Evaluating the ability of the pairwise joint site frequency spectrum to co-estimate selection and demography

Frontiers in Genetics

Volumn 6, Issue Aug, 2015, Pages

  Mathew, Lisha A ^a   Jensen, Jeffrey D ^a  

^a EPFL   (Switzerland)

Author keywords

Genetic hitchhiking; Joint estimation; Joint site frequency spectrum; Positive selection; Selection and demography

Indexed keywords

ALLELE; ARTICLE; CYTOMEGALOVIRUS INFECTION; DEMOGRAPHY; GENE LOCUS; GENE MUTATION; GENE SEQUENCE; GENETIC SELECTION; GENETIC VARIABILITY; GENOME; HUMAN; JOINT SITE FREQUENCY SPECTRUM; POPULATION MIGRATION; POPULATION SIZE; POPULATION STRUCTURE; SERUM; SIMULATION; URINE;

EID: 84941008791     PISSN: None     EISSN: 16648021     Source Type: Journal    
DOI: 10.3389/fgene.2015.00268     Document Type: Article

References (36)

1. Alachiotis, N., Stamatakis, A., and Pavlidis, P. (2012). OmegaPlus: a scalable tool for rapid detection of selective sweeps in whole-genome datasets. Bioinformatics 28, 2274-2275. doi: 10.1093/bioinformatics/bts419.
2. Andolfatto, P., and Przeworski, M. (2000). A genome-wide departure from the standard neutral model in natural populations of Drosophila. Genetics 156, 257-268.
3. Bank, C., Hietpas, R. T., Wong, A., Bolon, D. N., and Jensen, J. D. (2014a). A Bayesian MCMC approach to assess the complete distribution of fitness effects of new mutations: uncovering the potential for adaptive walks in challenging environments. Genetics 196, 841-852. doi: 10.1534/genetics.113.156190.
4. Bank, C., Ewing, G. B., Ferrer-Admetlla, A., Foll, M., and Jensen, J. D. (2014b). Thinking too positive? Revisiting current methods of population genetic selection inference. Trends Genet. 30, 540-546. doi: 10.1016/j.tig.2014.09.010.
5. Crisci, J. L., Poh, Y. P., Mahajan, S., and Jensen, J. D. (2013). The impact of equilibrium assumptions on tests of selection. Front. Genet. 4:235. doi: 10.3389/fgene.2013.00235.
6. Domingues, V. S., Poh, Y. P., Peterson, B. K., Pennings, P. S., Jensen, J. D., and Hoekstra, H. E. (2012). Evidence of adaptation from ancestral variation in young populations of beach mice. Evolution 66, 3209-3221. doi: 10.1111/j.1558-5646.2012.01669.x.
7. Dowd, K. A., Netski, D. M., Wang, X. H., Cox, A. L., and Ray, S. C. (2009). Selection pressure from neutralizing antibodies drives sequence evolution during acute infection with hepatitis C virus. Gastroenterology 136, 2377-2386. doi: 10.1053/j.gastro.2009.02.080.
8. DuMont, V. B., Fay, J. C., Calabrese, P. P., and Aquadro, C. F. (2004). DNA variability and divergence at the notch locus in Drosophila melanogaster and D. simulans: a case of accelerated synonymous site divergence. Genetics 167, 171-185. doi: 10.1534/genetics.167.1.171.
9. Ewing, G., and Hermisson, J. (2010). MSMS: a coalescent simulation program including recombination, demographic structure and selection at a single locus. Bioinformatics 26, 2064-2065. doi: 10.1093/bioinformatics/btq322.
10. Foll, M., Poh, Y. P., Renzette, N., Ferrer-Admetlla, A., Bank, C., Shim, H., et al. (2014). Influenza virus drug resistance: a time-sampled population genetics perspective. PLoS Genet. 10:e1004185. doi: 10.1371/journal.pgen.1004185.
11. Foll, M., Shim, H., and Jensen, J. D. (2015). WFABC: a Wright-Fisher ABC-based approach for inferring effective population sizes and selection coefficients from time-sampled data. Mol. Ecol. Resour. 15, 87-98. doi: 10.1111/1755-0998.12280.
12. Gartner, J. J., Parker, S. C. J., Prickett, T. D., Dutton-Regester, K., Stitzel, M. L., Lin, J. C., et al. (2013). Whole-genome sequencing identifies a recurrent functional synonymous mutation in melanoma. Proc. Natl. Acad. Sci. U.S.A. 110, 13481-13486. doi: 10.1073/pnas.1304227110.
13. Hietpas, R. T., Bank, C., Jensen, J. D., and Bolon, D. N. A. (2013). Shifting fitness landscapes in response to altered environments. Evolution 67, 3512-3522. doi: 10.1111/evo.12207.
14. Jensen, J. D. (2014). On the unfounded enthusiasm for soft selective sweeps. Nat. Commun. 5:5281. doi: 10.1038/ncomms6281.
15. Jensen, J. D., Kim, Y., DuMont, V. B., Aquadro, C. F., and Bustamante, C. D. (2005). Distinguishing between selective sweeps and demography using DNA polymorphism data. Genetics 170, 1401-1410. doi: 10.1534/genetics.104.038224.
16. Jensen, J. D., Thornton, K. R., and Aquadro, C. F. (2008). Inferring selection in partially sequenced regions. Mol. Biol. Evol. 25, 438-446. doi: 10.1093/molbev/msm273.
17. Kim, Y., and Nielsen, R. (2004). Linkage disequilibrium as a signature of selective sweeps. Genetics 167, 1513-1524. doi: 10.1534/genetics.103.025387.
18. Kim, Y., and Stephan, W. (2002). Detecting a local signature of genetic hitchhiking along a recombining chromosome. Genetics 160, 765-777.
19. Mathew, L. A., Staab, P. R., Rose, L. E., and Metzler, D. (2013). Why to account for finite sites in population genetic studies and how to do this with Jaatha 2.0. Ecol. Evol. 3, 3647-3662. doi: 10.1002/ece3.722.
20. Messer, P. W., and Petrov, D. A. (2013). Frequent adaptation and the McDonald-Kreitman test. Proc. Natl. Acad. Sci. U.S.A. 110, 8615-8620. doi: 10.1073/pnas.1220835110.
21. Naduvilezhath, L., Rose, L. E., and Metzler, D. (2011). Jaatha: a fast composite-likelihood approach to estimate demographic parameters. Mol. Ecol. 20, 2709-2723. doi: 10.1111/j.1365-294X.2011.05131.x.
22. Nielsen, R., Williamson, S., Kim, Y., Hubisz, M. J., Clark, A. G., and Bustamante, C. (2005). Genomic scans for selective sweeps using SNP data. Genome Res. 15, 1566-1575. doi: 10.1101/gr.4252305.
23. Pavlidis, P., Jensen, J. D., and Stephan, W. (2010). Searching for footprints of positive selection in whole-genome SNP data from nonequilibrium populations. Genetics 185, 907-922. doi: 10.1534/genetics.110.116459.
24. Pavlidis, P., Zivkovic, D., Stamatakis, A., and Alachiotis, N. (2013). SweeD: likelihood-based detection of selective sweeps in thousands of genomes. Mol. Biol. Evol. 30, 2224-2234. doi: 10.1093/molbev/mst112.
25. Poh, Y. P., Domingues, V. S., Hoekstra, H. E., and Jensen, J. D. (2014). On the prospect of identifying adaptive loci in recently bottlenecked populations. PLoS ONE 9:e110579. doi: 10.1371/journal.pone.0110579.
26. Renzette, N., Bhattacharjee, B., Jensen, J. D., Gibson, L., and Kowalik, T. F. (2011). Extensive genome-wide variability of human cytomegalovirus in congenitally infected infants. PLoS Pathog. 7:e1001344. doi: 10.1371/journal.ppat.1001344.
27. Renzette, N., Gibson, L., Bhattacharjee, B., Fisher, D., Schleiss, M. R., Jensen, J. D., et al. (2013). Rapid intrahost evolution of human cytomegalovirus is shaped by demography and positive selection. PLoS Genet. 9:e1003735. doi: 10.1371/journal.pgen.1003735.
28. Renzette, N., Gibson, L., Jensen, J. D., and Kowalik, T. F. (2014). Human cytomegalovirus intrahost evolution-a new avenue for understanding and controlling herpesvirus infections. Curr. Opin. Virol. 8, 109-115. doi: 10.1016/j.coviro.2014.08.001.
29. Robertson, A. (1975). Remarks on the Lewontin-Krakauer test. Genetics 80:396.
30. Siol, M., Wright, S. I., and Barrett, S. C. H. (2010). The population genomics of plant adaptation. New Phytol. 188, 313-332. doi: 10.1111/j.1469-8137.2010.03401.x.
31. Tellier, A., Pfaffelhuber, P., Haubold, B., Naduvilezhath, L., Rose, L. E., Städler, T., et al. (2011). Estimating parameters of speciation models based on refined summaries of the joint site-frequency spectrum. PLoS ONE 6:e18155. doi: 10.1371/journal.pone.0018155.
32. Teshima, K., Coop, G., and Przeworski, M. (2006). How reliable are empirical genomic scans for selective sweeps? Genome Res. 16, 702-712. doi: 10.1101/gr.5105206.
33. Thornton, K. R., and Jensen, J. D. (2007). Controlling the false-positive rate in multilocus genome scans for selection. Genetics 175, 737-750. doi: 10.1534/genetics.106.064642.
34. Voight, B. F., Kudaravalli, S., Wen, X., and Pritchard, J. K. (2006). A map of recent positive selection in the human genome. PLoS Biol. 4:e72. doi: 10.1371/journal.pbio.0040072.
35. Williamson, S. H., Hernandez, R., Fledel-Alon, A., Zhu, L., Nielsen, R., and Bustamante, C. D. (2005). Simultaneous inference of selection and population growth from patterns of variation in the human genome. Proc. Natl. Acad. Sci. U.S.A. 102, 7882-7887. doi: 10.1073/pnas.0502300102.
36. Zhou, L., Bawa, R., and Holliday, J. A. (2014). Exome resequencing reveals signatures of demographic and adaptive processes across the genome and range of black cottonwood (Populus trichocarpa). Mol. Ecol. 23, 2486-2499. doi: 10.1111/mec.12752.