- THIS ARTICLE
- Full Text (PDF)
- Alert me when this article is cited
- Alert me if a correction is posted
- SERVICES
- Similar articles in this journal
- Similar articles in PubMed
- Alert me to new issues of the journal
- Download to citation manager
- Reprints & Permissions
- CITING ARTICLES
- Citing Articles via HighWire
- Citing Articles via Google Scholar
- GOOGLE SCHOLAR
- Articles by Smouse, P. E.
- Articles by Meagher, T. R.
- Search for Related Content
- PUBMED
- PubMed Citation
- Articles by Smouse, P. E.
- Articles by Meagher, T. R.
Genetics, Vol 136, 313-322, Copyright © 1994
INVESTIGATIONS |
Genetic Analysis of Male Reproductive Contributions in Chamaelirium luteum (L.) Gray (Liliaceae)
P. E. Smouse and T. R. Meagher
Center for Theoretical and Applied Genetics, and Institute of Marine and Coastal Sciences, Rutgers University, New Brunswick, New Jersey 08903-0231
Genealogical analysis is a powerful tool for analysis of reproductive performance in both natural and captive populations, but assignment of paternity has always been a stumbling block for this sort of work. Statistical methods for determining paternity have undergone several phases of development, ranging from straightforward genetic exclusion to assignment of paternity based on genetic likelihood criteria. In the present study, we present a genetic likelihood-based iterative procedure for fractional allocation of paternity within a progeny pool and apply this method to a population of Chamaelirium luteum, a dioecious member of the Liliaceae. Results from this analysis clearly demonstrate that different males make unequal contributions to the overall progeny pool, with many males contributing essentially nothing to the next generation. Furthermore, the distribution of paternal success among males shows a highly significant departure from (Poisson) randomness. The results from the present analysis were compared with earlier results obtained from the same data set, using likelihood-based categorical paternity assignments. The general biological pattern revealed by the two analyses is the same, but the estimates of reproductive success are only modestly (though significantly) correlated. The iterative procedure makes more complete use of the data and generates a more sharply resolved distribution of male reproductive success.
This article has been cited by other articles:
 |
|
 |
|
  B. Jones, G. D. Grossman, D. C. I. Walsh, B. A. Porter, J. C. Avise, and A. C. Fiumera Estimating Differential Reproductive Success From Nests of Related Individuals, With Application to a Study of the Mottled Sculpin, Cottus bairdi Genetics, August 1, 2007; 176(4): 2427 - 2439. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
D. A. Berry, J. D. Seltzer, C. Xie, D. L. Wright, and J. S. C. Smith Assessing Probability of Ancestry Using Simple Sequence Repeat Profiles: Applications to Maize Hybrids and Inbreds Genetics, June 1, 2002; 161(2): 813 - 824. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
R. Nielsen, D. K. Mattila, P. J. Clapham, and P. J. Palsbøll Statistical Approaches to Paternity Analysis in Natural Populations and Applications to the North Atlantic Humpback Whale Genetics, April 1, 2001; 157(4): 1673 - 1682. [Abstract] [Full Text]
|
|
|
|
 |
|
 B. D. Neff Genetic Paternity Analysis and Breeding Success in Bluegill Sunfish (Lepomis macrochirus) J. Hered., March 1, 2001; 92(2): 111 - 119. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. T. Morgan Properties of Maximum Likelihood Male Fertility Estimation in Plant Populations Genetics, June 1, 1998; 149(2): 1099 - 1103. [Abstract] [Full Text] [PDF]
|
|