Scientia Agricultura Sinica ›› 2022, Vol. 55 ›› Issue (2): 248-264.doi: 10.3864/j.issn.0578-1752.2022.02.002

• CROP GENETICS & BREEDING·GERMPLASM RESOURCES·MOLECULAR GENETICS • Previous Articles     Next Articles

Restricted Two-Stage Multi-Locus Genome-Wide Association Analysis and Candidate Gene Prediction of Boll Opening Rate in Upland Cotton

XIE XiaoYu1(),WANG KaiHong1,QIN XiaoXiao1,WANG CaiXiang1(),SHI ChunHui1,NING XinZhu2,YANG YongLin3,QIN JiangHong3,LI ChaoZhou1,MA Qi2(),SU JunJi1()   

  1. 1College of Life Science and Technology, Gansu Agricultural University/State Key Laboratory of Arid Land Crop Science, Lanzhou 730070
    2Cotton Research Institute, Xinjiang Academy of Agricultural and Reclamation Science, Shihezi 832000, Xinjiang
    3Shihezi Academy of Agriculture Science, Shihezi 832000, Xinjiang
  • Received:2021-08-13 Accepted:2021-10-26 Online:2022-01-16 Published:2022-01-26
  • Contact: CaiXiang WANG,Qi MA,JunJi SU E-mail:xiexiaoyu0924@126.com;wangcx8050@163.com;xjnkymaqi1123@163.com;sujunjicotton@126.com

Abstract:

【Objective】Boll opening rate (BOR) is one of the most important indicators reflecting the early maturing trait of upland cotton (Gossypium hirsutum L.). The genome-wide association study (GWAS) was applied to dissect the QTL (quantitative trait locus) and its genetic effect for providing a theoretical basis for molecular breeding of early maturing traits in upland cotton. 【Method】The natural population composed of 315 different upland cotton varieties (lines) were used to identify the BOR under three environments. Simultaneously, a total of 9 244 SNP linkage disequilibrium block (SNPLDB) markers with multiple alleles were constructed. Then, the restricted two-stage multi-locus GWAS (RTM-GWAS) was utilized to detect SNPLDB loci significantly associated with BOR, estimate its phenotypic effect value, establish QTL-Allele matrix for significantly associated loci in the population, and further detected the stable major SNPLDB loci and elite haplotypes. Finally, according to the gene expression levels of the two transcriptome data, candidate genes that may be related to the target trait were mined within the 1 Mb genome range of the flanking sequence of the significant SNPLDB loci. 【Result】The variation of BOR was ranged from 37.78% to 100.00% and the broad-sense heritability was 67.03% in the natural population under three environments. The multi-environment variance analysis revealed that the BOR was significantly different among genotype, environment and genotype × environment interaction (P<0.001). A total of 52 SNPLDB loci significantly associated with BOR were detected through the RTM-GWAS procedure, containing 179 alleles or haplotypes, among them, the effect values of 90 increasing alleles or haplotypes ranged from 0.014 to 19.43, and the effect values of 89 decreasing alleles or haplotypes ranged from -21.49 to -0.039. Among the significant SNPLDB loci mentioned above, 6 SNPLDB loci were detected simultaneously in both multi-environment and single environment, which were considered as stable SNPLDB loci significantly associated with BOR. Through the significance analysis of phenotypic traits corresponding to different allelic variations of the above six stable SNPLDB loci, the four favorable alleles were identified as LDB_16_37952328(TT), LDB_5_96395565(AA), LDB_16_49503485(TT), and LDB_4_81118668(TT). Besides, further analysis showed that there were significant differences in the frequency distribution of favorable alleles among varieties (lines) in four different ecological regions. Additionally, a total of 178 genes were annotated and 23 potential candidate genes were predicted in the adjacent regions of 4 stable major SNPLDB loci by transcriptome data analysis. 【Conclusion】A total of 52 SNPLDB loci significantly associated with BOR were identified, of which 4 loci were stable major SNPLDB loci. Furthermore, it was predicted that 23 genes might be related to the BOR of upland cotton. These SNPLDBs loci and candidate genes will provide a theoretical basis for marker-assisted breeding of early maturity in upland cotton.

Key words: Upland cotton, boll opening rate, RTM-GWAS, QTL allele matrix, candidate genes

Table 1

Frequency distribution and descriptive statistics of boll opening rate in upland cotton"

环境
Env.
吐絮率BOR(%) 平均数
Mean (%)
变幅
Range (%)
变异系数
CV (%)
13 19 25 31 37 43 49 55 61 67 73 79 85 91 97 N
AY-14 3 5 6 19 31 85 133 33 315 80.62 46.73—90.00 9.86
AY-15 4 5 11 23 25 32 35 43 36 22 24 20 19 9 7 315 55.99 10.42—100.00 34.60
SHZ-14 1 1 3 16 28 41 63 62 57 34 9 315 70.80 37.78—98.05 14.42
综合 Syn. 1 2 9 24 48 58 80 44 37 12 315 70.76 39.27—91.32 14.25

Table 2

Variance analysis of boll opening rate in upland cotton"

性状
Trait
方差来源
Variance
平方和
SS
均方
MS
F
F- value
P
P-value
遗传力
H2(%)
吐絮率
BOR
环境Environment 321981.19 160990.59 1084.69 <0.0001 67.03
基因型Genotype 288095.59 917.50 6.18 <0.0001
环境×基因型Environment ×Genotype 237515.09 378.21 2.55 <0.0001

Table 3

SNPLDB loci significantly associated with boll opening rate in upland cotton"

位点
Loci
染色体
Chr.
位置
Position (bp)
-lg(P) 表型变异
PV (%)
共同环境a
Common environments
LDB_16_37952328 16 (D03) 37952328 46.14 1.90 AY-15 (11.49)、SHZ-14 (5.91)
LDB_5_96395565 5 (A05) 96395565 22.69 0.40 AY-15 (7.42)
LDB_16_49503485 16 (D03) 49503485 17.79 0.91 AY-15 (8.49)
LDB_10_6908012 10 (A10) 6908012 16.70 0.87 AY-15 (8.75)
LDB_15_9697358 15 (D02) 9697358 13.52 1.89 AY-15 (8.41)
LDB_21_22036171 21 (D08) 22036171 13.44 1.34
LDB_4_81118668 4 (A04) 81118668 11.80 0.91 AY-15 (4.58)
LDB_3_6725154_6746183 3 (A03) 6725154 11.63 1.21
LDB_1_57527637_57527855 1 (A01) 57527637 10.44 1.11
LDB_16_36553916_36554161 16 (D03) 36553916 9.81 1.72
LDB_11_119047116 11 (A11) 119047116 9.76 0.86
LDB_19_52309050_52309284 19 (D06) 52309050 7.97 1.54
LDB_17_51465593 17 (D04) 51465593 7.93 0.51
LDB_13_54999733 13 (A13) 54999733 7.36 0.61
位点
Loci
染色体
Chr.
位置
Position (bp)
-lg(P) 表型变异
PV (%)
共同环境a
Common environments
LDB_20_6608424 20 (D07) 6608424 6.63
LDB_7_94884564_94884800 7 (A07) 94884564 6.34
LDB_19_53788858 19 (D06) 53788858 6.25 0.27
LDB_9_58666084_58666088 9 (A09) 58666084 6.06 1.12
LDB_6_41226103 6 (A06) 41226103 5.52 9.00
LDB_15_46384945_46385146 15 (D02) 46384945 5.17 0.36
LDB_15_67139952_67140180 15 (D02) 67139952 5.14 1.68
LDB_25_27281705 25 (D12) 27281705 5.10
LDB_23_6012092 23 (D10) 6012092 4.94 0.18
LDB_1_33221331 1 (A01) 33221331 4.06 0.38
LDB_12_96771402 12 (A12) 96771402 3.84 0.97
LDB_15_65780303 15 (D02) 65780303 3.65 0.67
LDB_22_48423583 22 (D09) 48423583 3.64 0.88
LDB_14_45778715_45778973 14 (D01) 45778715 3.58 1.08
LDB_21_5030313_5030325 21 (D08) 5030313 3.55 0.15
LDB_25_39776065 25 (D12) 39776065 3.47 0.37
LDB_26_45642548 26 (D13) 45642548 3.42 SHZ-14 (1.77)
LDB_5_30493466 5 (A05) 30493466 3.20
LDB_12_103902963 12 (A12) 103902963 3.15 0.39
LDB_3_42046528_42046540 3 (A03) 42046528 2.86
LDB_10_70110862_70110882 10 (A10) 70110862 2.51
LDB_13_72681594_72681843 13 (A13) 72681594 2.46 0.21
LDB_19_39327466 19 (D06) 39327466 2.43
LDB_11_18062977 11 (A11) 18062977 2.42 0.44
LDB_8_113962673 8 (A08) 113962673 2.30
LDB_23_24053424 23 (D10) 24053424 2.25 0.43
LDB_21_25090078 21 (D08) 25090078 2.19 0.47
LDB_6_108270563 6 (A06) 108270563 2.05
LDB_25_1835041 25 (D12) 1835041 1.86 0.18
LDB_2_4064617 2 (A02) 4064617 1.76 0.29
LDB_18_52473670 18 (D05) 52473670 1.71 0.32
LDB_13_62696637 13 (A13) 62696637 1.62 0.30
LDB_8_8677270 8 (A08) 8677270 1.56
LDB_24_59986795 24 (D11) 59986795 1.48
LDB_17_1478345 17 (D04) 1478345 1.39 0.42
LDB_5_23314512 5 (A05) 23314512 1.34
LDB_15_17739938 15 (D02) 17739938 1.34
LDB_17_53762505_53762526 17 (D04) 53762505 1.33 AY-14 (4.68)

Fig. 1

Genetic analysis of boll opening rate in upland cotton by MLM-GWAS and RTM-GWAS procedure A: Manhattan diagram of the RTM-GWAS; B: Manhattan diagram of the MLM-GWAS; C: QTL-allele effect distribution of the tested population; D: QTL-allele matrix of boll opening rate in the tested population. The numbers 1-6 in the Fig.A and Fig.C represent the six stable SNPLDB loci. In the Fig. D, the warm color system represents the positive effect allele, the cool color system represents the negative effect allele, and the color depth represents the size of the effect value"

Fig. 2

Comparison of boll opening rate with different allelic variation at six stable and significant association SNPLDB loci BOR: Boll opening rate. Lowercase letters indicate significant difference at P<0.05 according to LSD multiple-comparison. The same as below"

Fig. 3

Frequency distribution of superior alleles of four stable association loci A: Comparison of the frequency of superior alleles of four stable four SNPLDB loci between extreme materials with high and low BOR; B: Comparison of boll opening rate of four varieties among different geographic regions. Capital letters indicate significant difference at P<0.01 according to LSD multiple-comparison; C-F: Comparison of superior allelic variation frequencies of four stable SNPLDB loci among four regional varieties and lines. YRR: Yellow River Region; YZRR: Yangtze River Region; NSER: Northern Super Early-maturing Region; NIR: Northwest Inland Region"

Fig. 4

Prediction of candidate genes related to the BOR of upland cotton A and B: Gene expression patterns of upland cotton RNA-Seq data of NAU (A) and CRI (B) in different tissues; C: Venn diagrams of common genes between two RNA sequence data (NAU and CRI); D: Heat map of expression patterns of 23 candidate genes related to the BOR of upland cotton. Red indicates high expression of the gene at a certain location or period, while green and black indicate low expression of the gene at a certain location or period"

Table 4

Candidate genes related to BOR in upland cotton"

组别
Group
候选基因
Candidate gene
基因名称
Gene name
基因功能注释
Gene function annotation
a类
Group a
GH_D03G1078 SWEET10 双向糖转运体SWEET10 Bidirectional sugar transporter SWEET10
GH_D03G1058 slc25a24 钙结合线粒体载体蛋白 SCAMC-1 Calcium-binding mitochondrial carrier protein SCaMC-1
GH_D03G1629 IRL5 植物细胞内Ras-group相关LRR蛋白5 Plant intracellular Ras-group-related LRR protein 5
GH_D03G1059 NA NA
GH_D03G1067 Bicc1 蛋白双尾C同源物1 Protein bicaudal C homolog 1
GH_D03G1594 RABD2C Ras-related蛋白质RABD2c Ras-related protein RABD2c
GH_D03G1618 NA 假定的转化酶抑制剂 Putative invertase inhibitor
GH_A04G1255 RRP6L3 蛋白质RRP6-like 3 Protein RRP6-like 3
GH_D03G1643 ABCB2 ABC转运体B家族成员2 ABC transporter B family member 2
b类
Group b
GH_D03G1586 HOS1 E3泛素蛋白连接酶HOS1 E3 ubiquitin-protein ligase HOS1
GH_D03G1616 BRG3 可能与BOI相关的E3泛素蛋白连接酶3 Probable BOI-related E3 ubiquitin-protein ligase 3
GH_A04G1248 P3H1 脯氨酰3-羟化酶 1 Prolyl 3-hydroxylase 1
GH_D03G1644 HSF8 热休克因子蛋白HSF8 Heat shock factor protein HSF8
c类
Group c
GH_D03G1617 UPF1 无意义转录本1同源物的调节器 Regulator of nonsense transcripts 1 homolog
GH_D03G1083 NA NA
GH_D03G1610 caskin2 Caskin-2
GH_A04G1266 SPL6 Squamosa启动子结合样蛋白6 Squamosa promoter-binding-like protein 6
GH_D03G1087 PAP27 可能失活的紫色酸性磷酸酶27 Probable inactive purple acid phosphatase 27
GH_D03G1608 At2g01680 含锚蛋白重复蛋白At2g01680 Ankyrin repeat-containing protein At2g01680
GH_D03G1063 GLO1 过氧化物酶体(S)-2-羟基氧化酶 Peroxisomal (S)-2-hydroxy-acid oxidase GLO1
GH_D03G1085 IRX15 蛋白质不规则木质部15 Protein IRREGULAR XYLEM 15
GH_A05G3660 At3g52300 ATP合酶亚基d,线粒体 ATP synthase subunit d, mitochondrial
GH_A05G3680 NA NA
[1] 喻树迅, 黄祯茂. 短季棉品种早熟性构成因素的遗传分析. 中国农业科学, 1990, 23(6):48-54.
YU S X, HUANG Z M. Genetic analysis of precocious factors of cotton varieties in the short season. Scientia Agricultura Sinica, 1990, 23(6):48-54. (in Chinese)
[2] 宋美珍, 喻树迅, 范术丽, 原日红, 黄祯茂. 短季棉主要农艺性状的遗传分析. 棉花学报, 2005, 17(2) : 94-98.
SONG M Z, YU S X, FAN S L, YUAN R H, HUANG Z M. Genetic analysis of main agronomic traits in short season upland cotton. Cotton Science, 2005, 17(2):94-98. (in Chinese)
[3] 李轲, 李志博, 魏亦农. 棉花早熟性状的相关性分析和QTL定位. 新疆农业科学, 2010, 47(1):78-81.
LI K, LI Z B, WEI Y N. Correlation of early maturing traits and QTL mapping in cotton. Xinjiang Agricultural Sciences, 2010, 47(1):78-81. (in Chinese)
[4] 高玉虹, 姜艳丽, 李朋波, 宋建中, 皇甫张龙, 胡晓丽, 黄晋玲, 石跃进. 棉花早熟性QTL定位研究进展. 山西农业科学, 2012, 40(1):84-86.
GAO Y H, JIANG Y L, LI P B, SONG J Z, HUANGFU Z L, HU X L, HUANG J L, SHI Y J. Research progress in QTL mapping of early maturing traits in cotton. Journal of Shanxi Agricultural Sciences, 2012, 40(1):84-86. (in Chinese)
[5] 赵树琪, 庞朝友, 魏恒玲, 王寒涛, 李黎贝, 宿俊吉, 范术丽, 喻树迅. 陆地棉早熟性状多世代联合遗传分析. 棉花学报, 2017, 29(2):119-127.
ZHAO S Q, PANG C Y, WEI H L, WANG H T, LI L B, SU J J, FAN S L, YU S X. Genetic inheritance of earliness traits in upland cotton (Gossypium hirsutum L.) inferred by joint analysis of multiple generations. Cotton Science, 2017, 29(2):119-127. (in Chinese)
[6] 喻树迅, 王寒涛, 魏恒玲, 宿俊吉. 棉花早熟性研究进展及其应用. 棉花学报, 2017, 29(S1):1-10.
YU S X, WANG H T, WEI H L, SU J J. Research progress and application of early maturity in upland cotton. Cotton Science, 2017, 29(S1):1-10. (in Chinese)
[7] 高玉千, 聂以春, 张献龙. 棉花抗黄萎病基因的QTL定位. 棉花学报, 2003, 15(2):73-78.
GAO Y Q, NIE Y C, ZHANG X L. QTL mapping of genes resistant to verticillium wilt in cotton. Cotton Science, 2003, 15(2):73-78. (in Chinese)
[8] 范术丽, 喻树迅, 宋美珍, 原日红. 短季棉早熟性的分子标记及QTL定位. 棉花学报, 2006, 18(3):135-139.
FAN S L, YU S X, SONG M Z, YUAN R H. Construction of molecular linkage map and QTL mapping for earliness in short season cotton. Cotton Science, 2006, 18(3):135-139. (in Chinese)
[9] 张西英, 李金荣, 朱永军, 韩璐, 张薇. 海岛棉(Gossypium barbadense L.)产量和早熟性状QTL定位. 植物遗传资源学报, 2012, 13(4):614-621.
ZHANG X Y, LI J R, ZHU Y J, HAN L, ZHANG W. QTL Mapping of yield and earliness-related traits in seaisland cotton (Gossypium barbadense L.). Journal of Plant Genetic Resources, 2012, 13(4):614-621. (in Chinese)
[10] LI C Q, WANG X Y, DONG N, ZHAO H H, XIA Z, WANG R, RICHARD L C, WANG Q L. QTL analysis for early-maturing traits in cotton using two upland cotton (Gossypium hirsutum L.) crosses. Breeding Science, 2013, 63(2):154-163.
doi: 10.1270/jsbbs.63.154
[11] JIA X Y, PANG C Y, WEI H L, WANG H T, MA Q F, YANG J L, CHENG S S, SU J J, FAN S L, SONG M Z, WUSIMAN N, YU S X. High-density linkage map construction and QTL analysis for earliness-related traits in Gossypium hirsutum L. BMC Genomics, 2016, 17(1):909.
doi: 10.1186/s12864-016-3269-y
[12] 唐富福, 徐非非, 包劲松. 全基因组关联分析在水稻遗传育种中的应用. 核农学报, 2013, 27(5):598-606.
TANG F F, XU F F, BAO J S. Application of genome-wide association studies in rice genetics and breeding. Journal of Nuclear Agricultural Sciences, 2013, 27(5):598-606. (in Chinese)
[13] ZHANG F, HU Z Q, WU Z C, LU J L, SHI Y Y, XU J L, WANG X Y, WANG J P, ZHANG F, WANG M M, SHI X R, CUI Y R, CASIANA V C, ZHUO D L, HU D D, LI M, WANG W S, ZHAO X Q, ZHENG T Q, FU B Y, JAUHAR A, ZHOU Y L, LI Z K. Reciprocal adaptation of rice and Xanthomonas oryzae pv. oryzae: Cross-species 2D GWAS reveals the underlying genetics. The Plant Cell, 2021, 33(8):2538-2561. doi: 10.1093/PLCELL/KOAB146.
doi: 10.1093/plcell/koab146
[14] 刘坤, 张雪海, 孙高阳, 闫鹏帅, 郭海平, 陈思远, 薛亚东, 郭战勇, 谢惠玲, 汤继华, 李卫华. 玉米株型相关性状的全基因组关联分析. 中国农业科学, 2018, 51(5):821-834.
LIU K, ZHANG X H, SUN G Y, YAN P S, GUO H P, CHEN S Y, XUE Y D, GUO Z Y, XIE H L, TANG J H, LI W H. Genome-wide association studies of plant type traits in maize. Scientia Agricultura Sinica, 2018, 51(5):821-834. (in Chinese)
[15] 张蕊, 邓文亚, 杨柳, 王亚萍, 肖芳枝, 禾健, 卢坤. 盐胁迫下甘蓝型油菜发芽期下胚轴和根长的全基因组关联分析. 中国农业科学, 2017, 50(1):15-35.
ZHANG R, DENG W Y, YANG L, WANG Y P, XIAO F Z, HE J, LU K. Genome-wide association study of root length and hypocotyl length at germination stage under saline conditions in Brassica napus. Scientia Agricultura Sinica, 2017, 50(1):15-35. (in Chinese)
[16] LIN F, SHABIR H W, PAUL J C, WEN Z X, LI W L, ZHANG N, AUSTIN G M, BI Y D, TAN R J, ZHANG S C, GU C H, MARTIN I C, WANG D C. QTL mapping and GWAS for identification of loci conferring partial resistance to pythium sylvaticum in soybean (Glycine max (L.) Merr). Molecular Breeding: New Strategies in Plant Improvement, 2020, 40(6):19-27.
[17] HUANG C, NIE X H, SHEN C, YOU C Y, LI W, ZHAO W X, LIN Z X. Population structure and genetic basis of the agronomic traits of upland cotton in China revealed by a genome-wide association study using high-density SNPs. Plant Biotechnology Journal, 2017, 15(11):1374-1386.
doi: 10.1111/pbi.2017.15.issue-11
[18] LI L B, ZHANG C, HUANG J Q, LIU Q B, WEI H L, WANG H T, LIU G Y, GU L J, YU S X. Genomic analyses reveal the genetic basis of early maturity and identification of loci and candidate genes in upland cotton (Gossypium hirsutum L.). Plant Biotechnology Journal, 2021, 19(1):109-123.
doi: 10.1111/pbi.v19.1
[19] SUN Z W, WANG X F, LIU Z W, GU Q S, ZHANG Y, LI Z K, KE H F, YANG J, WU J H, WU L Q, ZHANG GY, MA Z Y. Genome-wide association study discovered genetic variation and candidate genes of fiber quality traits in Gossypium hirsutum L. Plant Biotechnology Journal, 2017, 15(8):982-996.
doi: 10.1111/pbi.2017.15.issue-8
[20] SUN Z W, WANG X F, LIU Z W, GU Q S, ZHANG Y, LI Z K, KE H F, YANG J, WU J H, WU L Q, ZHANG G Y, ZHANG C Y, MA Z Y. A genome-wide association study uncovers novel genomic regions and candidate genes of yield-related traits in upland cotton. Theoretical and Applied Genetics, 2018, 131(11):2413-2425.
doi: 10.1007/s00122-018-3162-y
[21] SHEN C, WANG N, HUANG C, WANG M J, ZHANG X L, LIN Z X. Population genomics reveals a fine-scale recombination landscape for genetic improvement of cotton. The Plant Journal, 2019, 99(3):494-505.
doi: 10.1111/tpj.v99.3
[22] MA Z Y, HE S P, WANG X F, SUN J L, ZHANG Y, ZHANG G Y, WU L Q, LI Z K, LIU Z H, SUN G F, YAN Y Y, JIA Y H, YANG J, PAN Z E, GU Q S, LI X Y, SUN Z W, DAI P H, LIU Z W, GONG W F, WU J H, WANG M, LIU H W, FENG K Y, KE H F, WANG J D, LAN H Y, WANG G N, PENG J, WANG N, WANG L R, PANG B Y, PENG Z, LI R Q, DU X M. Resequencing a core collection of upland cotton identifies genomic variation and loci influencing fiber quality and yield. Nature Genetics, 2018, 50(6):803-813.
doi: 10.1038/s41588-018-0119-7
[23] SU J J, WANG C X, YANG D L, SHI C H, ZHANG A, MA Q, LIU J J, ZHANG X L, HUANG L, MA X F. Decryption of favorable haplotypes and potential candidate genes for five fiber quality properties using a relatively novel genome-wide association study procedure in upland cotton. Industrial Crops and Products, 2020, 158:113004.
doi: 10.1016/j.indcrop.2020.113004
[24] SU J J, PANG C Y, WEI H L, LI L B, LIANG B, WANG C X, SONG M Z, WANG H T, ZHAO S Q, JIA X Y, MAO G Z, HUANG L, GENG D D, WANG C S, YU S X. Identification of favorable SNP alleles and candidate genes for traits related to early maturity via GWAS in upland cotton. BMC Genomics, 2016, 17:687.
doi: 10.1186/s12864-016-2875-z
[25] LI C Q, WANG Y Y, AI N J, LI Y, SONG J F. A genome-wide association study of early-maturation traits in upland cotton based on the cottonSNP8oK array. Journal of Integrative Plant Biology, 2018, 60(10):970-985.
doi: 10.1111/jipb.v60.10
[26] 王香茹, 张恒恒, 胡莉婷, 庞念厂, 董强, 贵会平, 宋美珍, 张西岭. 新疆棉区棉花脱叶催熟剂的筛选研究. 中国棉花, 2018, 45(2):8-14.
WANG X R, ZHANG H H, HU L T, PANG N C, DONG Q, GUI H P, SONG M Z, ZHANG X L. Screening for suitable cotton harvest aids in Xinjiang. China Cotton, 2018, 45(2):8-14. (in Chinese)
[27] 高丽丽. 脱叶剂喷施时间对棉花生理调节效应的研究. 乌鲁木齐: 新疆农业大学, 2016.
GAO L L. Study of defoliants spraying time on cotton physiological mechanism. Urumqi: Xinjiang Agricultural University, 2016. (in Chinese)
[28] 李俊文, 贾菲, 孙福鼎, 刘爱英, 石玉真, 龚举武, 商海红, 王涛, 巩万奎, 贾新合, 张建宏, 袁有禄, 华金平. 陆地棉吐絮铃数及吐絮率的QTL定位. 棉花学报, 2013, 25(6):471-477.
LI J W, JIA F, SUN F D, LIU A Y, SHI Y Z, GONG J W, SHANG H H, WANG T, GONG W K, JIA X H, ZHANG J H, YUAN Y L, HUA J P. Quantitative trait locus mapping of number and percentage of cracked and open bolls in Gossypium hirsutum L. Cotton Science, 2013, 25(6):471-477. (in Chinese)
[29] HE J B, MENG S, ZHAO T J, XING G N, YANG S P, LI Y, GUAN R Z, LU J J, WANG Y F, XIA Q J, YANG B, GAI J Y. An innovative procedure of genome-wide association analysis fits studies on germplasm population and plant breeding. Theoretical and Applied Genetics, 2017, 130(11):2327-2343.
doi: 10.1007/s00122-017-2962-9
[30] 盖钧镒, 贺建波. 限制性两阶段多位点全基因组关联分析法(RTM-GWAS)的特点、常见提问与应用前景. 中国农业科学, 2020, 53(9):1699-1703.
GAI J Y, HE J B. Major characteristics, often-raised queries and potential usefulness of the restricted two-stage multi-locus genome- wide association analysis. Scientia Agricultura Sinica, 2020, 53(9):1699-1703. (in Chinese)
[31] 潘丽媛, 贺建波, 赵晋铭, 王吴彬, 邢光南, 喻德跃, 张小燕, 李春燕, 陈受宜, 盖钧镒. RTM-GWAS方法应用于大豆RIL群体百粒重QTL检测的功效. 中国农业科学, 2020, 53(9):1730-1742.
PAN L Y, HE J B, ZHAO J M, WANG W B, XING G N, YU D Y, ZHANG X Y, LI C Y, CHEN S Y, GAI J Y. Detection power of RTM-GWAS applied to 100-seed weight QTL identification in a recombinant inbred lines population of soybean. Scientia Agricultura Sinica, 2020, 53(9):1730-1742. (in Chinese)
[32] ZHANG Y, HE J, WANG Y, XING G, ZHAO J, LI Y, YANG S, PALMER R G, ZHAO T, GAI J. Establishment of a 100-seed weight quantitative trait locus-allele matrix of the germplasm population for optimal recombination design in soybean breeding programmes. Journal of Experimental Botany, 2015, 66(20):6311-6325.
doi: 10.1093/jxb/erv342
[33] ZHANG Y H, HE J B, WANG H W, MENG S, XING G N, LI Y, YANG S P, ZHAO J M, ZHAO T J, GAI J Y. Detecting the QTL-allele system of seed oil traits using multi-locus genome-wide association analysis for population characterization and optimal cross prediction in soybean. Frontiers in Plant Science, 2018, 9:1793.
doi: 10.3389/fpls.2018.01793
[34] 李曙光, 曹永策, 贺建波, 王吴彬, 邢光南, 杨加银, 赵团结, 盖钧镒. 大豆巢式关联作图群体蛋白质含量的遗传解析. 中国农业科学, 2020, 53(9):1743-1755.
LI S G, CAO Y C, HE J B, WANG W B, XING G N, YANG J Y, ZHAO T J, GAI J Y. Genetic dissection of protein content in a nested association mapping population of soybean. Scientia Agricultura Sinica, 2020, 53(9):1743-1755. (in Chinese)
[35] 刘再东, 孟珊, 贺建波, 邢光南, 王吴彬, 赵团结, 盖钧镒. 大豆重组自交系群体异黄酮含量QTL连锁定位与关联定位的比较研究. 中国农业科学, 2020, 53(9):1756-1772.
LIU Z D, MENG S, HE J B, XING G N, WANG W B, ZHAO T J, GAI J Y. A comparative study on linkage and association QTL mapping for seed isoflavone contents in a recombinant inbred line population of soybean. Scientia Agricultura Sinica, 2020, 53(9):1756-1772. (in Chinese)
[36] SU J J, WANG C X, MA Q, ZHANG A, SHI C H, LIU J J, ZHANG X L, YANG D L, MA X F. An RTM-GWAS procedure reveals the QTL alleles and candidate genes for three yield-related traits in upland cotton. BMC Plant Biology, 2020, 20(1):416-416.
doi: 10.1186/s12870-020-02613-y
[37] HU Y, CHEN J D, FANG L, ZHANG Z Y, MA W, NIU Y C, JU L Z, DENG J Q, ZHAO T, LIAN J M, KOBI B, FANG D, LIU X, RUAN Y L, RAHMAN M, HAN J L, WANG K, WANG Q, WU H T, MEI G F, ZANG Y H, HAN Z G, XU C Y, SHEN W J, YANG D F, SI Z F, DAI F, ZOU L F, HUANG F, BAI Y L, ZHANG Y G, AVITAL B, HILLA B H, ZHU X F, ZHOU B L, GUAN X Y, ZHU S J, CHEN X Y, ZHANG T Z. Gossypium barbadense and Gossypium hirsutum genomes provide insights into the origin and evolution of allotetraploid cotton. Nature Genetics, 2019, 51(4):739-748.
doi: 10.1038/s41588-019-0371-5
[38] 郝晓帅, 傅蒙蒙, 刘再东, 贺建波, 王燕平, 任海祥, 王德亮, 杨兴勇, 程延喜, 杜维广, 盖钧镒. 东北大豆种质群体百粒重QTL-等位变异的全基因组解析. 中国农业科学, 2020, 53(9):1717-1729.
HAO X S, FU M M, LIU Z D, HE J B, WANG Y P, REN H X, WANG D L, YANG X Y, CHENG Y X, DU W G, GAI J Y. Genome-Wide QTL-allele dissection of 100-seed weight in the northeast China soybean germplasm population. Scientia Agricultura Sinica, 2020, 53(9):1717-1729. (in Chinese)
[39] 马树庆, 杨菲芸 我国霜期、霜冻时空特征及其对气候变暖的响应. 气象灾害防御, 2015, 22(2):1-14+36.
MA S Q, YANG F Y. Temporal and spatial characteristics of frost period and frost and its response to climate warming in China. Meteorological Disaster Prevention, 2015, 22(2):1-14+36.(in Chinese)
[40] 王林, 张强, 马江锋, 朱玉永, 田英, 李红, 毕显杰, 宋敏, 王海标, 雷天翔, 李召虎, 田晓莉, 杜明伟, 张立祯, 赵冰梅. 新疆棉区植保无人机喷施棉花脱叶催熟剂效果研究. 棉花学报, 2021, 33(3):200-208.
WANG L, ZHANG Q, MA J F, ZHU Y Y, TIAN Y, LI H, BI X J, SONG M, WANG H B, LEI T X, LI Z H, TIAN X L, DU M W, ZHANG L Z, ZHAO B M. Study on the effect of spraying cotton defoliant by plant protection UAVs in Xinjiang cotton area. Cotton Science, 2021, 33(3):200-208. (in Chinese)
[41] 艾尼江, 刘任重, 赵图强, 秦江鸿, 张天真. 陆地棉早熟基因来源的遗传分析. 作物学报, 2013, 39(9):1548-1561.
doi: 10.3724/SP.J.1006.2013.01548
AI N J, LIU R Z, ZHAO T Q, QIN J H, ZHANG T Z. Analysis of early maturity gene sources in upland cotton using molecular markers. Acta Agronomica Sinica, 2013, 39(9):1548-1561. (in Chinese)
doi: 10.3724/SP.J.1006.2013.01548
[42] SU J J, FAN S L, LI L B, WEI H L, WANG C X, WANG H T, SONG M Z, ZHANG C, GU L J, ZHAO S Q, MAO G Z, WANG C S, PANG C Y, YU S X. Detection of favorable QTL alleles and candidate genes for lint percentage by GWAS in Chinese upland cotton. Frontiers in Plant Science, 2016, 7:1576.
[43] 黄璐瑶. 水稻乙醇酸氧化酶GLO1,GLO4生理功能分析[D]. 长沙: 湖南农业大学, 2019.
HUANG L Y. The analysis of the physiological functions of glycolate oxidase GLO1 and GLO4 in rice[D]. Changsha: Hunan Agricultural University, 2019. (in Chinese)
[44] PEI Z M, MURATA Y, BENNING G, THOMINE S, KLÜSENER B, ALLEN G J, GRILL E, SCHROEDER J I. Calcium channels activated by hydrogen peroxide mediate abscisic acid signalling in guard cells. Nature. 2000, 406(6797):731-4. doi: 10.1038/35021067.
doi: 10.1038/35021067
[45] 贺建波, 刘方东, 邢光南, 王吴彬, 赵团结, 管荣展, 盖钧镒. 限制性两阶段多位点全基因组关联分析方法的特点与计算程序. 作物学报, 2018, 44(9):1274-1289.
doi: 10.3724/SP.J.1006.2018.01274
HE J B, LIU D F, XING G N, WANG W B, ZHAO T J, GUAN R Z, GAI J Y. Characterization and analytical programs of the restricted two-stage multilocus genome-wide association analysis. Acta Agronomica Sinica, 2018, 44(9):1274-1289. (in Chinese)
doi: 10.3724/SP.J.1006.2018.01274
[46] 贺建波, 刘方东, 王吴彬, 邢光南, 管荣展, 盖钧镒. 限制性两阶段多位点全基因组关联分析法在遗传育种中的应用. 中国农业科学, 2020, 53(9):1704-1716.
HE J B, LIU F D, WANG W B, XING G N, GUAN R Z, GAI J Y. Restricted two-stage multi-locus genome-wide association analysis and its applications to genetic and breeding studies. Scientia Agricultura Sinica, 2020, 53(9):1704-1716. (in Chinese)
[1] WANG CaiXiang,YUAN WenMin,LIU JuanJuan,XIE XiaoYu,MA Qi,JU JiSheng,CHEN Da,WANG Ning,FENG KeYun,SU JunJi. Comprehensive Evaluation and Breeding Evolution of Early Maturing Upland Cotton Varieties in the Northwest Inland of China [J]. Scientia Agricultura Sinica, 2023, 56(1): 1-16.
[2] HU Sheng,LI YangYang,TANG ZhangLin,LI JiaNa,QU CunMin,LIU LieZhao. Genome-Wide Association Analysis of the Changes in Oil Content and Protein Content Under Drought Stress in Brassica napus L. [J]. Scientia Agricultura Sinica, 2023, 56(1): 17-30.
[3] LI Heng,ZI XiangDong,WANG Hui,XIONG Yan,LÜ MingJie,LIU Yu,JIANG XuDong. Screening of Key Regulatory Genes for Litter Size Trait Based on Whole Genome Re-Sequencing in Goats (Capra hircus) [J]. Scientia Agricultura Sinica, 2022, 55(23): 4753-4768.
[4] WANG Juan, MA XiaoMei, ZHOU XiaoFeng, WANG Xin, TIAN Qin, LI ChengQi, DONG ChengGuang. Genome-Wide Association Study of Yield Component Traits in Upland Cotton (Gossypium hirsutum L.) [J]. Scientia Agricultura Sinica, 2022, 55(12): 2265-2277.
[5] QIN HongDe, FENG ChangHui, ZHANG YouChang, BIE Shu, ZHANG JiaoHai, XIA SongBo, WANG XiaoGang, WANG QiongShan, LAN JiaYang, CHEN QuanQiu, JIAO ChunHai. F1 Performance Prediction of Upland Cotton Based on Partial NCII Design [J]. Scientia Agricultura Sinica, 2021, 54(8): 1590-1598.
[6] ZHANG PengFei,SHI LiangYu,LIU JiaXin,LI Yang,WU ChengBin,WANG LiXian,ZHAO FuPing. Advance in Genome-Wide Scan of Runs of Homozygosity in Domestic Animals [J]. Scientia Agricultura Sinica, 2021, 54(24): 5316-5326.
[7] WANG Na,ZHAO ZiBo,GAO Qiong,HE ShouPu,MA ChenHui,PENG Zhen,DU XiongMing. Cloning and Functional Analysis of Salt Stress Response Gene GhPEAMT1 in Upland Cotton [J]. Scientia Agricultura Sinica, 2021, 54(2): 248-260.
[8] YAN YongLiang,SHI XiaoLei,ZHANG JinBo,GENG HongWei,XIAO Jing,LU ZiFeng,NI ZhongFu,CONG Hua. Genome-Wide Association Study of Grain Quality Related Characteristics of Spring Wheat [J]. Scientia Agricultura Sinica, 2021, 54(19): 4033-4047.
[9] WANG JiQing,REN Yi,SHI XiaoLei,WANG LiLi,ZHANG XinZhong,SULITAN· GuZhaLiAYi,XIE Lei,GENG HongWei. Genome-Wide Association Analysis of Superoxide Dismutase (SOD) Activity in Wheat Grain [J]. Scientia Agricultura Sinica, 2021, 54(11): 2249-2260.
[10] JunYi GAI,JianBo HE. Major Characteristics, Often-Raised Queries and Potential Usefulness of the Restricted Two-Stage Multi-Locus Genome-Wide Association Analysis [J]. Scientia Agricultura Sinica, 2020, 53(9): 1699-1703.
[11] XiaoShuai HAO,MengMeng FU,ZaiDong LIU,JianBo HE,YanPing WANG,HaiXiang REN,DeLiang WANG,XingYong YANG,YanXi CHENG,WeiGuang DU,JunYi GAI. Genome-Wide QTL-Allele Dissection of 100-Seed Weight in the Northeast China Soybean Germplasm Population [J]. Scientia Agricultura Sinica, 2020, 53(9): 1717-1729.
[12] WANG LiuYan,WANG RuiLi,YE Sang,GAO HuanHuan,LEI Wei,CHEN LiuYi,WU JiaYi,MENG LiJiao,YUAN Fang,TANG ZhangLin,LI JiaNa,ZHOU QingYuan,CUI Cui. QTL Mapping and Candidate Genes Screening of Related Traits in Brassica napus L. During the Germination Under Tribenuron-Methyl Stress [J]. Scientia Agricultura Sinica, 2020, 53(8): 1510-1523.
[13] WEI Xin, WANG HanTao, WEI HengLing, FU XiaoKang, MA Liang, LU JianHua, WANG XingFen, YU ShuXun. Cloning and Drought Resistance Analysis of GhWRKY33 in Upland Cotton [J]. Scientia Agricultura Sinica, 2020, 53(22): 4537-4549.
[14] QU YuJie, SUN JunLing, GENG XiaoLi, WANG Xiao, Zareen Sarfraz, JIA YinHua, PAN ZhaoE, HE ShouPu, GONG WenFang, WANG LiRu, PANG BaoYin, DU XiongMing. Correlation Between Genetic Distance of Parents and Heterosis in Upland Cotton [J]. Scientia Agricultura Sinica, 2019, 52(9): 1488-1501.
[15] XU YunMei, LI YuMei, JIA YuXin, ZHANG ChunZhi, LI CanHui, HUANG SanWen, ZHU GuangTao. Fine Mapping and Candidate Genes Analysis for Regulatory Gene of Anthocyanin Synthesis in Red-Colored Tuber Flesh [J]. Scientia Agricultura Sinica, 2019, 52(15): 2678-2685.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!