Abstract
Two Markov chain Monte Carlo algorithms are proposed that allow the partitioning of individuals into full-sib groups using single-locus genetic marker data when no parental information is available. These algorithms present a method of moving through the sibship configuration space and locating the configuration that maximizes an overall score on the basis of pairwise likelihood ratios of being full-sib or unrelated or maximizes the full joint likelihood of the proposed family structure. Using these methods, up to 757 out of 759 Atlantic salmon were correctly classified into 12 full-sib families of unequal size using four microsatellite markers. Large-scale simulations were performed to assess the sensitivity of the procedures to the number of loci and number of alleles per locus, the allelic distribution type, the distribution of families, and the independent knowledge of population allelic frequencies. The number of loci and the number of alleles per locus had the most impact on accuracy. Very good accuracy can be obtained with as few as four loci when they have at least eight alleles. Accuracy decreases when using allelic frequencies estimated in small target samples with skewed family distributions with the pairwise likelihood approach. We present an iterative approach that partly corrects that problem. The full likelihood approach is less sensitive to the precision of allelic frequencies estimates but did not perform as well with the large data set or when little information was available (e.g., four loci with four alleles).
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Selected References
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- Blouin M. S., Parsons M., Lacaille V., Lotz S. Use of microsatellite loci to classify individuals by relatedness. Mol Ecol. 1996 Jun;5(3):393–401. doi: 10.1111/j.1365-294x.1996.tb00329.x. [DOI] [PubMed] [Google Scholar]
- Fitzsimmons N. N. Single paternity of clutches and sperm storage in the promiscuous green turtle (Chelonia mydas). Mol Ecol. 1998 May;7(5):575–584. doi: 10.1046/j.1365-294x.1998.00355.x. [DOI] [PubMed] [Google Scholar]
- Kirkpatrick S., Gelatt C. D., Jr, Vecchi M. P. Optimization by simulated annealing. Science. 1983 May 13;220(4598):671–680. doi: 10.1126/science.220.4598.671. [DOI] [PubMed] [Google Scholar]
- Marshall T. C., Slate J., Kruuk L. E., Pemberton J. M. Statistical confidence for likelihood-based paternity inference in natural populations. Mol Ecol. 1998 May;7(5):639–655. doi: 10.1046/j.1365-294x.1998.00374.x. [DOI] [PubMed] [Google Scholar]
- Reeve H. K., Westneat D. F., Noon W. A., Sherman P. W., Aquadro C. F. DNA "fingerprinting" reveals high levels of inbreeding in colonies of the eusocial naked mole-rat. Proc Natl Acad Sci U S A. 1990 Apr;87(7):2496–2500. doi: 10.1073/pnas.87.7.2496. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Size T. On being an advocate. Nurs Forum. 1992 Oct-Dec;27(4):33–34. doi: 10.1111/j.1744-6198.1992.tb00917.x. [DOI] [PubMed] [Google Scholar]
- Thomas C. P. Lung Abscess. Postgrad Med J. 1935 Jan;11(111):28.4–2843. doi: 10.1136/pgmj.11.111.28. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Thomas S. C., Hill W. G. Estimating quantitative genetic parameters using sibships reconstructed from marker data. Genetics. 2000 Aug;155(4):1961–1972. doi: 10.1093/genetics/155.4.1961. [DOI] [PMC free article] [PubMed] [Google Scholar]