Scientia Agricultura Sinica ›› 2024, Vol. 57 ›› Issue (11): 2065-2078.doi: 10.3864/j.issn.0578-1752.2024.11.002

• SPECIAL FOCUS: SOYBEAN DISEASE RESISTANCE, YIELD AND QUALITY CORRELATION • Previous Articles     Next Articles

Identification and Gene Mapping of Hard Seededness Mutant Mzp661 in Soybean

MIAO Long1(), SHU Kuo1, HU YanJiao1, HUANG Ru1, HE GenHua1, ZHANG WenMing1, WANG XiaoBo1(), QIU LiJuan2()   

  1. 1 College of Agriculture, Anhui Agricultural University, Hefei 230036
    2 Institute of Crop Science, Chinese Academy of Agricultural Sciences/National Key Facility for Crop Gene Resources and Genetic Improvement/Key Laboratory of Crop Gene Resource and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs, Beijing 100081
  • Received:2022-11-07 Accepted:2022-12-12 Online:2024-06-01 Published:2024-06-07
  • Contact: WANG XiaoBo, QIU LiJuan

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Abstract:

【Objective】Hardness, a structural feature of seed physical dormancy, is an important trait in soybean domestication. Although hardness is beneficial for seeds to survive in unfavorable environments, it will seriously reduce the emergence rate of soybean in the field, and detrimental to yield and processing quality. Analyzing the QTL and candidate genes using bulked segregant analysis sequencing (BSA-Seq), can provide a theoretical reference for understanding the molecular mechanism of hard seededness in soybean.【Method】The hard seed mutant Mzp661 was obtained from the seeds of Zhongpin 661 induced by ethyl methane sulfonate (EMS), and was crossed with cultivated soybean Zhonghuang 13 (male parent) to construct recombinant inbred line (RIL) population. The progeny lines were investigated for seed hardness, water absorption capacity and anatomical structure of seed coats. Two types of extreme lines in the RIL population, with hard seeds or with imbibed seeds, were selected to construct DNA mixed pools respectively, and then BSA-Seq technology was used to detect genotype differences in extreme-mixed pools and parents. Euclidean distance (ED), delta SNP-index, and delta InDel-index methods were applied to associate hard seed genetic loci of soybean. Combining with bioinformatics analysis, transcriptome data of different soybean tissues and gene annotation information, candidate genes within significant association regions were predicted.【Result】In the progenies of Mzp661, all areas of imbibitive seeds had the penetration ability, and the seed volume increased continuously with the soaking time. However, no changes were observed for hard seeds over 36 hours. With the prolonged of soaking time, the seed coat of hard seeds began to shrink locally and gradually spread to other parts, and finally cotyledons recovered their imbibition ability. The hard seed not only has smooth and compact seed coat, but also has regular network structure of cuticle and thicker palisade layer, while numbers of stomata and loose structures, tiny cracks and thinner palisade layer were existed in the imbibed seeds. These results suggest that the seed hardness of Mzp661 may be caused by the impermeability of the seed coat. ED, delta SNP-index and delta InDel-index association analysis methods not only identified the reported seed physical dormancy locus qHS1, but also simultaneously detected the candidate region Chr.06: 45897227-47746047, which contains a total of 189 genes. Further, transcriptome data and gene annotation predicted that Glyma.06G275300, which is specifically and highly expressed in seeds, might be the candidate gene for this associated region to regulate soybean seed hardness.【Conclusion】Seed hardness of soybean mutant Mzp661 was caused by the impermeability of the seed coat, and Glyma.06G275300 was predicted as a candidate gene affecting the structure of seed coat using BSA-Seq.

Key words: soybean, seed hardness, seed coat structure, BSA-Seq, candidate gene

Fig. 1

Comparison of water absorption capacity between hard seeds and imbibed seeds in progeny of Mzp661 A: The changes of the hard seeds and imbibed seeds of the progeny of Mzp661 after immersion for 24 hours; B: Variation of hardness rate of soybean hard seeds at different immersion time. C: Morphological changes of hard seeds and imbibed seeds in progeny of Mzp661 at different immersion time; D: The water absorption rates of hard seeds and imbibed seeds at different immersion time since the beginning of permeation"

Fig. 2

Effects of incised seed coat on the penetration ability of hard seeds in the progeny of MZP661 A: Comparison of the penetration capacity between completed and incised seed coat of hard seeds in progeny of Mzp661; The red dotted circle indicates the position of the incised seed coat; B: Imbibed seeds percentage between completed and incised seed coat of hard seeds at different immersion time; C: Comparison of water absorption rate between imbibed seeds and hard seeds with incised seed coat; D: Surface features of seed coats in imbibed seeds and hard seeds in progeny of Mzp661"

Fig. 3

Comparison of seed coats anatomical structures of hard seeds and imbibed seeds A: Surface structures of hard seeds and imbibed seeds under scanning electron microscope, scale bars = 1 mm; B: Cuticle of seed coat in hard seeds and imbibed seeds, scale bars=5 μm; C: Longitudinal section anatomical structures of the seed coat in hard seeds and imbibed seeds, scale bars=100 μm, PL: Palisade layer; HG: Hourglass cells; PA: Parenchyma cells"

Table 1

Statistical of sample sequencing data quality evaluation"

样本ID
Sample ID		 纯化过滤后读段数
Clean reads		 纯化过滤后碱基数
Clean base		 GC
(%)		 Q30
(%)		 比对上的序列
Mapped reads (%)
中黄13 Zhonghuang13 37644247 11293274100 36.24 94.85 98.40
Mzp661 43314597 12994379100 35.16 94.54 98.32
吸胀型种子池 Imbibed seeds pool 104513578 31201732144 34.58 93.10 97.99
硬实型种子池 Hard seeds pool 100627070 30040531870 34.37 93.49 98.14

Fig. 4

BSA association analysis of hard seededness trait in soybean A: The distribution of euclidean distance (ED)-associated values of each SNP on chromosomes. B: The distribution of delta SNP-index-associated values on chromosomes. C: The distribution of euclidean distance (ED)-associated values of each InDel on chromosomes. D: The distribution of delta InDel-index-associated values on chromosomes. The significant associated thresholds and association regions were indicated by the red dotted lines and arrows, respectively"

Table 2

Genetic loci of soybean hard seededness trait via different methods"

染色体
Chromosome		 起点
Start		 终点
End		 区间大小
Interval size (Mb)		 基因数量
Gene numbers		 关联分析方法
Association analysis methods
Chr.02 42109660 46476569 4.37 492 欧式距离Euclidean distance-SNP
Chr.02 46476993 46477131 0.00 1 欧式距离Euclidean distance-SNP
Chr.02 46498253 46498523 0.00 1 欧式距离Euclidean distance-SNP
Chr.02 46735046 46908635 0.17 24 欧式距离Euclidean distance-SNP
Chr.02 46909986 46910068 0.00 1 欧式距离Euclidean distance-SNP
Chr.02 46910916 46917627 0.01 2 欧式距离Euclidean distance-SNP
Chr.02 47020220 47194489 0.17 26 欧式距离Euclidean distance-SNP
Chr.06 45366934 48101187 2.73 266 欧式距离Euclidean distance-SNP
Chr.10 2448730 5133587 2.68 278 欧式距离Euclidean distance-SNP
Chr.10 5137986 5151545 0.01 4 欧式距离Euclidean distance-SNP
Chr.11 24641185 25370343 0.73 47 欧式距离Euclidean distance-SNP
Chr.18 46888666 47393725 0.51 24 欧式距离Euclidean distance-SNP
Chr.06 45478047 46640230 1.16 87 SNP-index
Chr.06 46640721 46648304 0.01 1 SNP-index
Chr.06 46648828 47945747 1.30 150 SNP-index
Chr.02 42244773 46558722 4.31 491 欧式距离Euclidean distance-InDel
Chr.06 45010321 48185175 3.17 303 欧式距离Euclidean distance-InDel
Chr.10 2707354 3441480 0.73 77 欧式距离Euclidean distance-InDel
Chr.06 45897227 47746047 1.85 189 InDel-index

Fig. 5

Identification of candidate genes in significantly associated regions A: GO annotation classification of genes in candidate QTL; B: Heat map with hierarchical cluster analysis of 189 candidate genes expression level in different soybean tissues"

Fig. 6

Analysis of relative expression and variations of candidate genes A: The relative expression of candidate genes between imbibed seeds and hard seeds; B: Sequence variations of Glyma.06G275300 in parents. *and ** indicate the relative expression difference of candidate genes between imbibed seeds and hard seeds. Gene expression level in imbibed seeds as control (* P<0.05, ** P<0.01, t-test)"

[1]
RAMAKRISHNA G, KAUR P, NIGAM D, CHADUVULA P K, YADAV S, TALUKDAR A, SINGH N K, GAIKWAD K. Genome- wide identification and characterization of InDels and SNPs in Glycine max and Glycine soja for contrasting seed permeability traits. BMC Plant Biology, 2018, 18(1): 141.
[2]
SMÝKAL P, VERNOUD V, BLAIR M W, SOUKUP A, THOMPSON R D. The role of the testa during development and in establishment of dormancy of the legume seed. Frontiers in Plant Science, 2014, 5: 351.

doi: 10.3389/fpls.2014.00351 pmid: 25101104
[3]
KEBEDE H, SMITH J R, RAY J D. Identification of a single gene for seed coat impermeability in soybean PI594619. Theoretical and Applied Genetics, 2014, 127(9): 1991-2003.
[4]
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(1): 499.
[5]
JANG S J, SATO M, SATO K, JITSUYAMA Y, FUJINO K, MORI H, TAKAHASHI R, BENITEZ E R, LIU B H, YAMADA T, ABE J. A single-nucleotide polymorphism in an endo-1,4-β-glucanase gene controls seed coat permeability in soybean. PLoS ONE, 2015, 10(6): e0128527.
[6]
艾丽娟, 陈强, 杨春燕, 闫龙, 王凤敏, 葛荣朝, 张孟臣. 大豆籽粒硬实加性和上位性QTL定位. 作物学报, 2018, 44(6): 852-858.

doi: 10.3724/SP.J.1006.2018.00852
AI L J, CHEN Q, YANG C Y, YAN L, WANG F M, GE R C, ZHANG M C. Mapping main-effect and epistatic QTL for hard seededness in soybean. Acta Agronomica Sinica, 2018, 44(6): 852-858. (in Chinese)
[7]
CHANDRA S, TAAK Y, RATHOD D R, YADAV R R, POONIA S, SREENIVASA V, TALUKDAR A. Genetics and mapping of seed coat impermeability in soybean using inter-specific populations. Physiology and Molecular Biology of Plants, 2020, 26(11): 2291-2299.

doi: 10.1007/s12298-020-00906-y pmid: 33268930
[8]
SUN L J, MIAO Z Y, CAI C M, ZHANG D J, ZHAO M X, WU Y Y, ZHANG X L, SWARM S A, ZHOU L W, ZHANG Z J, NELSON R L, MA J X. GmHs1-1, encoding a calcineurin-like protein, controls hard-seededness in soybean. Nature Genetics, 2015, 47(8): 939-943.

doi: 10.1038/ng.3339 pmid: 26098868
[9]
WANG F F, SUN X, LIU B H, KONG F J, PAN X W, ZHANG H Y. A polygalacturonase gene PG031 regulates seed coat permeability with a pleiotropic effect on seed weight in soybean. Theoretical and Applied Genetics, 2022, 135(5): 1603-1618.
[10]
WANG M, LI W Z, FANG C, XU F, LIU Y C, WANG Z, YANG R, ZHANG M, LIU S L, LU S J, LIN T, TANG J Y, WANG Y Q, WANG H R, LIN H, ZHU B G, CHEN M S, KONG F J, LIU B H, ZENG D L, JACKSON S A, CHU C C, TIAN Z X. Parallel selection on a dormancy gene during domestication of crops from multiple families. Nature Genetics, 2018, 50(10): 1435-1441.

doi: 10.1038/s41588-018-0229-2 pmid: 30250128
[11]
BOMBLIES K, SHUKLA V, GRAHAM C. Scanning electron microscopy (SEM) of plant tissues. Cold Spring Harbor Protocols, 2008, 2008: pdb.prot4933.
[12]
LI H, HANDSAKER B, WYSOKER A, FENNELL T, RUAN J, HOMER N, MARTH G, ABECASIS G, DURBIN R. 1000 GENOME PROJECT DATA PROCESSING SUBGROUP. The sequence alignment/map format and SAMtools. Bioinformatics, 2009, 25(16): 2078-2079.

doi: 10.1093/bioinformatics/btp352 pmid: 19505943
[13]
MCKENNA A, HANNA M, BANKS E, SIVACHENKO A, CIBULSKIS K, KERNYTSKY A, GARIMELLA K, ALTSHULER D, GABRIEL S, DALY M, DEPRISTO M A. The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data. Genome Research, 2010, 20(9): 1297-1303.

doi: 10.1101/gr.107524.110 pmid: 20644199
[14]
CINGOLANI P. Variant annotation and functional prediction: SnpEff. Methods in Molecular Biology, 2022, 2493: 289-314.

doi: 10.1007/978-1-0716-2293-3_19 pmid: 35751823
[15]
HILL J T, DEMAREST B L, BISGROVE B W, GORSI B, SU Y C, YOST H J. MMAPPR: Mutation mapping analysis pipeline for pooled RNA-seq. Genome Research, 2013, 23(4): 687-697.

doi: 10.1101/gr.146936.112 pmid: 23299975
[16]
CUI Y L, GE Q, ZHAO P, CHEN W, SANG X H, ZHAO Y L, CHEN Q J, WANG H M. Rapid mining of candidate genes for Verticillium wilt resistance in cotton based on BSA-seq analysis. Frontiers in Plant Science, 2021, 12: 703011.
[17]
LI R C, JIANG H W, ZHANG Z G, ZHAO Y Y, XIE J G, WANG Q, ZHENG H Y, HOU L L, XIONG X, XIN D W, HU Z B, LIU C Y, WU X X, CHEN Q S. Combined linkage mapping and BSA to identify QTL and candidate genes for plant height and the number of nodes on the main stem in soybean. International Journal of Molecular Sciences, 2019, 21(1): 42.
[18]
WU T Z, HU E Q, XU S B, CHEN M J, GUO P F, DAI Z H, FENG T Z, ZHOU L, TANG W L, ZHAN L, FU X C, LIU S S, BO X C, YU G C. ClusterProfiler 4.0: A universal enrichment tool for interpreting omics data. The Innovation, 2021, 2(3): 100141.
[19]
SZEWIŃSKA J, SIMINSKA J, BIELAWSKI W. The roles of cysteine proteases and phytocystatins in development and germination of cereal seeds. Journal of Plant Physiology, 2016, 207: 10-21.

doi: S0176-1617(16)30215-2 pmid: 27771502
[20]
SINGH K L, CHAUDHURI A, KAR R K. Role of peroxidase activity and Ca(2+)in axis growth during seed germination. Planta, 2015, 242(4): 997-1007.
[21]
张丹丹. 核糖体大亚基蛋白L11的环状区loop62在调控蛋白质翻译中的作用[D]. 合肥: 中国科学技术大学, 2011.
ZHANG D D. The function of ribosome large protein L11 loop 62 during regulating protein translation[D]. Hefei: University of Science and Technology of China, 2011. (in Chinese)
[22]
曹志琛, 吴娴, 汪德州, 柳珊, 杨慧玉, 郝小聪, 房兆峰, 朱文根, 王伟伟, 王小燕, 唐益苗. 小麦多蛋白桥梁因子基因TaMBF1c的克隆与表达分析. 麦类作物学报, 2021, 41(4): 391-400.
CAO Z C, WU X, LIU S, YANG H Y, HAO X C, FANG Z F, ZHU W G, WANG W W, WANG X Y, TANG Y M. Cloning and expression analysis of wheat multiprotein bridge factor gene TaMBF1c. Journal of Triticeae Crops, 2021, 41(4): 391-400. (in Chinese)
[23]
闫龙凤, 杨青川, 韩建国, 刘志鹏. 植物半胱氨酸蛋白酶研究进展. 草业学报, 2005(5): 11-19.
YAN L F, YANG Q C, HAN J G, LIU Z P. Summary of cysteine protease in plants. Acta Prataculturae Sinica, 2005(5): 11-19. (in Chinese)
[24]
HAN J Y, LI H, YIN B, ZHANG Y Z, LIU Y D, CHENG Z Y, LIU D, LU H. The papain-like cysteine protease CEP1 is involved in programmed cell death and secondary wall thickening during xylem development in Arabidopsis. Journal of Experimental Botany, 2018, 70(1): 205-215.
[25]
HELM M, SCHMID M, HIERL G, TERNEUS K, TAN L, LOTTSPEICH F, KIELISZEWSKI M J, GIETL C. KDEL-tailed cysteine endopeptidases involved in programmed cell death, intercalation of new cells, and dismantling of extensin scaffolds. American Journal of Botany, 2008, 95(9): 1049-1062.

doi: 10.3732/ajb.2007404 pmid: 21632425
[26]
CHAHTANE H, KIM W, LOPEZ-MOLINA L. Primary seed dormancy: A temporally multilayered riddle waiting to be unlocked. Journal of Experimental Botany, 2016, 68(4): 857-869.
[27]
SHU K, LIU X D, XIE Q, HE Z H. Two faces of one seed: Hormonal regulation of dormancy and germination. Molecular Plant, 2016, 9(1): 34-45.

doi: S1674-2052(15)00356-1 pmid: 26343970
[28]
WERKER E, MARBACH I, MAYER A M. Relation between the anatomy of the testa, water permeability and the presence of phenolics in the genus Pisum. Annals of Botany, 1979, 43(6): 765-771.
[29]
李一政, 隋超, 郭尚敬, 孙永旺. 大豆硬实性状研究进展. 江苏农业科学, 2022, 50(13): 77-82.
LI Y Z, SUI C, GUO S J, SUN Y W. Research progress of hard seed trait of soybean. Jiangsu Agricultural Science, 2022, 50(13): 77-82. (in Chinese)
[30]
MEYER C J, STEUDLE E, PETERSON C A. Patterns and kinetics of water uptake by soybean seeds. Journal of Experimental Botany, 2006, 58(3): 717-732.
[31]
宋芸, 崔芬芬, 陈亮, 王立, 乔永刚. 苦参种子形态解剖结构研究. 种子, 2017, 36(7): 48-50.
SONG Y, CUI F F, CHEN L, WANG L, QIAO Y G. Study on morphological and anatomical structure of Sophora flavescens seeds. Seed, 2017, 36(7): 48-50. (in Chinese)
[32]
徐亮, 李建东, 殷萍萍, 王国骄, 燕雪飞, 孙备. 野生大豆种皮形态结构和萌发特性的研究. 大豆科学, 2009, 28(4): 641-646.
XU L, LI J D, YIN P P, WANG G J, YAN X F, SUN B. Testa morphology structure and germination characteristic of Glycine soja. Soybean Science, 2009, 28(4): 641-646. (in Chinese)
[33]
DE SOUZA F H D, MARCOS-FILHO J. The seed coat as a modulator of seed-environment relationships in Fabaceae. Revista Brazilian De Botanica, 2001, 24(4): 365-375.
[34]
MULLIN W J, XU W. Study of soybean seed coat components and their relationship to water absorption. Journal of Agricultural and Food Chemistry, 2001, 49(11): 5331-5335.

doi: 10.1021/jf010303s pmid: 11714324
[35]
SHAO S Q, MEYER C J, MA F S, PETERSON C A, BERNARDS M A. The outermost cuticle of soybean seeds: Chemical composition and function during imbibition. Journal of Experimental Botany, 2007, 58(5): 1071-1082.

doi: 10.1093/jxb/erl268 pmid: 17218545
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