Biomedical subjects

B D Neff

Publications and source records attributed to B D Neff.

10 recordsLinked to original sources

PubMed2006

Sperm competition in a fish with external fertilization: the contribution of sperm number, speed and length.

The role of sperm number and quality in male competitiveness was investigated using in vitro fertilization experiments with bluegill (Lepomis macrochirus). Bluegill males use one of three mating tactics: 'sneakers', which streak spawn; 'satellites', which mimic females; and 'parentals', which are territorial. The in vitro experiments mimicked natural spawning by incorporating these males' mean proximity to eggs and timing of sperm release. Using a maximum-likelihood algorithm, raffle equations were fit to paternity data, which revealed a strong effect of sperm number on male competitiveness. There was no difference in sperm flagellum length, curvilinear swim speed or path linearity among the three male mating types, and these traits did not explain any additional variation in male competitiveness. It was estimated that, given closer proximity to eggs, satellites need release only 0.34 times as many sperm as parentals to obtain equal paternity. Despite being farther from the eggs and releasing sperm about half a second after parentals, sneakers need only release 0.58 times as many sperm as parentals to obtain equal paternity. Thus, the increased competitiveness of sneakers' sperm must come from a component of sperm quality other than speed or length.

Animals↗

PubMed2001

Dynamic adjustment of parental care in response to perceived paternity.

Theories of parental care evolution predict that genetic relatedness will be an important variable in the amount of care a parent provides. However, current inferences of relatedness-based parental investment from studies in humans and birds remain challenged. No study has yet demonstrated parental care adjustment in a manner uncomplicated by life-history correlates or experimental design. We now present a unique test that controls for individual life histories and demonstrates paternity-related dynamic adjustments in parental care. Brood-rearing male bluegill sunfish (Lepomis macrochirus) that are cuckolded to a varying degree will either increase or decrease their parental investment in response to changing information on paternity during brood development. Specifically, as parental males detect paternity lost to cuckolders and, hence, a reduction in the value of their brood, they adaptively lower their level of parental care. Conversely, if they detect that their paternity is higher than previously assessed, they adaptively raise their level of parental care. This dynamic adjustment during brood rearing indicates the importance of genetic relatedness in parental investment decisions and provides needed empirical support for theoretical predictions.

Animals↗

PubMed2001

Tactic-specific success in sperm competition.

Sperm competition is a major force in sexual selection, but its implications for mating-system and life-history evolution are only beginning to be understood. The well-known sneak-guard model predicts that sneaks will win in sperm competition. We now provide empirical confirmation of this prediction. Bluegill sunfish (Lepomis macrochirus) have both sneak (cuckolder) and guard (parental) males. Guards make nests, court females and provide solitary parental care for the embryos. Sneaks include small cuckolders, which are termed 'sneakers', that dart in and out of nests in order to ejaculate between the spawning pair and larger cuckolders, which are termed 'satellites', that mimic females in order to ejaculate between the spawning pair. Using field behavioural data, genetic data and new mathematical models for paternity analyses, we show, for the first time to the authors' knowledge, that sneaks fertilize more eggs than guards during sperm competition. In addition, we show that sneakers are superior to satellites in sperm competition and, thus, that even among sneaks there are tactic-specific differences in competitive success.

Animals↗

PubMed2001

A bayesian framework for parentage analysis: the value of genetic and other biological data.

We develop fractional allocation models and confidence statistics for parentage analysis in mating systems. The models can be used, for example, to estimate the paternities of candidate males when the genetic mother is known or to calculate the parentage of candidate parent pairs when neither is known. The models do not require two implicit assumptions made by previous models, assumptions that are potentially erroneous. First, we provide formulas to calculate the expected parentage, as opposed to using a maximum likelihood algorithm to calculate the most likely parentage. The expected parentage is superior as it does not assume a symmetrical probability distribution of parentage and therefore, unlike the most likely parentage, will be unbiased. Second, we provide a mathematical framework for incorporating additional biological data to estimate the prior probability distribution of parentage. This additional biological data might include behavioral observations during mating or morphological measurements known to correlate with parentage. The value of multiple sources of information is increased accuracy of the estimates. We show that when the prior probability of parentage is known, and the expected parentage is calculated, fractional allocation provides unbiased estimates of the variance in reproductive success, thereby correcting a problem that has previously plagued parentage analyses. We also develop formulas to calculate the confidence interval in the parentage estimates, thus enabling the assessment of precision. These confidence statistics have not previously been available for fractional models. We demonstrate our models with several biological examples based on data from two fish species that we study, coho salmon (Oncorhychus kisutch) and bluegill sunfish (Lepomis macrochirus). In coho, multiple males compete to fertilize a single female's eggs. We show how behavioral observations taken during spawning can be combined with genetic data to provide an accurate calculation of each male's paternity. In bluegill, multiple males and multiple females may mate in a single nest. For a nest, we calculate the fertilization success and the 95% confidence interval of each candidate parent pair.

Animals↗

PubMed2001

Microsatellite evolution in vertebrates: inference from AC dinucleotide repeats.

We analyze published data from 592 AC microsatellite loci from 98 species in five vertebrate classes including fish, reptiles, amphibians, birds, and mammals. We use these data to address nine major questions about microsatellite evolution. First, we find that larger genomes do not have more microsatellite loci and therefore reject the hypothesis that microsatellites function primarily to package DNA into chromosomes. Second, we confirm that microsatellite loci are relatively rare in avian genomes, but reject the hypothesis that this is due to physical constraints imposed by flight. Third, we find that microsatellite variation differs among species within classes, possibly relating to population dynamics. Fourth, we reject the hypothesis that microsatellite structure (length, number of alleles, allele dispersion, range in allele sizes) differs between poikilotherms and homeotherms. The difference is found only in fish, which have longer microsatellites and more alleles than the other classes. Fifth, we find that the range in microsatellite allele size at a locus is largely due to the number of alleles and secondarily to allele dispersion. Sixth, length is a major factor influencing mutation rate. Seventh, there is a directional mutation toward an increase in microsatellite length. Eighth, at the species level, microsatellite and allozyme heterozygosity covary and therefore inferences based on large-scale studies of allozyme variation may also reflect microsatellite genetic diversity. Finally, published microsatellite loci (isolated using conventional hybridization methods) provide a biased estimate of the actual mean repeat length of microsatellites in the genome.

Adenine↗

PubMed2000

Statistical confidence in parentage analysis with incomplete sampling: how many loci and offspring are needed?

We have recently presented models to estimate parentage in breeding systems with multiple mating and incomplete sampling of the candidate parents. Here we provide formulas to calculate the statistical confidence and the optimal trade-off between the number of loci and offspring. These calculations allow an understanding of the statistical significance of the parentage estimates as well as the appropriate sampling regime required to obtain a desired level of confidence. We show that the trade-off generally depends on the parentage of the putative parents. When parentage is low, sampling effort should concentrate on increasing the number of loci. Otherwise, there are similar benefits from increasing the number of loci or offspring. We demonstrate these methods using genetic data from a nest of the bluegill sunfish (Lepomis macrochirus).

Animals↗

PubMed2000

Parentage analysis with incomplete sampling of candidate parents and offspring.

Many breeding systems include 'multiple mating' in which males or females mate with multiple partners. We identify two forms of multiple mating: 'single-sex', where the next-generation individuals (NGIs) are the product of multiple mating by one sex; and 'two-sex', where the NGIs are the product of multiple mating by both sexes. For both mating systems we develop models that estimate the proportion of NGIs that is fathered (paternity) or mothered (maternity) by the putative parents. The models only require genetic data from the parent or parents in question and the sample of NGIs, as well as an estimate of population allele frequencies. The models provide unbiased estimates, can accommodate loci with many alleles and are robust to violations of their assumptions. They allow researchers to address intractable problems such as the parentage of seeds found on the ground, juvenile fish in a stream, and nestlings in a communal breeding bird. We demonstrate the models using genetic data from a nest of the bluegill sunfish Lepomis macrochirus, where the NGIs may be from multiple females that have spawned with multiple males from different life histories (cuckolder and parental).

Alleles↗

PubMedDate not supplied

Genetic paternity analysis and breeding success in bluegill sunfish (Lepomis macrochirus).

Fish have some of the most complex mating systems known in the animal kingdom. With the advent of powerful genetic markers and an emerging mathematical framework to calculate parentage, it is now possible to analyze genetic relatedness and gene flow in these systems. An important example is the bluegill sunfish (Lepomis macrochirus) which consists of parental males that provide sole care for the young, cuckolder males that parasitize the parentals, and females that actively choose among males within dense breeding colonies. In this article genetic markers for bluegill are characterized and their utility in parentage studies is demonstrated by calculating the genetic relatedness of parental males to their broods for an entire natural breeding colony. A novel Monte Carlo simulation is developed to calculate the confidence in the relatedness estimates and these data are used to provide an estimate of the mean breeding success of parental and cuckolder males. Finally, the applications of genetic analyses to understanding mating systems, parental care, and life-history evolution in bluegill are discussed.

Alleles↗

PubMedDate not supplied

A Bayesian model for assessing the frequency of multiple mating in nature.

Many breeding systems have multiple mating, in which males or females mate with multiple partners. With the advent of molecular markers, it is now possible to detect multiple mating in nature. However, no model yet exists to effectively assess the frequency of multiple mating (f(mm))--the proportion of broods with at least two males (or females) genetically contributing--from limited genetic data. We present a single-sex model based on Bayes' rule that incorporates the numbers of loci, alleles, offspring, and genetic parents. Two genetic criteria for calculating f(mm) are considered: the proportion of broods with three or more paternal (or maternal) alleles at any one locus and the total number of haplotypes observed in each brood. The former criterion provides the most precise estimates of f(mm). The model enables the calculation of confidence intervals and allows mutations (or typing errors) to be incorporated into the calculation. Failure to account for mutations can result in overestimates of f(mm). The model can also utilize other biological data, such as behavioral observations during mating, thereby increasing the accuracy of the calculation as compared to previous models. For example, when two sires contribute equally to multiply mated broods, only three loci with five equally common alleles are required to provide estimates of f(mm) with high precision. We demonstrate the model with an example addressing the frequency of multiple paternity in small versus large clutches of the endangered Kemp's Ridley sea turtle (Lepidochelys kempi) and show that females that lay large clutches are more likely to have multiply mated.

Animals↗

PubMedDate not supplied

Mean d(2) and divergence time: transformations and standardizations.

The fitness consequences of inbreeding and outbreeding have intrigued biologists for a long time. Recently a measure of relatedness of parental haplotypes has been proposed called mean d(2). This measure is based on a stepwise mutational process and therefore is tailored to microsatellite genetic markers. Theoretical work suggests that mean d(2) typically is less suited for measuring fitness consequences due to close inbreeding rather than heterozygosity. However, mean d(2) may be more appropriate than heterozygosity for measuring divergence times over longer time scales and thus for detecting outbreeding depression. Here, simulations are used to (1). identify appropriate standardization coefficients and transformations for mean d(2), and (2). evaluate mean d(2) as a measure of divergence time of parental lineages over time scales up to 10000 generations. Results show that mean d(2) is a linear predictor of divergence time. The coefficient of variation of mean d(2) approaches a constant value with increasing divergence time and therefore logarithm transformation is appropriate to restore homoscedasticity. When mutation rates and sizes are known for each locus they can be incorporated into a standardization coefficient to increase the precision of mean d(2). As few as 10 loci can explain more than 70% of the variation in divergence time between lineages. While heterozygosity outperforms mean d(2) at detecting differences in divergence time over relative short time periods ( or=1000 generations). However, gene flow of as little as 1% per generation can significantly reduce the ability of either mean d(2) or heterozygosity to estimate divergence time.

Computer Simulation↗