夏大豆重组自交系群体遗传图谱构建及开花期QTL分析

doi:10.3864/j.issn.0578-1752.2020.04.002

Abstract

Abstract:

【Background】 Flowering time (FT) is an important agronomic trait, which determines the planting range of cultivars and has a significant influence on the yield and quality of soybean. The Chinese Jiang-Huai valley is an important soybean producing area. However, little is known about the genetic basis of flowering time in these genotypes. 【Objective】 The objectives of this study were to map mapping quantitative trait loci (QTLs) and identify stable and reliable loci that can be used for molecular marker-assisted selection (MAS) and map-based gene cloning, and then dissect the genetic basis of flowering time in summer planting soybean. 【Method】 A recombinant inbred lines (RIL) population containing 91 lines (F_2:8) developed by crossing KF35 with NN1138-2 was planted in six environments to investigate phenotypic data. Restriction-site associated DNA sequencing (RAD-seq) technology was used to genotype all lines and their parents. And then bin markers were obtained by window sliding method based on the SNP markers and used to construct the genetic map. The mixed-model based composite interval mapping (MCIM) method in the software of QTL Network 2.2 and the composite interval mapping (CIM) method in the software of Windows QTL Cartographer V2.5_011 were used to reveal the effects of the QTLs of FT. 【Result】 A total of 36778 high-quality SNP markers were obtained in the whole soybean genome, and further divided into 1733 bin markers. A high-density genetic map with 1733 bin markers was constructed that spanned 2362.4 cM of the soybean genome with an average marker distance of 1.4 cM. Nine additive QTLs, two pairs of epistatic QTLs and one environmental interaction QTL were detected by MCIM method. The cumulative contribution of additive, epistatic and environmental interaction effects were 63.9%, 4.6% and 2.1%, respectively. Ten QTLs were detected by CIM method, and four of them, qFT-8-1, qFT-11-1, qFT-15-1 and qFT-16-1 could be detected in three or more environments. Altogether, 12 QTLs controlling FT were mapped using MCIM and CIM methods. Six of them, qFT-8-1, qFT-11-1, qFT-15-1, qFT-16-1, qFT-16-2, qFT-20-1 and qFT-20-2 could be detected by two methods. Six novel QTLs, qFT-5-1, qFT-8-1, qFT-8-2, qFT-13-1, qFT-15-1 and qFT-20-2 were detected in this study. 【Conclusion】 The genetic composition of FT in summer planting soybean is relatively complex. However, the additive effect was dominant, epistatic interaction and environmental interaction had little effect on FT. Four QTLs, qFT-8-1, qFT-11-1, qFT-15-1 and qFT-16-1 can be detected by two methods and in multiple environments, which are important loci for controlling FT in NJK3N-RIL population.

Key words: soybean, flowering time, genetic map, QTL

YongCe CAO, ShuGuang LI, XinCao ZHANG, JieJie KONG, TuanJie ZHAO. Construction of Genetic Map and Mapping QTL for Flowering Time in A Summer Planting Soybean Recombinant Inbred Line Population[J].Scientia Agricultura Sinica, 2020, 53(4): 683-694.

0
/ Save 0 / Recommend

Add to citation manager EndNote|Reference Manager|ProCite|BibTeX|RefWorks

URL: https://www.chinaagrisci.com/EN/10.3864/j.issn.0578-1752.2020.04.002

https://www.chinaagrisci.com/EN/Y2020/V53/I4/683

Figures/Tables 8

Table 1

Fig. 1

Table 2

Fig. 2

Table 3

Fig. 3

Table 4

Table 5

Detection of QTL associated with flowering time in the NJK3N-RIL population grown in different environments"

位点 QTL	染色体 Chromosome	遗传位置 Position (cM)	相邻标记 Flank markers	LOD	置信区间 Confidence interval (cM)	加性效应 Additive (d)	贡献率 R² (%)	环境 Environment	报道位点 Reported locus
qFT-5-1	5	69.4	bin398-bin399	4.4	67.5—71.8	-0.6	9.9	2014JP	Novel
qFT-6-1	6	108.3	bin482-bin483	3.8	106.9—109.5	0.6	5.0	2013JP	First flower 1-1
qFT-8-1	8	105.2	bin670-bin671	4.5	99.2—108.2	0.8	9.1	2013FY	Novel
		107.2	bin671-bin672	3.2	102.9—108.4	0.5	6.6	2012JP
		106.2	bin670-bin671	4.6	100.9—111.3	0.6	9.0	2014YC
qFT-8-2	8	123.1	bin685-bin686	4.8	121.4—125.2	0.7	9.4	2012FY	Novel
		123.1	bin685-bin686	3.8	121.3—125.2	0.6	5.9	2013JP
qFT-11-1	11	84.6	bin927-bin928	12.7	84.2—85.8	1.3	34.3	2012JP	First flower 11-2
		84.5	bin927-bin928	14.2	83.6—87.5	1.5	39.6	2012FY
		87.2	bin930-bin931	18.2	86.5—88.4	1.9	49.6	2013FY
		88.2	bin930-bin931	8.6	86.8—89.2	1.0	18.5	2014YC
		92.9	bin932-bin933	9.4	89.0—95.6	1.1	17.7	2013JP
qFT-15-1	15	130.1	bin1290-bin1291	9.3	127.4—133.5	0.9	23.0	2014JP	Novel
		134.6	bin1291-bin1292	4.5	130.6—136.8	0.7	7.6	2013JP
		134.6	bin1291-bin1292	4.6	131.0—138.3	0.6	8.3	2014YC
		135.4	bin1292-bin1293	4.0	130.6—138.8	0.6	8.6	2012JP
qFT-16-1	16	21.3	bin1313-bin1314	5.6	17.2—26.1	0.9	10.8	2013FY	First flower 13-7
		22.3	bin1313-bin1314	4.7	21.7—25.0	0.6	10.9	2014JP
		23.3	bin1313-bin1314	7.9	21.1—26.3	0.9	18.1	2012FY
		24.3	bin1313-bin1314	11.1	21.2—26.3	1.0	24.8	2014YC
		26.7	bin1315-bin1316	13.9	23.9—28.0	1.3	28.9	2013JP
		32.7	bin1320-bin1321	5.2	31.9—33.6	0.7	11.5	2012JP
qFT-16-2	16	66.2	bin1359-bin1360	3.4	65.9—69.6	0.7	6.2	2013FY	First flower 9-3
qFT-20-1	20	44.8	bin1682-bin1683	10.3	43.8—45.4	1.1	19.1	2013JP	First flower 21-2
qFT-20-2	20	97.3	bin1728-bin1729	5.3	94.7—99.0	0.7	11.9	2014JP	Novel

Table 5

References 58

[1]	XIA Z, WATANABE S, YAMADA T, TSUBOKURA Y, NAKASHIMA H, ZHAI H, ANAI T, SATO S, YAMAZAKI T, LU S, WU H, TABATA S, HARADA K . Positional cloning and characterization reveal the molecular basis for soybean maturity locus E1 that regulates photoperiodic flowering. Proceedings of the National Academy of Sciences of the United States of America , 2012,109(32):2155-2164.
[2]	KONG F J, NAN H Y, CAO D, LI Y, WU F F, WANG J L, LU S J, YUAN X H, COBER E R, ABE J, LIU B H . A new dominant gene conditions early flowering and maturity in soybean. Crop Science, 2014,54(6):2529-2535.
[3]	JIA H C, JIANG B J, WU C X, LU W C, HOU W S, SUN S, YAN H R, HAN T F . Maturity group classification and maturity locus geno-typing of early-maturing soybean varieties from high-latitude cold regions. PLoS ONE, 2014,9:e94139.
[4]	COBER E R, MOLNAR S J, CHARETTE M, VOLDENG H D . A new locus for early maturity in soybean. Crop Science, 2010,50(2):524-527.
[5]	ZHANG W K, WANG Y J, LUO G Z, ZHANG J S, HE C Y, WU X L, GAI J 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. Theoretical and Applied Genetics, 2004,108(6):1131-1139.
[6]	LIU W, KIM M Y, VAN K, LEE Y H, LI H L, LIU H L, LEE S H . QTL identification of yield-related traits and their association with flowering and maturity in soybean. Journal of Crop Science and Biotechnology, 2011,14(1):65-70.
[7]	COOPER R L . A delayed flowering barrier to higher soybean yields. Field Crop Research, 2003,82(1):27-35.
[8]	KEIM P, DIERS B W, OLSON T C, SHOEMAKER R C . RFLP mapping in soybean: Association between marker loci and variation in quantitative traits. Genetics, 1990,126(3):735-742.
[9]	BERNARD R L . Two major genes for time of flowering and maturity in soybeans. Crop Science, 1971,11(2):242-244.
[10]	BUZZELL R I . Inheritance of a soybean flowering response to fluorescent-daylength conditions. Canadian Journal of Genetics and Cytology, 1971,13(4):703-707.
[11]	BUZZELL R I, VOLDENG H D . Inheritance of insensitivity to long daylength. Soybean Genetics Newsletter, 1980,7(1):26-29.
[12]	MCBLAIN B A, BERNARD R L . A new gene affecting the time of flowering and maturity in soybeans. Journal of Heredity, 1987,78(3):160-162.
[13]	BONATO E R, VELLO N A . E6, a dominant gene conditioning early flowering and maturity in soybeans. Genetics and Molecular Biology, 1999,22(2):229-232.
[14]	COBER E R, VOLDENG H D . A new soybean maturity and photoperiod-sensitivity locus linked to E1 and T. Crop Science, 2001,41(3):698-701.
[15]	SAMANFAR B, MOLNAR S J, CHARETTE M, SCHOENROCK A, DEHNE F, GOLSHANI A, BELZILE F, COBER E R . Mapping and identification of a potential candidate gene for a novel maturity locus,E10, in soybean. Theoretical and Applied Genetics, 2017,130(2):377-390.
[16]	RAY J D, HINSON K, MANKONO J, MALO M F . Genetic control of a long-juvenile trait in soybean. Crop Science, 1995,35(4):1001-1006.
[17]	WANG F F, NAN H Y, CHEN L Y, FANG C, ZHANG H Y, SU T, LI S C, CHENG Q, DONG L D, LIU B H, KONG F J, LU S J . A new dominant locus,E11, controls early flowering time and maturity in soybean. Molecular Breeding, 2019,39(5):70.
[18]	WATANABE S, XIA Z, HIDESHIMA R, TSUBOKURA Y, SATO S, YAMANAKA N, TAKAHASHI R, ANAI T, TABATA S, KITAMURA K, HARADA K . A map-based cloning strategy employing a residual heterozygous line reveals that the GIGANTEA gene is involved in soybean maturity and flowering. Genetics, 2011,188(2):395-407.
[19]	WATANABE S, HIDESHIMA R, XIA Z, TSUBOKURA Y, SATO S, NAKAMOTO Y, YAMANAKA N, TAKAHASHI R, ISHIMOTO M, ANAI T, TABATA S, HARADA K . Map-based cloning of the gene associated with the soybean maturity locus E3. Genetics, 2009,182(4):1251-1262.
[20]	LIU B, KANAZAWA A, MATSUMURA H, TAKAHASHI R, HARADA K, ABE J . Genetic redundancy in soybean photoresponses associated with duplication of the phytochrome A gene. Genetics, 2008,180(2):995-1007.
[21]	ZHAO C, TAKESHIMA R, ZHU J, XU M, SATO M, WATANABE S, KANAZAWA A, LIU B H, KONG F J, YAMADA T, ABE J . A recessive allele for delayed flowering at the soybean maturity locus E9 is a leaky allele of FT2a, a FLOWERING LOCUS T ortholog. BMC Plant Biology, 2016,16:20.
[22]	LU S J, ZHAO X H, HU Y L, LIU S L, NAN H Y, LI X M, FANG C, CAO D, SHI X Y, KONG L P, SU T, ZHANG F G, LI S C, WANG Z, YUAN X H, COBER E R, WELLER J L, LIU B H, HOU X L, TIAN Z X, KONG F J . Natural variation at the soybean J locus improves adaptation to the tropics and enhances yield. Nature Genetics, 2017,49(5):773-779.
[23]	DISSANAYAKA A, RODRIGUEZ T O, DI S, YAN F, GITHIRI S M, RODAS F R, ABE J, TAKAHASHI R . Quantitative trait locus mapping of soybean maturity gene E5. Breeding Science, 2016,66(3):407-415.
[24]	向仕华, 王吴彬, 何庆元, 杨红燕, 刘成, 邢光南, 赵团结, 盖钧镒 . 多环境下野生大豆染色体片段代换系群体农艺性状相关QTL/片段的鉴定. 中国农业科学, 2015,48(1):10-22.
	XIANG S H, WANG W B, HE Q Y, YANG H Y, LIU C, XING G N, ZHAO T J, GAI J Y . Identification of QTL/segments related to agronomic traits using CSSL population under multiple environments. Scientia Agricultura Sinica, 2015,48(1):10-22. (in Chinese)
[25]	宋晓宇, 毛婷婷, 王立伟, 刘丽凤, 李晓那, 孙石, 韩天富 . 不同播期条件下大豆开花期性状的全基因组关联分析. 中国油料作物学报, 2018,40(4):459.
	SONG X Y, MAO T T, WANG L W, LIU L F, LI X N, SUN S, HAN T F . Genome–wide association analysis of soybean flowering time under different sowing dates. Chinese Journal of Oil Crop Sciences, 2018, 40(4):459.(in Chinese)
[26]	张雅娟, 曹永策, 李曙光, 常芳国, 孔杰杰, 盖钧镒, 赵团结 . 夏大豆重组自交系群体 NJRIMN开花期和株高QTL定位. 大豆科学, 2018,37(6):860-865.
	ZHANG Y J, CAO Y C, LI S G, CHANG F G, KONG J J, GAI J Y, ZHAO T J . Mapping QTL for flowering time and plant height in a summer-sowing soybean RIL population NJRIMN. Soybean Science, 2018, 37(6):860-865. (in Chinese)
[27]	ORF J H, CHASE K, JARVIK T, MANSURC L M, CREGAN P B, ADLER F R, LARK K G . Genetics of soybean agronomic traits: I. Comparison of three related recombinant inbred populations. Crop Science, 1999,39(6):1642-1651.
[28]	YAMANAKA N, NINOMIYA S, HOSHI M, TSUBOKURA Y, YANO M, NAGAMURA Y, SASAKI T, HARADA K . An informative linkage map of soybean reveals QTLs for flowering time, leaflet morphology and regions of segregation distortion. DNA Research, 2001,8(2):61-72.
[29]	LEE S, JUN T H, MICHEL A P, MIAN M A R . SNP markers linked to QTL conditioning plant height, lodging, and maturity in soybean. Euphytica, 2015,203(3):521-532.
[30]	MAO T T, LI J Y, WEN Z X, WU T T, WU C X, SUN S, JIANG B J, HOU W S, LI W B, SONG Q J, WANG D C, HAN T F . Association mapping of loci controlling genetic and environmental interaction of soybean flowering time under various photo-thermal conditions. BMC Genomics, 2017,18(1):415.
[31]	WATANABE S, TSUKAMOTO C, OSHITA T, YAMADA T, ANAI T, KAGA A . Identification of quantitative trait loci for flowering time by a combination of restriction site-associated DNA sequencing and bulked segregant analysis in soybean. Breeding Science, 2017,67(3), 277-285.
[32]	KONG L P, LU S J, WANG Y P, FANG C, WANG F F, NAN H Y, SU T, LI S C, ZHANG F G, LI X M, ZHAO X H, YUAN X H, LIU B H, KONG F J . Quantitative trait locus mapping of flowering time and maturity in soybean using next-generation sequencing-based analysis. Frontiers in Plant Science, 2018,9:995.
[33]	KIM M Y, SHIN J H, KANG Y J, SHIM S R, LEE S H . Divergence of flowering genes in soybean. Journal of Biosciences, 2012,37(5):857-870.
[34]	ZHAI H, LÜ S X, WANG Y Q, CHEN X, REN H X, YANG J Y, CHENG W, ZONG C M, GU H P, QIU H M, WU H Y, ZHANG X Z, CUI T T, XIA Z J . Allelic variations at four major maturity E genes and transcriptional abundance of the E1 gene are associated with flowering time and maturity of soybean cultivars. PLoS ONE, 2014,9(5):e97636.
[35]	邱丽娟, 常汝镇 . 大豆种质资源描述规范和数据标准. 北京:中国农业出版社, 2006.
	QIU L J, CHANG R Z. Descriptors and data standard for soybean (Glycine spp). Beijing:China Agriculture Press, 2006. (in Chinese)
[36]	NYQUIST W E, BAKER R J . Estimation of heritability and prediction of selection response in plant-populations. Critical Reviews in Plant Sciences, 1991,10.3:235-322.
[37]	HAN K, JEONG H J, YANG H B, KANG S M, KWON J Y, KIM S, CHOI D, KANG B C . An ultra-high-density bin map facilitates high-throughput QTL mapping of horticultural traits in pepper (Capsicum annuum). DNA Research, 2016,23(2):81-91.
[38]	HUANG X H, FENG Q, QIAN Q, ZHAO Q, WANG L, WANG A, GUAN J P, FAN D L, WENG Q J, HUANG T, DONG G J, SANG T, HAN B . High-throughput genotyping by whole-genome resequencing. Genome Research, 2009,19(6):1068-1076.
[39]	VAN OOIJEN J W . JoinMap® 4, Software for the calculation of genetic linkage maps in experimental populations. Wageningen,Kyazma BV, 2006.
[40]	YANG J, HU C C, HU H, YU R D, XIA Z, YE X Z, ZHU J . QTLNetwork: Mapping and visualizing genetic architecture of complex traits in experimental populations. Bioinformatics, 2008,24(5):721-723.
[41]	WANG S, BASTEN C, ZENG Z . Windows QTL cartographer 2.5. Department of Statistics, North Carolina State University, Raleigh,NC, 2007.
[42]	GUTIERREZ-GONZALEZ J J, VUONG T D, ZHONG R, YU O, LEE J D, SHANNON G, ELLERSIECK M, NGUYEN H T, SLEPER D A . Major locus and other novel additive and epistatic loci involved in modulation of isoflavone concentration in soybean seeds. Theoretical and Applied Genetics, 2011,123(8):1375-1385.
[43]	ZOU G H, ZHAI G W, FENG Q, YAN S, WANG A, ZHAO Q, SHAO J F, ZHANG Z P, ZOU J Q, HAN B, TAO Y Z . Identification of QTLs for eight agronomically important traits using an ultra-high- density map based on SNPs generated from high-throughput sequencing in sorghum under contrasting photoperiods. Journal of Experimental Botany, 2012,63(15):5451-5462.
[44]	ZHANG D, LI H, WANG J, ZHANG H, HU Z, CHU S, LV H, YU D . High-density genetic mapping identifies new major loci for tolerance to low-phosphorus stress in soybean. Frontiers in Plant Science, 2016,7:372.
[45]	JIANG N, SHI S, SHI H, KHANZADA H, WASSAN G M, ZHU C, PENG X, YU Q, CHEN X, HE X, FU J, HU L, XU J, OUYANG L, SUN X, ZHOU D, HE H, BIAN J . Mapping QTL for seed germinability under low temperature using a new high-density genetic map of rice. Frontiers in Plant Science, 2017,8:1223.
[46]	ARDISSON M, RANWEZ V, BESNARD A, BESNARD A, LEROY P, POUX G, ROUMET P, VIADER V, SANTONI S, DAVID J . Genotyping by sequencing using specific allelic capture to build a high-density genetic map of durum wheat. PLoS ONE, 2016,11(5):e0154609.
[47]	张传量, 简俊涛, 冯洁, 崔紫霞, 许小宛, 孙道杰 . 基于90K芯片标记的小麦芒长QTL定位. 中国农业科学, 2018,51(1):17-25.
	ZHANG C L, JIAN J T, FENG J, CUI Z X, XU X W, SUN D J . QTL Identification for awn length based on 90K array mapping in wheat. Scientia Agricultura Sinica, 2018,51(1):17-25. (in Chinese)
[48]	WANG W B, LIU M F, WANG Y F, LI X L, CHENG S X, SHU L P, YU Z P, KONG J J, ZHAO T J, GAI J Y . Characterizing two inter-specific bin maps for the exploration of the QTLs/genes that confer three soybean evolutionary traits. Frontiers in Plant Science, 2016,7:1248.
[49]	CHENG Y B, MA Q B, REN H L, XIA Q J, SONG E L, TAN Z Y, LI S X, ZHANG G Y, NIAN H . Fine mapping of a Phytophthora- resistance gene RpsWY in soybean(Glycine max L.) by high- throughput genome-wide sequencing. Theoretical and Applied Genetics, 2017,130(5):1041-1051.
[50]	WANG L, CHENG Y, MA Q, MU Y, HUANG Z, XIA Q, ZHANG G, NIAN H . QTL fine-mapping of soybean (Glycine max L.) leaf type associated traits in two RILs populations. BMC Genomics, 2019,20(1):260.
[51]	XU Y, CROUCH J H . Marker-assisted selection in plant breeding: From publications to practice. Crop Science, 2008,48(2):391-407.
[52]	WANG D L, ZHU J, LI Z K L, PATERSON A H . Mapping QTLs with epistatic effects and QTL× environment interactions by mixed linear model approaches. Theoretical and Applied Genetics, 1999,99(7/8):1255-1264.
[53]	YANG J, ZHU J . Methods for predicting superior genotypes under multiple environments based on QTL effects. Theoretical and Applied Genetics, 2005,110(7):1268-1274.
[54]	CHEN X . A microRNA as a translational repressor of APETALA2 in Arabidopsis flower development. Science, 2004,303(5666):2022-2025.
[55]	ABE M, KAYA H, WATANABE-TANEDA A, SHIBUTA M, YAMAGUCHI A, SAKAMOTO T, KURATA T, AUSIN I, ARAKI T, ALONSO‐BLANCO C . FE, a phloem specific Myb related protein, promotes flowering through transcriptional activation of FLOWERING LOCUS T and FLOWERING LOCUS T INTERACTING PROTEIN 1. The Plant Journal, 2015,83(6):1059-1068.
[56]	HU R B, QI G, KONG Y Z, KONG D J, GAO Q, ZHOU G K . Comprehensive analysis of NAC domain transcription factor gene family in Populus trichocarpa. BMC Plant Biology, 2010,10(1):145.
[57]	KIM S G, KIM S Y, PARK C M . A membrane-associated NAC transcription factor regulates salt-responsive flowering via FLOWERING LOCUS T in Arabidopsis. Planta, 2007,226(3):647-654.
[58]	KONG F J, LIU B H, XIA Z J, SATO S, KIM B M, WATANABE S, YAMADA T, TABATA S, KANAZAWA A, HARADA K, ABE J . Two coordinately regulated homologs of FLOWERING LOCUS T are involved in the control of photoperiodic flowering in soybean. Plant Physiology, 2010,154(3):1220-1231.

Metrics

Viewed

Full text

751

HTML			PDF

Just accepted	Online first	Issue	Just accepted	Online first	Issue
0	0	30	0	0	721

From	Others	local

Times	523	228
Rate	70%	30%

Abstract

430

Just accepted	Online first	Issue

0	0	430

From	Others	local

Times	387	43
Rate	90%	10%

Cited

Web of Science	Crossref	ScienceDirect	Search for Citations in Google Scholar >>


This page requires you have already subscribed to WoS.

Shared

Discussed

Comments

Recommended 0

No Suggested Reading articles found!

环境 Environment	亲本 Parents		NJK3N-RIL群体
环境 Environment	科丰35 KF35 (d)	南农1138-2 NN1138-2 (d)	均值±标准差 Mean ± SD (d)	变幅 Range (d)	偏度 Skewness	峰度 Kurtosis	变异系数 CV (%)
2012JP	36.8 ± 2.4	39.8 ± 1.5	37.7 ± 1.9	31.0—41.3	-0.5	0.3	5.2
2012FY	48.3 ± 2.3	54.0 ± 4.6	51.1 ± 2.0	47.7—57.3	0.3	-0.3	4.0
2013JP	40.7 ± 3.1	50.5 ± 3.7	44.8 ± 2.4	40.0—50.7	0.3	-0.4	5.3
2013FY	41.0± 0.0	51.3 ± 2.0	47.1 ± 2.5	43.0—53.7	0.9	0.6	5.4
2014JP	40.3 ± 2.3	47.0 ± 1.3	49.3 ± 1.9	37.7—48.7	-0.4	1.0	4.2
2014YC	35.3 ± 0.6	45.7 ± 1.2	42.1 ± 2.6	35.7—48.3	0.4	0.1	6.2

染色体 Chromosome	SNP数目 SNP numbers	bin标记数目 bin numbers	遗传图谱长度 Linkage distance (cM)	标记间平均距离 Mean distance of adjacent markers(cM)
Chr. 01	528	57	110.3	1.9
Chr. 02	1127	114	146.4	1.3
Chr. 03	3521	81	110.2	1.4
Chr. 04	1272	90	126.4	1.4
Chr. 05	1333	73	94.5	1.3
Chr. 06	1497	87	133.6	1.5
Chr. 07	1700	85	132.1	1.6
Chr. 08	1111	109	144.5	1.3
Chr. 09	1030	85	140.7	1.7
Chr. 10	3435	95	123.9	1.3
Chr. 11	2256	85	126.4	1.5
Chr. 12	733	65	115.5	1.8
Chr. 13	2264	104	125.5	1.2
Chr. 14	1752	81	80.1	1.0
Chr. 15	2008	88	148.6	1.7
Chr. 16	2384	84	85.4	1.0
Chr. 17	2220	84	118.0	1.4
Chr. 18	4513	110	98.2	0.9
Chr. 19	695	71	96.8	1.4
Chr. 20	1399	85	105.5	1.2
总计Total	36778	1733	2362.4	1.4

位点 QTL	染色体 Chromosome	两侧标记 Flank markers	位置 Position (cM)	QTL置信区间 Confidence interval (cM)	物理区间 1-LOD interval (Mb)	加性效应 A (d)	h²_A (%)	加性与环境互作效应 AE (d)	h²_AE (%)	报道位点 Reported locus
qFT-8-1	8	bin670-bin671	98.2	95.6—102.2	36.6—41.3	0.4	3.2			新位点 Novel
qFT-10-1	10	bin875-bin876	123.3	122.0—123.3	48.6—49.3	-0.5	4.8			First flower 24-4
qFT-11-1	11	bin928-bin929	85.8	84.6—86.5	14.9—15.6	0.7	9.9	0.6(2013FY) -0.8(2014JP)	4.6	First flower 11-2
qFT-13-1	13	bin1093-bin1094	68.0	66.8—68.5	28.4—29.5	0.4	3.0			新位点 Novel
qFT-15-1	15	bin1289-bin1290	130.1	128.1—130.1	48.1—49.0	0.6	7.9			新位点 Novel
qFT-16-1	16	bin1313-bin1314	24.2	21.2—27.7	3.8—5.0	0.7	10.5			First flower 13-7
qFT-16-2	16	bin1357-bin1358	64.3	62.2—66.2	31.1—32.0	0.6	7.2			First flower 9-3
qFT-20-1	20	bin1688-bin1689	47.7	46.8—48.3	34.3—34.5	0.7	12.0			First flower 21-2
qFT-20-2	20	bin1727-bin1728	95.8	95.2—96.8	44.0—44.5	0.5	5.4			新位点 Novel

上位性QTL对 Epistatic QTL pairs	位点 QTL	相邻标记 Flanking marker	位置 position (cM)	置信区间 Confidence interval (cM)	上位性效应 AA (d)	h²_AA (%)	上位性与环境互作效应 AAE (d)	h²_AAE (%)
1	qFT-11-1	bin928-bin929	85.8	84.6—86.5	-0.2	0.6	-0.3*(2013FY) 0.2(2014JP)	0.8
	qFT-16-1	bin1313-bin1314	24.2	21.2—27.7			-0.3*(2013FY) 0.2(2014JP)
2	qFT-13-1	bin1093-bin1094	68.0	66.8—68.5	0.3	1.5
	qFT-16-2	bin1357-bin1358	64.3	62.2—66.2

Construction of Genetic Map and Mapping QTL for Flowering Time in A Summer Planting Soybean Recombinant Inbred Line Population

RichHTML

PDF

Abstract

Cite this article

share this article

Figures/Tables 8

References 58

Related Articles 15

Metrics

Comments

Recommended 0

[1]	WEN YiBo, CHEN ShuTing, XU ZhengJin, SUN Jian, XU Quan. Combination of DEP1, Gn1a, and qSW5 Regulates the Panicle Architecture in Rice [J]. Scientia Agricultura Sinica, 2023, 56(7): 1218-1227.
[2]	LI RuXiang, ZHOU Kai, WANG DaChuan, LI QiaoLong, XIANG AoNi, LI Lu, LI MiaoMiao, XIANG SiQian, LING YingHua, HE GuangHua, ZHAO FangMing. Analysis of QTLs and Breeding of Secondary Substitution Lines for Panicle Traits Based on Rice Chromosome Segment Substitution Line CSSL-Z481 [J]. Scientia Agricultura Sinica, 2023, 56(7): 1228-1247.
[3]	JIA XiaoYun, WANG ShiJie, ZHU JiJie, ZHAO HongXia, LI Miao, WANG GuoYin. Construction of A High-Density Genetic Map and QTL Mapping for Yield Related Traits in Upland Cotton [J]. Scientia Agricultura Sinica, 2023, 56(4): 587-598.
[4]	CHEN JiHao, ZHOU JieGuang, QU XiangRu, WANG SuRong, TANG HuaPing, JIANG Yun, TANG LiWei, $\boxed{\hbox{LAN XiuJin}}$, WEI YuMing, ZHOU JingZhong, MA Jian. Mapping and Analysis of QTL for Embryo Size-Related Traits in Tetraploid Wheat [J]. Scientia Agricultura Sinica, 2023, 56(2): 203-216.
[5]	LI Yan, TAO KeYu, HU Yue, LI YongXiang, ZHANG DengFeng, LI ChunHui, HE GuanHua, SONG YanChun, SHI YunSu, LI Yu, WANG TianYu, ZOU HuaWen, LIU XuYang. Function of Maize ZCN7 in Regulating Drought Resistance at Flowering Stage [J]. Scientia Agricultura Sinica, 2023, 56(16): 3051-3061.
[6]	SUN Tao, FENG XiaoMin, GAO XinHao, DENG AiXing, ZHENG ChengYan, SONG ZhenWei, ZHANG WeiJian. Effects of Diversified Cropping on the Soil Aggregate Composition and Organic Carbon and Total Nitrogen Content [J]. Scientia Agricultura Sinica, 2023, 56(15): 2929-2940.
[7]	CAO Jie, GU YongZhe, HONG HuiLong, WU HaiTao, ZHANG Xia, SUN JianQiang, BAO LiGao, QIU LiJuan. Pigment Identification and Gene Mapping in Red Seed Coat of Soybean [J]. Scientia Agricultura Sinica, 2023, 56(14): 2643-2659.
[8]	LI YunJing, XIAO Fang, WU YuHua, LI Jun, GAO HongFei, ZHAI ShanShan, LIANG JinGang, WU Gang. Establishment and Standardization of Event-Specific Real-Time Quantitative PCR Detection Method of Stress-Resistant Soybean IND-ØØ41Ø-5 [J]. Scientia Agricultura Sinica, 2023, 56(13): 2443-2460.
[9]	YAO QiFu, CHEN HuangXin, ZHOU JieGuang, MA RuiYing, DENG Liang, TAN ChenXinYu, SONG JingHan, LÜ JiJuan, MA Jian. QTL Identification and Genetic Analysis of Plant Height in Wheat Based on 16K SNP Array [J]. Scientia Agricultura Sinica, 2023, 56(12): 2237-2248.
[10]	LIU YuYing, SHEN Feng, YANG JinFeng, CAI FangFang, FU ShiFeng, LUO PeiYu, LI Na, DAI Jian, HAN XiaoRi. Variation Characteristics of Soybean Yield and Soil Nitrogen Distribution in Brown Soil Under Long-Term Fertilization [J]. Scientia Agricultura Sinica, 2023, 56(10): 1920-1934.
[11]	YIN YanZhen, HOU LiMing, LIU Hang, TAO Wei, SHI ChuanZong, LIU KaiYue, ZHANG Ping, NIU PeiPei, LI Qiang, LI PingHua, HUANG RuiHua. Identifying Quantitative Trait Loci Associated with Teat Number of Pig by Genomic Analysis [J]. Scientia Agricultura Sinica, 2023, 56(10): 1994-2006.
[12]	DONG YongXin,WEI QiWei,HONG Hao,HUANG Ying,ZHAO YanXiao,FENG MingFeng,DOU DaoLong,XU Yi,TAO XiaoRong. Establishment of ALSV-Induced Gene Silencing in Chinese Soybean Cultivars [J]. Scientia Agricultura Sinica, 2022, 55(9): 1710-1722.
[13]	LI YiLing, PENG XiHong, CHEN Ping, DU Qing, REN JunBo, YANG XueLi, LEI Lu, YONG TaiWen, YANG WenYu. Effects of Reducing Nitrogen Application on Leaf Stay-Green, Photosynthetic Characteristics and System Yield in Maize-Soybean Relay Strip Intercropping [J]. Scientia Agricultura Sinica, 2022, 55(9): 1749-1762.
[14]	GUO ShiBo, ZHANG FangLiang, ZHANG ZhenTao, ZHOU LiTao, ZHAO Jin, YANG XiaoGuang. The Possible Effects of Global Warming on Cropping Systems in China XIV. Distribution of High-Stable-Yield Zones and Agro-Meteorological Disasters of Soybean in Northeast China [J]. Scientia Agricultura Sinica, 2022, 55(9): 1763-1780.
[15]	TANG HuaPing, CHEN HuangXin, LI Cong, GOU LuLu, TAN Cui, MU Yang, TANG LiWei, LAN XiuJin, WEI YuMing, MA Jian. Unconditional and Conditional QTL Analysis of Wheat Spike Length in Common Wheat Based on 55K SNP Array [J]. Scientia Agricultura Sinica, 2022, 55(8): 1492-1502.