The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Genomics advances the study of inbreeding depression in the wild
Open accessAbstract
Inbreeding depression (reduced fitness of individuals with related parents) has long been a major focus of ecology, evolution, and conservation biology. Despite decades of research, we still have a limited understanding of the strength, underlying genetic mechanisms, and demographic consequences of inbreeding depression in the wild. Studying inbreeding depression in natural populations has been hampered by the inability to precisely measure individual inbreeding. Fortunately, the rapidly increasing availability of high‐throughput sequencing data means it is now feasible to measure the inbreeding of any individual with high precision. Here, we review how genomic data are advancing our understanding of inbreeding depression in the wild. Recent results show that individual inbreeding and inbreeding depression can be measured more precisely with genomic data than via traditional pedigree analysis. Additionally, the availability of genomic data has made it possible to pinpoint loci with large effects contributing to inbreeding depression in wild populations, although this will continue to be a challenging task in many study systems due to low statistical power. Now that reliably measuring individual inbreeding is no longer a limitation, a major focus of future studies should be to more accurately quantify effects of inbreeding depression on population growth and viability.
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PLINK: a tool set for whole-genome association and population-based linkage analyses.
Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A. R., Bender, D., Maller, J., Sklar, P., de Bakker, P. I. W., Daly, M. J., et al. (2007) · The American Journal of Human Genetics · doi:10.1086/519795 · Cited by 34,089
A method and server for predicting damaging missense mutations.
Adzhubei, I. A., Schmidt, S., Peshkin, L., Ramensky, V. E., Gerasimova, A., Bork, P., Kondrashov, A. S., & Sunyaev, S. R. (2010) · Nature Methods · doi:10.1038/nmeth0410-248 · Cited by 13,194
Habitat fragmentation and its lasting impact on Earth’s ecosystems
Haddad, N. M., Brudvig, L. A., Clobert, J., Davies, K. F., Gonzalez, A., Holt, R. D., Lovejoy, T. E., Sexton, J. O., Austin, M. P., Collins, C. D., et al. (2015) · Science Advances · doi:10.1126/sciadv.1500052 · Cited by 4,773
Gutenkunst, R. N., Hernandez, R. D., Williamson, S. H., & Bustamante, C. D. (2009) · PLoS Genetics · doi:10.1371/journal.pgen.1000695 · Cited by 1,906
SAMPLING VARIANCES OF HETEROZYGOSITY AND GENETIC DISTANCE
Nei, M., & Roychoudhury, A. K. (1974) · Genetics · doi:10.1093/genetics/76.2.379 · Cited by 1,641
Approximate Bayesian Computation (ABC) in practice
Csilléry, K., Blum, M. G. B., Gaggiotti, O. E., & François, O. (2010) · Trends in Ecology & Evolution · doi:10.1016/j.tree.2010.04.001 · Cited by 1,302
Male-male competition magnifies inbreeding depression in wild house mice.
Meagher, S., Penn, D. J., & Potts, W. K. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.97.7.3324 · Cited by 322
Relatedness in the post-genomic era: is it still useful?
Speed, D., & Balding, D. J. (2015) · Nature Reviews Genetics · doi:10.1038/nrg3821 · Cited by 316
An investigation of inbreeding depression and purging in captive pedigreed populations
Boakes, E. H., Wang, J., & Amos, W. (2007) · Heredity · doi:10.1038/sj.hdy.6800923 · Cited by 217
Genomic legacy of the African cheetah, Acinonyx jubatus
Dobrynin, P., Liu, S., Tamazian, G., Xiong, Z., Yurchenko, A. A., Krasheninnikova, K., Kliver, S., Schmidt-Küntzel, A., Koepfli, K.-P., Johnson, W., et al. (2015) · Genome Biology · doi:10.1186/s13059-015-0837-4 · Cited by 204
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Population genomics for wildlife conservation and management
Hohenlohe, P. A., Funk, W. C., & Rajora, O. P. (2021) · Molecular Ecology · doi:10.1111/mec.15720 · Cited by 702
Understanding Inbreeding Depression, Purging, and Genetic Rescue
Hedrick, P. W., & Garcia-Dorado, A. (2016) · Trends in Ecology & Evolution · doi:10.1016/j.tree.2016.09.005 · Cited by 668
How genomics can help biodiversity conservation
Theissinger, K., Fernandes, C., Formenti, G., Bista, I., Berg, P. R., Bleidorn, C., Bombarely, A., Crottini, A., Gallo, G. R., Godoy, J. A., et al. (2023) · Trends in Genetics · doi:10.1016/j.tig.2023.01.005 · Cited by 401
The era of reference genomes in conservation genomics
Formenti, G., Theissinger, K., Fernandes, C., Bista, I., Bombarely, A., Bleidorn, C., Ciofi, C., Crottini, A., Godoy, J. A., Höglund, J., et al. (2022) · Trends in Ecology & Evolution · doi:10.1016/j.tree.2021.11.008 · Cited by 340
Purfield, D. C., McParland, S., Wall, E., & Berry, D. P. (2017) · PLOS ONE · doi:10.1371/journal.pone.0176780 · Cited by 308
Metadata
- Authors
- Kardos, M., Taylor, H. R., Ellegren, H., Luikart, G., & Allendorf, F. W.
- Venue
- Evolutionary Applications
- Publisher
- Wiley
- Published
- 2016-10-23
- Volume
- 9
- Issue
- 10
- Pages
- 1205-1218
- ISSN
- 1752-4563 (ISSN-L)
- 1752-4571
- OpenAlex
- W2513975280
- Cited by
- 387
- References
- 11
- FWCI
- 22.02
- Type
- journal article
- Language
- en
- Open access
- gold
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