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      Territorial Males Can Sire More Offspring in Nests with Smaller Doors in the Cichlid Lamprologus lemairii

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      Journal of Heredity
      Oxford University Press (OUP)

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          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 delta for resolving paternity. Using allele frequencies from the study population in question, a simulation program generates criteria for delta 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.
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            Sibship reconstruction from genetic data with typing errors.

            Likelihood methods have been developed to partition individuals in a sample into full-sib and half-sib families using genetic marker data without parental information. They invariably make the critical assumption that marker data are free of genotyping errors and mutations and are thus completely reliable in inferring sibships. Unfortunately, however, this assumption is rarely tenable for virtually all kinds of genetic markers in practical use and, if violated, can severely bias sibship estimates as shown by simulations in this article. I propose a new likelihood method with simple and robust models of typing error incorporated into it. Simulations show that the new method can be used to infer full- and half-sibships accurately from marker data with a high error rate and to identify typing errors at each locus in each reconstructed sib family. The new method also improves previous ones by adopting a fresh iterative procedure for updating allele frequencies with reconstructed sibships taken into account, by allowing for the use of parental information, and by using efficient algorithms for calculating the likelihood function and searching for the maximum-likelihood configuration. It is tested extensively on simulated data with a varying number of marker loci, different rates of typing errors, and various sample sizes and family structures and applied to two empirical data sets to demonstrate its usefulness.
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              Sperm in competition: not playing by the numbers.

              The outcome of sperm competition is mediated largely by the relative numbers of sperm from competing males. However, substantial variation in features of sperm morphology and behaviour, such as length, longevity and motility, exists and researchers have suggested that this variation functions in postcopulatory sexual selection. Recent studies have determined the effect of these sperm-quality traits on fertilization success and a synthesis of this literature reveals that they are important in both sperm competition and cryptic female choice. To understand how postcopulatory sexual selection influences sperm traits, future research should determine sex-specific interactions that influence paternity, identify genetic correlations between ejaculate characters, quantify the relative costs of producing different sperm traits, and test assumptions of models of sperm quality evolution. Such research will shed light on what evolutionary pressures are responsible for the diversity in sperm morphometry and behaviour.
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                Author and article information

                Journal
                Journal of Heredity
                Journal of Heredity
                Oxford University Press (OUP)
                0022-1503
                1465-7333
                April 12 2014
                May 01 2014
                February 26 2014
                May 01 2014
                : 105
                : 3
                : 416-422
                Article
                10.1093/jhered/esu009
                24574486
                46cb45fd-e831-43ca-abba-bb88085f4d71
                © 2014
                History

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