Perspectives for Genomic Selection Applications and Research in Plants

Crop Science

Volumn 55, Issue 1, 2015, Pages 1-12

  Heslot, Nicolas ^a,b   Jannink, Jean Luc ^a   Sorrells, Mark E ^a  

^a Dep of Plant Breeding and Genetics ^*  (United States)

^b Limagrain Europe ^*  (France)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 85082119545     PISSN: 0011183X     EISSN: 14350653     Source Type: Journal    
DOI: 10.2135/cropsci2014.03.0249     Document Type: Article

References (87)

1. Adzhubei, I.A., Schmidt, S., Peshkin, L., Ramensky, V.E., Gerasimova, A., Bork, P., Kondrashov, A.S., and Sunyaev, S.R. 2010. A method and server for predicting damaging missense mutations. Nat. Methods 7:248–249. doi: https://doi.org/10.1038/nmeth0410-248 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000276150600004&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
2. Albrecht, T., Auinger, H.-J., Wimmer, V., Ogutu, J.O., Knaak, C., Ouzunova, M., Piepho, H.-P., and Schon, C.-C. 2014. Genome-based prediction of maize hybrid performance across genetic groups, testers, locations, and years. Theor. Appl. Genet. 127:1375–1386. doi: https://doi.org/10.1007/s00122-014-2305-z http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000336756200009&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
3. Asoro, F.G., Newell, M.A., Beavis, W.D., Scott, M.P., Tinker, N.A., and Jannink, J.-L. 2013. Genomic, marker-assisted, and pedigree-BLUP selection methods for β-glucan concentration in elite oat. Crop Sci. 53:1894–1906. doi: https://doi.org/10.2135/cropsci2012.09.0526 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000323116900009&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
4. Bernardo, R. 1991. Retrospective index weights used in multiple trait selection in a maize breeding program. Crop Sci. 31:1174–1179. doi: https://doi.org/10.2135/cropsci1991.0011183X003100050020x http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=A1991GH12300020&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
5. Bernardo, R. 2008. Molecular markers and selection for complex traits in plants: Learning from the last 20 years. Crop Sci. 48:1649–1664. doi: https://doi.org/10.2135/cropsci2008.03.0131 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000259792100001&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
6. Bernardo, R. 2009. Genomewide selection for rapid introgression of exotic germplasm in maize. Crop Sci. 49:419–425. doi: https://doi.org/10.2135/cropsci2008.08.0452 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000264654000006&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
7. Bernardo, R. 2013. Genomewide selection when major genes are known. Crop Sci. 54:68–75. doi: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000336745400007&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
8. Bernardo, R., and Yu, J. 2007. Prospects for genomewide selection for quantitative traits in maize. Crop Sci. 47:1082–1090. doi: https://doi.org/10.2135/cropsci2006.11.0690 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000247424200020&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
9. Burgueño, J., de los Campos, G., Weigel, K., and Crossa, J. 2012. Genomic prediction of breeding values when modeling genotype × environment interaction using pedigree and dense molecular markers. Crop Sci. 52:707–719. doi: https://doi.org/10.2135/cropsci2011.06.0299 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000300800400026&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
10. Calus, M.P.L., and Veerkamp, R.F. 2011. Accuracy of multi-trait genomic selection using different methods. Genet. Sel. Evol. 43:26. doi: https://doi.org/10.1186/1297-9686-43-26
11. Combs, E., and Bernardo, R. 2013. Genomewide selection to introgress semidwarf maize germplasm into U.S. corn belt inbreds. Crop Sci. 53:1427–1436. doi: https://doi.org/10.2135/cropsci2012.11.0666 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000319918300022&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
12. Cooper M., Hammer G.L., editors. 1996. Plant adaptation and crop improvement. CAB International, Wallingford, UK.
13. Crossa, J., de Los Campos, G., Pérez, P., Gianola, D., Burgueño, J., Araus, J.L., Makumbi, D., Singh, R.P., Dreisigacker, S., Yan, J., Arief, V., Banziger, M., and Braun, H.J. 2010. Prediction of genetic values of quantitative traits in plant breeding using pedigree and molecular markers. Genetics 186:713–724. doi: https://doi.org/10.1534/genetics.110.118521 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000282807400022&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
14. Cullis, B.R., Smith, A.B., Beeck, C.P., and Cowling, W.A. 2010. Analysis of yield and oil from a series of canola breeding trials. Part II. Exploring variety by environment interaction using factor analysis. Genome 53:1002–1016. doi: https://doi.org/10.1139/G10-080 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000285555000017&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
15. Cullis, B.R., Smith, A.B., and Coombes, N. 2006. On the design of early generation variety trials with correlated data. J. Agric. Biol. Environ. Stat. 11:381–393. doi: https://doi.org/10.1198/108571106X154443 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000242477500002&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
16. Daetwyler, H.D., Villanueva, B., Bijma, P., and Woolliams, J.A. 2007. Inbreeding in genome-wide selection. J. Anim. Breed. Genet. 124:369–376. doi: https://doi.org/10.1111/j.1439-0388.2007.00693.x http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000251432800007&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
17. de Los Campos, G., Gianola, D., and Rosa, G.J.M. 2009. Reproducing kernel Hilbert spaces regression: A general framework for genetic evaluation. J. Anim. Sci. 87:1883–1887. doi: https://doi.org/10.2527/jas.2008-1259 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000266108600006&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
18. de los Campos, G., Vazquez, A.I., Fernando, R., Klimentidis, Y.C., and Sorensen, D. 2013. Prediction of complex human traits using the genomic best linear unbiased predictor (Editor, M.E. Goddard). PLoS Genet. 9(7): E1003608. doi: https://doi.org/10.1371/journal.pgen.1003608
19. de Bueno Filho, S.J.S., and Gilmour, S.G. 2003. Planning incomplete block experiments when treatments are genetically related. Biometrics 59:375–381. doi: https://doi.org/10.1111/1541-0420.00044 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000183735100018&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
20. Elshire, R.J., Glaubitz, J.C., Sun, Q., Poland, J., Kawamoto, K., Buckler, E.S., and Mitchell, S.E. 2011. A robust, simple genotyping-by-sequencing (GBS) approach for high diversity species. PLoS One 6(5): E19379. doi: https://doi.org/10.1371/journal.pone.0019379
21. Endelman, J.B., Atlin, G.N., Beyene, Y., Semagn, K., Zhang, X., Sorrells, M.E., and Jannink, J.-L. 2014. Optimal design of preliminary yield trials with genome-wide markers. Crop Sci. 54:48–59. doi: https://doi.org/10.2135/cropsci2013.03.0154 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000336745400005&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
22. Endelman, J.B., and Jannink, J.-L. 2012. Shrinkage estimation of the realized relationship matrix. G3 2:1405–1413. doi: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000312457000012&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
23. Erbe, M., Hayes, B.J., Matukumalli, L.K., Goswami, S., Bowman, P.J., Reich, C.M., Mason, B.A., and Goddard, M.E. 2012. Improving accuracy of genomic predictions within and between dairy cattle breeds with imputed high-density single nucleotide polymorphism panels. J. Dairy Sci. 95:4114–4129. doi: https://doi.org/10.3168/jds.2011-5019 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000305363100062&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
24. Falconer, D.S. 1952. The problem of environment and selection. Am. Nat. 86:293–298. doi: https://doi.org/10.1086/281736 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=A1952UY00500003&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
25. Falconer, D.S., and Mackay, T.F.C. 1996. Introduction to quantitative genetics. 4th ed. Pearson, Prentice Hall, Harlow, UK.
26. Fernando, R.L., and Gianola, D. 1986. Optimal properties of the conditional mean as a selection criterion. Theor. Appl. Genet. 72:822–825.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=A1986E084700020&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
27. Garrick, D.J., Taylor, J.F., and Fernando, R.L. 2009. Deregressing estimated breeding values and weighting information for genomic regression analyses. Genet. Sel. Evol. 41:55. doi:.https://doi.org/10.1186/1297-9686-41-55
28. Gianola, D. 2013. Priors in whole-genome regression: The bayesian alphabet returns. Genetics 194:573–596. doi: https://doi.org/10.1534/genetics.113.151753 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000321255800005&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
29. Gianola, D., de los Campos, G., Hill, W.G., Manfredi, E., and Fernando, R. 2009. Additive genetic variability and the Bayesian alphabet. Genetics 183:347–363. doi: https://doi.org/10.1534/genetics.109.103952 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000272067000031&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
30. Goddard, M.E. 2009. Genomic selection: Prediction of accuracy and maximisation of long term response. Genetica (The Hague) 136:245–357. doi:
31. Habier, D., Fernando, R.L., and Dekkers, J.C.M. 2007. The impact of genetic relationship information on genome-assisted breeding values. Genetics 177:2389–2397. doi: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000251949800035&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
32. Habier, D., Fernando, R.L., and Garrick, D.J. 2013. Genomic BLUP decoded: A look into the black box of genomic prediction. Genetics 194:597–607. doi: https://doi.org/10.1534/genetics.113.152207 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000321255800006&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
33. Hayes, B.J., Bowman, P.J., Chamberlain, A.J., and Goddard, M.E. 2009a. Invited review: Genomic selection in dairy cattle: Progress and challenges. J. Dairy Sci. 92:433–443. doi: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000262654900001&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
34. Hayes, B.J., Bowman, P.J., Chamberlain, A.J., Verbyla, K.L., and Goddard, M.E. 2009b. Accuracy of genomic breeding values in multi-breed dairy cattle populations. Genet. Sel. Evol. 41:51. doi:
35. Heffner, E.L., Jannink, J.-L., Iwata, H., Souza, E., and Sorrells, M.E. 2011. Genomic selection accuracy for grain quality traits in biparental wheat populations. Crop Sci. 51:2597–2606. doi: https://doi.org/10.2135/cropsci2011.05.0253 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000295839200031&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
36. Heffner, E.L., Lorenz, A.J., Jannink, J.-L., and Sorrells, M.E. 2010. Plant breeding with genomic selection: Gain per unit time and cost. Crop Sci. 50:1681–1690. doi: https://doi.org/10.2135/cropsci2009.11.0662 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000281060300010&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
37. Heffner, E.L., Sorrells, M.E., and Jannink, J.-L. 2009. Genomic selection for crop improvement. Crop Sci. 49:1–12. doi: https://doi.org/10.2135/cropsci2008.08.0512 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000263344300001&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
38. Henderson, C.R., and Quaas, R.L. 1976. Multiple trait evaluation using relatives’ records. J. Anim. Sci. 43:1188–1197.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=A1976CP41700009&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
39. Henderson, C.R. 1984. Applications of linear models in animal breeding. University of Guelph, Guelph, Ontario.
40. Heslot, N., Akdemir, D., Sorrells, M.E., and Jannink, J.-L. 2013a. Integrating environmental covariates and crop modeling into the genomic selection framework to predict genotype by environment interactions. Theor. Appl. Genet. 127:463–480. doi: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000330723900017&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
41. Heslot, N., Jannink, J.-L., and Sorrells, M.E. 2013b. Using genomic prediction to characterize environments and optimize prediction accuracy in applied breeding data. Crop Sci. 53:921–933. doi: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000319527000022&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
42. Heslot, N., Rutkoski, J., Poland, J., Jannink, J.-L., and Sorrells, M.E. 2013c. Impact of marker ascertainment bias on genomic selection accuracy and estimates of genetic diversity. PLoS ONE 8(9):E74612. doi:
43. Heslot, N., Yang, H.-P., Sorrells, M.E., and Jannink, J.-L. 2012. Genomic selection in plant breeding: A comparison of models. Crop Sci. 52:146–160. doi: https://doi.org/10.2135/cropsci2011.06.0297 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000298289600016&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
44. Hickey, J.M., Dreisigacker, S., Crossa, J., Hearne, S., Babu, R., Prasanna, B.M., Grondona, M., Zambelli, A., Windhausen, V.S., Mathews, K., and Gorjanc, G. 2014. Evaluation of genomic selection training population designs and genotyping strategies in plant breeding programs using simulation. Crop Sci. 54:1476–1488. doi: https://doi.org/10.2135/cropsci2013.03.0195 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000338773100018&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
45. Hill, W.G., and Weir, B.S. 2011. Variation in actual relationship as a consequence of Mendelian sampling and linkage. Genet. Res. (Cambridge) 93:47–64. doi: https://doi.org/10.1017/S0016672310000480 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000290178700005&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
46. Jannink, J.-L. 2010. Dynamics of long-term genomic selection. Genet. Sel. Evol. 42(35):35. doi: https://doi.org/10.1186/1297-9686-42-35
47. Jia, Y., and Jannink, J.-L. 2012. Multiple-trait genomic selection methods increase genetic value prediction accuracy. Genetics 192:1513–1522. doi: https://doi.org/10.1534/genetics.112.144246 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000311960500024&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
48. Knapp, S.J., and Bridges, W.C. 1990. Using molecular markers to estimate quantitative trait locus parameters: Power and genetic variances for unreplicated and replicated progeny. Genetics 126:769–777.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=A1990EF29100026&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
49. König, S., Simianer, H., and Willam, A. 2009. Economic evaluation of genomic breeding programs. J. Dairy Sci. 92:382–391. doi: https://doi.org/10.3168/jds.2008-1310 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000261948600039&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
50. Laloë, D. 1993. Precision and information in linear models of genetic evaluation. Genet. Sel. Evol. 25:556–576. doi:
51. Laloë, D., Phocas, F., and Ménissier, F. 1996. Considerations on measures of precision and connectedness in mixed linear models of genetic evaluation. Genet. Sel. Evol. 28:359. doi: https://doi.org/10.1186/1297-9686-28-4-359 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=A1996VT86900004&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
52. Lande, R., and Thompson, R. 1990. Efficiency of marker-assisted selection in the improvement of quantitative traits. Genetics 124:743–756.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=A1990CQ97500027&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
53. Lillehammer, M., Meuwissen, T.H.E., and Sonesson, A.K. 2013. A low-marker density implementation of genomic selection in aquaculture using within-family genomic breeding values. Genet. Sel. Evol. 45(1):39. doi: https://doi.org/10.1186/1297-9686-45-39
54. Long, N., Gianola, D., Rosa, G.J.M., and Weigel, K.A. 2011. Long-term impacts of genome-enabled selection. J. Appl. Genet. 52:467–480. doi: https://doi.org/10.1007/s13353-011-0053-1 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000295682700010&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
55. Lorenz, A.J. 2013. Resource allocation for maximizing prediction accuracy and genetic gain of genomic selection in plant breeding: A simulation experiment. G3 3(3):481–491. doi: https://doi.org/10.1534/g3.112.004911 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000315950000009&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
56. Lorenz, A.J., Chao, S., Asoro, F.G., Heffner, E.L., Hayashi, T., Iwata, H., Smith, K.P., Sorrells, M.E., and Jannink, J.-L. 2011. Genomic selection in plant breeding: Knowledge and prospects. Adv. Agron. 110:77–123. doi: https://doi.org/10.1016/B978-0-12-385531-2.00002-5 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000287331100002&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
57. Lorenz, A.J., Smith, K.P., and Jannink, J.-L. 2012. Potential and optimization of genomic selection for fusarium head blight resistance in six-row barley. Crop Sci. 52:1609–1621. doi: https://doi.org/10.2135/cropsci2011.09.0503 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000305804900016&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
58. Lorenzana, R.E., and Bernardo, R. 2009. Accuracy of genotypic value predictions for marker-based selection in biparental plant populations. Theor. Appl. Genet. 120:151–161. doi: https://doi.org/10.1007/s00122-009-1166-3 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000271939900013&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
59. Massman, J.M., Gordillo, A., Lorenzana, R.E., and Bernardo, R. 2013. Genomewide predictions from maize single-cross data. Theor. Appl. Genet. 126:13–22. doi: https://doi.org/10.1007/s00122-012-1955-y http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000313056900002&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
60. Massman, J.M., Jung, H.-J.G., and Bernardo, R. 2012. Genomewide selection versus marker-assisted recurrent selection to improve grain yield and stover-quality traits for cellulosic ethanol in maize. Crop Sci. 53:58–66. doi: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000315623700006&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
61. Maurano, M.T., Humbert, R., Rynes, E., Thurman, R.E., Haugen, E., Wang, H., Reynolds, A.P., Sandstrom, R., Qu, H., Brody, J., Shafer, A., Neri, F., Lee, K., Kutyavin, T., Stehling-Sun, S., Johnson, A.K., Canfield, T.K., Giste, E., Diegel, M., Bates, D., Hansen, R.S., Neph, S., Sabo, P.J., Heimfeld, S., Raubitschek, A., Ziegler, S., Cotsapas, C., Sotoodehnia, N., Glass, I., Sunyaev, S.R., Kaul, R., and Stamatoyannopoulos, J.A. 2012. Systematic localization of common disease-associated variation in regulatory DNA. Science 337:1190–1195. doi: https://doi.org/10.1126/science.1222794 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000308414000028&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
62. Meuwissen, T. 2010. Use of whole genome sequence data for QTL mapping and genomic selection. In: Proceedings of the 9th World Congress on Genetics Applied to Livestock Production. 1–6 Aug. 2010. Leipzig, Germany.
63. Meuwissen, T.H., Hayes, B.J., and Goddard, M.E. 2001. Prediction of total genetic value using genome-wide dense marker maps. Genetics 157:1819–1829.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000168223400036&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
64. Moreau, L., Charcosset, A., and Gallais, A. 2004. Experimental evaluation of several cycles of marker-assisted selection in maize. Euphytica 137:111–118. doi: https://doi.org/10.1023/B:EUPH.0000040508.01402.21 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000223738600011&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
65. Muir, W.M. 2007. Comparison of genomic and traditional BLUP-estimated breeding value accuracy and selection response under alternative trait and genomic parameters. J. Anim. Breed. Genet. 124:342–355. doi: https://doi.org/10.1111/j.1439-0388.2007.00700.x http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000251432800004&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
66. Myles, S., Peiffer, J., Brown, P.J., Ersoz, E.S., Zhang, Z., Costich, D.E., and Buckler, E.S. 2009. Association mapping: Critical considerations shift from genotyping to experimental design. Plant Cell 21:2194–2202. doi: https://doi.org/10.1105/tpc.109.068437 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000270416700004&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
67. Piepho, H.P., and Möhring, J. 2005. Best linear unbiased prediction of cultivar effects for subdivided target regions. Crop Sci. 45:1151–1159. doi: https://doi.org/10.2135/cropsci2004.0398 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000229105700046&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
68. Piepho, H.P., Möhring, J., Melchinger, A.E., and Büchse, A. 2007. BLUP for phenotypic selection in plant breeding and variety testing. Euphytica 161:209–228. doi: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000254877800019&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
69. Podlich, D.W., Cooper, M., and Basford, K.E. 1999. Computer simulation of a selection strategy to accommodate genotype-environment interactions in a wheat recurrent selection programme. Plant Breed. 118:17–28. doi: https://doi.org/10.1046/j.1439-0523.1999.118001017.x http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000079902700002&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
70. Riedelsheimer, C., Endelman, J.B., Stange, M., Sorrells, M.E., Jannink, J.-L., and Melchinger, A.E. 2013. Genomic predictability of interconnected biparental maize populations. Genetics 194:493–503. doi: https://doi.org/10.1534/genetics.113.150227 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000319814700017&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
71. Riedelsheimer, C., Technow, F., and Melchinger, A.E. 2012. Comparison of whole-genome prediction models for traits with contrasting genetic architecture in a diversity panel of maize inbred lines. BMC Genomics 13:452. doi: https://doi.org/10.1186/1471-2164-13-452
72. Rincent, R., Laloë, D., Nicolas, S., Altmann, T., Brunel, D., Revilla, P., Rodríguez, V.M., Moreno-Gonzalez, J., Melchinger, A., Bauer, E., Schoen, C.-C., Meyer, N., Giauffret, C., Bauland, C., Jamin, P., Laborde, J., Monod, H., Flament, P., Charcosset, A., and Moreau, L. 2012. Maximizing the reliability of genomic selection by optimizing the calibration set of reference individuals: Comparison of methods in two diverse groups of maize inbreds (Zea mays L.). Genetics 192:715–728. doi: https://doi.org/10.1534/genetics.112.141473 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000309547400026&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
73. Rutkoski, J.E., Benson, J., Jia, Y., Brown-Guedira, G., Jannink, J.-L., and Sorrells, M.E. 2012. Evaluation of genomic prediction methods for fusarium head blight resistance in wheat. Plant Genome 5:51–61. doi: https://doi.org/10.3835/plantgenome2012.02.0001 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000312662500002&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
74. Schaeffer, L.R. 2006. Strategy for applying genome-wide selection in dairy cattle. J. Anim. Breed. Genet. 123:218–223. doi: https://doi.org/10.1111/j.1439-0388.2006.00595.x http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000239006300002&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
75. Searle, S.R., Casella, G., and McCulloch, C.E. 1992. Variance components. John Wiley & Sons, Hoboken, NJ.
76. Servin, B., Martin, O.C., Mézard, M., and Hospital, F. 2004. Toward a theory of marker-assisted gene pyramiding. Genetics 168:513–523. doi: https://doi.org/10.1534/genetics.103.023358 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000224393700040&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
77. Smith, A.B., Cullis, B.R., and Thompson, R. 2005. The analysis of crop cultivar breeding and evaluation trials: An overview of current mixed model approaches. J. Agric. Sci. 143:449–462. doi: https://doi.org/10.1017/S0021859605005587 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000235201600002&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
78. Stuber, C.W., Goodman, M.M., and Moll, R.H. 1982. Improvement of yield and ear number resulting from selection at allozyme loci in a maize population. Crop Sci. 22:737–740. doi: https://doi.org/10.2135/cropsci1982.0011183X002200040010x http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=A1982PG45700010&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
79. Tanksley, S.D., Young, N.D., Paterson, A.H., and Bonierbale, M.W. 1989. RFLP mapping in plant breeding: New tools for an old science. Nat. Biotechnol. 7:257–264. doi: https://doi.org/10.1038/nbt0389-257
80. Tardieu, F. 2012. Any trait or trait-related allele can confer drought tolerance: Just design the right drought scenario. J. Exp. Bot. 63:25–31. doi: https://doi.org/10.1093/jxb/err269 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000298383400003&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
81. Tribout, T., Larzul, C., and Phocas, F. 2013. Economic aspects of implementing genomic evaluations in a pig sire line breeding scheme. Genet. Sel. Evol. 45(1):40. doi: https://doi.org/10.1186/1297-9686-45-40
82. Van Raden, P.M. 2008. Efficient methods to compute genomic predictions. J. Dairy Sci. 91:4414–4423. doi: https://doi.org/10.3168/jds.2007-0980 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000260277200035&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
83. Vitezica, Z.G., Varona, L., and Legarra, A. 2013. On the additive and dominant variance and covariance of individuals within the genomic selection scope. Genetics 195:1223–1230. doi: https://doi.org/10.1534/genetics.113.155176 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000328816400003&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
84. Wimmer, V., Lehermeier, C., Albrecht, T., Auinger, H.-J., Wang, Y., and Schön, C.-C. 2013. Genome-wide prediction of traits with different genetic architecture through efficient variable selection. Genetics 195:573–587. doi: https://doi.org/10.1534/genetics.113.150078 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000325286200024&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
85. Xu, Y., and Crouch, J.H. 2008. Marker-assisted selection in plant breeding: From publications to practice. Crop Sci. 48:391–407. doi: https://doi.org/10.2135/cropsci2007.04.0191 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000254855500001&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
86. Zhong, S., and Jannink, J.-L. 2007. Using quantitative trait loci results to discriminate among crosses on the basis of their progeny mean and variance. Genetics 177:567–576. doi: https://doi.org/10.1534/genetics.107.075358 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000250049300047&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4
87. Ziyomo, C., and Bernardo, R. 2013. Drought tolerance in maize: Indirect selection through secondary traits versus genomewide selection. Crop Sci. 53:1269–1275. doi: https://doi.org/10.2135/cropsci2012.11.0651 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=agrocropsoil&KeyUT=000319918300006&DestLinkType=FullRecord&DestApp=WOS_CPL&UsrCustomerID=523bbf5d2a868de7bbaeea0bc70ec0e4