in the genetic variance can be quite pronounced, and bottlenecks in the genetic variance temporarily can impair the population's adaptive capacity enough to cause extinction when it would otherwise be unlikely in an effectively infinite population. We find that maximum sustainable rates of evolution or, equivalently, critical rates of environmental change, may be considerably less than 10% of a phenotypic standard deviation per generation.