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Journal of Integrative Agriculture  2025, Vol. 24 Issue (7): 2475-2491    DOI: 10.1016/j.jia.2024.11.014
Crop Science Advanced Online Publication | Current Issue | Archive | Adv Search |
Genetic analysis of maize crude fat content by multi-locus genome-wide association study

Dan Lü1, Jianxin Li2, Xuehai Zhang2, Ran Zheng1, Aoni Zhang1, Jingyun Luo3, Bo Tong1, Hongbing Luo1, Jianbing Yan3, Min Deng1#

1 College of Agronomy, Hunan Agricultural University/Yuelushan Laboratory, Hunan Agricultural University/Maize Engineering Technology Research Center of Hunan Province, Changsha 410128, China

2 National Key Laboratory of Wheat and Maize Crop Science/College of Agronomy, Henan Agricultural University, Zhengzhou 450002, China

3 National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China

 Highlights 
The genetic architecture of crude fat content in maize kernels was studied by genome-wide association studies using six models.
A total of 744 significant quantitative trait nucleotides (QTNs) and 64 novel QTNs were found for the crude fat content in maize kernels.
Four known genes were identified, and eight promising candidate genes were successfully screened.
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摘要  

粗脂肪是玉米籽粒的重要营养成分。然而,目前玉米籽粒粗脂肪含量的遗传机制仍然不清晰前人研究使用单一模型进行玉米籽粒粗脂肪含量的全基因组关联分析GWAS),且群体数量有限,可能导致假阳性位点,阻碍功能基因的鉴定。因此,本研究利用495玉米自交系,结合125万个单核苷酸多态性标记SNP),利用6个模型进行GWAS分析,鉴定控制粗脂肪含量的数量性状核苷酸位点QTNs并挖掘关键基因。结果表明,粗脂肪含量变异范围较广0.62%~16.03%,且广义遗传力较高96.23%)。通过GWAS分析在6个模型中共检测到744个显著的QTNs,其中147QTNs定位在不同模型、环境和方法中。基于147个共定位的QTNs,在每个QTN的上下50 kb区间内搜索候选基因。最终筛选到8个与粗脂肪含量相关的候选基因(GRMZM2G169089GRMZM2G117935GRMZM2G002075GRMZM2G368838GRMZM2G058496GRMZM2G090669GRMZM2G001241GRMZM2G333454),这些基因在玉米自交系B73的籽粒发育过程中高表达。值得注意的是,GRMZM2G169089GRMZM2G117935GRMZM2G002075GRMZM2G368838参与了玉米籽粒亚油酸代谢途径、油脂代谢和籽粒生长发育等途径。此外,共表达网络分析显示,8个候选基因与30个已知基因具有很强的相关性。同时,候选基因编码的蛋白质与其他多种蛋白质相互作用,在玉米籽粒含油量和油酸代谢中起重要作用。候选基因的最佳单倍型可能在不降低玉米产量的情况下提高玉米籽粒的粗脂肪含量。这些结果拓宽了我们对玉米粗脂肪含量遗传机制的认识,并为高粗脂肪含量玉米育种标记辅助选择提供了便利。



Abstract  


Crude fat is an important nutritional component of maize kernels.  However, the genetic mechanisms underlying crude fat content in maize kernels remain elusive.  Previous studies used single-model genome-wide association studies (GWAS) with limited population sizes, which can result in false loci positives and hinder functional gene identification.  Therefore, this study used a population consisting of 495 maize inbred lines, combined with 1.25 million single nucleotide polymorphisms (SNPs), and implemented GWAS using six models to identify quantitative trait nucleotides (QTNs) controlling crude fat content and to mine key genes.  The results revealed a wide variation in crude fat content (0.62–16.03%) and broad-sense heritability (H2) (96.23%).  In total, 744 significant QTNs were detected, with 147 co-located across different models, environments, and methods.  Based on the 147 co-located QTNs, candidate genes were searched at 50 kb up- and down-stream intervals of each QTN.  We finally screened eight candidate genes (GRMZM2G169089, GRMZM2G117935, GRMZM2G002075, GRMZM2G368838, GRMZM2G058496, GRMZM2G090669, GRMZM2G001241, and GRMZM2G333454) related to crude fat content that exhibited high expression levels during kernel development in maize inbred line B73.  Notably, GRMZM2G169089, GRMZM2G117935, GRMZM2G002075, and GRMZM2G368838 are involved in the linoleic acid metabolic pathway, oil metabolism, kernel growth, and development in maize.  Furthermore, co-expression network analysis revealed that the eight candidate genes strongly correlated with 30 known genes.  Proteins encoded by candidate genes interact with other proteins and play an important role in oil content and oleic acid metabolism in maize kernels.  The best haplotypes of candidate genes might increase crude fat content without decreasing maize yield.  These results broaden the understanding of the genetic mechanism of crude fat content and facilitate marker-assisted selection for high-crude fat breeding programs for maize.


Keywords:  maize       crude fat content        GWAS        model        candidate gene  
Received: 02 August 2024   Online: 05 November 2024   Accepted: 08 October 2024
Fund: 

This work was supported by the National Natural Science Foundation of China (32101700), the China Postdoctoral Science Foundation (2022M7111220), the Science and Technology Innovation Program of Hunan Province, China (2021RC2082), and the Postgraduate Scientific Research Innovation Project of Hunan Province, China (CX20230697).

About author:  #Correspondence Min Deng, E-mail: Hdengmin@163.com

Cite this article: 

Dan Lü, Jianxin Li, Xuehai Zhang, Ran Zheng, Aoni Zhang, Jingyun Luo, Bo Tong, Hongbing Luo, Jianbing Yan, Min Deng. 2025. Genetic analysis of maize crude fat content by multi-locus genome-wide association study. Journal of Integrative Agriculture, 24(7): 2475-2491.

Abudigin W I, Bajaber A, Subash-Babu P. 2024. Impact of various dietary lipids on amelioration of biomarkers linked to metabolic syndrome in both healthy and diabetic wistar rats. BMC Nutrition, 10, 75.

Alqudah A M, Sallam A, Stephen Baenziger P, Börner A. 2019. GWAS: Fast-forwarding gene identification and characterization in temperate cereals: Lessons from barley - A review. Journal of Advanced Research, 22, 119–135.

Bates P D. 2016. Understanding the control of acyl flux through the lipid metabolic network of plant oil biosynthesis. Biochimica et Biophysica Acta, 1861, 1214–1225.

Benitez J A, Gernat A G, Murillo J G, Araba M. 1999. The use of high oil corn in broiler diets. Poultry Science, 78, 861–865.

Cernac A, Benning C. 2004. WRINKLED1 encodes an AP2/EREB domain protein involved in the control of storage compound biosynthesis in Arabidopsis. The Plant Journal, 40, 575–585.

Chen J, Zeng B, Zhang M, Xie S J, Wang G K, Hauck A, Lai J S. 2014. Dynamic transcriptome landscape of maize embryo and endosperm development. Plant Physiology, 166, 252–264.

Chen S, Glawischnig E, Jørgensen K, Naur P, Jørgensen B, Olsen C E, Hansen C H, Rasmussen H, Pickett J A, Halkier B A. 2003. CYP79F1 and CYP79F2 have distinct functions in the biosynthesis of aliphatic glucosinolates in Arabidopsis. Plant Journal, 33, 923–937.

Ding L N, Guo X J, Li M, Fu Z L, Yan S Z, Zhu K M, Wang Z, Tan X L. 2019. Improving seed germination and oil contents by regulating the GDSL transcriptional level in Brassica napus. Plant Cell Reports, 38, 243–253.

Ding S, Liu X Y, Wang H C, Wang Y, Tang J J, Yang Y Z, Tan B C. 2019. SMK6 mediates the C-to-U editing at multiple sites in maize mitochondria. Journal of Plant Physiology, 240, 152992.

Downs S M, Marie T A, Ghosh-Jerath S, Leeder S R. 2015. Aligning food-processing policies to promote healthier fat consumption in India. Health Promotion International, 30, 595–605.

Edstam M M, Blomqvist K, Eklöf A, Wennergren U, Edqvist J. 2013. Coexpression patterns indicate that GPI-anchored non-specific lipid transfer proteins are involved in accumulation of cuticular wax, suberin and sporopollenin. Plant Molecular Biology, 83, 625–649.

Edstam M M, Edqvist J. 2014. Involvement of GPI-anchored lipid transfer proteins in the development of seed coats and pollen in Arabidopsis thaliana. Plant Physiology, 152, 32–42.

Fang H, Fu X Y, Ge H Q, Zhang A X, Shan T Y, Wang Y D, Li P, Wang B H. 2021. Genetic basis of maize kernel oil-related traits revealed by high-density SNP markers in a recombinant inbred line population. BMC Plant Biology, 21, 344.

Furmanek T, Demski K, Banaś W, Haslam R, Napier J, Stymne S, Banaś A. 2014. The utilization of the acyl-CoA and the involvement PDAT and DGAT in the biosynthesis of erucic acid-rich triacylglycerols in Crambe seed oil. Lipids, 49, 327–333.

Gao M J, Yin X, Yang W B, Lam S M, Tong X H, Liu J Y, Wang X, Li Q, Shui G H, He Z H. 2017. GDSL lipases modulate immunity through lipid homeostasis in rice. PLoS Pathogens, 13, e1006724.

Guo L, Ma F F, Wei F, Fanella B, Allen D K, Wang X M. 2014. Cytosolic phosphorylating glyceraldehyde-3-phosphate dehydrogenases affect Arabidopsis cellular metabolism and promote seed oil accumulation. The Plant Cell, 26, 3023–3035.

Henderson C R. 1975. Best linear unbiased estimation and prediction under a selection model. Biometrics, 31, 423–447.

Hu X, Yasir M, Zhuo Y J, Cai Y J, Ren X F, Rong J K. 2024. Genomic insights into glume pubescence in durum wheat: GWAS and haplotype analysis implicates TdELD1-1A as a candidate gene. Gene, 909, 148309.

Hu X Y, Sullivan-Gilbert M, Gupta M, Thompson S A. 2006. Mapping of the loci controlling oleic and linolenic acid contents and development of fad2 and fad3 allele-specific markers in canola (Brassica napus L.). Theoretical and Applied Genetics, 113, 497–507.

Huang M, Liu X L, Zhou Y, Summers R M, Zhang Z W. 2019. BLINK: A package for the next level of genome-wide association studies with both individuals and markers in the millions. Gigascience, 8, giy154.

Ingvarsson P K, Street N R. 2011. Association genetics of complex traits in plants. New Phytologist, 189, 909–922.

Jako C, Kumar A, Wei Y, Zou J, Barton D L, Giblin E M, Covello P S, Taylor D C. 2001. Seed-specific over-expression of an Arabidopsis cDNA encoding a diacylglycerol acyltransferase enhances seed oil content and seed weight. Plant Physiology, 126, 861–874.

Jiang L Y, Ma X, Zhao S S, Tang Y Y, Liu F X, Gu P, Fu Y C, Zhu Z F, Cai H W, Sun C Q, Tan L B. 2019. The APETALA2-like transcription factor supernumerary bract controls rice seed shattering and seed size. Plant Cell, 31, 17–36.

Jones A M, Xuan Y, Xu M, Wang R S, Ho C H, Lalonde S, You C H, Sardi M I, Parsa S A, Smith-Valle E, Su T, Frazer K A, Pilot G, Pratelli R, Grossmann G, Acharya B R, Hu H C, Engineer C, Villiers F, Ju C, et al. 2014. Border control - A membrane-linked interactome of Arabidopsis. Science, 344, 711–716.

Karn A, Gillman J D, Flint-Garcia S A. 2017. Genetic analysis of teosinte alleles for kernel composition traits in maize. G3 (Bethesda), 7, 1157–1164.

Katavic V, Agrawal G K, Hajduch M, Harris S L, Thelen J J. 2006. Protein and lipid composition analysis of oil bodies from two Brassica napus cultivars. Proteomics, 6, 4586–4598.

Katavic V, Reed D W, Taylor D C, Giblin E M, Barton D L, Zou J, Mackenzie S L, Covello P S, Kunst L. 1995. Alteration of seed fatty acid composition by an ethyl methanesulfonate-induced mutation in Arabidopsis thaliana affecting diacylglycerol acyltransferase activity. Plant Physiology, 108, 399–409.

Knapp S J, Stroup W W, Ross W M. 1985. Exact confidence intervals for heritability on a progeny mean basis. Crop Science, 25, 192.

Li H, Peng Z Y, Yang X H, Wang W D, Fu J J, Wang J H, Han Y J, Chai Y C, Guo T T, Yang N, Liu J, Warburton M L, Cheng Y B, Hao X M, Zhang P, Zhao J Y, Liu Y J, Wang G Y, Li J S, Yan J B. 2013. Genome-wide association study dissects the genetic architecture of oil biosynthesis in maize kernels. Nature Genetics, 45, 43–50.

Li H, Pinot F, Sauveplane V, Werck-Reichhart D, Diehl P, Schreiber L, Franke R, Zhang P, Chen L, Gao Y W, Liang W Q, Zhang D B. 2010. Cytochrome P450 family member CYP704B2 catalyzes the ω-hydroxylation of fatty acids and is required for anther cutin biosynthesis and pollen exine formation in rice. The Plant Cell, 22, 173–190.

Li L, Liu K H, Sheen J. 2021. Dynamic nutrient signaling networks in plants. Annual Review of Cell and Developmental Biology, 37, 341–367.

Li M, Zhang Y W, Xiang Y, Liu M H, Zhang Y M. 2022. IIIVmrMLM: The R and C++ tools associated with 3VmrMLM, a comprehensive GWAS method for dissecting quantitative traits. Molecular Plant, 15, 1251–1253.

Li N, Gügel I L, Giavalisco P, Zeisler V, Schreiber L, Soll J, Philippar K. 2015. FAX1, a novel membrane protein mediating plastid fatty acid export. PLoS Biology, 13, e1002053.

Li Y L, Niu S Z, Dong Y B, Cui D Q, Wang Y Z, Liu Y Y, Wei M G. 2007. Identification of trait-improving quantitative trait loci for grain yield components from a dent corn inbred line in an advanced backcross BC2F2 population and comparison with its F2:3 population in popcorn. Theoretical and Applied Genetics, 115, 129–140.

Li Y L, Wang Y Z, Wei M G, Li X H, Fu J F. 2009. QTL identification of grain protein concentration and its genetic correlation with starch concentration and grain weight using two populations in maize (Zea mays L.). Journal of Genetics, 88, 61–67.

Liu H J, Luo X, Niu L Y, Xiao Y J, Chen L, Liu J, Wang X Q, Jin M L, Li W Q, Zhang Q H, Yan J B. 2017. Distant eQTLs and non-coding sequences play critical roles in regulating gene expression and quantitative trait variation in maize. Molecular Plant, 10, 414–426.

Liu X, Huang M, Fan B, Buckler E S, Zhang Z. 2016. Iterative usage of fixed and random effect models for powerful and efficient genome-wide association studies. PLoS Genetics, 12, e1005767.

Mertz E T, Bates L S, Nelson O E. 1964. Mutant gene that changes protein composition and increases lysine content of maize endosperm. Science, 145, 279–280.

Napier J A, Graham I A. 2010. Tailoring plant lipid composition: Designer oilseeds come of age. Current Opinion in Plant Biology, 13, 330–337.

Olsen L T, Divon H H, Al R, Fosnes K, Lid S E, Opsahl-Sorteberg H G. 2008. The defective seed5 (des5) mutant: Effects on barley seed development and HvDek1, HvCr4, and HvSal1 gene regulation. Journal of Experimental Botany, 59, 3753–3765.

Segura V, Vilhjálmsson B J, Platt A, Korte A, Seren Ü, Long Q, Nordborg M. 2012. An efficient multi-locus mixed-model approach for genome-wide association studies in structured populations. Nature Genetics, 44, 825–830.

Shen B, Li C, Min Z, Meeley R B, Tarczynski M C, Olsen O A. 2003. sal1 determines the number of aleurone cell layers in maize endosperm and encodes a class E vacuolar sorting protein. Proceedings of the National Academy of Sciences of the United States of America, 100, 6552–6557.

Shigyo M, Hasebe M, Ito M. 2006. Molecular evolution of the AP2 subfamily. Gene, 366, 256–265.

Shockey J M, Gidda S K, Chapital D C, Kuan J C, Dhanoa P K, Bland J M, Rothstein S J, Mullen R T, Dyer J M. 2006. Tung tree DGAT1 and DGAT2 have nonredundant functions in triacylglycerol biosynthesis and are localized to different subdomains of the endoplasmic reticulum. Plant Cell, 18, 2294–2313.

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 Y F. 2020. Decryption of favourable haplotypes and potential candidate genes for five fibre quality properties using a relatively novel genome-wide association study procedure in upland cotton. Industrial Crops and Products, 158, 113004.

Tan W J, Yang Y C, Zhou Y, Huang L P, Xu L, Chen Q F, Yu L J, Xiao S. 2018. Diacylglycerol acyltransferase and diacylglycerol kinse modulate triacylglycerol and phosphatidic acid production in the plant response to freezing stress. Plant Physiology, 177, 1303–1318.

Wan W T, Wu Y, Hu D, Ye F, Wu X P, Qi X Y, Liang H Y, Zhou H Y, Xue J Q, Xu S T, Zhang X H. 2023. Genome-wide association analysis of kernel nutritional quality in two natural maize populations. Molecular Breeding, 43, 18.

Wang Q, Tian F, Pan Y, Buckler E S, Zhang Z. 2014. A SUPER powerful method for genome wide association study. PLoS ONE, 9, e107684.

Warburton M L, Woolfolk S W, Smith J S, Hawkins L K, Castano-Duque L, Lebar M D, Williams W P. 2023. Genes and genetic mechanisms contributing to fall armyworm resistance in maize. The Plant Genome, 16, e20311.

Wei K F, Chen J, Wang Y M, Chen Y H, Chen S X, Lin Y A, Pan S, Zhong X J, Xie D X. 2012. Genome-wide analysis of bZIP-encoding genes in maize. DNA Research, 19, 463–476.

Weis C, Hildebrandt U, Hoffmann T, Hemetsberger C, Pfeilmeier S, König C, Schwab W, Eichmann R, Hückelhoven R. 2014. CYP83A1 is required for metabolic compatibility of Arabidopsis with the adapted powdery mildew fungus Erysiphe cruciferarum. New Phytologist, 202, 1310–1319.

Xie Y H, Feng Y, Chen Q, Zhao F K, Zhou S J, Ding Y, Song X L, Li P, Wang B H. 2019. Genome-wide association analysis of salt tolerance QTLs with SNP markers in maize (Zea mays L.). Genes & Genomics, 41, 1135–1145.

Xu C C, Shanklin J. 2016. Triacylglycerol metabolism, function, and accumulation in plant vegetative tissues. Annual Review of Plant Biology, 67, 179–206.

Yang G H, Dong Y B, Li Y L, Wang Q L, Shi Q L, Zhou Q A. 2013. Verification of QTL for grain starch content and its genetic correlation with oil content using two connected RIL populations in high-oil maize. PLoS ONE, 8, e53770.

Yang N, Lu Y L, Yang X H, Huang J, Zhou Y, Ali F, Wen W W, Liu J, Li J S, Yan J B. 2014. Genome wide association studies using a new nonparametric model reveal the genetic architecture of 17 agronomic traits in an enlarged maize association panel. PLoS Genetics, 10, e1004573.

Yang X H, Guo Y Q, Yan J B, Zhang J, Song T M, Rocheford T, Li J S. 2010. Major and minor QTL and epistasis contribute to fatty acid compositions and oil concentration in high-oil maize. Theoretical and Applied Genetics, 120, 665–678.

Yang X H, Ma H L, Zhang P, Yan J B, Guo Y Q, Song T M, Li J S. 2012. Characterization of QTL for oil content in maize kernels. Theoretical and Applied Genetics, 125, 1169–1179.

Yang Z, Li X, Zhang N, Zhang Y N, Jiang H W, Gao J, Kuai B K, Ding Y L, Huang X. 2016. Detection of quantitative trait loci for kernel oil and protein concentration in a B73 and Zheng58 maize cross. Genetics and Molecular Research, 15, doi: 10.4238/gmr.15038951.

Zhang H J, Yuan Y S, Zhu X X, Xu R Z, Shen H S, Zhang Q, Ge X Z. 2022. The effect of different extraction methods on extraction yield, physicochemical properties, and volatile compounds from field muskmelon seed oil. Foods, 11, 721.

Zhang X L, Wang M, Guan H T, Wen H T, Zhang C Z, Dai C J, Wang J, Pan B, Li J L, Liao H. 2023. Genetic dissection of QTLs for oil content in four maize DH populations. Frontiers in Plant Science, 14, 1174985.

Zhang Y J, Fernie A R. 2023. The role of TCA cycle enzymes in plants. Advanced Biology, 7, e2200238.

Zhao Y P, Wu N, Li W J, Shen J L, Chen C, Li F G, Hou Y X. 2021. Evolution and characterization of acetyl coenzyme A: Diacylglycerol acyltransferase genes in cotton identify the roles of GhDGAT3D in oil biosynthesis and fatty acid composition. Genes (Basel), 12, 1045.

Zheng L, Shockey J, Guo F, Shi L M, Li X G, Shan L, Wan S B, Peng Z Y. 2017. Discovery of a new mechanism for regulation of plant triacylglycerol metabolism: The peanut diacylglycerol acyltransferase-1 gene family transcriptome is highly enriched in alternative splicing variants. Journal of Plant Physiology, 219, 62–70.

Zheng P Z, Allen W B, Roesler K, Williams M E, Zhang S R, Li J M, Glassman K, Ranch J, Nubel D, Solawetz W, Bhattramakki D, Llaca V, Deschamps S, Zhong G Y, Tarczynski M C, Shen B. 2008. A phenylalanine in DGAT is a key determinant of oil content and composition in maize. Nature Genetics, 40, 367–372.

Zheng Y X, Yuan F, Huang Y Q, Zhao Y F, Jia X Y, Zhu L Y, Guo J J. 2021. Genome-wide association studies of grain quality traits in maize. Scientific Reports, 11, 9797.

Zheng Z P, Li Z, He F, Lv J J, Xie B, Yi X Y, Li J M, Li J, Song J H, Pu Z E, Ma J, Peng Y Y, Chen G Y, Wei Y M, Zheng Y L, Li W. 2023. Genome-wide association and linkage mapping strategies reveal the genetic loci and candidate genes of important agronomic traits in Sichuan wheat. Journal of Integrative Agriculture, 22, 3380–3393.

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