4.5 Review

Quantifying inbreeding in natural populations of hermaphroditic organisms

Journal

HEREDITY
Volume 100, Issue 4, Pages 431-439

Publisher

NATURE PUBLISHING GROUP
DOI: 10.1038/hdy.2008.2

Keywords

self-fertilization; inbreeding; genetic markers; population structure; progeny-arrays; MLTR

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We review molecular methods for estimating selfing rates and inbreeding in populations. Two main approaches are available: the population structure approach (PSA) and progeny-array approach (PAA). The PSA approach relies on single-generation samples and produces estimates that integrate the inbreeding history over several generations, but is based on strong assumptions (for example, inbreeding equilibrium). The PSA has classically relied on single-locus inbreeding coefficients averaged over loci. Unfortunately PSA estimates are very sensitive to technical problems such as the occurrence of null alleles at one or more of the loci. Consequently inbreeding might be substantially overestimated, especially in outbred populations. However, the robustness of the PSA has recently been greatly improved by the development of multilocus methods free of such bias. The PAA, on the other hand, is based on the comparison between offspring and mother genotypes. As a consequence, PAA estimates do not reflect long- term inbreeding history but only recent mating events of the maternal individuals studied ('here and now' selfing). In addition to selfing rates, the PAA allows estimating other mating system parameters, including biparental inbreeding and the correlation of selfing among sibs. Although PAA estimates could also be biased by technical problems, incompatibilities between the mother's genotype and her offspring allow the identification and correction of such bias. For all methods, we provide guidelines on the required number of loci and sample sizes. We conclude that the PSA and PAA are equally robust, provided multilocus information is used. Although experimental constraints may make the PAA more demanding, especially in animals, the two methods provide complementary information, and can fruitfully be conducted together.

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