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作物学报 ›› 2022, Vol. 48 ›› Issue (5): 1091-1102.doi: 10.3724/SP.J.1006.2022.14063

• 作物遗传育种·种质资源·分子遗传学 • 上一篇    下一篇

栽培大豆×半野生大豆高密度遗传图谱构建及株高QTL定位

于春淼1,3(), 张勇2, 王好让3, 杨兴勇2, 董全中2, 薛红2, 张明明2, 李微微2, 王磊2, 胡凯凤2, 谷勇哲3, 邱丽娟1,3,*()   

  1. 1东北农业大学农学院, 黑龙江哈尔滨 150030
    2黑龙江省农业科学院克山分院, 黑龙江齐齐哈尔 161606
    3农作物基因资源与遗传改良国家重大科学工程 / 农业农村部种质资源利用重点实验室 / 中国农业科学院作物科学研究所, 北京 100081
  • 收稿日期:2021-04-16 接受日期:2021-09-09 出版日期:2022-05-12 网络出版日期:2021-10-18
  • 通讯作者: 邱丽娟
  • 作者简介:于春淼, E-mail: 17709858735@163.com第一联系人:**同等贡献
  • 基金资助:
    国家自然科学基金项目(31601326);中央级公益性科研院所基本科研业务费专项(S2021ZD02);中国农业科学院科技创新工程;大豆种质资源保护与利用项目资助(2019NWB036-05)

Construction of a high density genetic map between cultivated and semi-wild soybeans and identification of QTLs for plant height

YU Chun-Miao1,3(), ZHANG Yong2, WANG Hao-Rang3, YANG Xing-Yong2, DONG Quan-Zhong2, XUE Hong2, ZHANG Ming-Ming2, LI Wei-Wei2, WANG Lei2, HU Kai-Feng2, GU Yong-Zhe3, QIU Li-Juan1,3,*()   

  1. 1College of Agriculture, Northeast Agricultural University, Harbin 150030, Heilongjiang, China
    2Keshan Branch of Heilongjiang Academy of Agricultural Sciences, Qiqihar 161606, Heilongjiang, China
    3National Key Facility for Gene Resources and Genetic Improvement / Key Laboratory of Crop Germplasm Utilization, Ministry of Agriculture / Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
  • Received:2021-04-16 Accepted:2021-09-09 Published:2022-05-12 Published online:2021-10-18
  • Contact: QIU Li-Juan
  • About author:First author contact:**Contributed equally to this work
  • Supported by:
    National Natural Science Foundation of China(31601326);Central Public-interest Scientific Institution Basal Research Fund(S2021ZD02);Agricultural Science and Technology Innovation Program of Chinese Academy of Agricultural Sciences;Protection and Utilization of Soybean Germplasm Resources(2019NWB036-05)

摘要:

采用中SNP160K芯片对丰收24×通交83-611 F2群体252个植株及其亲本进行基因分型, 构建了一张由5861个SNP标记组成的全长为3661.46 cM的高密度遗传连锁图谱。利用完备区间作图法(ICIM)定位到7个株高QTL, 每个QTL可解释2.56%~10.41%的株高变异。qPH-6-1具有最高的表型变异贡献率和显性效应, 可解释10.41%的株高变异, 加性效应和显性效应分别为-1.72和18.94; qPH-18-1贡献率次之, 可解释9.64%的株高变异, 但具有最高的加性效应, 达-12.42。在F2群体中筛选出11个qPH-6-1qPH-18-1基因型为Q6Q6/Q18Q18的单株, 平均株高167.00 cm; 筛选出16个基因型为q6q6/q18q18的植株, 平均株高为91.25 cm。在qPH-18-1定位区间内外增加23个SNP标记, 将定位区间由766.97 kb缩小至66.03 kb, 包含8个基因, 结合基因注释和相对表达量差异分析, 推测Glyma.18G279800Glyma.18G280200可能与大豆的株高相关。本研究为大豆株型的改良提供了分子参考依据和遗传基础。

关键词: 大豆, 株高, SNP, 遗传图谱, QTL定位, 候选基因

Abstract:

In this study, 252 plants and their parents of Fengshou 24 × Tongjiao 83-611 were genotyped by SNP160K DNA-chip. A high-density genetic linkage map with a total length of 3661.46 cM was constructed, composing of 5861 SNP markers. Seven QTLs of plant height were detected by inclusive composite interval mapping (ICIM), and each one explained 2.56%-10.41% of the variation in plant height. qPH-6-1 had the highest contribution rate of phenotypic variation and dominant effect, explaining 10.41% of plant height variation, and the additive and dominant effects are -1.72 and 18.94, respectively. The contribution rate of qPH-18-1 was the second, explaining 9.64% of plant height variation, but qPH-18-1 has the highest additive effect, reaching -12.42. 11 plants with qPH-6-1 and qPH-18-1 genotypes Q6Q6/Q18Q18 were screened in F2 population with an average plant height of 167.00 cm, and 16 plants with 2-locus genotypes q6q6/q18q18 were screened out with an average plant height of 91.25 cm. The addition of 23 SNP markers inside and outside the qPH-18-1 locus interval narrowed the locus interval from 766.97 kb to 66.03 kb, containing eight genes. Combined with gene annotation and relative expression difference analysis, it was hypothesized that Glyma.18G279800 and Glyma.18G280200 might be associated with plant height of soybean. This study provides a molecular reference base and genetic basis for the improvement of soybean plant architecture.

Key words: soybean, plant height, SNP, genetic linkage map, QTLs mapping, candidate gene

表1

候选基因和内参基因表达引物序列"

引物名称
Primer name
基因编号
Gene ID
上游引物
Forward primer (5'-3')
下游引物
Reverse primer (5'-3')
产物长度
Product length (bp)
Fbox Glyma.12G051100 CTAATGGCAATTGCAGCTCTC AGATAGGGAAATTGTGCAGGT 93
Q2795 Glyma.18G279500 GTAGCAGCCATGGAAGCGATAC AGATTTGTCTCGGTGGGGAAC 122
Q2796 Glyma.18G279600 CTGCTGGCTATGATGCACAGTCA AGGTTCATATCCACCTCCACTACG 122
Q2797 Glyma.18G279700 TACATGCGTGGTTCGCCTTGC TGTATGTTAGAGGGTGGGGAAAGG 135
Q2798 Glyma.18G279800 CCTTGATGAGCCAGATGAGAAATG CATAGTACATGGTTAAGTCAGGAAC 170
Q2799 Glyma.18G279900 CATCACCACCACAAGTAGTTTGG GATTTTGAGAGTTCATTGGAACTG 132
Q2800 Glyma.18G280000 GATCCTCTCCAGAAACATTGAGATG GGGTTATTATGTGGCTCTACTTGTG 128
Q2802 Glyma.18G280200 GTACATGCAAGGACCCTCTTGG TCACTGCTCTAACACACTGGCG 124

表2

鉴定qPH-18-1基因型所用SSR标记"

标记名称
Marker name
上游引物
Forward sequence (5'-3')
下游引物
Reverse sequence (5'-3')
物理位置
Physical position (bp)
BARCSOYSSR_18_1842 TGAAATGGAGGAGAAAATGGA GTCCGGGGAAACTGAACC 56,015,746-56,015,789
BARCSOYSSR_18_1843 TCGTTCGCAAAGAAAAATCC TTGGCAACAATGGAGTCTCA 56,035,543-56,035,596
BARCSOYSSR_18_1844 TGCAAGGCATTGATCTGATT AGAGGCGTCCTTCTGTTGTT 56,063,881-56,063,916
BARCSOYSSR_18_1845 TCATTGAGCCGAATCTTTTAAT CGTGCACATGGTGAGACATA 56,066,436-56,066,463
BARCSOYSSR_18_1846 CTTTTAACGATTGGGTTGGG CTTCGGCCTTAGACTTTTCG 56,068,160-56,068,221
BARCSOYSSR_18_1848 CGGTGTTGCTGACTATTGTCCT GGCTTTTGTAAACTGCTGGC 56,110,310-56,110,343
BARCSOYSSR_18_1849 TCTCGTCCCCGTATAAGGCT GGCGGATTGGAGAGAACATA 56,110,482-56,110,503
BARCSOYSSR_18_1850 AAATGCATTCGTGGCTTTCT TGGGTATTATTTGGCAAGCAC 56,138,357-56,138,410

图1

F2群体单株株高的表型分布"

表3

亲本及F2群体株高的统计分析"

性状
Trait
亲本Parent 群体Population
丰收24
Fengshou 24
通交83-611
Tongjiao 83-611
幅度
Range
均值
Mean
标准差
SD
峰度
Kurtosis
偏度
Skewness
株高Plant height (cm) 90.67±3.67 191.17±6.91 60.00-230.00 144.28 30.65 0.36 -0.54

图2

大豆遗传连锁图谱中5861个SNP标记的分布 图中黑色横线表示标记位置; 图中颜色表示标记密度, 由红到蓝色渐变表示标记密度由大到小。"

表4

SNP标记在构建的遗传图谱中分布"

染色体号
Chromosome-ID
标记数量
Number of markers
总图距
Total distance (cM)
平均图矩
Average distance (cM)
1 277 170.23 0.61
2 338 220.66 0.65
3 344 158.81 0.46
4 379 195.95 0.52
5 312 176.98 0.57
6 310 209.66 0.68
7 236 170.11 0.72
8 250 203.31 0.81
9 304 192.14 0.63
10 354 200.50 0.57
11 268 195.60 0.73
12 150 118.50 0.79
13 261 227.96 0.87
14 276 152.34 0.55
15 272 162.66 0.60
16 244 177.84 0.73
17 455 185.47 0.41
18 285 195.06 0.68
19 240 177.67 0.74
20 306 170.02 0.56
合计Total 5861 3661.46 0.62

表5

完备区间作图法定位的大豆株高QTL"

QTL 染色体
Chr.
标记区间
Marker flanking
位置
Position (cM)
区间长度
Length
(cM)
LOD 贡献率
PVE (%)
加性效应
Add
显性效应
Dmo
已报道位点
Reported
qPH-6-1 6 Gm06_18957454-Gm06_17916496 57 3.00 9.24 10.41 -1.72 18.94 Rossi et al., 2013[4]
qPH-8-1 8 Gm08_9294990-Gm08_9210707 143 10.00 2.57 2.56 2.45 -9.12
qPH-10-1 10 Gm10_8606306-Gm10_7981987 134 7.00 3.00 2.95 4.30 -8.25
qPH-13-1 13 Gm13_38753560-Gm13_37989992 56 6.00 4.16 4.73 -9.04 3.38 Pathan et al., 2013[25]
qPH-13-2 13 Gm13_28621502-Gm13_28455484 115 3.00 2.70 2.67 -2.20 9.56 Li et al., 2009[26]
qPH-18-1 18 Gm18_56044812-Gm18_56811782 16 6.00 8.58 9.64 -12.42 1.84 Kim et al., 2012[12]
qPH-20-1 20 Gm20_33777405-Gm20_33894103 56 1.00 3.77 4.05 -8.10 -1.49 Chapman et al., 2003[27]

表6

聚合不同基因型株高QTL对株高的影响"

聚合纯合提升株高基因型的QTL
QTL of polymerized homozygous genotypes with increase plant height
聚合纯合降低株高基因型的QTL
QTL of polymerized homozygous genotypes with reduce plant height
位点数
No. of QTL
植株数量
No. of plants
平均株高
Average height (cm)
分组
Group
P
P-value
位点数
No. of QTL
植株数量
No. of plants
平均株高
Average height (cm)
分组
Group
P
P-value
0 36 131.39±4.48 AC 对照Control 0 35 170.86±3.30 a 对照Control
1 64 139.45±3.89 AB 0.548 1 61 154.18±3.19 b 0.013*
2 74 146.49±3.28 BD 0.043* 2 70 137.14±3.18 c 0.000*
3 26 154.23±4.78 DE 0.010* 3 33 125.00±4.99 d 0.000*
4 15 166.67±5.66 E 0.000* 4 15 133.00±7.49 cd 0.000*
5 3 160.00±10.00 5 4 115.00±10.41 cd 0.000*

图3

使用丰收24和通交83-611 F2群体定位到的新qPH-18-1"

表7

定位区间内基因注释及同源基因"

基因编号
Gene ID
基因注释
Gene annotation
同源基因
Homologous gene
Glyma.18G279500 后期促进复合物3 (APC3, CDC27)
Anaphase-promoting complex subunit 3 (APC3, CDC27)
Phvul.008G021500
AT2G20000
Glyma.18G279600
Glyma.18G279700
Glyma.18G279800 在Pmr5和Cas1p中发现的GDSL/SGNH类酰基酯酶家族(PC-酯酶)
GDSL/SGNH-like Acyl-Esterase family found in Pmr5 and Cas1p (PC-Esterase);
PMR5 N terminal Domain (PMR5N)
Phvul.008G021200
AT5G15900
Glyma.18G279900 在Pmr5和Cas1p中发现的GDSL/SGNH类酰基酯酶家族(PC-酯酶)
GDSL/SGNH-like Acyl-Esterase family found in Pmr5 and Cas1p (PC-Esterase);
PMR5 N terminal Domain (PMR5N)
Phvul.008G021100
Glyma.18G280000
Glyma.18G280100 与F27J15.22相关; 油质蛋白
F27J15.22-RELATED; Oleosin
Glyma.18G280200 富脯氨酸受体样蛋白激酶perk8
Proline-rich receptor-like protein kinase perk8
AL7G52030

图4

群体中植株基因型与表型相关性分析 *、**和***分别表示在0.05、0.01和0.001水平差异显著。方形柱上下边框分别表示上下四分位数所在位置, 中部黑线为该组数据的中位数。"

图5

区间内基因的组织表达模式和表达分析"

表8

使用SNP芯片检测标记构建的遗传图谱比较"

芯片名称
SNP-chip name
亲本间SNP数
No. of parental SNPs
图谱标记数
No. of markers
图谱总长
Total distance (cM)
标记间平均距离
Average distance (cM)
BARCSoySNP6K 1133-2585 1063-2283 1908.7-2834 1.10-1.80
SoyaSNP180K 23,429-28,385 1570-8967 3454-5050 0.50-2.2
SNP160K 48,248 5861 3661.46 0.62
[1] Wilcox J R, Sediyama T. Interrelationships among height, lodging and yield in determinate and indeterminate soybeans. Euphytica, 1981, 30:323-326.
doi: 10.1007/BF00033993
[2] 李灿东, 郭泰, 王志新, 郑伟, 张振宇, 赵海红, 郭美玲, 李志民. 大豆耐密性状与产量的相关分析. 大豆科学, 2019, 38:862-867.
Li C D, Guo T, Wang Z X, Zheng W, Zhang Z Y, Zhao H H, Guo M L, Li Z M. Correlation analysis between density tolerance and yield of soybean. Soybean Sci, 2019, 38:862-867 (in Chinese with English abstract).
[3] Mansur L M, Orf J, Lark K G. Determining the linkage of quantitative trait loci to RFLP markers using extreme phenotypes of recombinant in breds of soybean [Glycine max.(L). Merr.]. Theor Appl Genet, 1993, 86:914-918.
doi: 10.1007/BF00211041 pmid: 24193997
[4] Rossi M, Orf J H, Liu L J. Genetic basis of soybean adaptation to north American vs. Asian mega-environments in two independent populations from Canadian × Chinese crosses. Theor Appl Genet, 2013, 126:1809-1823.
doi: 10.1007/s00122-013-2094-9
[5] Kabelka E A, Diers B W, Fehr W R. Putative alleles for increased yield from soybean plant introductions. Crop Sci, 2004, 44:784-791.
doi: 10.2135/cropsci2004.7840
[6] Diers B W, Specht J, Rainey K M, Cregan P, Song Q, Ramasubramanian V, Graef G, Nelson R, Schapaugh W, Wang D, Shannon G, McHale L, Kantartzi S K, Xavier A, Mian R, Stupar R M, Michno J M, An Y C, Goettel W, Ward R, Fox C, Lipka A E, Hyten D, Cary T, Beavis W D. Genetic architecture of soybean yield and agronomic traits. G3: Genes Genom Genet, 2018, 8:3367-3375.
[7] Palomeque L, Liu L J, Li W B, Hedges B R, Cober E R, Smid M P, Lukens L, Rajcan I. Validation of mega-environment universal and specific QTL associated with seed yield and agronomic traits in soybeans. Theor Appl Genet, 2010, 120:997-1003.
doi: 10.1007/s00122-009-1227-7 pmid: 20012262
[8] Specht J E, Chase K, Macrander M, Graef G L, Chung J, Markwell J P, Germann M, Orf J H, Lark K G. Soybean response to water: a QTL analysis of drought tolerance. Crop Sci, 2001, 41:493-509.
doi: 10.2135/cropsci2001.412493x
[9] Li D D, Pfeiffer T W, Cornelius P L. Soybean QTL for yield and yield components associated with Glycine soja alleles. Crop Sci, 2008, 48:571-581.
doi: 10.2135/cropsci2007.06.0361
[10] Lee S, Jun T H, Michel A P, Rouf Mian M A. SNP markers linked to QTL conditioning plant height, lodging, and maturity in soybean. Euphytica, 2015, 203:521-532.
doi: 10.1007/s10681-014-1252-8
[11] Zhang W K, Wang Y J, Luo G Z, Zhang J S, He C Y, Wu X L, Gai Y, Chen S Y. QTL mapping of ten agronomic traits on the soybean [Glycine max(L). Merr.] genetic map and their association with EST markers. Theor Appl Genet, 2004, 108:1131-1139.
pmid: 15067400
[12] Kim K S, Diers B W, Hyten D L, Rouf Mian M A, Shannon J G, Nelson R L. Identification of positive yield QTL alleles from exotic soybean germplasm in two backcross populations. Theor Appl Genet, 2012, 125:1353-1369.
doi: 10.1007/s00122-012-1944-1 pmid: 22869284
[13] Palomeque L, Liu L J, Li W B, Hedges B, Cober E R, Rajcan I. QTL in mega-environments: II. Agronomic trait QTL co-localized with seed yield QTL detected in a population derived from a cross of high-yielding adapted × high-yielding exotic soybean lines. Theor Appl Genet, 2009, 119:429-436.
doi: 10.1007/s00122-009-1048-8 pmid: 19462149
[14] 周蓉, 王贤智, 陈海峰, 张晓娟, 单志慧, 吴学军, 蔡淑平, 邱德珍, 周新安, 吴江生. 大豆倒伏性及其相关性状的QTL分析. 作物学报, 2009, 35:57-65.
Zhou R, Wang X Z, Chen H F, Zhang X J, Shan Z H, Wu X J, Cai S Z, Qiu D Z, Zhou X A, Wu J S. QTL Analysis of lodging and related traits in soybean. Acta Agron Sin, 2009, 35:57-65 (in Chinese with English abstract).
[15] Zhang X L, Wang W B, Guo N, Zhang Y Y, Bu Y P, Zhao J M, Xing H. Combining QTL-seq and linkage mapping to fine map a wild soybean allele characteristic of greater plant height. BMC Genomics, 2018, 19:226-237.
doi: 10.1186/s12864-018-4582-4
[16] Chen L Y, Nan H Y, Kong L P, Yue L, Yang H, Zhao Q S, Li H Y, Cheng Q, Lu S J, Kong F J, Liu B H, Dong L D. Soybean AP1 homologs control flowering time and plant height. J Integr Plant Biol, 2020, 62:1868-1879.
doi: 10.1111/jipb.v62.12
[17] Yang X, Li X, Shan J M, Li Y H, Zhang Y T, Wang Y H, Li W B, Zhao L. Overexpression of GmGAMYB accelerates the transition to flowering and increases plant height in soybean. Front Plant Sci, 2021, 12:667242.
doi: 10.3389/fpls.2021.667242 pmid: 34040624
[18] Li Z F, Guo Y, Ou L, Hong H L, Wang J, Liu Z X, Guo B F, Zhang L J, Qiu L J. Identification of the dwarf gene GmDW1 in soybean(Glycine max L.) by combining mapping-by-sequencing and linkage analysis. Theor Appl Genet, 2018, 131:1001-1016.
doi: 10.1007/s00122-017-3044-8
[19] Cheng Q, Dong L D, Su T, Li T Y, Gan Z R, Nan H Y, Lu S L, Fang C, Kong L P, Li H Y, Hou Z H, Kou K, Tang Y, Lin X Y, Zhao X H, Chen L Y, Liu B H, Kong F J. CRISPR/ Cas9-mediated targeted mutagenesis of GmLHY genes alters plant height and internode length in soybean. BMC Plant Biol, 2019, 19:562-572.
doi: 10.1186/s12870-019-2145-8 pmid: 31852439
[20] Zhang H, Zhang D, Han S, Zhang X, Yu D. Identification and gene mapping of a soybean chlorophyll-deficient mutant. Plant Breed, 2011, 130:133-138.
doi: 10.1111/pbr.2011.130.issue-2
[21] Chen K, Liu W C, Li X W, Li H Y. GmGASA32 overexpression of promoted soybean height by interacting with GmCDC25. Plant Signal Behav, 2021, 16:e1855017.
[22] Weigel D, Glazebrook J. Dellaporta miniprep for plant DNA isolation. Cold Spring Harb Protoc, 2009, 3(4):1-2.
[23] 王建康. 数量性状基因的完备区间作图方法. 作物学报, 2009, 35:239-245.
Wang J W. Inclusive composite interval mapping of guantitative trait genes. Acta Agron Sin, 2009, 35:239-245 (in Chinese with English abstract).
[24] McCouch S R, Chen X, Panaud O, Temnykb S, Xu Y, Cho Y G, Huang N, Ishii T, Blair M. Microsatellite marker development, mapping and applications in rice genetics and breeding. Plant Mol Biol, 1997, 35:89-99.
pmid: 9291963
[25] Pathan S M, Vuong T, Clark T, Lee J D, Shannon J G, Roberts A C, Ellersieck M A, Burton J W, Cregan P B, Hyten D L, Nguyen H T, Sleper D A. Genetic mapping and confirmation of quantitative trait loci for seed protein and oil contents and seed weight in soybean. Crop Sci, 2013, 53:765-774.
doi: 10.2135/cropsci2012.03.0153
[26] Li D M, Sun M M, Han Y P, Teng W L, Li W B. Identification of QTL underlying soluble pigment content in soybean stems related to resistance to soybean white mold (Sclerotinia sclerotiorum). Euphytica, 2010, 172:49-57.
doi: 10.1007/s10681-009-0036-z
[27] Chapman A, Pantalone V. R, Ustun A, Allen F L, Landau-Ellis D, Trigiano R N, Gresshoff P M. Quantitative trait loci for agronomic and seed quality traits in an F2 and F4:6 soybean population. Euphytica, 2003, 129:387-393.
doi: 10.1023/A:1022282726117
[28] Hu W F, Yan H W, Lou S S, Pan F, Wang Y, Xiang Y. Genome-wide analysis of poplar SAUR gene family and expression profiles under cold, polyethylene glycol and indole-3-acetic acid treatments. Plant Physiol Biochem, 2018, 128:50-65.
doi: 10.1016/j.plaphy.2018.04.021
[29] Gil P, Green P J. Regulatory activity exerted by the SAUR-AC1 promoter region in transgenic plants. Plant Mol Biol, 1997, 34:803-808.
pmid: 9278170
[30] Aleman F, Yazaki J, Lee M, Takahashi Y, Kim A Y, Li Z, Kinoshita T, Ecker J R, Schroeder J I. An ABA-increased interaction of thePYL6 ABA receptor with MYC2 transcription factor: a putative link of ABA and JA signaling. Sci Rep, 2016, 6:28941-28950.
doi: 10.1038/srep28941
[31] 杨琪. 大豆遗传基础拓宽问题. 大豆科学, 1993, (1):75-80.
Yang Q. The problem of broadening the genetic basis of soybean. Soybean Sci, 1993, (1):75-80 (in Chinese).
[32] 王彩洁, 孙石, 吴宝美, 常汝镇, 韩天富. 20世纪40年代以来中国大面积种植大豆品种的系谱分析. 中国油料作物学报, 2013, 35:246-252.
Wang C J, Sun S, Wu B M, Chang R Z, Han T F. Pedigree analysis of soybean varieties planted in large areas in China since the 1940s. J Oil Crop Sci, 2013, 35:246-252 (in Chinese with English abstract).
[33] Tan C, Han Z M, Yu H H, Zhan W, Xie W B, Chen X, Zhao H, Zhou F S, Xing Y Z. QTL scanning for rice yield using a whole genome SNP array. Genet Genomics, 2013, 40:629-638.
[34] Chen H T, Kumawat G, Yan Y L, Fan B J, Xu D H. Mapping and validation of a major QTL for primary root length of soybean seedlings grown in hydroponic conditions. BMC Genomics, 2021, 22:132-140.
doi: 10.1186/s12864-021-07445-0
[35] Li H Y, L H C, Han Y P, Wu X X, Teng W L, Liu G F, Li W B. Identification of QTL underlying vitamin E contents in soybean seed among multiple environments. Theor Appl Genet, 2010, 120:1405-1413.
doi: 10.1007/s00122-010-1264-2
[36] Ma Y J, Kan G Z, Zhang X N, Wang Y L, Zhang W, Du H Y, Yu D Y. Quantitative trait loci (QTL) mapping for glycinin and β-conglycinin contents in soybean (Glycine max L. Merr.). Agric Food Chem, 2016, 64:3473-3483.
doi: 10.1021/acs.jafc.6b00167
[37] Li X Y, Xue H, Zhang K X, Li W B, Fang Y L, Qi Z Y, Wang Y, Tian X C, Song J, Li W X, Ning H L. Mapping QTLs for protein and oil content in soybean by removing the influence of related traits in a four-way recombinant inbred line population. J Agric Sci, 2019, 157:659-675.
doi: 10.1017/S0021859620000040
[38] Choi I, Hyten D L, Matukumalli L K, Song Q J, Chaky J M, Quigley C V, Chase K, Lark K G, Reiter R S, Yoon M, Hwang E, Yi S, Young N D, Shoemaker R C, Tassell C P, Specht J E, Cregan P B. A soybean transcript map: gene distribution, haplotype and single-nucleotide polymorphism analysis. Genetics, 2007, 176:685-696.
doi: 10.1534/genetics.107.070821
[39] Liu N X, Li M, Hu X B, Ma Q B, Ma Y H, Tan Z Y, Xia Q J, Zhang G Y, Nian H. Construction of high-density genetic map and QTL mapping of yield-related and two quality traits in soybean RILs population by RAD-sequencing. BMC Genomics, 2017, 18:466-478.
doi: 10.1186/s12864-017-3854-8
[40] Zhang X, Hina A, Song S Y, Kong J J, Bhat J A, Zhao T J. Whole-genome mapping identified novel “QTL hotspots regions” for seed storability in soybean (Glycine max L.). BMC Genomics, 2019, 20:499-512.
doi: 10.1186/s12864-019-5897-5 pmid: 31208334
[41] Li B, Fan S X, Yu F K, Chen Y, Zhang S R, Han F X, Yan S R, Wang L Z, Sun J M. High-resolution mapping of QTL for fatty acid composition in soybean using specific-locus amplified fragment sequencing. Theor Appl Genet, 2017, 130:1467-1479.
doi: 10.1007/s00122-017-2902-8
[42] Silva M P, Klepadlo M, Gbur E E, Pereira A, Mason R E, Rupe J C, Bluhm B H, Wood L, Mozzoni L A, Chen P Y. QTL mapping of charcoal rot resistance in PI 567562A soybean accession. Crop Sci, 2019, 59:474-479.
doi: 10.2135/cropsci2018.02.0145
[43] Shim S, Kim M Y, Ha J, Lee Y H, Lee S H. Identification of QTLs for branching in soybean [Glycine max(L.) Merrill]. Euphytica, 2017, 213:225-233.
doi: 10.1007/s10681-017-2016-z
[44] Li X Y, Zhang K X, Sun X, Huang S S, Wang J J, Yang C, Siyal M, Wang C, Guo C L, Hu X Y, Li W X, Ning H L. Detection of QTL and QTN and candidate genes for oil content in soybean using a combination of four-way-RIL and germplasm populations. Crop J, 2020, 8:802-811.
doi: 10.1016/j.cj.2020.07.004
[45] Wang J, Chu S S, Zhang H R, Zhu Y, Cheng H, Yu D Y. Development and application of a novel genome-wide SNP array reveals domestication history in soybean. Sci Rep, 2016, 6:20728.
doi: 10.1038/srep20728
[46] Song Q J, Hyten D L, Jia G F, Quigly C V, Fickus E W, Nelson R L, Cregan P B. Development and evaluation of SoySNP50K, a high density genotyping array for soybean. PLoS One, 2013, 8:e54985.
[47] Song Q J, Jenkins J, Jia G F, Hyten D L, Pantalone V, Jackson S A, Schmutz J, Cregan P B. Construction of high resolution genetic linkage maps to improve the soybean genome sequence assembly Glyma1.01. BMC Genomics, 2016, 17:33-43.
doi: 10.1186/s12864-015-2344-0
[48] Boehm J D, Nguyen V, Tashiro R M, Anderson D T, Shi C, Wu X G, Woodrow L, Yu K F, Cui Y H, Li Z L. Genetic mapping and validation of the loci controlling 7S α’ and 11S a‑type storage protein subunits in soybean [Glycine max(L.) Merr.]. Theor Appl Genet, 2018, 131:659-671.
doi: 10.1007/s00122-017-3027-9
[49] Song Q J, Yan L, Quigley C, Fickus E, Wei H, Chen L F, Dong F M, Araya S, Liu J L, Hyten D, Pantalone V, Nelson R L. Soybean BARCSoySNP6K: an assay for soybean genetics and breeding research. Plant J, 2020, 104:800-811.
doi: 10.1111/tpj.v104.3
[50] Lee S, Freewalt K R, McHale L K, Song Q J, Jun T, Michel A P, Dorrance A E, Rouf Mian M A. A high-resolution genetic linkage map of soybean based on 357 recombinant inbred lines genotyped with BARCSoySNP6K. Mol Breed, 2015, 35:58.
doi: 10.1007/s11032-015-0209-5
[51] Bhusal S J, Jiang G L, Song Q J, Cregan P B, Wright D, Jose L, Hernandez G. Genome-wide detection of genetic loci associated with soybean aphid resistance in soybean germplasm PI603712. Euphytica, 2017, 213:144-159.
doi: 10.1007/s10681-017-1933-1
[52] Stasko A K, Wickramasinghe D, Nauth B J, Acharya B, Ellis M L, Taylor C G, Mchale L K, Dorrance A E. High-density mapping of resistance QTL toward Phytophthora sojae, Pythium irregulare, and Fusarium graminearum in the same soybean population. Crop Sci, 2016, 56:2476-2492.
doi: 10.2135/cropsci2015.12.0749
[53] Do T D, Vuong T D, Dunn D, Smothers S, Patil G, Yungbluth D C, Chen P Y, Scaboo A, Xu D, Carter T E, Nguyen H T, Shannon J G. Mapping and confirmation of loci for salt tolerance in a novel soybean germplasm, Fiskeby III. Theor Appl Genet, 2018, 131:513-524.
doi: 10.1007/s00122-017-3015-0
[54] Beche E, Gillman J D, Song Q J, Nelson R, Beissinger T, Decker J, Shannon G, Scaboo A M. Nested association mapping of important agronomic traits in three interspecific soybean populations. Theor Appl Genet, 2020, 133:1039-1054.
doi: 10.1007/s00122-019-03529-4
[55] Contreras-Soto R I, Oliveira M D, Costenaro-Da-Silva D, Scapim C A, Schuster I. Population structure, genetic relatedness and linkage disequilibrium blocks in cultivars of tropical soybean (Glycine max). Euphytica, 2017, 213:173-184.
doi: 10.1007/s10681-017-1966-5
[56] Lee S, Jun T H, McHale L K, Miche A P, Dorrance A E, Song Q J, Mian M A R. Registration of Wyandot × PI 567301B soybean recombinant inbred line population. J Plant Regist, 2017, 11:324-327.
doi: 10.3198/jpr2016.09.0042crmp
[57] Lee Y G, Jeong N, Kim J H, Lee K, Kim K H, Pirani A, Ha B K, Kang S T, Park B S, Moon J K, Kim N, Jeong S C. Development, validation and genetic analysis of a large soybean SNP genotyping array. Plant J, 2015, 81:625-636.
doi: 10.1111/tpj.2015.81.issue-4
[58] Lee J S, Kim S M, Kang S. Fine mapping of quantitative trait loci for sucrose and oligosaccharide contents in soybean [Glycine max(L.) Merr.] using 180 K Axiom® SoyaSNP genotyping platform. Euphytica, 2016, 208:195-203.
doi: 10.1007/s10681-015-1622-x
[59] Lee J S, Kim K R, Ha B K, Kang S. Identification of SNPs tightly linked to the QTL for pod shattering in soybean. Mol Breed, 2017, 37:54-63.
doi: 10.1007/s11032-017-0656-2
[60] Seo J H, Kim K S, Ko J M, Choi M S, Kang B K, Kwon S W, Jun T H. Quantitative trait locus analysis for soybean (Glycine max) seed protein and oil concentrations using selected breeding populations. Plant Breed, 2019, 138:95-104.
doi: 10.1111/pbr.2019.138.issue-1
[61] Orf J H, Chase K, Jarvik T, Mansur M L, Cregan P B, Adler F R, Lark K G. Genetics of soybean agronomic traits: I. Comparison of three related recombinant inbred populations. Crop Sci, 1999, 39:1642-1651.
doi: 10.2135/cropsci1999.3961642x
[62] Anantharaman V, Aravind L. Novel eukaryotic enzymes modifying cell-surface biopolymers. Biol Direct, 2010, 5:1.
doi: 10.1186/1745-6150-5-1 pmid: 20056006
[63] Bischoff V, Selbig J, Scheible W. Involvement of TBL/DUF231 proteins into cell wall biology. Plant Signal Behav, 2010, 5:1057-1059.
doi: 10.4161/psb.5.8.12414 pmid: 20657172
[64] Lefebvre V, Fortabat M N, Ducamp A, North H M, Maia-Grondard A, Trouverie J, Boursiac Y, Mouille G, Durand-Tardif M. ESKIMO1 disruption in Arabidopsis alters vascular tissue and impairs water transport. PLoS One, 2011, 6:e16645.
[65] Herr A J, Molnàr A, Jones A, Baulcombe D C. Defective RNA processing enhances RNA silencing and influences flowering of Arabidopsis. Proc Natl Acad Sci USA, 2006, 103:14994-15001.
doi: 10.1073/pnas.0606536103
[66] Howles P A, Gebbie L K, Collings D A, Varsani A, Broad R C, Ohms S, Birch R J, Cork A H, Arioli T, Williamson R E. A temperature-sensitive allele of a putative mRNA splicing helicase down-regulates many cell wall genes and causes radial swelling in Arabidopsis thaliana. Plant Mol Biol, 2016, 91:1-13.
doi: 10.1007/s11103-016-0428-0 pmid: 27008640
[67] He Y H, Doyle M R, Amasino R M. PAF1-complex-mediated histone methylation of FLOWERING LOCUS C chromatin is required for the vernalization-responsive, winter-annual habit in Arabidopsis. Genes Dev, 2004, 18:2774-2784.
doi: 10.1101/gad.1244504
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