Status and Prospects of Association Mapping in Plants

Plant Genome - Tập 1 Số 1 - 2008
Chengsong Zhu1, Michael A. Gore2, Edward S. Buckler3, Jianming Yu4,5,6
1Dep. of Agronomy Kansas State University 2004 Throckmorton Hall Manhattan KS 66506
2Dep. of Plant Breeding and Genetics Cornell University Ithaca NY 14853
3USDA‐ARS and Institute for Genomic Diversity, Cornell University Ithaca NY 14853
4Cornell University, Ithaca, NY 14853
5USDA-ARS and Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853.
6of Agronomy, Kansas State University, 2004 Throckmorton Hall, Manhattan, KS 66506; M. Gore, Dep. of Plant Breeding and Genetics,

Tóm tắt

There is tremendous interest in using association mapping to identify genes responsible for quantitative variation of complex traits with agricultural and evolutionary importance. Recent advances in genomic technology, impetus to exploit natural diversity, and development of robust statistical analysis methods make association mapping appealing and affordable to plant research programs. Association mapping identifies quantitative trait loci (QTLs) by examining the marker‐trait associations that can be attributed to the strength of linkage disequilibrium between markers and functional polymorphisms across a set of diverse germplasm. General understanding of association mapping has increased significantly since its debut in plants. We have seen a more concerted effort in assembling various association‐mapping populations and initiating experiments through either candidate‐gene or genome‐wide approaches in different plant species. In this review, we describe the current status of association mapping in plants and outline opportunities and challenges in complex trait dissection and genomics‐assisted crop improvement.

Từ khóa


Tài liệu tham khảo

10.1086/302698

10.1038/ng786

10.1007/s11032‐006‐9066‐6

10.1038/nmeth1111

Allison D.B., 1997, Transmission‐disequilibrium tests for quantitative traits, Am. J. Hum. Genet., 60, 676

10.1007/s00122‐005‐1996‐6

10.1371/journal.pgen.0010060

10.1007/s00122‐005‐0189‐7

10.1038/nrg777

10.1007/s00122‐006‐0394‐z

10.1111/j.1365-313X.2007.03193.x

10.1007/s00438‐007‐0289‐y

Bernardo R., 2002, Breeding for Quantitative Traits in Plants

10.1007/s00122‐003‐1375‐0

10.2135/cropsci2005.05‐0088

10.2135/cropsci2006.11.0690

10.1371/journal.pone.0000197

10.1093/genetics/163.1.253

Boldman K.G., 1993, A manual for the use of MTDFREML: A set of programs to obtain estimates of variances and covariances

10.1146/annurev.genom.5.061903.180017

10.1101/gr.541303

10.1093/bioinformatics/btm308

10.1073/pnas.0230489100

10.2135/cropsci2005.09‐0305

10.1534/genetics.105.044586

10.1534/genetics.104.038489

10.1534/genetics.105.048603

10.2135/cropsci2007.02.0080

10.1038/ng1104‐1133

10.1126/science.1138632

10.1007/s00438‐006‐0198‐5

10.1073/pnas.0702165104

10.1111/j.0006‐341X.1999.00997.x

10.1038/nrn726

10.1534/genetics.107.084830

10.1534/genetics.107.071928

Ersoz E.S., 2008, Genomic assisted crop improvement: Vol. I: Genomics approaches and platforms, 97

Eskridge K.M.2003.Field design and the search for quantitative trait loci in plants. Available at:http://www.stat.colostate.edu/graybillconference2003/Abstracts/Eskridge.html; verified 20 May 2008.

10.1046/j.1365‐294X.2002.01576.x

10.1111/j.1365-294X.2005.02553.x

10.1111/j.1471‐8286.2007.01758.x

10.1146/annurev.arplant.54.031902.134907

10.1111/j.1365‐313X.2005.02591.x

Gilmour A.R., 2002, ASReml user guide release 1.0

10.1534/genetics.105.047126

10.1534/genetics.106.061127

10.2135/cropsci2007.02.0085tpg

Hamblin M.T., 2006, Challenges of detecting directional selection after a bottleneck: Lessons from sorghum bicolor, Science, 173, 953

10.1046/j.1471‐8286.2002.00305.x

10.1126/science.1150255

10.1093/genetics/117.2.331

10.1007/BF01245622

10.1126/science.1105436

10.1038/nrn1622

10.1038/ng.2007.42

10.1016/j.pbi.2007.01.003

10.1002/(SICI)1098‐2272(1997)14:6<803::AID‐GEPI40>3.3.CO;2‐2

10.2307/1390807

10.1038/ng1001‐233

Johnson R., 2004, Marker‐assisted selection, Plant Breed. Rev., 24, 293

10.1016/S0006‐3223(98)00319‐9

10.1046/j.1365‐2540.1998.00500.x

10.1534/genetics.105.052720

10.1126/science.1149504

10.1007/s11032‐005‐1119‐8

10.1086/344780

10.1371/journal.pone.0000284

10.1517/14622416.1.1.95

Levinson G., 1987, Slipped‐strand mispairing: A major mechanism for DNA sequence evolution, Mol. Biol. Evol., 4, 203

10.1093/genetics/49.1.49

10.1046/j.1365‐294X.2002.01643.x

10.1111/j.1095-8312.1999.tb01157.x

10.1146/annurev.genet.35.102401.090633

10.1534/genetics.105.054932

10.1038/nature03959

10.1104/pp.106.077313

10.1093/genetics/161.1.373

10.1093/nar/gkm380

10.2135/cropsci1997.0011183X003700020051x

10.1016/j.ygeno.2004.10.005

10.1093/genetics/160.4.1609

Muehlbauer.2006.Barley coordinated agricultural project proposal. Available at:http://barleycap.cfans.umn.edu/(verified 20 May 2008).

10.1016/S0168‐9525(02)02557‐X

10.1371/journal.pbio.0030196

10.1038/nmeth1109

10.1093/genetics/162.2.941

10.1534/genetics.103.024950

10.1073/pnas.0307839101

10.1093/nar/gkm760

10.1007/s00122-004-1666-0

10.1371/journal.pgen.0030090

10.1038/nmeth1110

10.1016/j.tplants.2006.03.006

10.1038/ng1847

10.1086/302449

10.1111/j.1365-294X.2004.02396.x

10.1086/302959

10.1016/S1369‐5266(02)00240‐6

10.1017/S0016672399004358

10.1126/science.273.5281.1516

10.1111/j.1365‐294X.2005.02667.x

10.1186/gb‐2005‐6‐6‐r54

Rostoks N. Ramsay L. Mackenzie K. Cardle L. Bhat P.R. Roose M.L. Svensson J.T. Stein N. Varshney R.K. Marshall D.F. Graner A. Close T.J. andWaugh R..2006.Recent history of artificial outcrossing facilitates whole‐genome association mapping in elite inbred crop varieties.Proc. Natl. Acad. Sci. USA.

Salisbury M., 2007, Next‐gen sequencing: The waiting game, Genome Technol., 72, 26

10.1073/pnas.0704145104

SAS Institute, 1999, SAS/STAT user's guide. Version 8

10.1126/science.311.5767.1544

10.1126/science.1117389

10.1016/j.tplants.2004.07.003

10.1534/genetics.107.071522

10.1007/s11032‐004‐4824‐9

Spielman R.S., 1993, Transmission test for linkage disequilibrium: The insulin gene region and insulin‐dependent diabetes mellitus (IDDM), Am. J. Hum. Genet., 52, 506

10.1086/319501

10.1534/genetics.106.067033

10.1038/35103535

10.1038/ng1558

10.1007/s00122‐005‐1973‐0

10.1038/nrm836

10.1126/science.277.5329.1063

10.1038/nature05911

10.1038/90135

10.1534/genetics.105.042028

10.2135/cropsci2006-03-0149tpg

10.1038/sj.hdy.6800763

10.1007/PL00006361

10.1093/oxfordjournals.molbev.a004186

10.1093/nar/23.21.4407

10.1534/genetics.107.080424

10.1007/s00122‐006‐0418‐8

Whitt S.R., 2003, Using natural allelic diversity to evaluate gene function, Methods Mol. Biol., 236, 123

10.1093/nar/18.22.6531

10.1105/tpc.104.025700

10.1126/science.281.5380.1194

10.1534/genetics.104.035816

10.1093/genetics/160.2.779

10.1093/genetics/148.1.517

10.1016/j.copbio.2006.02.003

10.1007/s00122‐005‐1926‐7

10.1534/genetics.107.074245

10.1038/ng1702

10.1038/ni1101‐983

Zeng Z.B.2005.QTL mapping and the genetic basis of adaptation: Recent developmentsGenetica:25–37.10.1007/s10709‐004‐2705‐0

10.1371/journal.pgen.0030004

Thông tin
Thông tin xuất bản

Plant Genome

Tập 1 Số 1

Thông tin tác giả