Comprehensive paternity assignment: genotype,spatial location and social status in song sparrows,Melospiza Melodia

Comprehensive, accurate paternity assignment is critical to answering numerous questions in evolutionary ecology. Yet, most studies of species with extra‐pair paternity (EPP) fail to assign sires to all offspring. Common limitations include incomplete and biased sampling of offspring and males, particularly with respect to male location and social status, potentially biasing estimated patterns of paternity. Studies that achieve comprehensive sampling and paternity assignment are therefore required. Accordingly, we genotyped virtually all males and >99% of 6‐day‐old offspring over 16 years in a song sparrow (Melospiza melodia) population and used three complementary statistical methodologies to attempt complete paternity assignment for all 2207 offspring. Assignments were highly consistent across maximum likelihood methods that used solely genotype data, and heuristic and integrated Bayesian analyses that included data describing individual locations. Sires were assigned to >99% of all genotyped offspring with ≥95% confidence, revealing an EPP rate of c. 28%. Extra‐pair sires primarily occupied territories neighbouring their extra‐pair offspring; spatial location was therefore highly informative for paternity assignment. EPP was biased towards paired territorial males, although unpaired territorial and floater males sired c. 13% of extra‐pair offspring. Failing to sample and include unpaired males as candidate sires would therefore substantially reduce assignment rates. These analyses demonstrate the integration of genetic and ecological information to achieve comprehensive paternity assignment and direct biological insight, illustrate the potential biases that common forms of incomplete sampling could have on estimated patterns of EPP, and provide an essential basis for understanding the evolutionary causes and consequences of EPP.     

Inbreeding is reduced by female-biased dispersal and mating behavior in Ethiopian wolves

Molecular tools have enabled wildlife researchers to obtainaccurate information on the kinship, mating behavior, and dispersalof individuals. We genotyped 192 Ethiopian wolves (n = 29 packs)in the Bale Mountains for 17 microsatellite loci to 1) elucidatekinship within and between packs, 2) assess parentage of pups,and 3) evaluate whether inbreeding is avoided by dispersal and/ormating behavior. Mean pairwise relatedness within packs (R =0.39) was significantly greater than that estimated from randomassignment of individuals to packs. However, breeding pairswere most often unrelated, suggesting that female-biased dispersalreduces inbreeding. We assigned maternity to 49 pups and paternityto 47 pups (n = 12 litters) using a combination of exclusion,likelihood analyses (using CERVUS software), and sibship reconstruction.Multiple paternity occurred in 33% of litters; extrapack paternityaccounted for 28% of all resolved paternities, occurring in50% of litters. We found no evidence that extrapack copulationsreduce inbreeding; however, more detailed analyses may elucidatethe effect of recent population declines and demographic disturbancesdue to recurring disease outbreaks. The adaptive advantagesof female-biased dispersal and the observed mating system arediscussed in relation to Ethiopian wolf sociobiology and ecology.     

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.