小麦苗期生物量及氮效率相关性状的全基因组关联分析

doi:10.3864/j.issn.0578-1752.2021.21.001

Abstract

Abstract:

【Objective】 To identify and locate the molecular markers which were stable and significantly correlated to the traits of biomass and N efficiency under different N nutrition levels will help to provide reference for cloning and characterization of the related genes.【Method】A group of 134 wheat varieties (or lines) were used in a two-years (2013 and 2014) hydroponic experiments, in which three treatments applying normal level N, low level N and high level N were set up. Fourteen traits related to biomass and N efficiency were measured, as the respective average values of each treatment in one year and two years. Genome-wide association analysis using 90K SNP molecular markers was carried out for the tested traits by MLM+K+Q mixed linear model. 【Result】 Compared with normal nitrogen treatments, roots, shoots, and plant nitrogen content and nitrogen accumulation were significantly reduced in low nitrogen treatments, while root biomass and root and plant nitrogen efficiency were significantly increased. In high nitrogen treatments, almost all traits are significantly increased. The heritability of all the tested traits were above 40%. According to genome-wide association analysis on the 9 329 SNPs, a total of 838 molecular marker sites were identified associating with 14 traits significantly (P≤0.001). These markers located on 21 chromosomes, among which 435 (51.91%) molecular marker sites were detected in only one environment, 403 and 8 environment stable sites were identified in at least two or three environments, two environmental stable SNP marker sites were identified in at least four environments. The two stable markers (Kukri_c65481_121 and tplb0025f09_1052) were significantly related to total nitrogen use efficiency of plant (TNUE) and root nitrogen use efficiency (RNUE), respectively. Five multi-trait co-location SNP marker sites which simultaneously associated with at least six traits were located on chromosomes 1A, 1B(2), and 2A(2). Furtherly, candidate gene prediction was conducted in the 214 kb genomic region of 5 SNP sites co-located with 6 traits (biomass and N efficiency traits) and 2 SNP sites associated with multiple environments (4 environments). According to the genome annotation and LD attenuation level, a total of 84 candidate genes were determined. Gene function annotations of these genes were performed using the coding protein types of known cloned nitrogen efficiency genes, candidate gene function annotation information and the use of plant comparative genomics resource library protein sequence homology analysis, 3 candidate genes were initially determined. 【Conclusion】 Different N treatments significantly affected the phenotypic traits of biomass, N efficiency and the expression of related QTLs at seedling stage of wheat. Most SNPs were detected in only one N environment, but there were some locations with relatively strong environmental stability. There was a significant correlation between biomass and N efficiency related traits, and they might be partly controlled by the same QTL/gene. The functions of related candidate genes related to N efficiency and biomass of wheat selected in this paper needed to be further verified.

Key words: wheat, GWAS, biomass, nitrogen efficiency

ZHANG PengXia,ZHOU XiuWen,LIANG Xue,GUO Ying,ZHAO Yan,LI SiShen,KONG FanMei. Genome-Wide Association Analysis for Yield and Nitrogen Efficiency Related Traits of Wheat at Seedling Stage[J].Scientia Agricultura Sinica, 2021, 54(21): 4487-4499.

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Figures/Tables 8

Table 1

Table 2

Statistical parameters and heritability between traits related to biomass and nitrogen efficiency at seedling"

性状 Trait	处理 Treatment	均值 Average	变异系数 CV (%)	遗传力 hB² (%)	性状 Trait	处理 Treatment	均值 Average	变异系数 CV (%)	遗传力 hB² (%)
地上部干重 SDW (mg)	T1E1	107.95cd	21.40	94.95	地上部氮累积量 SNA (mg/plant)	T1E1	5.00d	12.77	93.53
	T2E1	104.08d	23.99			T2E1	5.98c	6.93
	T3E1	124.71b	23.51			T3E1	7.64b	10.36
	T1E2	112.33c	19.16			T1E2	4.32e	8.64
	T2E2	129.49b	22.28			T2E2	7.79b	10.23
	T3E2	148.77a	22.62			T3E2	9.68a	4.76
根系干重 RDW (mg)	T1E1	27.80c	35.87	92.76	根系氮累积量 RNA(mg/plant)	T1E1	0.99c	22.54	93.49
	T2E1	19.50e	21.49			T2E1	0.77d	24.18
	T3E1	22.40d	22.99			T3E1	0.98c	24.21
	T1E2	50.10a	27.03			T1E2	1.14b	19.78
	T2E2	27.60c	22.30			T2E2	1.00c	23.44
	T3E2	32.20b	22.89			T3E2	1.27a	23.85
植株总干重 TDW (mg)	T1E1	136.06d	21.00	95.37	植株总氮累积量 TNA (mg/plant)	T1E1	5.97d	26.93	94.31
	T2E1	123.08e	21.99			T2E1	6.75c	24.20
	T3E1	147.10c	22.81			T3E1	8.62b	25.48
	T1E2	162.52b	20.53			T1E2	5.46d	21.53
	T2E2	157.18b	21.77			T2E2	8.79b	25.94
	T3E2	180.66a	22.03			T3E2	10.95a	23.66
生物量根冠比 RSDW	T1E1	0.27b	32.68	89.72	氮累积量根冠比 RSNA	T1E1	0.20b	37.13	84.25
	T2E1	0.19d	16.80			T2E1	0.13c	23.66
	T3E1	0.18d	17.48			T3E1	0.13c	26.83
	T1E2	0.44a	16.12			T1E2	0.27a	28.16
	T2E2	0.22c	13.16			T2E2	0.13c	26.20
	T3E2	0.22c	14.00			T3E2	0.13c	27.63
地上部氮含量 SNC (g·kg^-1)	T1E1	46.31d	6.42	86.39	地上部氮利用效率 SNUE (g·g^-1kg^-1)	T1E1	2.35bc	26.93	94.79
	T2E1	57.55c	3.86			T2E1	1.82e	24.20
	T3E1	61.21b	3.85			T3E1	2.04d	25.48
	T1E2	38.66e	10.41			T1E2	3.00a	21.53
	T2E2	59.79b	4.75			T2E2	2.18cd	25.94
	T3E2	64.96a	4.47			T3E2	2.29b	23.66
根系氮含量 RNC (g·kg^-1)	T1E1	35.32c	8.21	85.71	根系氮利用效率 RNUE (g·g^-1kg^-1)	T1E1	0.80b	27.23	89.44
	T2E1	40.48b	8.09			T2E1	0.47c	22.32
	T3E1	43.74a	12.5			T3E1	0.51c	18.75
	T1E2	22.64d	7.25			T1E2	2.26a	19.18
	T2E2	35.51c	10.1			T2E2	0.78b	16.92
	T3E2	39.44b	9.37			T3E2	0.81b	17.52
植株总氮含量 TNC (g·kg^-1)	T1E1	44.07d	5.26	23.68	植株总氮利用效率 TNUE (g·g^-1kg^-1)	T1E1	3.09b	22.66	41.34
	T2E1	54.87c	6.12			T2E1	2.25e	24.62
	T3E1	58.56b	4.25			T3E1	2.51d	23.62
	T1E2	33.75e	5.10			T1E2	4.92a	22.15
	T2E2	55.50c	11.20			T2E2	2.84c	21.40
	T3E2	60.44a	5.26			T3E2	2.99b	22.11

Table 2

Fig. 1

Fig. 2

Table 3

Table 4

Fig. 3

Table 5

References 45

[1]	GUTTIERI M J, FRELS K, REGASSA T, WATERS B M, BAENZIGER P S. Variation for nitrogen use efficiency traits in current and historical great plains hard winter wheat. Euphytica, 2017, 213(4):87. doi: 10.1007/s10681-017-1869-5
[2]	GU B, JU X, CHANG S X, GE Y, CHANG J. Nitrogen use efficiencies in Chinese agricultural systems and implications for food security and environmental protection. Regional Environmental Change, 2017, 17(4):1217-1227. doi: 10.1007/s10113-016-1101-5
[3]	LIANG S, LI Y, ZHANG X, SUN Z, SUN N, DUAN Y, XU M, WU L. Response of crop yield and nitrogen use efficiency for wheat-maize cropping system to future climate change in northern China. Agricultural and Forest Meteorology, 2018, 262:310-321. doi: 10.1016/j.agrformet.2018.07.019
[4]	SCHACHTMAN D P, SHIN R. Nutrientsensing and signaling: NPKS. Annual Review Plant Biology, 2007, 58: 47/69.
[5]	DAVIDSON E. A. The contribution of manure and fertilizer nitrogen to atmospheric nitrous oxide since 1860. Nature Geoscience, 2009, 2(9):659-662. doi: 10.1038/ngeo608
[6]	PALME K, LI X, TEALE W D. Towards second green revolution: engineering nitrogen use efficiency. Genet Genomics, 2014, 41(6):315-326.
[7]	YIN L, DAI X, HE M. Delayed sowing improves nitrogen utilization efficiency in winter wheat without impacting yield. Field Crops Research, 2018, 221: 90/97.
[8]	CEOTTO E. The issues of energy and carbon cycle: New perspectives for assessing the environmental impact of animal waste utilization. Bioresour Technology, 2005, 96(2):191-196. doi: 10.1016/j.biortech.2004.05.007
[9]	HITZ K, CLARK A J, VAN SANFORD D A. Identifying nitrogen-use efficient soft red winter wheat lines in high and low nitrogen environments. Field Crops Research, 2017, 200:1-9. doi: 10.1016/j.fcr.2016.10.001
[10]	MAHJOURIMAJD S, KUCHEL H, LANGRIDGE P, OKAMOTO M. Evaluation of Australian wheat genotypes for response to variable nitrogen application. Plant and Soil, 2015, 399(1/2):247-255. doi: 10.1007/s11104-015-2694-z
[11]	WANG Y Y, SUN X Y, ZHAO Y, KONG F M, GUO Y, ZHANG G Z, PU Y Y, WU K, LI S S. Enrichment of a common wheat genetic map and QTL mapping for fatty acid content in grain. Plant Science, 2011, 181(1):65-75. doi: 10.1016/j.plantsci.2011.03.020
[12]	FRELS K, GUTTIERI M, JOYCE B, LEAVITT B, BAENZIGER P S. Evaluating canopy spectral reflectance vegetation indices to estimate nitrogen use traits in hard winter wheat. Field Crops Research, 2018, 217:82-92. doi: 10.1016/j.fcr.2017.12.004
[13]	JIN D, GAO J, JIANG P, LV X, WANG Y, ZHANG W. Nitrogen use efficiency and rice yield of different locations in Northeast China. National Academy Science Letters, 2017, 40(4):227-232. doi: 10.1007/s40009-017-0553-6
[14]	RENGEL Z, MARSCHNER P. Nutrient availability and management in the rhizosphere: Exploiting genotypic differences. New Phytology, 2005, 168(2):305-312. doi: 10.1111/nph.2005.168.issue-2
[15]	QUARRIE S A, STEED A, CALESTANI C, SEMIKHODSKII A, LEBRETON C, CHINOY C, STEELE N, PLJEVLJAKUSIC D, WATERMAN E, WEYEN J, SCHONDELMAIER J, HABASH D Z, FARMER P, SAKER L, CLARKSON D T, ABUGALIEVA A, YESSIMBEKOVA M, TURUSPEKOV Y, ABUGALIEVA S, TUBEROSA R, SANGUINETI M C, HOLLINGTON P A, ARAGUES R, ROYO A, DODIG D. A high-density genetic map of hexaploid wheat (Triticum aestivum L.) from the cross Chinese Spring× SQ1 and its use to compare QTLs for grain yield across a range of environments. Theoretical and Applied Genetics, 2005, 110(5):865-880. doi: 10.1007/s00122-004-1902-7
[16]	LÉTIZIA C K, JEAN-BAPTISTE V, DELPHINE M, VALÉRIE C, MARIE F, STÉPHANIE B, PIERRE D, BRIGITTE G, DOMENICA M, ALAIN C. Maize adaptation to temperate climate: Relationship between population structure and polymorphism in the Dwarf8 gene. Genetics, 172(4):2449-2463. doi: 10.1534/genetics.105.048603
[17]	THORNSBERRY J M, GOODMAN M M, DOEBLEY J, KRESOVICH S, NIELSEN D, BUCKLER E S. Dwarf8 polymorphisms associate with variation in flowering time. Nature Genetics, 2001, 28(3):286-289 doi: 10.1038/90135
[18]	DONG Y, LIU J, ZHANG Y, GENG H HE Z J P O, . Genome-wide association of stem water soluble carbohydrates in bread wheat. PLoS ONE, 2016, 11(11):e0164293. doi: 10.1371/journal.pone.0164293
[19]	LIU J, HE Z, RASHEED A, WEN W, YAN J, ZHANG P, WAN Y, ZHANG Y, XIE C, XIA X J B P B. Genome-wide association mapping of black point reaction in common wheat (Triticum aestivum L.). BMC Plant Biology, 2017, 17(1):220. doi: 10.1186/s12870-017-1167-3
[20]	GUO J, SHI W, ZHANG Z, CHENG J, SUN D, YU J, LI X, GUO P, HAO C J B P B. Association of yield-related traits in founder genotypes and derivatives of common wheat (Triticum aestivum L.). BMC Plant Biology, 2018, 18(1):38. doi: 10.1186/s12870-018-1234-4
[21]	RASHEED A, XIA X, OGBONNAYA F, MAHMOOD T, ZHANG Z, MUJEEB-KAZI A, HE Z J B P B. Genome-wide association for grain morphology in synthetic hexaploid wheats using digital imaging analysis. BMC Plant Biology, 2014, 14(1):128. doi: 10.1186/1471-2229-14-128
[22]	BULL P, ZHANG J, CHAO S, CHEN X, PUMPHREY M. Genetic architecture of resistance to stripe rust in a global winter wheat germplasm collection. Genetics, 2016, 6(8):2237-2253.
[23]	MACCAFERRI M, RICCI A, SALVI S, MILNER S G, JOURNAL R T J P B. A high-density, SNP-based consensus map of tetraploid wheat as a bridge to integrate durum and bread wheat genomics and breeding. Biotechnology, 2015, 13(5):648-663.
[24]	SIDDIQI M Y, GLASS A D M. Utilization index: A modified approach to the estimation and comparison of nutrient utilization efficiency in plants. Journal of Plant Nutrition, 1981, 4(3):289-302. doi: 10.1080/01904168109362919
[25]	KNAPP S J, STROUP W W, ROSS W M. Exact confidence intervals for heritability on a progeny mean basis. Theoretical and Applied Genetics, 1985, 25(1):192-204.
[26]	屈春艳. 水旱条件下小麦产量性状和抗旱性的全基因组关联分析[D]. 泰安: 山东农业大学, 2018.
	QU C Y. Genome-wide association study on yield traits and drought tolerance under irrigation and drought conditions in wheat[D]. Taian: Shandong Agricultural University, 2018. (in Chinese)
[27]	MARCO M, WALID E F, GHASEMALI N, SILVIO S, ANGELA C M, CHIARA C M, SANDRA S, ROBERTO T. Prioritizing quantitative trait loci for root system architecture in tetraploid wheat. Journal of Experimental Botany, 2016, (4):1161-1178
[28]	BISHOPP A, LYNCH J P. The hidden half of crop yields. Nature Plants, 2015, 1(8):15117. doi: 10.1038/nplants.2015.117
[29]	CHENYANG H, YUQUAN W, SHIAOMAN C, TIAN L, HONGXIA L, LANFEN W, XUEYONG Z. The iSelect 9 K SNP analysis revealed polyploidization induced revolutionary changes and intense human selection causing strong haplotype blocks in wheat. Scientific Reports, 2017, 7:41247. doi: 10.1038/srep41247
[30]	CUI F, ZHAO C, DING A, LI J, WANG L, LI X, BAO Y, LI J, WANG H. Construction of an integrative linkage map and QTL mapping of grain yield-related traits using three related wheat RIL populations. Theoretical and Applied Genetics, 2014, 127(3):659-675. doi: 10.1007/s00122-013-2249-8
[31]	FONTAINE J X, RAVEL C, PAGEAU K, HEUMEZ E, DUBOIS F, HIREL B, LE GOUIS J. A quantitative genetic study for elucidating the contribution of glutamine synthetase, glutamate dehydrogenase and other nitrogen-related physiological traits to the agronomic performance of common wheat. Theoretical and Applied Genetics, 2009, 119(4):645-662. doi: 10.1007/s00122-009-1076-4
[32]	GUO Y, KONG F M, XU Y F, ZHAO Y, LIANG X, WANG Y Y, AN D G, LI S S. QTL mapping for seedling traits in wheat grown under varying concentrations of N, P and K nutrients. Theoretical and Applied Genetics, 2012, 124(5):851-865. doi: 10.1007/s00122-011-1749-7
[33]	HABASH D Z, BERNARD S, SCHONDELMAIER J, WEYEN J, QUARRIE S A. The genetics of nitrogen use in hexaploid wheat: N utilisation, development and yield. Theoretical and Applied Genetics, 2007, 114(3):403-419. doi: 10.1007/s00122-006-0429-5
[34]	XU Y, WANG R, TONG Y, ZHAO H, XIE Q, LIU D, ZHANG A, LI B, XU H, AN D. Mapping QTLs for yield and nitrogen-related traits in wheat: Influence of nitrogen and phosphorus fertilization on QTL expression. Theoretical and Applied Genetics, 2014, 127(1):59-72. doi: 10.1007/s00122-013-2201-y
[35]	AN D, SU J, LIU Q, ZHU Y, TONG Y, LI J, JING R, LI B, LI Z. Mapping QTLs for nitrogen uptake in relation to the early growth of wheat (Triticum aestivum L.). Plant and Soil, 2006, 284(1/2):73-84. doi: 10.1007/s11104-006-0030-3
[36]	CUI F, FAN X, ZHAO C, ZHANG W, CHEN M, JI J, LI J. A novel genetic map of wheat: Utility for mapping QTL for yield under different nitrogen treatments. BMC Genetics, 2014, 15(1):57. doi: 10.1186/1471-2156-15-57
[37]	FONTAINE J X, RAVEL C, PAGEAU K, HEUMEZ E, DUBOIS F, HIREL B, GOUIS J. A quantitative genetic study for elucidating the contribution of glutamine synthetase, glutamate dehydrogenase and other nitrogen-related physiological traits to the agronomic performance of common wheat. Theoretical and Applied Genetics, 2009, 119(4):645-662. doi: 10.1007/s00122-009-1076-4
[38]	KONG F M, GUO Y, LIANG X, WU C H, WANG Y Y, ZHAO Y, LI S S. Potassium (K) effects and QTL mapping for K efficiency traits at seedling and adult stages in wheat. Plant and Soil, 2013, 373(1/2):877-892. doi: 10.1007/s11104-013-1844-4
[39]	张国华. 黄淮麦区小麦品种(系)产量性状与分子标记的关联分析[D]. 泰安: 山东农业大学, 2013.
	ZHANG G H. Association analysis of yield traits and molecular markers of wheat varieties (lines) in Huanghuai wheat region [D]. Tai'an: Shandong Agricultural University, 2013. (in Chinese)
[40]	MESSENGUY F, DUBOIS E J G. Role of MADS box proteins and their cofactors in combinatorial control of gene expression and cell development. Gene, 2003, 316(1):1-21. doi: 10.1016/S0378-1119(03)00747-9
[41]	HECK G O. AGL15, a MADS domain protein expressed in developing embryos. The Plant Cell, 1995, 7(8):1271-1282.
[42]	KUO M H, NADEAU E T, GRAYHACK E J J M, BIOLOGY C. Multiple phosphorylated forms of the Saccharomyces cerevisiae Mcm1 protein include an isoform induced in response to high salt concentrations. Molecular and Celluar Biology, 1997, 17(2):819-832.
[43]	LOZANO, PHYSIOLOGY R J P. Tomato flower abnormalities induced by low temperatures are associated with changes of expression of MADS-box genes. Plant Physiology, 1998, 117(1):91-100. doi: 10.1104/pp.117.1.91
[44]	LEI L, LI G, ZHANG H, POWERS C, FANG T, CHEN Y, WANG S, ZHU X and YAN L. Nitrogen use efficiency is regulated by interacting proteins relevant to development in wheat. Plant Biotechnology Journal, 2018, 16(6):1214-1226. doi: 10.1111/pbi.2018.16.issue-6
[45]	WANG M, ZHANG P, LIU Q, LI G, SHI W. TaANR1-TaBG1 and TaWabi5-TaNRT2s/NARs link ABA metabolism and nitrate acquisition in wheat roots. Plant Physiology, 2020, 182:1440-1453. doi: 10.1104/pp.19.01482

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大量元素 Macronutrients	浓度 Concentration (mmol·L^-1)	微量元素 Trace elements	浓度 Concentration (μmol·L^-1)
KH₂PO₄	0.2	H₃BO₃	1.0
MgSO₄·7H₂O	0.5	(NH₄)₆Mo₇O₂₄·4H₂O	0.1
KCl	1.8	CuSO₄·5H₂O	0.5
CaCl₂	1.5	ZnSO₄·7H₂O	1.0
(NH₄)₂SO₄·H₂O	1.0	MnSO₄·H₂O	1.0
Ca(NO₃)₂·4H₂O	1.0	Fe·EDTA	100.0

性状 Trait	环境 Environment	标记 Marker	染色体 Chr.	位置 Position (bp)	P		贡献率 R²(%)
性状 Trait	环境 Environment	标记 Marker	染色体 Chr.	位置 Position (bp)	最大值 Max	最小值 Min	贡献率 R²(%)
RNUE	T1E1, T3AV, T3E2	RAC875_c29540_391	1A	8290703	9.95E-04	1.39E-05	11.05—18.34
根系干重RDW	T2E1, T3AV, T3E2	BobWhite_c9881_1312	1B	10256166	3.58E-04	3.49E-04	10.09—10.13
根系氮利用效率RNUE	T2AV, T2E1, T3E1	BobWhite_c9881_1312	1B	10256166	7.45E-04	3.75E-05	9.04—13.69
地上部氮含量SNC	T1E1, T3AV, T3E2	GENE-0427_442	1B	5688119	5.79E-04	8.62E-05	9.35—12.35
植株总干重TDW	T1E1, T3AV, T3E2	GENE-0427_442	1B	5688119	6.54E-04	1.88E-04	9.17—11.11
植株总氮含量TNC	T1E1, T3AV, T3E2	GENE-0427_442	1B	5688119	6.25E-04	1.08E-04	9.23—11.98
地上部氮含量SNC	T2AV, T2E1, T1E2	wsnp_RFL_Contig3060_2967139	2A	9928033	8.05E-04	1.87E-04	11.41—13.91
植株总氮含量TNC	T2AV, T2E1, T1E2	wsnp_RFL_Contig3060_2967139	2A	9928033	2.95E-04	2.05E-04	12.57—13.74
植株总氮利用效率TNUE	T2AV, T2E1, T1AV, T1E2	Kukri_c65481_121	3B	13483435	7.19E-04	2.08E-04	9.09—11.40
根系氮利用效率RNUE	T1AV, T1E1, T3AV, T3E2	tplb0025f09_1052	4B	1591267	7.25E-04	1.32E-09	11.49—36.09
地上部干重SDW	T2E2, T1AV, T1E1	wsnp_Ku_c1765_3452586	6A	14086572	6.09E-04	1.39E-04	9.07—11.58
生物量根冠比RSDW	T2AV, T2E2, T3E2	BS00022498_51	7B	6251008	5.32E-04	3.25E-04	12.01—12.85

标记和染色体 Marker and Chr.	性状 Trait	分析环境 Analysis environment	贡献率 R² (%)
BS00077492_51 1A	地上部干重SDW	T1E1	12.63
	植株总干重TDW	T1E1	11.31
	地上部氮含量SNC	T1E1	11.73
	植株总氮含量TNC	T1E1	11.76
	地上部氮利用效率SNUE	T1E1	12.42
	植株总氮利用效率TNUE	T1E1	11.80
BS00065737_51 1B	地上部干重SDW	T1E1, T3E2	8.93—11.37
	植株总干重TDW	T1E1	8.60
	地上部氮含量SNC	T1E1	9.80
	植株总氮含量TNC	T1E1	8.87
	地上部氮利用效率SNUE	T1E1, T3E2	10.11—10.75
	植株总氮利用效率TNUE	T3E2	9.01
GENE-0427_442 1B	地上部干重SDW	T1E1, T3E2	10.86—11.65
	植株总干重TDW	T1E1, T3AV, T3E2	9.17—11.11
	地上部氮含量SNC	T1E1, T3AV, T3E2	9.35—12.35
	植株总氮含量TNC	T1E1, T3AV, T3E2	9.23—11.98
	地上部氮利用效率SNUE	T3E2	10.44
	植株总氮利用效率TNUE	T3AV, T3E2	9.65—11.33
IACX16577 1B	地上部干重SDW	T1E1, T3E2	9.49—11.83
	植株总干重TDW	T1E1, T3E2	8.82—8.97
	地上部氮含量SNC	T1E1, T3E2	8.92—9.96
	植株总氮含量TNC	T1E1, T3E2	8.72—9.30
	地上部氮利用效率SNUE	T1E1, T3E2	10.82—11.02
	植株总氮利用效率TNUE	T1E1, T3E2	9.19—9.81
wsnp_RFL_Contig3060_2967139 2A	地上部干重SDW	T2AV, T2E1	13.39—13.77
	植株总干重TDW	T2AV, T2E1	12.85—13.57
	地上部氮含量SNC	T2AV, T2E1, T1E2	13.25—13.91
	植株总氮含量TNC	T2AV, T2E1, T1E2	13.33—13.74
	地上部氮利用效率SNUE	T2AV, T2E1	12.99—13.69
	植株总氮利用效率TNUE	T2AV, T2E1	12.04—12.73

染色体 Chr.	基因 Gene	位置 Position (Mb)	标记 Marker	基因注释或编码蛋白 Gene annotation or coding protein
1B	TraesCS1B02G058300	183.39	BS00065737_51	无性的MADS盒子转录因子 Agamous MADS-box transcription factor
2A	TraesCS2A02G122000	332.13	wsnp_RFL_Contig3060_2967139	与膜相关的30 kD蛋白 Membrane-associated 30 kD protein
4B	TraesCS4B02G007100	46.43	tplb0025f09_1052	含R3h结构域的蛋白质 R3h domain containing protein

Genome-Wide Association Analysis for Yield and Nitrogen Efficiency Related Traits of Wheat at Seedling Stage

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