Jon Slate

Statistical confidence for likelihood-based paternity inference in natural populations

Paternity inference using highly polymorphic codominant markers is becoming common in the study of natural populations. However, multiple males are often found to be genetically compatible with each offspring tested, even when the probability of excluding an unrelated male is high. While various methods exist for evaluating the likelihood of paternity of each nonexcluded male, interpreting these likelihoods has hitherto been difficult, and no method takes account of the incomplete sampling and error‐prone genetic data typical of large‐scale studies of natural systems. We derive likelihood ratios for paternity inference with codominant markers taking account of typing error, and define a statistic Δ for resolving paternity. Using allele frequencies from the study population in question, a simulation program generates criteria for Δ that permit assignment of paternity to the most likely male with a known level of statistical confidence. The simulation takes account of the number of candidate males, the proportion of males that are sampled and gaps and errors in genetic data. We explore the potentially confounding effect of relatives and show that the method is robust to their presence under commonly encountered conditions. The method is demonstrated using genetic data from the intensively studied red deer (Cervus elaphus) population on the island of Rum, Scotland. The Windows‐based computer program, CERVUS , described in this study is available from the authors. CERVUS can be used to calculate allele frequencies, run simulations and perform parentage analysis using data from all types of codominant markers.

Nonamplifying alleles at microsatellite loci: a caution for parentage and population studies.

While genotyping wild red deer (Cervus elaphus) at microsatellite loci for paternity assignment, we found three loci (MAP65, BOVIRBP and CelJP23) with segregating nonamplifying alleles. Nonamplifying alleles were detected through mismatches between known mother‐offspring pairs and by significant deviations from Hardy‐Weinberg equilibria. In a wide range of molecular ecology applications, and especially in parentage assignment, the possible existence of undetectable alleles must be taken into account; this may be particularly important for microsatellite data.

The genome of a songbird.

The zebra finch is an important model organism in several fields with unique relevance to human neuroscience. Like other songbirds, the zebra finch communicates through learned vocalizations, an ability otherwise documented only in humans and a few other animals and lacking in the chicken—the only bird with a sequenced genome until now. Here we present a structural, functional and comparative analysis of the genome sequence of the zebra finch (Taeniopygia guttata), which is a songbird belonging to the large avian order Passeriformes. We find that the overall structures of the genomes are similar in zebra finch and chicken, but they differ in many intrachromosomal rearrangements, lineage-specific gene family expansions, the number of long-terminal-repeat-based retrotransposons, and mechanisms of sex chromosome dosage compensation. We show that song behaviour engages gene regulatory networks in the zebra finch brain, altering the expression of long non-coding RNAs, microRNAs, transcription factors and their targets. We also show evidence for rapid molecular evolution in the songbird lineage of genes that are regulated during song experience. These results indicate an active involvement of the genome in neural processes underlying vocal communication and identify potential genetic substrates for the evolution and regulation of this behaviour.

Adaptation genomics: the next generation

Understanding the genetics of how organisms adapt to changing environments is a fundamental topic in modern evolutionary ecology. The field is currently progressing rapidly because of advances in genomics technologies, especially DNA sequencing. The aim of this review is to first briefly summarise how next generation sequencing (NGS) has transformed our ability to identify the genes underpinning adaptation. We then demonstrate how the application of these genomic tools to ecological model species means that we can start addressing some of the questions that have puzzled ecological geneticists for decades such as: How many genes are involved in adaptation? What types of genetic variation are responsible for adaptation? Does adaptation utilise pre-existing genetic variation or does it require new mutations to arise following an environmental change?

Microsatellites reveal heterosis in red deer

The fitness consequences of inbreeding and outbreeding are poorly understood in natural populations. We explore two microsatellite–based variables, individual heterozygosity (likely to correlate with recent inbreeding) and a new individual–specific internal distance measure, meand2 (focusing on events deeper in the pedigree), in relation to two measures of fitness expressed early in life, birth weight and neonatal survival, in 670 red deer calves (Cervus elaphus) born on the Isle of Rum between 1982 and 1996. For comparison, we also analyse inbreeding coefficients derived from pedigrees in which paternity was inferred by molecular methods.Only 14 out of 231 calves (6.1%) had non–zero inbreeding coefficients, and neither inbreeding coefficient nor individual heterozygosity was consistently related to birth weight or neonatal survival. However, meand2 was consistently related to both fitness measures. Low meand2 was associated with low birth weight, especially following cold Aprils, in which foetal growth is reduced. Low meand2 was also associated with low neonatal survival, but this effect was probably mediated by birth weight because fitting birth weight to the neonatal survival model displaced meand2 as an explanatory variable. We conclude that in the deer population fitness measures expressed early in life do not show evidence of inbreeding depression, but they do show evidence of heterosis, possibly as a result of population mixing. We also demonstrate the practical problems of estimating inbreeding via pedigrees compared with a direct marker–based estimate of individual heterozygosity. We suggest that, together, individual heterozygosity and meand2, estimated using microsatellites, are useful tools for exploring inbreeding and outbreeding in natural populations.

ANTLER SIZE IN RED DEER: HERITABILITY AND SELECTION BUT NO EVOLUTION

Abstract We present estimates of the selection on and the heritability of a male secondary sexual weapon in a wild population: antler size in red deer. Male red deer with large antlers had increased lifetime breeding success, both before and after correcting for body size, generating a standardized selection gradient of 0.44 (±0.18 SE). Despite substantial age- and environment-related variation, antler size was also heritable (heritability of antler mass = 0.33 ± 0.12). However the observed selection did not generate an evolutionary response in antler size over the study period of nearly 30 years, and there was no evidence of a positive genetic correlation between antler size and fitness nor of a positive association between breeding values for antler size and fitness. Our results are consistent with the hypothesis that a heritable trait under directional selection will not evolve if associations between the measured trait and fitness are determined by environmental covariances: In red deer males, for example, both antler size and success in the fights for mates may be heavily dependent on an individuals nutritional state.

Understanding the relationship between the inbreeding coefficient and multilocus heterozygosity: theoretical expectations and empirical data

Geneticists have been interested in inbreeding and inbreeding depression since the time of Darwin. Two alternative approaches that can be used to measure how inbred an individual is involve the use of pedigree records to estimate inbreeding coefficients or molecular markers to measure multilocus heterozygosity. However, the relationship between inbreeding coefficient and heterozygosity has only rarely been investigated. In this paper, a framework to predict the relationship between the two variables is presented. In addition, microsatellite genotypes at 138 loci spanning all 26 autosomes of the sheep genome were used to investigate the relationship between inbreeding coefficient and multilocus heterozygosity. Multilocus heterozygosity was only weakly correlated with inbreeding coefficient, and heterozygosity was not positively correlated between markers more often than expected by chance. Inbreeding coefficient, but not multilocus heterozygosity, detected evidence of inbreeding depression for morphological traits. The relevance of these findings to the causes of heterozygosity–fitness correlations is discussed and predictions for other wild and captive populations are presented.

A retrospective assessment of the accuracy of the paternity inference program cervus

cervus is a Windows‐based software package written to infer paternity in natural populations. It offers advantages over exclusionary‐based methods of paternity inference in that multiple nonexcluded males can be statistically distinguished, laboratory typing error is considered and statistical confidence is determined for assigned paternities through simulation. In this study we use a panel of 84 microsatellite markers to retrospectively determine the accuracy of statistical confidence when cervus was used to infer paternity in a population of red deer (Cervus elaphus). The actual confidence of cervus‐assigned paternities was not significantly different from that predicted by simulation.

MICROSATELLITE MEASURES OF INBREEDING: A META‐ANALYSIS

Abstract Meta‐analyses of published and unpublished correlations between phenotypic variation and two measures of genetic variation at microsatellite loci, multilocus heterozygosity (MLH) and mean d2, revealed that the strength of these associations are generally weak (mean r < 0.10). Effects on life‐history trait variation were significantly greater than zero for both measures over all reported effect sizes (r= 0. 0856 and 0.0479 for MLH and mean d2, respectively), whereas effects on morphometric traits were not (r= 0.0052 and r= 0.0038), which is consistent with the prediction that life‐history traits exhibit greater inbreeding depression than morphometric traits. Effect sizes reported using mean d2 were smaller and more variable than those reported using MLH, suggesting that MLH may be a better metric for capturing inbreeding depression most of the time. However, analyses of paired effect sizes reported using both measures from the same data did not differ significantly. Several lines of evidence suggest that published effects sizes are upwardly biased. First, effect sizes from published studies were significantly higher than those reported in unpublished studies. Second, fail‐safe numbers for reported effect sizes were generally quite low, with the exception of correlations between MLH and life‐history traits. Finally, the slope of the regression of effect size on sample size was negative for most sets of traits. Taken together, these results suggest that studies designed to detect inbreeding depression on a life‐history trait using microsatellites will need to sample in excess of 600 individuals to detect an average effect size (r= 0.10) with reasonable statistical power (0.80). Very few published studies have used samples sizes approaching this value.

Quantitative trait locus mapping in natural populations: progress, caveats and future directions

Over the last 15 years quantitative trait locus (QTL) mapping has become a popular method for understanding the genetic basis of continuous variation in a variety of systems. For example, the technique is now an integral tool in medical genetics, livestock production, plant breeding and population genetics of model organisms. Ten years ago, it was suggested that the method could be used to understand continuous variation in natural populations. In this review I: (i) clarify what is meant by natural population in the QTL context, (ii) discuss whether evolutionary biologists have successfully mapped QTL in natural populations, (iii) highlight some of the questions that have been addressed by QTL mapping in natural populations, (iv) describe how QTL mapping can be conducted in unmanipulated natural populations, (v) highlight some of the limitations of QTL mapping and (vi) try to predict some future directions for QTL mapping in natural populations.