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Acta Agronomica Sinica ›› 2020, Vol. 46 ›› Issue (7): 1016-1024.doi: 10.3724/SP.J.1006.2020.93054

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

Fine mapping of a major QTL qMES20-10 associated with deep-seeding tolerance in maize and analysis of differentially expressed genes

REN Meng-Meng1,**,ZHANG Hong-Wei1,**,WANG Jian-Hua2,WANG Guo-Ying1,ZHENG Jun1,*()   

  1. 1 Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
    2 College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
  • Received:2019-10-12 Accepted:2020-04-15 Online:2020-07-12 Published:2020-04-26
  • Contact: Jun ZHENG E-mail:zhengjun02@caas.cn
  • About author:** Contributed equally to this work
  • Supported by:
    National Key Research and Development Program of China(2016YFD0101002);Agricultural Science and Technology Innovation Program of Chinese Academy of Agricultural Sciences

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Abstract:

Drought stress is a major threat to maize (Zea mays L.) yield. Deep-seeding tolerant maize variety can absorb water in deep soil and thus have strong drought tolerance. Therefore, it is of great theoretical and practical importance to study the genetic mechanism of deep-seeding tolerance. In our previous work, we identified a major QTL qMES20-10 controlling maize deep-seeding tolerance on chromosome 10 using an F2:3 population derived from a deep-seeding tolerant inbred line 3681-4 and a common inbred line X178. In this study, a BC3F3:4 population was constructed through background and foreground selection using X178 as the recurrent parent. The major QTL, qMES20-10, was firstly verified in this BC3F3:4 population. Furthermore, advanced backcross population was constructed through marker-assisted selection, and qMES20-10 was fine-mapped within the interval of 133.3-136.0 Mb on chromosome 10. Moreover, RNA-Seq analysis of two near-isogenic lines screened from the BC3F3:4 families identified the differentially expressed genes, mainly involved in chemical stimulus response, oxidation reduction, and oxidative stress response. These results lay a foundation of further cloning the major QTL qMES20-10.

Key words: maize, deep-seeding tolerance, QTL, fine mapping, differentially expressed genes

Fig. 1

Phenotyping method and phenotype of the two parents A: diagram of phenotyping method. B: mesocotyl of two parents sowing in 20 cm roseite, scale bar = 1 cm. C: mesocotyl length of two parents; ** means significant difference at P < 0.01."

Table 1

Primers used in this study"

引物
Primer		 物理位置
Position		 正向序列
Forward sequence (5'-3')		 反向序列
Reverse sequence (5'-3')
umc1506 133,239,898 ATAAAGGTTGGCAAAACGTAGCCT AAAAGAAACATGTTCAGTCGAGCG
DST_InD25 133,799,178 TGCGCTTTATTAGGCGAAAC TTTACGCGTTATGGGAGACC
DST_Ind7 134,830,243 GCTTGCTGCATTGTCTTGAA GGCAGATTGACACTGGTGAA
DST_Ind105 136,072,789 AGAGAGACAGCCGCACTTG TCGACCGTACTTGTTCATGG
DST_InD13 136,274,298 GGCAACAGTTCGACGGATTA TCCGGATGATGTTTACATGG
bnlg1028 138,503,281 AGGAAACGAACACAGCAGCT TGCATAGACAAAACCGACGT

Fig. 2

Validation of the major QTL qMES20-10 for deep-seeding tolerance A: mesocotyl length of seedlings in three different genotypes of BC3F3:4 lines. A, H, B denote homozygous X178, heterozygous, and homozygous 3681-4 genotype respectively. P-value is determined by ANOVA for mesocotyl length of different genotypic seedlings. B: QTL-mapping using BC3F3:4 lines in the whole genome."

Fig. 3

Fine mapping of the major QTL qMES20-10 for deep-seeding tolerance A: the locus of target QTL qMES20-1 on bin 10.06. B: fine-mapping utilizing BC4F2:3 lines. R1-R9 represent the nine recombinant types. Black and white bars represent chromosomal segments derived from 3681-4 and X178. ** and * mean significant difference at the P < 0.01 and P < 0.05, respectively; NS means no significant difference."

Fig. 4

Validation of the mapping region using progeny test A: the crossover regions of the recombinants. B: progeny test of the recombinants. Black, white, and grey bars represent homozygous regions for 3681-4, homozygous regions for X178 and heterozygous regions, respectively. n means the number of plants with different genotype; P-values were determined by Student’s t test for mesocotyl length of plants with different genotype."

Fig. 5

Statistics and distribution of differentially expressed genes A: Venn diagram of differentially expressed genes. B: distribution of differentially expressed genes on chromosomes. The big and small circles denote differentially expressed genes of two parents and NILs respectively. P-value is determined by students’ t-test, and red dots represent genes with P-value < 0.0001."

Fig. 6

GO analysis of differentially expressed genes in near-isogenic lines A: grey boxes show the GO terms that can be enriched. B: enriched differentially expressed genes related to plant hormone signal transduction according to KEGG."

[1] Lobell D B, Roberts M J, Schlenker W, Braun N, Little B B, Rejesus R M, Hammer G L. Greater sensitivity to drought accompanies maize yield increase in the U.S. Midwest. Science, 2014,344:516-519.
doi: 10.1126/science.1251423 pmid: 24786079
[2] Molatudi R L, Mariga I K. The effect of maize seed size and depth of planting on seedling emergence and seedling vigour. J Appl Sci Res, 2009,5:2234-2237.
[3] Rebetzke G J, Bruce S E, Kirkegaard J A. Longer coleoptile improve emergence through crop residues to increase seedling number and biomass in wheat (Triticum aestivum L.). Plant Soil, 2005,272:87-100.
doi: 10.1007/s11104-004-4040-8
[4] Zhou L, Wang J K, Yi Q, Wang Y Z, Zhu Y G, Zhang Z H. Quantitative trait loci for seedling vigor in rice under field conditions. Field Crops Res, 2007,100:294-301.
doi: 10.1016/j.fcr.2006.08.003
[5] Spielmeyer W, Hyles J, Joaquim P, Azanza F, Bonnett D, Ellis M E, Moore C, Richards R A. A QTL on chromosome 6A in bread wheat (Triticum aestivum L.) is associated with longer coleoptile, greater seedling vigor and final plant height. Theor Appl Genet, 2007,115:59-66.
doi: 10.1007/s00122-007-0540-2
[6] Zhang Z H, Yu S B, Yu T, Huang Z, Zhu Y G. Mapping quantitative trait loci (QTLs) for seedling-vicror using recombinant inbred lines of rice (Oryza sativa L.). Field Crops Res, 2005,91:161-170.
doi: 10.1016/j.fcr.2004.06.004
[7] Alibu S, Saito Y, Shiwachi H, Irie K. Genotypic variation in coleoptile or mesocotyl lengths of upland rice (Oryza sativa L.) and seedling emergence in deep sowing. Afr J Agric Res, 2012,7:6239-6248.
doi: 10.5897/AJAR
[8] van Ast A, van Delft G J, Graves J D, Fitter A H. Striga seed avoidance by deep planting and no-tillage in sorghum and maize. Int J Pest Manage, 2000,46:251-256.
doi: 10.1080/09670870050206019
[9] Troyer A F. The location of genes governing long first internode of corn. Genetics, 1997,145:1149-1154.
pmid: 9093865
[10] Dungan G H. Response of corn to extremely deep planting. Agron J, 1950,42:256-257.
doi: 10.2134/agronj1950.00021962004200050010x
[11] Flint L H. Light and the elongation of the mesocotyl in corn. Plant Physiol, 1944,19:537-543.
doi: 10.1104/pp.19.3.537 pmid: 16653935
[12] Rebetzke G J, Richards R A, Fettell N A, Long M, Condon A G, Forrester R I, Botwright T L. Genotypic increases in coleoptile length improves stand establishment, vigor and grain yield of deep-sown wheat. Field Crops Res, 2007,100:10-23.
doi: 10.1016/j.fcr.2006.05.001
[13] Lu Q, Zhang M C, Niu X J, Wang C H, Xu Q, Feng Y, Wang S, Yuan X P, Yu H Y, Wang Y P, Wei X H. Uncovering novel loci for mesocotyl elongation and shoot length in indica rice through genome-wide association mapping. Planta, 2016,243:645-657.
doi: 10.1007/s00425-015-2434-x pmid: 26612069
[14] Wu J L, Feng F J, Lian X M, Teng X Y, Wei H B, Yu H H, Xie W B, Yan M, Fan P Q, Li Y, Ma X S, Liu H Y, Yu S B, Wang G W, Zhou F S, Luo L J, Mei H W. Genome-wide association study (GWAS) of mesocotyl elongation based on re-sequencing approach in rice. BMC Plant Biol, 2016,15:218.
doi: 10.1186/s12870-015-0608-0 pmid: 26362270
[15] Zhao Y, Zhao W P, Jiang C H, Wang X L, Xiong H Y, Elana G T, Yin Z G, Chen Y F, Wang X, Xie J Y, Pan Y H, Rashid M R, Zhang H L Li J X, Li Z C. Genetic architecture and candidate genes for deep-sowing tolerance in rice revealed by non-syn GWAS. Front Plant Sci, 2018,9:332.
doi: 10.3389/fpls.2018.00332 pmid: 29616055
[16] 赵光武, 马攀, 王建华, 王国英. 不同玉米自交系耐深播能力鉴定及对深播胁迫的生理响应. 玉米科学, 2009,17(5):9-13.
Zhao G W, Ma P, Wang J H, Wang G Y. Identification of deep-seeding tolerance in different maize inbred lines and their physiological response to deep-seeding condition. J Maize Sci, 2009,17(5):9-13 (in Chinese with English abstract).
[17] Liu H J, Zhang L, Wang J C, Li C S, Zeng X, Xie S P, Zhang Y Z, Liu S S, Hu S L, Wang J H, Lee M, Lübberstedt T, Zhao G W. Quantitative trait locus analysis for deep-sowing germination ability in the maize IBM Syn10 DH population. Front Plant Sci, 2017,8:813.
doi: 10.3389/fpls.2017.00813 pmid: 28588594
[18] Henry A, Swamy B P, Dixit S, Torres R D, Batoto T C, Manalili M, Anantha M S, Mandal N P, Kumar A. Physiological mechanisms contributing to the QTL-combination effects on improved performance of IR64 rice NILs under drought. J Exp Bot, 2015,66:1787-1799.
doi: 10.1093/jxb/eru506 pmid: 25680791
[19] 饶志明, 董海涛, 庄杰云, 柴荣耀, 樊叶杨, 李德葆, 郑康乐. 水稻抗稻瘟病近等基因系的cDNA微阵列分析. 遗传学报, 2002,29:887-893.
Rao Z M, Dong H T, Zhuang Z J, Chai R Y, Fan Y Y, Li D B, Zheng K L. Analysis of gene expression profiles during host-Magnaporthe grisea interactions in a pair of near isogenetic lines of rice. Acta Genet Sin, 2002,29:887-893 (in Chinese with English abstract).
[20] Zhao G, Fu J, Wang G, Ma P, Wu L, Wang J H. Gibberellin- induced mesocotyl elongation in deep-sowing tolerant maize inbred line 3681-4. Plant Breed, 2010,129:87-91.
doi: 10.1111/pbr.2010.129.issue-1
[21] Zhang H W, Ma P, Zhao Z N, Zhao G W, Tian B H, Wang J H, Wang G Y. Mapping QTL controlling maize deep-seeding tolerance-related traits and confirmation of a major QTL for mesocotyl length. Theor Appl Genet, 2012,124:223-232.
doi: 10.1007/s00122-011-1700-y
[22] Prigge V, Xu X W, Li L, Babu R, Chen S J, Atlin G N, Melchinger A E. New insights into the genetics of in vivo induction of maternal haploids, the backbone of doubled haploid technology in maize. Genetics, 2012,190:781-793.
doi: 10.1534/genetics.111.133066
[23] Chen D H, Ronald P C. A rapid DNA min preparation method suitable for AFLP and other PCR applications. Plant Mol Biol Rep, 1999,17:53-57.
doi: 10.1023/A:1007585532036
[24] Settles A M, Bagadion A M, Bai F, Zhang J, Barron B, Leach K, Mudunkothge J S, Hoffner C, Bihmidine S, Finefield E, Hibbard J, Dieter E, Malidelis I A, Gustin J L, Karoblyte V, Tseung C W, Braun D M. Efficient molecular marker design using the MaizeGDB Mo17 SNPs and Indels track. G3: Genes Genom Genet, 2014,4:1143-1145.
doi: 10.1534/g3.114.010454 pmid: 24747759
[25] Li H H, Ribaut J M, Li Z L, Wang J K. Inclusive composite interval mapping (ICIM) for digenic epistasis of quantitative traits in biparental populations. Theor Appl Genet, 2008,116:243-260.
doi: 10.1007/s00122-007-0663-5
[26] Revele W. Procedures for Personality and Psychological Research. Evanston, IL, USA: Northwestern University, 2015.
[27] Rio D C, Ares M, Hannon G J, Nilsen T W. Purification of RNA using TRIzol (TRI reagent). Cold Spring Harb Protoc, 2010,6:0-0.
[28] Yang Q, Zhang D F, Xu M L. A sequential quantitative trait locus fine-mapping strategy using recombinant-derived progeny. J Integr Plant Biol, 2012,54:228-237.
doi: 10.1111/j.1744-7909.2012.01108.x
[29] Von Korff M, Wang H, Léon J, Pillen K. AB-QTL analysis in spring barley: II. Detection of favourable exotic alleles for agronomic traits introgressed from wild barley (H. vulgare ssp. spontaneum). Theor Appl Genet, 2006,112:1221-1231.
doi: 10.1007/s00122-006-0223-4
[30] Ghosh S, Chan C K. Analysis of RNA-Seq data using TopHat and Cufflinks. Methods Mol Biol, 2016,1374:339-361.
doi: 10.1007/978-1-4939-3167-5_18 pmid: 26519415
[31] Trapnell C, Williams B A, Pertea G, Mortazavi A, Kwan G, van Baren M J, Salzberg S L, Wold B J, Pachter L. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol, 2010,28:511-515.
doi: 10.1038/nbt.1621 pmid: 20436464
[32] Anders S, Huber W. Differential expression analysis for sequence count data. Genome Biol, 2010,11:R106.
doi: 10.1186/gb-2010-11-10-r106 pmid: 20979621
[33] Tian T, Liu Y, Yan H Y, You Q, Yi X, Du Z, Xu W Y, Su Z. agriGO v2.0: a GO analysis toolkit for the agricultural community. Nucleic Acids Res, 2017,45:W122-W129.
doi: 10.1093/nar/gkx382 pmid: 28472432
[34] Habib A, Powell J J, Stiller J, Liu M, Shabala S, Zhou M X, Gardiner D M, Liu C J. A multiple near isogenic line (multi-NIL) RNA-Seq approach to identify candidate genes underpinning QTL. Theor Appl Genet, 2018,131:613-624.
doi: 10.1007/s00122-017-3023-0 pmid: 29170790
[35] Glagoleva A Y, Shmakov N A, Shoeva O Y, Vasiliev G V, Shatskaya N V, Börner A, Afonnikov D A, Khlestkina E K. Metabolic pathways and genes identified by RNA-Seq analysis of barley near-isogenic lines differing by allelic state of the Black lemma and pericarp (Blp) gene. BMC Plant Biol, 2017,17:182.
doi: 10.1186/s12870-017-1124-1 pmid: 29143606
[36] Smets R, Le J, Prinsen E, Verbelen J P, Van Onckelen H A. Cytokinin-induced hypocotyl elongation in light-grownArabidopsis plants with inhibited ethylene action or indole-3-acetic acid transport. Planta, 2005,221:39-47.
doi: 10.1007/s00425-004-1421-4 pmid: 15843964
[37] Hayashi Y, Takahashi K, Inoue S, Kinoshita T. Abscisic acid suppresses hypocotyl elongation by dephosphorylating plasma membrane H+-ATPase in Arabidopsis thaliana. Plant Cell Physiol, 2014,55:845-853.
doi: 10.1093/pcp/pcu028 pmid: 24492258
[38] Luo Q, Lian H L, He S B, Li L, Jia K P, Yang H Q. COP1 and PhyB physically interact with PIF1 to regulate its stability and photomorphogenic development in Arabidopsis. Plant Cell, 2014,26:2441-2456.
doi: 10.1105/tpc.113.121657 pmid: 24951480
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