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Genetic Lines (genetic + line)

Distribution by Scientific Domains

Life Sciences	75%

Selected Abstracts

EVOLUTION AND STABILITY OF THE G-MATRIX ON A LANDSCAPE WITH A MOVING OPTIMUM

EVOLUTION, Issue 8 2004
Adam G. Jones
Abstract In quantitative genetics, the genetic architecture of traits, described in terms of variances and covariances, plays a major role in determining the trajectory of evolutionary change. Hence, the genetic variance-covariance matrix (G-matrix) is a critical component of modern quantitative genetics theory. Considerable debate has surrounded the issue of G-matrix constancy because unstable G-matrices provide major difficulties for evolutionary inference. Empirical studies and analytical theory have not resolved the debate. Here we present the results of stochastic models of G-matrix evolution in a population responding to an adaptive landscape with an optimum that moves at a constant rate. This study builds on the previous results of stochastic simulations of G-matrix stability under stabilizing selection arising from a stationary optimum. The addition of a moving optimum leads to several important new insights. First, evolution along genetic lines of least resistance increases stability of the orientation of the G-matrix relative to stabilizing selection alone. Evolution across genetic lines of least resistance decreases G-matrix stability. Second, evolution in response to a continuously changing optimum can produce persistent maladaptation for a correlated trait, even if its optimum does not change. Third, the retrospective analysis of selection performs very well when the mean G-matrix (,) is known with certainty, indicating that covariance between G and the directional selection gradient (3 is usually small enough in magnitude that it introduces only a small bias in estimates of the net selection gradient. Our results also show, however, that the contemporary ,-matrix only serves as a rough guide to ,. The most promising approach for the estimation of G is probably through comparative phylogenetic analysis. Overall, our results show that directional selection actually can increase stability of the G-matrix and that retrospective analysis of selection is inherently feasible. One ?riajor remaining challenge is to gain a sufficient understanding of the G-matrix to allow the confident estimation of ,. [source]

Biodemographic analysis of male honey bee mortality

AGING CELL, Issue 1 2005
Olav Rueppell
Summary Biodemographic studies of insects have significantly enhanced our understanding of the biology of aging. Eusocial insects have evolved to form different groups of colony members that are specialized for particular tasks and highly dependent on each other. These different groups (castes and sexes) also differ strongly in their life expectancy but relatively little is known about their mortality dynamics. In this study we present data on the age-specific flight activity and mortality of male honey bees from two different genetic lines that are exclusively dedicated to reproduction. We show that males initiating flight at a young age experience more flight events during their lifetime. No (negative) relation between the age at flight initiation and lifespan exists, as might be predicted on the basis of the antagonistic pleiotropy theory of aging. Furthermore, we fit our data to different aging models and conclude that overall a slight deceleration of the age-dependent mortality increase at advanced ages occurs. However, mortality risk increases according to the Gompertz,Makeham model when only days with flight activity (active days) are taken into account. Our interpretation of the latter is that two mortality components act on honey bee males during flight: increasing, age-dependent deaths (possibly from wear-and-tear), and age-independent deaths (possibly due to predation). The overall mortality curve is caused by the interaction of the distribution of age at foraging initiation and the mortality function during the active (flight) lifespan. [source]

Multivariate Cluster Analysis Regression Procedures as Tools to Identify Motile Sperm Subpopulations in Rabbit Semen and to Predict Semen Fertility and Litter Size

REPRODUCTION IN DOMESTIC ANIMALS, Issue 3 2007
A Quintero-Moreno
Contents Computerized motility analysis (CASA) shows that four separate subpopulations of spermatozoa with different motility characteristics co-exist in rabbit ejaculates. There were significant (p < 0.01) differences in the distribution of these subpopulations among separate genetic lines, total sperm abnormalities and the percentage of altered acrosomes. Furthermore, logistic and linear multivariate regressions among several parameters of rabbit semen quality analysis were tested for use as predictive tools for the fertilizing ability of a specific artificial insemination semen sample. Logistic regression analysis rendered two mathematical, significant (p < 0.01) models: one between sperm viability and conception rate and the other between total sperm abnormalities and conception rate. Multiple linear regression analyses also yielded some significant relationships between both fertility (p < 0.001) and litter size (p < 0.05), with respect to some semen characteristics. Our results support the hypothesis that the predictive in vivo fertility use of the standard rabbit semen quality analysis coupled with a CASA determination could be reasonably achieved by applying linear and logistic regression analyses among several parameters of rabbit semen quality analysis. [source]

Polymorphisms in vitamin D receptor, osteopontin, insulin-like growth factor 1 and insulin, and their associations with bone, egg and growth traits in a layer , broiler cross in chickens

ANIMAL GENETICS, Issue 3 2006
A. K. Bennett
Summary Bone strength traits in chickens are gaining importance due to economic losses and welfare concerns associated with bone fractures and other abnormalities. A chicken F2 resource population was generated from layer and broiler genetic lines, and traits relating to bone strength, egg production, egg quality and growth rate were measured in approximately 500 F2 hens. Four biological candidate genes (vitamin D receptor, VDR; insulin, INS; insulin-like growth factor 1, IGF1; and osteopontin, SPP1) were selected for investigation. Single nucleotide polymorphisms (SNPs) were identified for each candidate gene by comparing sequences between grandparent lines. Polymerase chain reaction restriction-fragment length polymorphism or SNaPshot assays were developed to genotype the F2 population and to evaluate associations between each SNP genotype and multiple phenotypes. Significant associations (P < 0.0125) were found between VDR and bone mineral content of the humerus at 35 weeks of age; between IGF1 and SPP1 and 5-week body weight; and between INS and 55-week body weight. [source]