/data/v2/LEGUMES/Fabaceae/genefamilies/legume.genefam.fam1.M65K/legume.genefam.fam1.M65K.trees_ML_rooted
LIS gene family phylogenetic tree files
0518BW-8_x_0734BW-1.gen.Oyoo_Benitez_2011
Further information provided in 10.2135/cropsci2010.02.0121
93705KS4895_x_Jackson.gen.Hwang_King_2015
Further information provided in 10.1007/s00122-015-2566-1
A5403_x_Archer.gen.Cornelious_Chen_2005
Further information provided in 10.1007/s11032-005-5911-2
A81356022_x_A81356022.gen.Keim_Diers_1990
Further information provided in 10.1093/genetics/126.3.735
A81356022_x_PI468916.gen.Diers_Cianzio_1992
Further information provided in 10.1080/01904169209364462
A81356022_x_PI468916.gen.Diers_Keim_1992
Further information provided in 10.1007/bf00226905
A81356022_x_PI468916.gen.Diers_Shoemaker_1992
Further information provided in 10.1007/bf02637690
A81356022_x_PI468916.gen.Keim_Diers_1990
Further information provided in 10.1007/bf00226154
A95-684043_x_LS94-3207.gen.Swaminathan_Abeysekara_2016
Further information provided in 10.1007/s00122-015-2643-5
A95-684043_x_LS98-0582.gen.Swaminathan_Abeysekara_2018
Further information provided in 10.1007/s00122-018-3057-y
A96-492058_x_A97-775026.gen.Hoeck_2002
Further information provided in 10.31274/rtd-180813-9889
AC756_x_RCATAngora.gen.Primomo_Poysa_2006
Further information provided in 10.2135/cropsci2004.0672er
AGSBoggs-RR_x_CX1834-1-2.gen.Walker_Scaboo_2006
Further information provided in 10.2135/cropsci2005.0245
Anoka_x_A7.gen.Lin_Baumer_2000
Further information provided in 10.1080/01904160009382153
Anoka_x_A7.gen.Peiffer_King_2012
Further information provided in 10.1104/pp.111.189860
Archer_x_Minsoy.gen.VanToai_St.-Martin_2001
Further information provided in 10.2135/cropsci2001.4141247x
BARC-8_x_Garimpo.gen.Vieira_Oliveira_2006
Further information provided in 10.1590/s1677-04202006000200004
BD2_x_BX10.gen.Liang_Cheng_2010a
Further information provided in 10.1093/aob/mcq097
BD2_x_BX10.gen.Liang_Cheng_2010b
Further information provided in 10.1093/aob/mcq097
BSR101_x_LG82-8379.gen.Kabelka_Diers_2004
Further information provided in 10.2135/cropsci2004.0784
BSR101_x_PI437654.gen.Klos_Paz_2000
Further information provided in 10.2135/cropsci2000.4051445x
Bell_x_Colfax.gen.Glover_Wang_2004
Further information provided in 10.2135/cropsci2004.0936
Bell_x_Colfax.gen.Patzoldt_Grau_2005
Further information provided in 10.2135/cropsci2003.0615
BenningPI595645_x_DanbaekkongPI619083.gen.Warrington_Abdel-Haleem_2015
Further information provided in 10.1007/s00122-015-2474-4
BenningPI595645_x_PI416937.gen.Abdel-Haleem_Lee_2011
Further information provided in 10.1007/s00122-010-1500-9
BenningPI595645_x_PI416937.gen.Carpentieri-Pipolo_Pipolo_2012
Further information provided in 10.1007/s10681-011-0535-6
Benning_x_PI416937.gen.Abdel-Haleem_Carter_2012
Further information provided in 10.1007/s00122-012-1876-9
Birsasoya-1_x_JS71-05.gen.Singh_Raipuria_2008
Further information provided in 10.15258/sst.2008.36.1.17
Bogao_x_Nannong94-156.gen.Jun_Freewalt_2014
Further information provided in 10.1111/pbr.12107
Bossier_x_Embrapa20.gen.Santos_Geraldi_2013
Further information provided in 10.1111/j.1601-5223.2013.02275.x
CNS_x_PI230977.gen.Tamulonis_Luzzi_1997a
Further information provided in 10.2135/cropsci1997.0011183x003700060039x
CNS_x_PI230977.gen.Tamulonis_Luzzi_1997b
Further information provided in 10.2135/cropsci1997.0011183x003700030015x
CSSL3228_x_NN1138D2.gen.Zhang_Wang_2018
Further information provided in 10.1186/s12864-018-4582-4
CX1834-1-2_x_5601T.gen.Scaboo_Pantalone_2009
Further information provided in 10.2135/cropsci2007.11.0614
CX1834-1-6_x_V99-3337.gen.Gao_Biyashev_2008
Further information provided in 10.2135/cropsci2007.11.0633
Chamame_x_Laco-1.gen.Juwattanasomran_Somta_2012
Further information provided in 10.1007/s11032-010-9523-0
Charleston_x_DongNong594.gen.Teng_Han_2009
Further information provided in 10.1038/hdy.2008.108
Charleston_x_DongNong594.gen.Yang_Xin_2013
Further information provided in 10.1007/s00438-013-0779-z
Charleston_x_Dongnong.gen.Qi_Wu_2011
Further information provided in 10.1007/s10681-011-0386-1
Charleston_x_Dongnong594.gen.Qi_Hou_2014
Further information provided in 10.1111/pbr.12179
Charleston_x_Dongnong594.gen.Sun_Li_2006
Further information provided in 10.1007/s00122-005-0169-y
Charleston_x_Dongnong594.gen.Sun_Pan_2012
Further information provided in 10.1007/s11033-012-1808-4
Cobb_x_PI171451.gen.Rector_All_1999
Further information provided in 10.2135/cropsci1999.0011183x003900020038x
Cobb_x_PI229358.gen.Narvel_Walker_2001
Further information provided in 10.2135/cropsci2001.1931
Cobb_x_PI229358.gen.Rector_All_1998
Further information provided in 10.1007/s001220050803
Cobb_x_PI229358.gen.Rector_All_2000
Further information provided in 10.2135/cropsci2000.401233x
Conrad_x_Harosoy.gen.Burnham_Dorrance_2003
Further information provided in 10.2135/cropsci2003.1610
Conrad_x_Hefeng25.gen.Mideros_Nita_2007
Further information provided in 10.1094/phyto-97-5-0655
Conrad_x_OX760-6-1.gen.Han_Teng_2008
Further information provided in 10.1007/s10681-007-9558-4
Conrad_x_OX760-6-1.gen.Weng_Yu_2007
Further information provided in 10.1007/s10681-007-9428-0
Conrad_x_Sloan.gen.Ellis_Wang_2012
Further information provided in 10.2135/cropsci2011.11.0624
Conrad_x_Sloan.gen.Wang_St.-Martin_2012
Further information provided in 10.2135/cropsci2011.06.0336
Conrad_x_Sloan.gen.Wang_Waller_2010
Further information provided in 10.3835/plantgenome2009.12.0029
Conrad_x_Sloan.gen.Wang_Wijeratne_2012a
Further information provided in 10.1186/1471-2164-13-428
Conrad_x_Sloan.gen.Wang_Wijeratne_2012b
Further information provided in 10.1186/1471-2164-13-428
Cook_x_N87-2122-4.gen.Li_Wilson_2002
Further information provided in 10.2135/cropsci2002.0373
DongNong1068_x_DongNong8004.gen.Zhao_Wang_2008
Further information provided in 10.1007/s10681-008-9728-z
DongNong46_x_KenJian23.gen.Mao_Jiang_2013
Further information provided in 10.1111/pbr.12091
Douglas_x_Pyramid.gen.Njiti_Meksem_2002
Further information provided in 10.1007/s001220100682
DunbarPI552538_x_GsojaPI326582A.gen.Manavalan_Prince_2015
Further information provided in 10.1371/journal.pone.0120490
Elgin_x_PI436684.gen.Kim_Diers_2012a
Further information provided in 10.1007/s00122-012-1944-1
Elgin_x_PI436684.gen.Kim_Diers_2012b
Further information provided in 10.1007/s00122-012-1944-1
Embrapa20_x_BRS133.gen.Nicolás_Hungria_2005
Further information provided in 10.1016/j.fcr.2005.04.012
Essex_x_Forrest.gen.Brensha_Kantartzi_2017
Further information provided in 10.5147/jpgs.2012.0051
Essex_x_Forrest.gen.Chang_Doubler_1996
Further information provided in 10.2135/cropsci1996.0011183x003600060044x
Essex_x_Forrest.gen.Chang_Doubler_1997
Further information provided in 10.2135/cropsci1997.0011183x003700030044x
Essex_x_Forrest.gen.Cho_Njiti_2002
Further information provided in 10.1155/s1110724302204039
Essex_x_Forrest.gen.Hnetkovsky_Chang_1996
Further information provided in 10.2135/cropsci1996.0011183x003600020030x
Essex_x_Forrest.gen.Iqbal_Meksem_2001
Further information provided in 10.1007/s001220051634
Essex_x_Forrest.gen.Josie_Alcivar_2007
Further information provided in 10.1893/0005-3155(2007)78[119:ragrcq]2.0.co;2
Essex_x_Forrest.gen.Kassem_Meksem_2004a
Further information provided in 10.1155/s1110724304304018
Essex_x_Forrest.gen.Kassem_Meksem_2004b
Further information provided in 10.1023/b:plso.0000030189.96115.21
Essex_x_Forrest.gen.Meksem_Doubler_1999
Further information provided in 10.1007/s001220051317
Essex_x_Forrest.gen.Meksem_Pantazopoulos_2001
Further information provided in 10.1007/s001220100597
Essex_x_Forrest.gen.Sharma_Sharma_2011
Further information provided in 10.1007/s00122-010-1478-3
Essex_x_Forrest.gen.Yesudas_Sharma_2010
Further information provided in 10.1007/s00122-010-1314-9
Essex_x_Forrest.gen.Yuan_Njiti_2002
Further information provided in 10.2135/cropsci2002.0271
Essex_x_PI437654.gen.Gutierrez-Gonzalez_Wu_2009
Further information provided in 10.1007/s00122-009-1109-z
Essex_x_PI437654.gen.Gutierrez-Gonzalez_Wu_2010
Further information provided in 10.1186/1471-2229-10-105
Essex_x_Williams.gen.Hyten_Pantalone_2004
Further information provided in 10.1007/s11746-004-1027-z
Essex_x_Williams.gen.Hyten_Pantalone_2004a
Further information provided in 10.1007/s11746-004-1027-z
Essex_x_Williams.gen.Hyten_Pantalone_2004b
Further information provided in 10.1007/s00122-004-1661-5
Evans_x_PI88788.gen.Concibido_Young_1996
Further information provided in 10.1007/bf00225751
Evans_x_Peking.gen.Concibido_Lange_1997
Further information provided in 10.2135/cropsci1997.0011183x003700010046x
F_IGA1003.gnm1.V9RB
Files in this directory are genome assembly files for Glycine soja F (F_IGA1003 in publication; WHFS_GsojaF_1.0 in the GenBank assembly record), Chu et al. (2021): Egiht soybean reference genome resources from varying latitudes and agronmic traits.
F_IGA1003.gnm1.ann1.G61B
Files in this directory are genome annotation files for cultivar F, Chu et al. (2021): Egiht soybean reference genome resources from varying latitudes and agronmic traits.
FiskbeyIII_x_Williams82.gen.Do_Vuong_2018
Further information provided in 10.1007/s00122-017-3015-0
FiskebyIII.gnm1.F177
Files in this diretory are genome assembly files for genome type Fiskeby III, Stupar (2020)
FiskebyIII.gnm1.ann1.SS25
Files in this directory are genome annotation files for Glycine max Fiskeby III, Stupar et al. (2020)
FiskebyIII_x_Mandarin.gen.Burton_Burkey_2016
Further information provided in 10.1007/s00122-016-2687-1
FiskebyIII_x_Mandarin.gen.Hacisalihoglu_Burton_2018
Further information provided in 10.1111/jipb.12612
Flyer_x_Hartwig.gen.Kazi_Shultz_2008
Further information provided in 10.1007/s00122-008-0728-0
Flyer_x_Hartwig.gen.Prabhu_Njiti_1999
Further information provided in 10.2135/cropsci1999.0011183x003900040005x
Fukuyutaka_x_Himeshirazu.gen.Oki_Komatsu_2012
Further information provided in 10.1270/jsbbs.61.608
G1134.gnm1.PP7B
Files in this directory are genome assemblies for Glycine dolichocarpa, accession G1134, from Zhuang, Wang et al. (2021): "A super-pangenome framework of the genus Glycine unveils polyploid evolution and life-strategy transition."
G1267.gnm1.YWW6
Files in this directory are genome assemblies for Glycine cyrtoloba, accession G1267, from Zhuang, Wang et al. (2021): "A super-pangenome framework of the genus Glycine unveils polyploid evolution and life-strategy transition."
G1267.gnm1.ann1.HRFD
Files in this directory are genome annotation files for Glycine cyrtoloba, accession G1267, from Zhuang, Wang et al. (2021): "A super-pangenome framework of the genus Glycine unveils polyploid evolution and life-strategy transition."
G1300.gnm1.C11H
Files in this directory are genome assemblies for Glycine syndetika, accession G1300, from Zhuang, Wang et al. (2021): "A super-pangenome framework of the genus Glycine unveils polyploid evolution and life-strategy transition."
G1300.gnm1.ann1.RRK6
Files in this directory are genome annotation files for Glycine syndetika, accession G1300, from Zhuang, Wang et al. (2021): "A super-pangenome framework of the genus Glycine unveils polyploid evolution and life-strategy transition."
G1403.gnm1.CL6K
Files in this directory are genome assemblies for Glycine D3 tomentella, accession G1403, from Zhuang, Wang et al. (2021): "A super-pangenome framework of the genus Glycine unveils polyploid evolution and life-strategy transition." The D3 identifier in the name signifies an isozyme class for G. tomentella, marking this as a diploid species in a diploid/polyploid complex in the tomentella group. See Sherman-Broyles ... Doyle et al., 2014 (doi:10.3732/ajb.1400121).
G1403.gnm1.ann1.XNZQ
Files in this directory are genome annotation files for Glycine D3 tomentella, accession G1403, from Zhuang, Wang et al. (2021): "A super-pangenome framework of the genus Glycine unveils polyploid evolution and life-strategy transition." The D3 identifier in the name signifies an isozyme class for G. tomentella, marking this as a diploid species in a diploid/polyploid complex in the tomentella group. See Sherman-Broyles ... Doyle et al., 2014 (doi:10.3732/ajb.1400121).
G1718.gnm1.B1PY
Files in this directory are genome assemblies for Glycine falcata, accession G1718, from Zhuang, Wang et al. (2021): "A super-pangenome framework of the genus Glycine unveils polyploid evolution and life-strategy transition."
G1718.gnm1.ann1.2KSV
Files in this directory are genome annotation files for Glycine falcata, accession G1718, from Zhuang, Wang et al. (2021): "A super-pangenome framework of the genus Glycine unveils polyploid evolution and life-strategy transition."
G1974.gnm1.7MZB
Files in this directory are genome assemblies for Glycine stenophita, accession G1974, from Zhuang, Wang et al. (2021): "A super-pangenome framework of the genus Glycine unveils polyploid evolution and life-strategy transition."
G1974.gnm1.ann1.F257
Files in this directory are genome annotation files for Glycine stenphyta, accession G1974,from Zhuang, Wang et al. (2021): "A super-pangenome framework of the genus Glycine unveils polyploid evolution and life-strategy transition."
GD2422_x_LD01-5907.gen.Tan_Serven_2018
Further information provided in 10.1007/s00122-018-3110-x
Glycinemaxvariety7499_x_GlycinesojaPI245331.gen.Li_Pfeiffer_2008
Further information provided in 10.2135/cropsci2007.06.0361
Hamilton_x_PI90763.gen.Guo_Sleper_2005
Further information provided in 10.1007/s00122-005-0031-2
Hamilton_x_PI90763.gen.Guo_Sleper_2006
Further information provided in 10.1007/s00122-005-0150-9
Harosoy_x_Fukuyutaka.gen.Benitez_Hajika_2010
Further information provided in 10.2135/cropsci2009.11.0664
Hartwig_x_Flyer.gen.Kazi_Shultz_2010
Further information provided in 10.1007/s00122-009-1181-4
Hartwig_x_Williams82.gen.Vierling_Faghihi_1996
Further information provided in 10.1007/bf00222955
Hartwig_x_Y23.gen.Ferreira_Cervigni_2011
Further information provided in 10.1590/s0100-204x2011000400012
Hayahikari_x_Toyomusume.gen.Funatsuki_Ishimoto_2006
Further information provided in 10.1111/j.1439-0523.2006.01199.x
HeFeng25_x_DongnongL-5.gen.Xie_Han_2012
Further information provided in 10.1007/s11032-011-9607-5
Hefeng25_IGA1002.gnm1.L69T
Files in this directory are genome assembly files for cultivar Hefeng 25 (Hefeng25_IGA1002 in publication; WHFS_GmHF25_1.0 in the GenBank assembly record), Chu et al. (2021): Eight soybean reference genome resources from varying latitudes and agronmic traits.
Hefeng25_IGA1002.gnm1.ann1.320V
Files in this directory are genome annotation files for cultivar Hefeng 25, Chu et al. (2021): Eight soybean reference genome resources from varying latitudes and agronmic traits.
Hefeng25_x_Conrad.gen.Han_Li_2012
Further information provided in 10.1007/s00122-012-1859-x
Hefeng25_x_MapleArrow.gen.Li_Sun_2010
Further information provided in 10.1007/s10681-009-0036-z
Hefeng25_x_OACBayfield.gen.Li_Wang_2016
Further information provided in 10.1111/pbr.12346
Hefeng45_x_Dongnong48.gen.yang_Ding_2017
Further information provided in 10.1139/cjps-2016-0270
Huachun_x_Wayao.gen.Cai_Cheng_2018
Further information provided in 10.1007/s00122-017-3018-x
Huaxia3_IGA1007.gnm1.RGGN
Files in this directory are genome assembly files for cultivar Huaxia 3 (Huaxia3_IGA1007; WHFS_GmHX3_1.0 in the GenBank assembly record), Chu et al. (2021): Eight soybean reference genome resources from varying latitudes and agronmic traits.
Huaxia3_IGA1007.gnm1.ann1.LKC7
Files in this directory are genome annotation files for cultivar Huaxia3, Chu et al. (2021): Eight soybean reference genome resources from varying latitudes and agronmic traits.
Hwangkeum_x_IT182932.gen.Yang_Moon_2011
Further information provided in 10.1007/s13258-011-0043-z
IA2008_x_PI468916.gen.Wang_Graef_2004
Further information provided in 10.1007/s00122-003-1449-z
IA2008_x_PI468916.gen.Wang_Graef_2004a
Further information provided in 10.1007/s00122-003-1449-z
IA2008_x_PI468916.gen.Wang_Graef_2004b
Further information provided in 10.1007/s00122-003-1449-z
Ippon-Sangoh_x_Fukuyutaka.gen.Komatsu_Hwang_2012
Further information provided in 10.1270/jsbbs.61.646
Iyodaizu_x_Tachinagaha.gen.Van_Takahashi_2017
Further information provided in 10.1007/s00122-016-2847-3
JP036034_x_Ryuhou.gen.Wang_Chen_2015
Further information provided in 10.2135/cropsci2014.04.0280
JP110755_x_Fukuyutaka.gen.Kuroda_Kaga_2013
Further information provided in 10.1002/ece3.606
JWS156-1_x_Jackson.gen.Tuyen_Lal_2010
Further information provided in 10.1007/s00122-010-1304-y
Jackson_x_JWS156-1.gen.Hamwieh_Xu_2008
Further information provided in 10.1270/jsbbs.58.355
Jidou12_x_JiNF58.gen.Shi_Yan_2018
Further information provided in 10.1186/s13104-018-3202-3
Jidou9_x_ZYD2738.gen.Yan_Li_2014
Further information provided in 10.1111/pbr.12197
Jindou23_x_Huibuzhi.gen.LIANG_YU_2010
Further information provided in 10.1016/s1671-2927(09)60197-8
JindouNo6PI574484_x_197PI471938.gen.Hamwieh_Tuyen_2011
Further information provided in 10.1007/s10681-011-0347-8
Jingdou23_x_ZDD2315.gen.Liang_Yu_2014
Further information provided in 10.1007/s00122-014-2366-z
Jinpumkong2_x_SS2-2.gen.Liu_Kim_2011
Further information provided in 10.1007/s12892-010-0115-7
Jinpumkong_x_SS2-2.gen.Liu_Kim_2011
Further information provided in 10.1007/s00122-011-1606-8
Jinyuan_IGA1006.gnm1.LXM0
Files in this directory are genome assembly files for cultivar Jinyuan (Jinyuan_IGA1006 in the publication; WHFS_GmJY_1.0 in the GenBank assembly record), Chu et al. (2020); https://www.ncbi.nlm.nih.gov/bioproject/?term=prjna561626. Note: the publication uses the form Jingyuan in one place, but we use the form Jinyuan (lacking g) as used in the GenBank record. This accession may be in the same lineage as others called Jinuan, e.g. https://npgsweb.ars-grin.gov/gringlobal/accessiondetail?id=1370763
Jinyuan_IGA1006.gnm1.ann1.2NNX
Files in this directory are genome annotation files for cultivar Jinyuan, Chu et al. (2021): Eight soybean reference genome resources from varying latitudes and agronmic traits. Note: the publication uses the form Jingyuan in one place, but we use the form Jinyuan (lacking g) as used in the GenBank record. This accession may be in the same lineage as others called Jinuan, e.g. https://npgsweb.ars-grin.gov/gringlobal/accessiondetail?id=1370763
Jiyu50_x_Jinong18.gen.Yao_Liu_2015
Further information provided in 10.4238/2015.June.8.8
Jiyu69_x_SS0404-T5-76.gen.Shim_Kim_2017
Further information provided in 10.1007/s10681-017-2016-z
KF1_x_NN1138-2.gen.Li_Zhao_2011
Further information provided in 10.1007/s10681-011-0524-9
KFNo1_x_NN1138-2.gen.Korir_Qi_2011
Further information provided in 10.1111/j.1439-0523.2011.01862.x
KS4303sp_x_PI407818B.gen.Orazaly_Chen_2015
Further information provided in 10.2135/cropsci2014.03.0219
KS4895_x_Jackson.gen.Charlson_Bhatnagar_2009
Further information provided in 10.1007/s00122-009-1068-4
KS4895_x_Jackson.gen.Hwang_Ray_2014
Further information provided in 10.1007/s10681-013-1005-0
Kaori_x_ChiangMai60.gen.Juwattanasomran_Somta_2011
Further information provided in 10.1007/s00122-010-1467-6
Karafuto-1_x_Toyosuzu.gen.Khan_Githiri_2008
Further information provided in 10.1007/s00122-008-0792-5
Keburi_x_Mosshokutou.gen.Choi_Mano_2010
Further information provided in 10.1007/s11816-009-0115-6
Kefeng1_x_Nannon1138-2.gen.Du_Wang_2009
Further information provided in 10.1016/s1673-8527(08)60165-4
Kefeng1_x_Nannong1138-2.gen.DU_YU_2009
Further information provided in 10.1016/s1671-2927(08)60243-6
KefengNo1_x_1138-2.gen.Gai_Wang_2007
Further information provided in 10.1007/s11703-007-0001-3
KefengNo1_x_Nannong1138-2.gen.Ma_Kan_2016
Further information provided in 10.1021/acs.jafc.6b00167
KefengNo1_x_Nannong1138-2.gen.Yan_Wang_2015
Further information provided in 10.1111/jipb.12323
KefengNo1_x_Nannong1138-2.gen.Yang_Zhao_2011
Further information provided in 10.1007/s10059-011-0063-1
KefengNo1_x_Nannong1138-2.gen.Yin_Meng_2010
Further information provided in 10.1007/s00425-009-1094-0
KefengNo1_x_Nannong1138-2.gen.Zhang_Wang_2004
Further information provided in 10.1007/s00122-003-1527-2
KenfengNo1_x_Nannong.gen.Li_Wang_2005
Further information provided in 10.1007/s10681-005-1192-4
Kenjian4_x_Fengshou24.gen.Hu_Zhang_2013
Further information provided in 10.1007/s10709-013-9723-8
Kenjian4_x_Fengshou24.gen.Wu_Xu_2012
Further information provided in 10.1109/icbeb.2012.269
Kenwood_x_LG94-1713.gen.Guzman_Diers_2007
Further information provided in 10.2135/cropsci2006.01.0003
Keunol_x_Iksan10.gen.Lee_Kim_2016
Further information provided in 10.1007/s11032-016-0471-1
Keunolkong_x_Iksan10.gen.Kim_Kim_2010
Further information provided in 10.5352/jls.2010.20.8.1186
Keunolkong_x_Iksan10.gen.Shim_Ha_2015
Further information provided in 10.1007/s10681-014-1233-y
Keunolkong_x_Shinpaldalkong.gen.Kim_Kang_2005
Further information provided in 10.1111/j.1439-0523.2005.01152.x
Keunolkong_x_Shinpaldalkong.gen.Kim_Kang_2006
Further information provided in 10.1007/s10265-006-0004-9
Keunolkong_x_Sinpaldalkong.gen.Ha_Kim_2012
Further information provided in 10.1007/s10681-012-0719-8
Keunolkong_x_Sinpaldalkong.gen.Kang_Kwak_2009
Further information provided in 10.1007/s10681-008-9810-6
Kitakomachi_x_Koganejiro.gen.Githiri_Yang_2007
Further information provided in 10.1093/jhered/esm042
Kottman_x_PI391589B.gen.Guo_Wang_2008
Further information provided in 10.2135/cropsci2007.04.0198
L-10_x_Heinong37.gen.Chang_Dong_2011
Further information provided in 10.1186/1471-2164-12-233
LD00-2817P_x_LDX01-1-65.gen.Valdés-López_Thibivilliers_2011
Further information provided in 10.1104/pp.111.183327
Lee.gnm1.BXNC
Initial genome assembly for Glycine max cultivar Lee. The assembly incorporates Illumina sequence and optical mapping from NRGene. Pseudomolecule anchoring of scaffolds was accomplished using two dense genetic maps as well as synteny comparisons with Glycine max reference assembly for cultivar Williams 82 and Glycine soja PI 483463. This assembly corresponds to quality control round 12 (QC12), Oct 26, 2017
Lee.gnm1.ann1.6NZV
Genome annotations for the Glycine max Lee genome assembly
Lee.gnm2.K7BV
Files in this directory are genome assembly files for genotype Lee, Garg (2021)
Lee.gnm2.ann1.1FNT
Gene annotations, on genome assembly 2
Lineage69_x_Tucunare.gen.Leite_Pinheiro_2016
Further information provided in 10.4238/gmr.15017685
Lishuizhongzihuangdou_x_Nannong493-1.gen.LI_LI_2010
Further information provided in 10.1016/s1875-2780(09)60033-x
Luheidou2_x_Nanhuizao.gen.Fan_Li_2015
Further information provided in 10.1007/s10681-015-1491-3
M82806_x_HHP.gen.Brummer_Graef_1997
Further information provided in 10.2135/cropsci1997.0011183x003700020011x
M91-212006_x_SZG9652.gen.Vollmann_Schausberger_2002
Further information provided in 10.1046/j.1439-0523.2002.00707.x
MD96-5722_x_Spencer.gen.Akond_Liu_2014
Further information provided in 10.4236/ajps.2014.51021
MD96-5722_x_Spencer.gen.Anderson_Akond_2015
Further information provided in 10.1007/s13205-014-0211-3
MFS-553_x_PI243545.gen.Zeng_Chen_2014
Further information provided in 10.2135/cropsci2013.01.0036
MN1606SP_x_Spencer.gen.Luckew_Swaminathan_2017
Further information provided in 10.1007/s00122-017-2947-8
MaBelle_x_Proto.gen.Csanádi_Vollmann_2001
Further information provided in 10.1007/s001220100621
Magellan_x_PI404198A.gen.Guo_Sleper_2006
Further information provided in 10.2135/cropsci2004.0757
Magellan_x_PI437654.gen.Gutierrez-Gonzalez_Vuong_2011
Further information provided in 10.1007/s00122-011-1673-x
Magellan_x_PI438489B.gen.Vuong_Sleper_2011
Further information provided in 10.1007/s10681-011-0430-1
Magellan_x_PI567516C.gen.Vuong_Sleper_2010
Further information provided in 10.1007/s00122-010-1385-7
MapleDonovan_x_OACBayfield.gen.Huynh_Bastien_2010
Further information provided in 10.2135/cropsci2009.06.0311
Merit_x_PI194639.gen.Vuong_Diers_2008
Further information provided in 10.2135/cropsci2008.01.0019
Minsoy_x_Archer.gen.Orf_Chase_1999a
Further information provided in 10.2135/cropsci1999.3961652x
Minsoy_x_Archer.gen.Orf_Chase_1999b
Further information provided in 10.2135/cropsci1999.3961642x
Minsoy_x_Archer.gen.Stombaugh_Orf_2004
Further information provided in 10.2135/cropsci2004.2101
Minsoy_x_Noir1.gen.Njiti_Lightfoot_2006
Further information provided in 10.4141/p05-046
Minsoy_x_Noir1.gen.Specht_Chase_2001
Further information provided in 10.2135/cropsci2001.412493x
Minsoy_x_Noir1.gen.Terry_Chase_2000
Further information provided in 10.2135/cropsci2000.402375x
Minsoy_x_Noir1.gen.Tischner_Allphin_2003
Further information provided in 10.2135/cropsci2003.0464
Misuzudaizu_x_MoshidouGong503.gen.Tajuddin_Watanabe_2003
Further information provided in 10.1270/jsbbs.53.133
Misuzudaizu_x_MoshidouGong503.gen.Yamanaka_2001
Further information provided in 10.1093/dnares/8.2.61
Misuzudaizu_x_MoshidouGong503.gen.Yamanaka_Nagamura_2000
Further information provided in 10.1270/jsbbs.50.109
Misuzudaizu_x_MoshidouGong503MG503.gen.Githiri_Watanabe_2006
Further information provided in 10.1111/j.1439-0523.2006.01291.x
Msoy8001_x_Conquista.gen.Silva_Schuster_2007
Further information provided in 10.1590/s0100-204x2007000800011
N87-984-16_x_TN93-99.gen.Panthee_Kwanyuen_2004
Further information provided in 10.1007/s11746-004-1014-4
N87-984-16_x_TN93-99.gen.Panthee_Pantalone_2004
Further information provided in 10.1007/s11746-004-0860-4
N87-984-16_x_TN93-99.gen.Panthee_Pantalone_2005
Further information provided in 10.2135/cropsci2004.0720
N87-984-16_x_TN93-99.gen.Panthee_Pantalone_2006a
Further information provided in 10.1007/s00122-005-0161-6
N87-984-16_x_TN93-99.gen.Panthee_Pantalone_2006b
Further information provided in 10.1007/s11032-005-2519-5
N87-984-16_x_TN93-99.gen.Panthee_Pantalone_2006c
Further information provided in 10.1007/s10681-006-9179-3
N87-984-16_x_TN93-99.gen.Panthee_Pantalone_2007
Further information provided in 10.1111/j.1439-0523.2006.01305.x
N97-3363-3_x_PI423893.gen.Bachlava_Dewey_2009
Further information provided in 10.2135/cropsci2008.06.0324
N97-3708-13_x_Anand.gen.Spencer_Landau-Ellis_2004
Further information provided in 10.1007/s11746-006-0941-4
Nannong94-156_x_Bogao.gen.Zhang_Cheng_2009
Further information provided in 10.1007/s10681-009-9880-0
Nannong94-156_x_Bogao.gen.Zhang_Cheng_2010
Further information provided in 10.1016/s1673-8527(09)60074-6
Nannong94-156_x_Bogao.gen.Zhang_Li_2016
Further information provided in 10.3389/fpls.2016.00372
Nasushirome_x_Enrei.gen.Oyoo_Benitez_2010
Further information provided in 10.2135/cropsci2009.08.0440
No9-I_x_Harosoy-e3.gen.Liu_Abe_2010
Further information provided in 10.1093/jhered/esp113
Noir1_x_Archer.gen.Reyna_Sneller_2001
Further information provided in 10.2135/cropsci2001.4141317x
Noir1_x_Minsoy.gen.Mansur_Orf_1996
Further information provided in 10.2135/cropsci1996.0011183x003600050042x
Noir1_x_Minsoy.gen.Salas_Oyarzo-Llaipen_2006
Further information provided in 10.1007/s00122-006-0392-1
OACBayfield_x_Hefeng25.gen.Li_Liu_2010
Further information provided in 10.1007/s00122-010-1264-2
OACBayfield_x_OACShire.gen.Shaw_Rajcan_2017
Further information provided in 10.1111/pbr.12437
OACMillennium_x_Heinong38.gen.Palomeque_Li-Jun_2009a
Further information provided in 10.1007/s00122-009-1048-8
OACMillennium_x_Heinong38.gen.Palomeque_Li-Jun_2009b
Further information provided in 10.1007/s00122-009-1049-7
OACWallace_x_OACGlencoe.gen.Eskandari_Cober_2013a
Further information provided in 10.1007/s00122-012-1995-3
OACWallace_x_OACGlencoe.gen.Eskandari_Cober_2013b
Further information provided in 10.1007/s00122-013-2083-z
OX20-8_x_PI398841.gen.Lee_Mian_2013
Further information provided in 10.1007/s00122-013-2040-x
Ohsuzu_x_PI595926.gen.Kato_Sayama_2014
Further information provided in 10.1007/s00122-014-2304-0
Osage_x_RA-452.gen.Zeng_Lara_2017
Further information provided in 10.2135/cropsci2016.07.0600
P9254_x_A97-770012.gen.Charlson_Bailey_2005
Further information provided in 10.2135/cropsci2004.0510
PI200538_x_CNS.gen.Tamulonis_Luzzi_1997
Further information provided in 10.1007/s001220050610
PI27890_x_PI290136.gen.Lark_Chase_1995
Further information provided in 10.1073/pnas.92.10.4656
PI27890_x_PI290136.gen.Lark_Orf_1994
Further information provided in 10.1007/bf00223665
PI27890_x_PI290136.gen.Mansur_Lark_1993
Further information provided in 10.1007/BF00211040
PI27890_x_PI290136.gen.Mansur_Orf_1993
Further information provided in 10.1007/bf00211041
PI417479_x_Williams82.gen.Berger_Minor_1999
Further information provided in 10.2135/cropsci1999.0011183x003900030031x
PI437654_x_BSR101.gen.Webb_Baltazar_1995
Further information provided in 10.1007/bf00223282
PI437654_x_Bell.gen.Brucker_Carlson_2005
Further information provided in 10.1007/s00122-005-1970-3
PI437654_x_Essex.gen.Wu_Blake_2009
Further information provided in 10.1007/s00122-009-0965-x
PI438489B_x_Hamilton.gen.Bobby_Bazzelle_2012
Further information provided in 10.5539/jas.v4n9p98
PI438489B_x_Hamilton.gen.Masum-Akond_Ragin_2012
Further information provided in 10.5539/jas.v4n11p16
PI438489B_x_Hamilton.gen.My-Abdelmajid_Ramos_2017a
Further information provided in 10.5147/ajpb.2014.0140
PI438489B_x_Hamilton.gen.My-Abdelmajid_Ramos_2017b
Further information provided in 10.5147/pggb.v1i1.148
PI438489B_x_Hamilton.gen.Yue_Arelli_2001
Further information provided in 10.1007/s001220000453
PI442031_x_Sterling.gen.Zhao_Ablett_2005
Further information provided in 10.2135/cropsci2004.0560
PI468916_x_A81-356022.gen.Kabelka_Carlson_2005
Further information provided in 10.2135/cropsci2005.0027
PI468916_x_A81-356022.gen.Nichols_Glover_2006
Further information provided in 10.2135/cropsci2005.05-0168
PI468916_x_A81356022.gen.Wang_Diers_2001
Further information provided in 10.1007/pl00002910
PI483463.gnm1.YJWS
The aims of this project were to generate a high-quality reference genome assembly for Glycine soja accession PI 483463, which shows high genotypic diversity with respect to elite cultivars from Glycine max (soybean). The assembly incorporates Illumina sequence and optical mapping from NRGene. Pseudomolecule anchoring of scaffolds was accomplished using two dense genetic maps as well as synteny comparisons with the Glycine max reference assembly for cultivar Williams 82 (JGI Glyma.Wm82.a2) and Glycine max cultivar Lee. This assembly corresponds to quality control round 13 (QC13), Nov 7, 2017
PI483463.gnm1.ann1.3Q3Q
Genome annotations for the Glycine soja PI483463 genome assembly
PI483463_x_Hutcheson.gen.Asekova_Kulkarni_2016
Further information provided in 10.2135/cropsci2016.02.0125
PI483463_x_Hutcheson.gen.Ha_Kim_2014
Further information provided in 10.1007/s00122-014-2314-y
PI483463_x_Hutcheson.gen.Ha_Vuong_2013
Further information provided in 10.1007/s10681-013-0944-9
PI507531_x_Spencer.gen.Brzostowski_Pruski_2017
Further information provided in 10.1007/s00122-017-2961-x
PI561356_x_LD02-4485.gen.Kim_Unfried_2012
Further information provided in 10.1007/s00122-012-1932-5
PI567296B_x_Century84.gen.Patzoldt_Carlson_2005
Further information provided in 10.2135/cropsci2004.0393
PI567541B_x_Skylla.gen.Zhang_Gu_2009
Further information provided in 10.1007/s00122-008-0914-0
PI595645_x_PI416937.gen.Harris_Abdel-Haleem_2015
Further information provided in 10.2135/cropsci2015.01.0058
PI68658_x_Lawrence.gen.Fox_Cary_2015
Further information provided in 10.2135/cropsci2014.10.0688
PI88287_x_PI89008.gen.Vaghchhipawala_Bassüner_2001
Further information provided in 10.1094/mpmi.2001.14.1.42
PI89772_x_Hamilton.gen.Yue_Sleper_2001
Further information provided in 10.2135/cropsci2001.4151589x
PI96354_x_Bossier.gen.Li_Jakkula_2001
Further information provided in 10.1007/s001220100672
PI97100_x_Coker237.gen.Lee_Bailey_1996
Further information provided in 10.1007/bf00224553
PI97100_x_Coker237.gen.Mian_Bailey_1996
Further information provided in 10.1007/bf00230118
PI97100_x_Coker237.gen.Mian_Shipe_1997
Further information provided in 10.1093/oxfordjournals.jhered.a023053
Parker_x_Gsoja.gen.Sebolt_Shoemaker_2000
Further information provided in 10.2135/cropsci2000.4051438x
Peking_x_Essex.gen.Mahalmgam_Skorupska_1995
Further information provided in 10.1270/jsbbs1951.45.435
Peking_x_Essex.gen.Qiu_Arelli_1999
Further information provided in 10.1007/s001220051080
Peking_x_Keburi.gen.Song_Han_2010
Further information provided in 10.1007/s00299-009-0804-1
Peking_x_Tamahomare.gen.Sayama_Nakazaki_2009
Further information provided in 10.1016/j.plantsci.2009.01.007
Peking_x_Tamahomare.gen.Yoshikawa_Okumoto_2010
Further information provided in 10.1270/jsbbs.60.243
Pioneer9071_x_8902.gen.Rossi_Orf_2013
Further information provided in 10.1007/s00122-013-2094-9
Pioneer9071_x_Line8902.gen.Palomeque_Liu_2010
Further information provided in 10.1007/s00122-009-1227-7
Pureunkong_x_Jinpumkong2.gen.Lee_Park_2001
Further information provided in 10.1007/s001220100595
RG10_x_OX948.gen.Reinprecht_Poysa_2006
Further information provided in 10.1139/g06-112
RIL6013_x_RIL3613.gen.Ning_Yuan_2018
Further information provided in 10.1371/journal.pone.0195830
Ripley_x_Spencer.gen.de-Farias-Neto_Hashmi_2007
Further information provided in 10.1007/s11032-006-9072-8
S-100_x_Tokyo.gen.Lee_Boerma_2004
Further information provided in 10.1007/s00122-004-1783-9
S08-80_x_PI464925B.gen.Winter_Shelp_2007
Further information provided in 10.1007/s00122-006-0446-4
S100_x_Tokyo.gen.Mian_Ashley_1998
Further information provided in 10.1007/s001220051012
S19-90_x_Williams82.gen.Arahana_Graef_2001
Further information provided in 10.2135/cropsci2001.411180x
S19-90_x_Williams82.gen.Kim_Diers_2000
Further information provided in 10.2135/cropsci2000.40155x
S99-2281_x_PI408105A.gen.Nguyen_Vuong_2012
Further information provided in 10.2135/cropsci2011.09.0466
SD02-4-59_x_A02-381100.gen.Wang_Jiang_2012
Further information provided in 10.1007/s11032-012-9704-0
SD02-4-59_x_A02-381100.gen.Wang_Jiang_2014
Further information provided in 10.1007/s00438-014-0865-x
SD02-4-59_x_A02-381100.gen.Wang_Jiang_2015
Further information provided in 10.1007/s10681-014-1223-0
SS-516_x_Camp.gen.Zhang_Chen_2008
Further information provided in 10.2135/cropsci2007.10.0544
SS-516_x_Camp.gen.Zhang_Chen_2009
Further information provided in 10.1093/jhered/esn096
Skylla_x_E00290.gen.Kandel_Chen_2018
Further information provided in 10.3389/fpls.2018.00505
Sowon_x_V94-5152.gen.Jeong_Moon_2011
Further information provided in 10.1007/s00122-010-1492-5
Su88-M21S_x_XinyixiaoheidouX.gen.Wu_Zhou_2011
Further information provided in 10.1111/j.1439-0523.2010.01799.x
TK780_x_Hidaka4.gen.Shibata_Takayama_2008
Further information provided in 10.1270/jsbbs.58.361
Taekwangkong_x_SS2-2.gen.Sun_Kim_2013
Further information provided in 10.1007/s00122-013-2115-8
Taekwangkong_x_SS2-2.gen.Sun_Kim_2013a
Further information provided in 10.1007/s00122-013-2115-8
Taekwangkong_x_SS2-2.gen.Sun_Kim_2013b
Further information provided in 10.1007/s00122-013-2115-8
Tokei758_x_To-8E.gen.Sayama_Hwang_2010
Further information provided in 10.1270/jsbbs.60.380
Toyoharuka_x_Toyomusume.gen.Ohnishi_Funatsuki_2011
Further information provided in 10.1007/s00122-010-1475-6
Toyomusume_x_Harosoy.gen.Yamada_Funatsuki_2009
Further information provided in 10.1270/jsbbs.59.435
Toyomusume_x_Hayahikan.gen.Funatsuki_Kawaguchi_2005
Further information provided in 10.1007/s00122-005-0007-2
Toyomusume_x_Tsurukogane.gen.Ferdous_Watanabe_2006
Further information provided in 10.1270/jsbbs.56.155
Uzuramame_x_L67-3469.gen.Oyoo_Githiri_2010
Further information provided in 10.1270/jsbbs.60.28
V71-370_x_PI407162.gen.Maughan_Maroof_1996
Further information provided in 10.1007/bf00417950
V71-370_x_PI407162.gen.Tucker_Saghai-Maroof_2010
Further information provided in 10.2135/cropsci2009.03.0161
W05.gnm1.SVL1
Genome assembly files for cultivar W05 from Xie, Lam et al. (2019): A reference-grade wild soybean genome
W05.gnm1.ann1.T47J
Genome annotations for the Glycine soja W05 genome assembly
W05_x_C08.gen.Qi_Li_2014
Further information provided in 10.1038/ncomms5340
Wan82-178_x_TSBPHDJ.gen.Xing_Zhou_2012
Further information provided in 10.1007/s00122-012-1878-7
Wenfeng7_IGA1001.gnm1.L0QH
Files in this directory are genome assembly files for cultivar Wenfeng 7 (Wenfeng7_IGA1001 in publication; WHFS_GmWF7_1.0 in the GenBank assembly redord); Chu et al. (2021): Eight soybean reference genome resources from varying latitudes and agronmic traits.
Wenfeng7_IGA1001.gnm1.ann1.ZK5W
Files in this directory are genome annotation files for cultivar Wenfeng 7, Chu et al. (2021): Eight soybean reference genome resources from varying latitudes and agronmic traits.
Wilis_x_Toyokomachi.gen.Uchibori_Sasaki_2009
Further information provided in 10.1007/s11032-008-9238-7
Williams82_x_PI366121.gen.Dhungana_Kulkarni_2017
Further information provided in 10.1111/pbr.12480
Williams82_x_PI366121.gen.Kulkarni_Asekova_2017
Further information provided in 10.1071/CP16246
Williams82_x_PI366121.gen.Lee_Yoo_2015
Further information provided in 10.1007/s00122-015-2519-8
Williams82_x_PI437655.gen.Jiao_Vuong_2015
Further information provided in 10.1007/s00122-014-2409-5
Wm82.gnm1.FCtY
Genome assembly
Wm82.gnm1.ann1.DvBy
Genome annotations for the Glycine max Williams82 v1 genome assembly
Wm82.gnm1.mrk.BARCSOYSSR
The objectives of this study were to determine the abundance of SSRs in the soybean genome and to develop and test soybean SSR markers to create a database of locus-specific markers with a high likelihood of polymorphism. A total of 210,990 SSRs with di-, tri-, and tetranucleotide repeats of five or more were identified in the soybean whole genome sequence (WGS) which included 61,458 SSRs consisting of repeat units of di- (≥10), tri- (≥8), and tetranucleotide (≥7). Among the 61,458 SSRs, (AT)n, (ATT)n and (AAAT)n were the most abundant motifs among di-, tri-, and tetranucleotide SSRs, respectively. After screening for a number of factors including locus-specificity using e-PCR, a soybean SSR database (BARCSOYSSR_1.0) with the genome position and primer sequences for 33,065 SSRs was created.
Wm82.gnm1.mrk.Li_Guo_2016
To discover genes or QTLs underlying naturally occurring variations in soybean P.sojae resistance, we performed a genome-wide association study using 59,845 single-nucleotide polymorphisms identified from re-sequencing of 279 accessions from Yangtze-Huai soybean breeding germplasm. We used two models for association analysis. The same strong peak was detected by both two models on chromosome 13. Within the 500-kb flanking regions, three candidate genes (Glyma13g32980, Glyma13g33900, Glyma13g33512) had SNPs in their exon regions.
Wm82.gnm1.mrk.SoySNP50K
SoySNP50K is an Illumina Infinium II BeadChip that contains over 50,000 SNPs from soybean. Of 60,800 SNPs, 50,701 were targeted to euchromatic regions and 10,000 to heterochromatic regions of the 20 soybean chromosomes. In addition, 99 SNPs were targeted to unanchored sequence scaffolds. Of the 60,800 SNPs, a total of 52,041 passed Illumina’s manufacturing phase to produce the SoySNP50K iSelect BeadChip. Validation of the SoySNP50K chip with 96 landrace genotypes, 96 elite cultivars and 96 wild soybean accessions showed that 47,337 SNPs were polymorphic and generated successful SNP allele calls. In addition, 40,841 of the 47,337 SNPs (86%) had minor allele frequencies ≥10% among the landraces, elite cultivars and the wild soybean accessions.
Wm82.gnm1.mrk.SoySNP6K
The limited number of recombinant events in recombinant inbred lines suggests that for a biparental population with a limited number of recombinant inbred lines, it is unnecessary to genotype the lines with many markers. For genomic prediction and selection, previous studies have demonstrated that only 1000–2000 genome-wide common markers across all lines/accessions are needed to reach maximum efficiency of genomic prediction in populations. Evaluation of too many markers will not only increase the cost but also generate redundant information. We developed a soybean (Glycine max) assay, BARCSoySNP6K, containing 6000 markers, which were carefully chosen from the SoySNP50K assay based on their position in the soybean genome and haplotype block, polymorphism among accessions and genotyping quality. The assay includes 5000 single nucleotide polymorphisms (SNPs) from euchromatic and 1000 from heterochromatic regions. The percentage of SNPs with minor allele frequency >0.10 was 95% and 91% in the euchromatic and heterochromatic regions, respectively. Analysis of progeny from two large families genotyped with SoySNP50K versus BARCSoySNP6K showed that the position of the common markers and number of unique bins along linkage maps were consistent based on the SNPs genotyped with the two assays; however, the rate of redundant markers was dramatically reduced with the BARCSoySNP6K. The BARCSoySNP6K assay is proven as an excellent tool for detecting quantitative trait loci, genomic selection and assessing genetic relationships. The assay is commercialized by Illumina Inc. and being used by soybean breeders and geneticists and the list of SNPs in the assay is an ideal resource for SNP genotyping by targeted amplicon sequencing.
Wm82.gnm1.mrk.SoySSR
The objective of the work reported here was to develop and map a large set of SSR markers. A total of 606 SSR loci were mapped in one or more of three populations: the USDA/Iowa State G. max × G. soja F2 population, the Univ. of Utah Minsoy × Noir 1 recombinant inbred population, and the Univ. of Nebraska Clark × Harosoy F2 population. Each SSR mapped to a single locus in the genome, with a map order that was essentially identical in all three populations. Many SSR loci were segregating in two or all three populations. Thus, it was relatively simple to align the 20+ linkage groups derived from each of the three populations into a consensus set of 20 homologous linkage groups presumed to correspond to the 20 pairs of soybean chromosomes.
Wm82.gnm2.DTC4
Genome assembly
Wm82.gnm2.ann1.RVB6
Genome annotations for the Glycine max Williams82 v02 genome assembly
Wm82.gnm2.ann1.expr.G7ZY
Soybean gene expression atlas from 14 conditions (Libault et al., 2010).
Wm82.gnm2.mrk.1536_USLP1
Our objectives were to add 2500 additional SNP markers to the soybean integrated map and select a set of 1536 SNPs to create a universal linkage panel for high-throughput soybean quantitative trait locus (QTL) mapping. The GoldenGate assay is one high-throughput analysis method capable of genotyping 1536 SNPs in 192 DNA samples over a 3-d period. We designed GoldenGate assays for 3456 SNPs (2956 new plus 500 previously mapped) which were used to screen three recombinant inbred line populations and diverse germplasm. A total of 3000 workable assays were obtained which added about 2500 new SNP markers to create a fourth version of the soybean integrated linkage map. To create this Universal Soy Linkage Panel (USLP 1.0) of 1536 SNP loci, SNPs were selected based on even distribution throughout each of the 20 consensus linkage groups and to have a broad range of allele frequencies in diverse germplasm. The 1536 USLP 1.0 will be able to quickly create a comprehensive genetic map in most QTL mapping populations and thus will serve as a useful tool for high-throughput QTL mapping.
Wm82.gnm2.mrk.BARCSOYSSR
The objectives of this study were to determine the abundance of SSRs in the soybean genome and to develop and test soybean SSR markers to create a database of locus-specific markers with a high likelihood of polymorphism. A total of 210,990 SSRs with di-, tri-, and tetranucleotide repeats of five or more were identified in the soybean whole genome sequence (WGS) which included 61,458 SSRs consisting of repeat units of di- (≥10), tri- (≥8), and tetranucleotide (≥7). Among the 61,458 SSRs, (AT)n, (ATT)n and (AAAT)n were the most abundant motifs among di-, tri-, and tetranucleotide SSRs, respectively. After screening for a number of factors including locus-specificity using e-PCR, a soybean SSR database (BARCSOYSSR_1.0) with the genome position and primer sequences for 33,065 SSRs was created.
Wm82.gnm2.mrk.Fang_Ma_2017
To understand the genetic networks underlying phenotypic correlations, we collected 809 soybean accessions worldwide and phenotyped them for two years at three locations for 84 agronomic traits. Genome-wide association studies identified 245 significant genetic loci, among which 95 genetically interacted with other loci. We determined that 14 oil synthesis-related genes are responsible for fatty acid accumulation in soybean and function in line with an additive model. Network analyses demonstrated that 51 traits could be linked through the linkage disequilibrium of 115 associated loci and these links reflect phenotypic correlations. We revealed that 23 loci, including the known Dt1, E2, E1, Ln, Dt2, Fan, and Fap loci, as well as 16 undefined associated loci, have pleiotropic effects on different traits.
Wm82.gnm2.mrk.Li_Zhao_2019
Soybean is globally cultivated primarily for its protein and oil. The protein and oil contents of the seeds are quantitatively inherited traits determined by the interaction of numerous genes. In order to gain a better understanding of the molecular foundation of soybean protein and oil content for the marker-assisted selection (MAS) of high quality traits, a population of 185 soybean germplasms was evaluated to identify the quantitative trait loci (QTLs) associated with the seed protein and oil contents. Using specific length amplified fragment sequencing (SLAF-seq) technology, a total of 12,072 single nucleotide polymorphisms (SNPs) with a minor allele frequency (MAF) ≥ 0.05 were detected across the 20 chromosomes (Chr), with a marker density of 78.7 kbp. A total of 31 SNPs located on 12 of the 20 soybean chromosomes were correlated with seed protein and oil content. Of the 31 SNPs that were associated with the two target traits, 31 beneficial alleles were identified. Two SNP markers, namely rs15774585 and rs15783346 on Chr 07, were determined to be related to seed oil content both in 2015 and 2016. Three SNP markers, rs53140888 on Chr 01, rs19485676 on Chr 13, and rs24787338 on Chr 20 were correlated with seed protein content both in 2015 and 2016. These beneficial alleles may potentially contribute towards the MAS of favorable soybean protein and oil characteristics.
Wm82.gnm2.mrk.Meng_He_2016
The RAD-seq (restriction-site-association DNA sequencing) was used in the present study. The genomic DNA samples were extracted from the leaves of soybean seedlings using the CTAB method (Murray and Thompson 1980). The sequences of the 366 CSLRP accessions were obtained using Illumina HiSeq2000 instrument through the multiplexed shotgun genotyping method (Andolfatto et al. 2011) with DNA fragments between 400 and 600 bp, generating a total of 1144.56 million paired-end reads of 90 bp (including 6-bp index) in length (110.87 Gb of sequence) × approximately 3.86 in depth and 4.57 % coverage. All sequence reads were aligned against the reference genome Glyma.Wm82.a1.v1.1 (Schmutz et al. 2010) using the SOAP2 software (Li et al. 2009), with parameters that included sequence similarity, pair-end relationships and sequence quality. The RealSFS software (Yi et al. 2010) was used for population SNP calling, based on the Bayesian estimation of site frequency at every site. The SNPs of the 366 accessions were polymorphic with a rate of missing and heterozygous allele calls ≤30 % and minor allele frequency (MAF) ≥0.01 (the third or more alleles were replaced no more than once with the missing alleles, when available). The fastPHASE software (Scheet and Stephens 2006) was used for genotyping SNP imputation after heterozygous alleles were turned into missing alleles.
Wm82.gnm2.mrk.NJAU355K
Domestication of soybeans occurred under the intense human-directed selections aimed at developing high-yielding lines. Tracing the domestication history and identifying the genes underlying soybean domestication require further exploration. Here, we developed a high-throughput NJAU 355K SoySNP array and used this array to study the genetic variation patterns in 367 soybean accessions, including 105 wild soybeans and 262 cultivated soybeans. The population genetic analysis suggests that cultivated soybeans have tended to originate from northern and central China, from where they spread to other regions, accompanied with a gradual increase in seed weight. Genome-wide scanning for evidence of artificial selection revealed signs of selective sweeps involving genes controlling domestication-related agronomic traits including seed weight. To further identify genomic regions related to seed weight, a genome-wide association study (GWAS) was conducted across multiple environments in wild and cultivated soybeans. As a result, a strong linkage disequilibrium region on chromosome 20 was found to be significantly correlated with seed weight in cultivated soybeans. Collectively, these findings should provide an important basis for genomic-enabled breeding and advance the study of functional genomics in soybean.
Wm82.gnm2.mrk.Sonah_ODonoughue_2015
Soya bean is a major source of edible oil and protein for human consumption as well as animal feed. Understanding the genetic basis of different traits in soya bean will provide important insights for improving breeding strategies for this crop. A genome-wide association study (GWAS) was conducted to accelerate molecular breeding for the improvement of agronomic traits in soya bean. A genotyping-by-sequencing (GBS) approach was used to provide dense genome-wide marker coverage (>47 000 SNPs) for a panel of 304 short-season soya bean lines. A subset of 139 lines, representative of the diversity among these, was characterized phenotypically for eight traits under six environments (3 sites × 2 years). Marker coverage proved sufficient to ensure highly significant associations between the genes known to control simple traits (flower, hilum and pubescence colour) and flanking SNPs. Between one and eight genomic loci associated with more complex traits (maturity, plant height, seed weight, seed oil and protein) were also identified. Importantly, most of these GWAS loci were located within genomic regions identified by previously reported quantitative trait locus (QTL) for these traits. In some cases, the reported QTLs were also successfully validated by additional QTL mapping in a biparental population. This study demonstrates that integrating GBS and GWAS can be used as a powerful complementary approach to classical biparental mapping for dissecting complex traits in soya bean.
Wm82.gnm2.mrk.SoySNP50K
SoySNP50K is an Illumina Infinium II BeadChip that contains over 50,000 SNPs from soybean. Of 60,800 SNPs, 50,701 were targeted to euchromatic regions and 10,000 to heterochromatic regions of the 20 soybean chromosomes. In addition, 99 SNPs were targeted to unanchored sequence scaffolds. Of the 60,800 SNPs, a total of 52,041 passed Illumina’s manufacturing phase to produce the SoySNP50K iSelect BeadChip. Validation of the SoySNP50K chip with 96 landrace genotypes, 96 elite cultivars and 96 wild soybean accessions showed that 47,337 SNPs were polymorphic and generated successful SNP allele calls. In addition, 40,841 of the 47,337 SNPs (86%) had minor allele frequencies ≥10% among the landraces, elite cultivars and the wild soybean accessions.
Wm82.gnm2.mrk.SoySNP6K
The limited number of recombinant events in recombinant inbred lines suggests that for a biparental population with a limited number of recombinant inbred lines, it is unnecessary to genotype the lines with many markers. For genomic prediction and selection, previous studies have demonstrated that only 1000–2000 genome-wide common markers across all lines/accessions are needed to reach maximum efficiency of genomic prediction in populations. Evaluation of too many markers will not only increase the cost but also generate redundant information. We developed a soybean (Glycine max) assay, BARCSoySNP6K, containing 6000 markers, which were carefully chosen from the SoySNP50K assay based on their position in the soybean genome and haplotype block, polymorphism among accessions and genotyping quality. The assay includes 5000 single nucleotide polymorphisms (SNPs) from euchromatic and 1000 from heterochromatic regions. The percentage of SNPs with minor allele frequency >0.10 was 95% and 91% in the euchromatic and heterochromatic regions, respectively. Analysis of progeny from two large families genotyped with SoySNP50K versus BARCSoySNP6K showed that the position of the common markers and number of unique bins along linkage maps were consistent based on the SNPs genotyped with the two assays; however, the rate of redundant markers was dramatically reduced with the BARCSoySNP6K. The BARCSoySNP6K assay is proven as an excellent tool for detecting quantitative trait loci, genomic selection and assessing genetic relationships. The assay is commercialized by Illumina Inc. and being used by soybean breeders and geneticists and the list of SNPs in the assay is an ideal resource for SNP genotyping by targeted amplicon sequencing.
Wm82.gnm2.mrk.SoySSR
The objective of the work reported here was to develop and map a large set of SSR markers. A total of 606 SSR loci were mapped in one or more of three populations: the USDA/Iowa State G. max × G. soja F2 population, the Univ. of Utah Minsoy × Noir 1 recombinant inbred population, and the Univ. of Nebraska Clark × Harosoy F2 population. Each SSR mapped to a single locus in the genome, with a map order that was essentially identical in all three populations. Many SSR loci were segregating in two or all three populations. Thus, it was relatively simple to align the 20+ linkage groups derived from each of the three populations into a consensus set of 20 homologous linkage groups presumed to correspond to the 20 pairs of soybean chromosomes.
Wm82.gnm2.mrk.SoyaSNP180K
Cultivated soybean (Glycine max) suffers from a narrow germplasm relative to other crop species, probably because of under-use of wild soybean (Glycine soja) as a breeding resource. Use of a single nucleotide polymorphism (SNP) genotyping array is a promising method for dissecting cultivated and wild germplasms to identify important adaptive genes through high-density genetic mapping and genome-wide association studies. Here we describe a large soybean SNP array for use in diversity analyses, linkage mapping and genome-wide association analyses. More than four million high-quality SNPs identified from high-depth genome re-sequencing of 16 soybean accessions and low-depth genome re-sequencing of 31 soybean accessions were used to select 180,961 SNPs for creation of the Axiom(®) SoyaSNP array. Validation analysis for a set of 222 diverse soybean lines showed that 170,223 markers were of good quality for genotyping. Phylogenetic and allele frequency analyses of the validation set data indicated that accessions showing an intermediate morphology between cultivated and wild soybeans collected in Korea were natural hybrids. More than 90 unanchored scaffolds in the current soybean reference sequence were assigned to chromosomes using this array. Finally, dense average spacing and preferential distribution of the SNPs in gene-rich chromosomal regions suggest that this array may be suitable for genome-wide association studies of soybean germplasm. Taken together, these results suggest that use of this array may be a powerful method for soybean genetic analyses relating to many aspects of soybean breeding.
Wm82.gnm2.mrk.Zhao_Teng_2017
A total of 200 diverse soybean accessions were screened for resistance to SCN HG Type 2.5.7 and genotyped through sequencing using the Specific Locus Amplified Fragment Sequencing (SLAF-seq) approach with a 6.14-fold average sequencing depth. A total of 33,194 SNPs were identified with minor allele frequencies (MAF) over 4%, covering 97% of all the genotypes. Genome-wide association mapping (GWAS) revealed thirteen SNPs associated with resistance to SCN HG Type 2.5.7. These SNPs were distributed on five chromosomes (Chr), including Chr7, 8, 14, 15 and 18. Four SNPs were novel resistance loci and nine SNPs were located near known QTL. A total of 30 genes were identified as candidate genes underlying SCN resistance. Conclusions: A total of sixteen novel soybean accessions were identified with significant resistance to HG Type 2.5.7. The beneficial alleles and candidate genes identified by GWAS might be valuable for improving marker-assisted breeding efficiency and exploring the molecular mechanisms underlying SCN resistance.
Wm82.gnm2.syn.HXNY
Synteny calculations involves identification of orthologous genes by selecting reciprocal top hits between chromosome pairs from an all-against-all blastp search of genes between two species (evalue threshold of 1e-10), followed by DAGchainer to predict chains of syntenic genes in complete genomes. Proportions of synonymous-site changes (Ks) between orthologs are calculated, and synteny blocks are filtered for block-wise median Ks values. Synteny blocks have also been calculated to show these paralogous WGD-derived duplications.
Wm82.gnm4.4PTR
Genome assembly for Williams 82. The Williams 82 version 4 assembly (Wm82v4) builds on the widely-used assembly version 2, as well as an incremental version 3 that involved incorporation of BAC sequence to fill contig gaps in 2016. The Wm82v2 assembly was primarily Sanger-based, and new gap-filling in v3 and v4 utilized PacBio-based BAC assemblies targeted to gap regions. The Wm82v4 assembly closed 3,626 gaps and added 5,138,978 bp of sequence relative to Wm82v2, increasing the contig N50 from 233.1 kbp to 419.3 kbp.
Wm82.gnm4.ann1.T8TQ
Genome annotations for the Glycine max Williams 82 v4 genome assembly
Wm82_IGA1008.gnm1.5CQQ
Files in this directory are genome assembly files for cultivar Williams 82 (Wm82_IGA1008 in publication; WHFS_GmW82_1.0 in the GenBank assembly record), Chu et al. (2021): Eight soybean reference genome resources from varying latitudes and agronmic traits.
Wm82_IGA1008.gnm1.ann1.FGN6
Files in this directory are genome annotation files for cultivar William 82, Chu et al. (2021): Eight soybean reference genome resources from varying latitudes and agronmic traits.
Wyandot_x_PI567301B.gen.Jun_Rouf-Mian_2012
Further information provided in 10.1007/s00122-011-1682-9
Wyandot_x_PI567301B.gen.Lee_Jun_2015
Further information provided in 10.1007/s10681-014-1252-8
Wyandot_x_PI567324.gen.Jun_Rouf-Mian_2013
Further information provided in 10.1038/hdy.2013.10
X3145-B-B-3-15_x_ACBrant.gen.Pandurangan_Pajak_2012
Further information provided in 10.1093/jxb/ers039
Xiaoheidou_x_GR8836.gen.Wang_Cheng_2015
Further information provided in 10.1007/s10681-014-1209-y
XuyongHongdouXu_x_Baohexuan3.gen.Cheng_Wang_2011
Further information provided in 10.1007/s00122-011-1594-8
Y23_x_Hartwig.gen.Arriagada_Mora_2012
Further information provided in 10.1007/s10681-012-0696-y
Young_x_PI229358.gen.Bianchi-Hall_Carter_2000
Further information provided in 10.2135/cropsci2000.402538x
Young_x_PI416937.gen.Bailey_Mian_1997
Further information provided in 10.1093/oxfordjournals.jhered.a023075
Young_x_PI416937.gen.Fasoula_Harris_2003
Further information provided in 10.2135/cropsci2003.1754
Young_x_PI416937.gen.Fasoula_Harris_2004
Further information provided in 10.2135/cropsci2004.1218
Young_x_PI416937.gen.Lee_Bailey_1996a
Further information provided in 10.2135/cropsci1996.0011183x003600030035x
Young_x_PI416937.gen.Lee_Bailey_1996b
Further information provided in 10.1007/bf00224058
Young_x_PI416937.gen.Mian_Ashley_1998a
Further information provided in 10.2135/cropsci1998.0011183x003800020020x
Young_x_PI416937.gen.Mian_Ashley_1998b
Further information provided in 10.2135/cropsci1998.0011183x003800020020x
Young_x_PI416937.gen.Mian_Bailey_1996
Further information provided in 10.2135/cropsci1996.0011183x003600050030x
ZDD09454_x_Yudou12.gen.Lu_Wen_2013
Further information provided in 10.1007/s00122-012-1990-8
Zh13.gnm1.N6C8
Files in this directory are genome assembly files for cultivar Zhonghuang 13, Shen et al. (2018): De novo assembly of a Chinese soybean genome
Zh13.gnm1.ann1.8VV3
Files in this directory are genome assembly files for cultivar Zhonghuang 13, Shen et al. (2018): De novo assembly of a Chinese soybean genome
Zh13.gnm2.LV9P
Genome assembly files for the Glycine max Zhonghuang 13 v02 genome assembly
Zh13.gnm2.ann1.FJ3G
Files in this directory are genome assembly files for cultivar Zhonghuang 13, Shen et al. (2019): Update soybean Zhonghuang 13 genome to a golden reference
Zh13_IGA1005.gnm1.FRXQ
Files in this directory are genome assembly files for cultivar Zhonghuang 13 (Zh13_IGA1005 in publication; WHFS_GmZH13_1.0 in the GenBank assembly record), Chu et al. (2021): Eight soybean reference genome resources from varying latitudes and agronmic traits.
Zh13_IGA1005.gnm1.ann1.87Z5
Files in this directory are genome annotation files for cultivar Zhonghuang 13, Chu et al. (2021): Eight soybean reference genome resources from varying latitudes and agronmic traits.
Zh35_IGA1004.gnm1.DBYJ
Files in this directory are genome assembly files for cultivar Zhonghuang 35 (Zh35_IGA1004 in publication; WHFS_GmZH35_1.0 in the GenBank assembly record), Chu et al. (2021): Eight soybean reference genome resources from varying latitudes and agronmic traits.
Zh35_IGA1004.gnm1.ann1.RGN6
Files in this directory are genome annotation files for cultivar Zhonghuang 35, Chu et al. (2021): Eight soybean reference genome resources from varying latitudes and agronmic traits.
ZhongDou27_x_JiuNong20.gen.Wang_Han_2015
Further information provided in 10.1371/journal.pone.0118447
Zhongdou27_x_Jiunong20.gen.Han_Teng_2015
Further information provided in 10.1111/pbr.12259
Zhongdou27_x_Jiunong20.gen.Meng_Han_2011
Further information provided in 10.1007/s00122-011-1680-y
Zhongdou27_x_Jiunong20.gen.Zeng_Li_2009
Further information provided in 10.1007/s00122-009-0994-5
Zhongdou32_x_Zhongdou29.gen.Chen_Shan_2011
Further information provided in 10.1007/s10681-011-0382-5
mixed.gen.Glover_Wang_2004
Further information provided in 10.2135/cropsci2004.0936
mixed.gen.Hwang_King_2016
Further information provided in 10.1007/s11032-016-0516-5
mixed.gen.Jun_Van_2008
Further information provided in 10.1007/s10681-007-9491-6
mixed.gen.Matthews_MacDonald_1998
Further information provided in 10.1007/s001220050990
mixed.gen.Meksem_Ruben_2001
Further information provided in 10.1007/s004380000418
mixed.gen.Mudge_Cregan_1997
Further information provided in 10.2135/cropsci1997.0011183x003700050034x
mixed.gen.Pathan_Vuong_2013
Further information provided in 10.2135/cropsci2012.03.0153
mixed.gen.Qi_Wu_2011
Further information provided in 10.1007/s10681-011-0386-1
mixed.gen.Ramamurthy_Jedlicka_2014
Further information provided in 10.1007/s11032-014-0045-z
mixed.gwas.Bandillo_Jarquin_2015
In this research, we conducted the first comprehensive analysis of population structure on the collection of 14,000 soybean accessions [Glycine max (L.) Merr. and G. soja Siebold & Zucc.] using a 50KSNP chip. Accessions originating from Japan were relatively homogenous and distinct from the Korean accessions. As a whole, both Japanese and Korean accessions diverged from the Chinese accessions. The ancestry of founders of the American accessions derived mostly from two Chinese subpopulations, which reflects the composition of the American accessions as a whole. A 12,000 accession GWAS conducted on seed protein and oil is the largest reported to date in plants and identified single nucleotide polymorphisms (SNPs) with strong signals on chromosomes 20 and 15. A chromosome 20 region previously reported to be important for protein and oil content was further narrowed and now contains only three plausible candidate genes. The haplotype effects show a strong negative relationship between oil and protein at this locus, indicating negative pleiotropic effects or multiple closely linked loci in repulsion phase linkage. The vast majority of accessions carry the haplotype allele conferring lower protein and higher oil.
mixed.gwas.Bao_Kurle_2015
Sudden death syndrome (SDS), caused by Fusarium virguliforme, has spread to northern soybean growing regions in the US causing significant yield losses. The objectives of this study were to identify loci underlying variation in plant responses to SDS through association mapping (AM) and to assess prediction accuracy of genomic selection (GS) in a panel of early maturing soybean germplasm. A set of 282 soybean breeding lines was selected from the University of Minnesota soybean breeding program and then genotyped using a genome-wide panel of 1536 single-nucleotide polymorphism markers. Four resistance traits, root lesion severity (RLS), foliar symptom severity (FSS), root retention (RR), and dry matter reduction (DMR), were evaluated using soil inoculation in the greenhouse. AM identified significant peaks in genomic regions of known SDS resistance quantitative trait loci cqSDS001, cqRfs4, and SDS11-2. Additionally, two novel loci, one on chromosome 3 and another on chromosome 18, were tentatively identified. A ninefold cross-validation scheme was used to assess the prediction accuracy of GS for SDS resistance. The prediction accuracy of single-trait GS (ST-GS) was 0.64 for RLS, but less than 0.30 for RR, DMR, and FSS. Compared to STGS, none of multi-trait GS (MT-GS) models significantly improved the prediction accuracy due to weak correlations between the four traits. This study suggests both AM and GS hold promise for implementation in genetic improvement of SDS resistance in existing soybean breeding programs.
mixed.gwas.Cao_Li_2017
We used both a linkage and association mapping methodology to dissect the genetic basis of seed oil content of Chinese soybean cultivars in various environments in the Jiang-Huai River Valley. One recombinant inbred line (RIL) population (NJMN-RIL), with 104 lines developed from a cross between M8108 and NN1138-2, was planted in five environments to investigate phenotypic data, and a new genetic map with 2,062 specific-locus amplified fragment markers was constructed to map oil content QTLs. A derived F2 population between MN-5 (a line of NJMN-RIL) and NN1138-2 was also developed to confirm one major QTL. A soybean breeding germplasm population (279 lines) was established to perform a genome-wide association study (GWAS) using 59,845 high-quality single nucleotide polymorphism markers. In the NJMN-RIL population, 8 QTLs were found that explained a range of phenotypic variance from 6.3 to 26.3% in certain planting environments. Among them, qOil-5-1, qOil-10-1, and qOil-14-1 were detected in different environments, and qOil-5-1 was further confirmed using the secondary F2 population. Three loci located on chromosomes 5 and 20 were detected in a 2-year long GWAS, and one locus that overlapped with qOil-5-1 was found repeatedly and treated as the same locus. qOil-5-1 was further localized to a linkage disequilibrium block region of approximately 440 kb. These results will not only increase our understanding of the genetic control of seed oil content in soybean, but will also be helpful in marker-assisted selection for breeding high seed oil content soybean and gene cloning to elucidate the mechanisms of seed oil content.
mixed.gwas.Chang_Brown_2016
TRSV-induced disease sensitivities of the 697 soybean PIs were rated on a one to five scale with plants rated as one exhibiting mild symptoms and plants rated as five displaying terminal bud necrosis (i.e., bud blight). The GWAS identified a single locus on soybean chromosome 2 strongly associated with TRSV sensitivity. Crossvalidation showed a correlation of 0.55 (P < 0.01) to TRSV sensitivity without including the most significant SNP marker from the GWAS as a covariate, which was a better estimation compared to the mean separation by using significant SNPs. The genomic estimated breeding values for the remaining 18,955 unscreened soybean PIs in the USDA Soybean Germplasm Collection were obtained using the GAPIT R package. To evaluate the prediction accuracy, an additional 55 soybean accessions were evaluated for sensitivity to TRSV, which resulted in a correlation of 0.67 (P < 0.01) between actual and predicted severities.
mixed.gwas.Che_Liu_2017
A genome-wide association study was conducted to accelerate molecular breeding for the improvement of resistance to SMV in soybean. A population of 165 soybean mutants derived from two soybean parents was used in this study. There were 104 SNPs identified significantly associated with resistance to SC7, some of which were located within previous reported quantitative trait loci. Three putative genes on chromosome 1, 9, and 12 were homologous to WRKY72, eEF1Bβ, and RLP9, which were involved in defense response to insect and disease in Arabidopsis.
mixed.gwas.Dhanapal_Ray_2016
A genome-wide associating mapping approach was employed using 31,253 single nucleotide polymorphisms (SNPs) to identify loci associated with the extract based eChl_A, eChl_B, eChl_R and eChl_T measurements and the two canopy spectral reflectance-based methods (tChl_T and iChl_T). A total of 23 (14 loci), 15 (7 loci) and 14 SNPs (10 loci) showed significant association with eChl_A, eChl_B and eChl_R respectively. A total of 52 unique SNPs were significantly associated with total chlorophyll content based on at least one of the three approaches (eChl_T, tChl_T and iChl_T) and likely tagged 27 putative loci for total chlorophyll content, four of which were indicated by all three approaches.
mixed.gwas.Fang_Ma_2017
To understand the genetic networks underlying phenotypic correlations, we collected 809 soybean accessions worldwide and phenotyped them for two years at three locations for 84 agronomic traits. Genome-wide association studies identified 245 significant genetic loci, among which 95 genetically interacted with other loci. We determined that 14 oil synthesis-related genes are responsible for fatty acid accumulation in soybean and function in line with an additive model. Network analyses demonstrated that 51 traits could be linked through the linkage disequilibrium of 115 associated loci and these links reflect phenotypic correlations. We revealed that 23 loci, including the known Dt1, E2, E1, Ln, Dt2, Fan, and Fap loci, as well as 16 undefined associated loci, have pleiotropic effects on different traits.
mixed.gwas.Kim_Kim_2020
This study reports on the identification of candidate markers associated with flower time in soybean (Glycine max). A large population of 2,662 cultivated soybean accessions was genotyped using the 180k Axiom SoyaSNP array, and the genomic architecture of these accessions was investigated to confirm the population structure. Then, GWAS was conducted to evaluate the association between SNP markers and flower ytime. A tyyotal of 93 significant SNP markers were detected within 59 significant genes, including E1 and E3, which are the main determinants of flower time. Based on the GWAS results, multilocus epistatic interactions were examined between the significant and non-significant SNP markers. Two significant and 16 non-significant SNP markers were discovered as candidate markers affecting flower time via interactions with each other. These 18 candidate SNP markers mapped to 18 candidate genes including E1 and E3, and the 18 candidate genes were involved in six major flower pathways.
mixed.gwas.Li_Zhao_2019
A GWAS study of seed protein and oil content using a population of 185 soybean (Glycine max) accessions from China and across the northern hemisphere. Specific length amplified fragment sequencing (SLAF-seq) tecyyhnology detected 12,072 SNPs across 20 chromosomes showing a marker density of 78.7 kbp. Thirty-one SNPs, and their 31 beneficial alleles, placed on 12 of the chromosomes represented QTLs associateyd with protein and oil. In both 2015 and 2016, the SNPs rs15774585 and rs15783346 (Chr 7) were correlated with seed oil, and the SNPs rs53140888 (Chr 01), rs19485676 (Chr 13), and rs24787338 (Chr 20) with seed protein.
mixed.gwas.Mamidi_Chikara_2011
The objective of this analysis was to employ single nucleotide polymorphism (SNP)-based genome-wide association mapping to uncover genomic regions associated with IDC tolerance. Two populations [2005 (n = 143) and 2006 (n = 141)] were evaluated in replicated, multilocation IDC trials. After controlling for population structure and individual relatedness, and selecting statistical models that minimized false positives, 42 and 88 loci, with minor allele frequency >10%, were significant in 2005 and 2006, respectively. The loci accounted for 74.5% of the phenotypic variation in IDC in2005 and 93.8% of the variation in 2006. Nine loci from seven genomic locations were significant in both years. These loci accounted for 43.7% of the variation in 2005 and 47.6% in 2006. A number of the loci discovered here mapped at or near previously discovered IDC quantitative trait loci (QTL). A total of 15 genes known to be involved in iron metabolism mapped in the vicinity (<500 kb) of significant markers in one or both populations.
mixed.gwas.Meng_He_2016
The seed isoflavone content (SIFC) of soybeans is of great importance to health care. The Chinese soybean landrace population (CSLRP) as a genetic reservoir was studied for its whole-genome quantitative trait loci (QTL) system of the SIFC using an innovative restricted twostage multi-locus genome-wide association study procedure (RTM-GWAS). A sample of 366 landraces was tested under four environments and sequenced using RAD-seq (restriction-site-associated DNA sequencing) technique to obtain 116,769 single nucleotide polymorphisms (SNPs) then organized into 29,119 SNP linkage disequilibrium blocks (SNPLDBs) for GWAS. The detected 44 QTL 199 alleles on 16 chromosomes (explaining 72.2 % of the total phenotypic variation) with the allele effects (92 positive and 107 negative) of the CSLRP were organized into a QTL-allele matrix showing the SIFC population genetic structure. Additional differentiation among eco-regions due to the SIFC in addition to that of genome-wide markers was found. All accessions comprised both positive and negative alleles, implying a great potential for recombination within the population. The optimal crosses were predicted from the matrices, showing transgressive potentials in the CSLRP. From the detected QTL system, 55 candidate genes related to 11 biological processes were χ2 -tested as an SIFC candidate gene system. The present study explored the genome-wide SIFC QTL/gene system with the innovative RTM-GWAS and found the potentials of the QTLallele matrix in optimal cross design and population genetic and genomic studies, which may have provided a solution to match the breeding by design strategy at both QTL and gene levels in breeding programs.
mixed.gwas.Moellers_Singh_2017
GWAS and GWES studies along with expression studies in soybean were leveraged to dissect the genetics of Sclerotinia stem rot (SSR), a significant fungal disease causing yield and quality losses. A large association panel of 466 diverse plant introduction accessions were phenotyped in multiple field and controlled environments to: (1) discover sources of resistance, (2) identify SNPs associated with resistance, and (3) determine putative candidate genes to elucidate the mode of resistance.
mixed.gwas.Sonah_ODonoughue_2015
Soya bean is a major source of edible oil and protein for human consumption as well as animal feed. Understanding the genetic basis of different traits in soya bean will provide important insights for improving breeding strategies for this crop. A genome-wide association study (GWAS) was conducted to accelerate molecular breeding for the improvement of agronomic traits in soya bean. A genotyping-by-sequencing (GBS) approach was used to provide dense genome-wide marker coverage (>47 000 SNPs) for a panel of 304 short-season soya bean lines. A subset of 139 lines, representative of the diversity among these, was characterized phenotypically for eight traits under six environments (3 sites × 2 years). Marker coverage proved sufficient to ensure highly significant associations between the genes known to control simple traits (flower, hilum and pubescence colour) and flanking SNPs. Between one and eight genomic loci associated with more complex traits (maturity, plant height, seed weight, seed oil and protein) were also identified. Importantly, most of these GWAS loci were located within genomic regions identified by previously reported quantitative trait locus (QTL) for these traits. In some cases, the reported QTLs were also successfully validated by additional QTL mapping in a biparental population. This study demonstrates that integrating GBS and GWAS can be used as a powerful complementary approach to classical biparental mapping for dissecting complex traits in soya bean.
mixed.gwas.Wang_Chu_2016
We developed a high-throughput NJAU 355K SoySNP array and used this array to study the genetic variation patterns in 367 soybean accessions, including 105 wild soybeans and 262 cultivated soybeans. The population genetic analysis suggests that cultivated soybeans have tended to originate from northern and central China, from where they spread to other regions, accompanied with a gradual increase in seed weight.
mixed.gwas.Yan_Hofmann_2017
We selected 166 accessions from the USDA Soybean Germplasm Collection with either large or small seed weight and could typically grow in the same location. The accessions were evaluated for seed weight in the field for two years and genotyped with the SoySNP50K BeadChip containing >42,000 SNPs. Of the 17 SNPs on six chromosomes that were significantly associated with seed weight in two years based on a GWAS of the selective population, eight on chromosome 4 or chromosome 17 had significant Fst values between the large and small seed weight sub-populations. The seed weight difference of the two alleles of these eight significant SNPs varied from 8.1 g to 11.7 g/100 seeds in two years. We also identified haplotypes in three haplotype blocks with significant effects on seed weight. These findings were validated in a panel with 3753 accessions from the USDA Soybean Germplasm Collection.
mixed.gwas.Zhang_Hao_2015
In this study, we performed genetic association analysis to dissect the relationships between plant architecture and yield component traits. Two hundred and nineteen accessions were employed, and eight agronomic traits were evaluated in six environments. Our results revealed strong positive correlations of plant architecture traits with yield components and the significant association of 4 SNPs with plant architecture traits and of 7 SNPs with yield component traits in two or more environments. Eight SNPs were co-associated with two traits.
mixed.gwas.Zhang_Song_2015
The linkage disequilibrium (LD) decayed slowly in soybean, and a substantial difference in LD pattern was observed between euchromatic and heterochromatic regions. A total of 27, 6, 18 and 27 loci for DTF, DTM, DFTM and PH were detected via GWAS, respectively. The Dt1 gene was identified in the locus strongly associated with both DTM and PH. Ten candidate genes homologous to Arabidopsis flowering genes were identified near the peak single nucleotide polymorphisms (SNPs) associated with DTF. Four of them encode MADS-domain containing proteins. Additionally, a pectin lyase-like gene was also identified in a major-effect locus for PH where LD decayed rapidly.
mixed.gwas.Zhang_Song_2016
Genome-wide association study in a population of 309 soybean germplasm accessions using 31,045 single nucleotide polymorphisms (SNPs), estimating the prediction accuracy of genomic selection (GS) and marker-assisted selection (MAS) for seed weight (SW). Twenty-two loci of minor effect associated with SW were identified, including hotspots on Gm04 and Gm19. The mixed model containing these loci explained 83.4 % of phenotypic variation.
mixed.gwas.Zhao_Teng_2017
A total of 200 diverse soybean accessions were screened for resistance to SCN HG Type 2.5.7 and genotyped through sequencing using the Specific Locus Amplified Fragment Sequencing (SLAF-seq) approach with a 6.14-fold average sequencing depth. A total of 33,194 SNPs were identified with minor allele frequencies (MAF) over 4%, covering 97% of all the genotypes. Genome-wide association mapping (GWAS) revealed thirteen SNPs associated with resistance to SCN HG Type 2.5.7. These SNPs were distributed on five chromosomes (Chr), including Chr7, 8, 14, 15 and 18. Four SNPs were novel resistance loci and nine SNPs were located near known QTL. A total of 30 genes were identified as candidate genes underlying SCN resistance. Conclusions: A total of sixteen novel soybean accessions were identified with significant resistance to HG Type 2.5.7. The beneficial alleles and candidate genes identified by GWAS might be valuable for improving marker-assisted breeding efficiency and exploring the molecular mechanisms underlying SCN resistance.
mixed.map.GmComposite1999
Consensus genetic map GmComposite1999 drawn from SoyBase.
mixed.map.GmComposite2003
Consensus genetic map GmComposite2003 drawn from SoyBase.
mixed.map.GmFeChlorosis
Consensus genetic map GmFeChlorosis drawn from SoyBase.
mixed.map.GmFeChlorosis2
Consensus genetic map GmFeChlorosis2 drawn from SoyBase.
mixed.map.GmRAPD-SIU
Consensus genetic map GmRAPD-SIU drawn from SoyBase.
mixed.map.GmRAPD-Sclero
Consensus genetic map GmRAPD-Sclero drawn from SoyBase.
mixed.map.GmRFLP-CEW
Consensus genetic map GmRFLP-CEW drawn from SoyBase.
mixed.map.GmRFLP-CEW2
Consensus genetic map GmRFLP-CEW2 drawn from SoyBase.
mixed.map.GmRFLP-CEW3
Consensus genetic map GmRFLP-CEW3 drawn from SoyBase.
mixed.map.GmRFLP-Chiba
Consensus genetic map GmRFLP-Chiba drawn from SoyBase.
mixed.map.GmRFLP-Chiba2
Consensus genetic map GmRFLP-Chiba2 drawn from SoyBase.
mixed.map.GmRFLP-GA1996a
Consensus genetic map GmRFLP-GA1996a drawn from SoyBase.
mixed.map.GmRFLP-GA1996b
Consensus genetic map GmRFLP-GA1996b drawn from SoyBase.
mixed.map.GmRFLP-GA1998
Consensus genetic map GmRFLP-GA1998 drawn from SoyBase.
mixed.map.GmRFLP-JPT
Consensus genetic map GmRFLP-JPT drawn from SoyBase.
mixed.map.GmRFLP-KGL
Consensus genetic map GmRFLP-KGL drawn from SoyBase.
mixed.map.GmRFLP-USDAARS-RCS
Consensus genetic map GmRFLP-USDAARS-RCS drawn from SoyBase.
mixed.map.GmSCN
Consensus genetic map GmSCN drawn from SoyBase.
mixed.map.GmSSR-MO
Consensus genetic map GmSSR-MO drawn from SoyBase.
mixed.map.GmSSR-SIU
Consensus genetic map GmSSR-SIU drawn from SoyBase.
mixed.map.GmSSR-Sclero
Consensus genetic map GmSSR-Sclero drawn from SoyBase.
mixed.map.GmSSR-Utah
Consensus genetic map GmSSR-Utah drawn from SoyBase.
mixed.map.GmSSR-Utah2
Consensus genetic map GmSSR-Utah2 drawn from SoyBase.
mixed.map.GmSSR-Utah3
Consensus genetic map GmSSR-Utah3 drawn from SoyBase.
mixed.map.GmUSDA1997
Consensus genetic map GmUSDA1997 drawn from SoyBase.
mixed.map.GmUtah1996
Consensus genetic map GmUtah1996 drawn from SoyBase.
