[en] The evaluation of the kernel oil content and fatty acid composition in maize is crucial for understanding maize nutrition. This study utilized an association population of 278 inbred lines and a F2 population of 229 individuals to identify candidate genes for 8 kernel weight and oil traits. By employing two genome-wide association study (GWAS) models, the K model and Q+K model, key SNP loci and candidate genes were identified. A total of 10 pleiotropic quantitative trait loci (QTLs) were discovered that collectively encompassed 82 candidate genes. Notably, the SAD gene catalyzed the conversion of stearoyl-acyl carrier protein (ACP) to oleoyl-ACP, playing a crucial role in regulating the content of unsaturated fatty acids in plants. Three candidate genes were identified through three methods (GWAS, QTL mapping, and RNA-seq), with the FALDH gene playing a role in regulating the grain oil content. Through the integration of GWAS analysis and QTL mapping, one stable QTL related to the oil content (qOC5) and one stable QTL related to arachidic acid (qAA9) were identified. Among them, the FAE2 gene was located in qAA9, which plays a crucial role in regulating the fatty acid content in plants. Additionally, the gene TT12, identified through a combination of GWAS and RNA-seq analyses, has been found to play a pivotal role in seed development. Overall, these findings provide a foundation for deeper insights into the genetic mechanisms underlying maize oil traits and offer valuable insights for molecular marker-assisted breeding.
Disciplines :
Genetics & genetic processes
Author, co-author :
Zhang, Lijun ✱; Guangxi Sugarcane Bio-breeding Laboratory, State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530005, China
Song, Yuhan ✱; Université de Liège - ULiège > TERRA Research Centre > Plant Sciences ; National Key Laboratory for Tropical Crop Breeding, Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangzhou 518120, China
Chen, Meiyan; Guangxi Sugarcane Bio-breeding Laboratory, State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530005, China
Hu, Chunyu; Guangxi Sugarcane Bio-breeding Laboratory, State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530005, China
Wang, Wanru; Guangxi Sugarcane Bio-breeding Laboratory, State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530005, China
Zhou, Xunbo ; College of Agriculture, Guangxi University, Nanning 530005, China
Hao, Xiaoqin; College of Agriculture, Guangxi University, Nanning 530005, China
Zhang, Xingtan ; National Key Laboratory for Tropical Crop Breeding, Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangzhou 518120, China
Yang, Xiping ; Guangxi Sugarcane Bio-breeding Laboratory, State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530005, China ; College of Agriculture, Guangxi University, Nanning 530005, China
✱ These authors have contributed equally to this work.
Language :
English
Title :
Integrating GWAS, QTL Mapping, and RNA-seq to Identify Candidate Genes for Kernel Weight and Oil Traits in Maize (Zea mays ssp. mays).
NSCF - National Natural Science Foundation of China
Funding text :
This work was supported by the Science and Technology Major Project of Guangxi (GK AD25069107), the National Natural Science Foundation of China (31960429), and the \u201COne Hundred Person\u201D Project of Guangxi Province.
Luo, M. J.; Lu, B. S.; Shi, Y. X.; Zhao, Y. X.; Liu, J. L.; Zhang, C. Y.; Wang, Y. D.; Liu, H.; Shi, Y. M.; Fan, Y. L.; Xu, L.; Wang, R.; Zhao, J. Genetic basis of the oil biosynthesis in ultra-high-oil maize grains with an oil content exceeding 20. Front. Plant Sci. 2023, 14, 1168216 10.1021/acs.jafc.3c02935
Ndlovu, N.; Kachapur, R. M.; Beyene, Y.; Das, B.; Ogugo, V.; Makumbi, D.; Spillane, C.; McKeown, P. C.; Prasanna, B. M.; Gowda, M. Linkage mapping and genomic prediction of grain quality traits in tropical maize (Zea mays L.). Front Genet 2024, 15, 1353289 10.3389/fgene.2024.1353289
Shi, M.; Sun, J.; Jiang, F.; Shaw, R. K.; Ijaz, B.; Fan, X. Mining of oil content genes in recombinant maize inbred lines with introgression from temperate and tropical germplasm. Int. J. Mol. Sci. 2024, 25 (19), 10813, 10.3390/ijms251910813
Wei, M.; Fu, J.; Li, X.; Wang, Y.; Li, Y. Influence of dent corn genetic backgrounds on QTL detection for plant-height traits and their relationships in high-oil maize. J. Appl. Genet 2009, 50 (3), 225–234, 10.1007/BF03195676
Shi, T. Q.; Wang, L. R.; Zhang, Z. X.; Sun, X. M.; Huang, H. Stresses as first-line tools for enhancing lipid and carotenoid production in microalgae. Front Bioeng Biotechnol 2020, 8, 610, 10.3389/fbioe.2020.00610
Li-Beisson, Y.; Shorrosh, B.; Beisson, F.; Andersson, M. X.; Arondel, V.; Bates, P. D.; Baud, S.; Bird, D.; Debono, A.; Durrett, T. P.; Franke, R. B.; Graham, I. A.; Katayama, K.; Kelly, A. A.; Larson, T.; Markham, J. E.; Miquel, M.; Molina, I.; Nishida, I.; Rowland, O.; Samuels, L.; Schmid, K. M.; Wada, H.; Welti, R.; Xu, C.; Zallot, R.; Ohlrogge, J. Acyl-lipid metabolism. Arabidopsis Book 2013, 11, e0161 10.1199/tab.0161
Beló, A.; Zheng, P.; Luck, S.; Shen, B.; Meyer, D. J.; Li, B.; Tingey, S.; Rafalski, A. Whole genome scan detects an allelic variant of fad2 associated with increased oleic acid levels in maize. Mol. Genet Genomics 2008, 279 (1), 1–10, 10.1007/s00438-007-0289-y
Fang, H.; Fu, X.; Ge, H.; Zhang, A.; Shan, T.; Wang, Y.; Li, P.; Wang, B. Genetic basis of maize kernel oil-related traits revealed by high-density SNP markers in a recombinant inbred line population. BMC Plant Biol. 2021, 21 (1), 344, 10.1186/s12870-021-03089-0
Shen, B.; Allen, W. B.; Zheng, P.; Li, C.; Glassman, K.; Ranch, J.; Nubel, D.; Tarczynski, M. C. Expression of ZmLEC1 and ZmWRI1 increases seed oil production in maize. Plant Physiol 2010, 153 (3), 980–987, 10.1104/pp.110.157537
Zheng, P.; Allen, W. B; Roesler, K.; Williams, M. E; Zhang, S.; Li, J.; Glassman, K.; Ranch, J.; Nubel, D.; Solawetz, W.; Bhattramakki, D.; Llaca, V.; Deschamps, S.; Zhong, G.-Y.; Tarczynski, M. C; Shen, B. A phenylalanine in DGAT is a key determinant of oil content and composition in maize. Nat. Genet. 2008, 40 (3), 367–372, 10.1038/ng.85
Du, H.; Huang, M.; Hu, J.; Li, J. Modification of the fatty acid composition in Arabidopsis and maize seeds using a stearoyl-acyl carrier protein desaturase-1 (ZmSAD1) gene. BMC Plant Biol. 2016, 16 (1), 137, 10.1186/s12870-016-0827-z
Zhang, P.; Allen, W. B.; Nagasawa, N.; Ching, A. S.; Heppard, E. P.; Li, H.; Hao, X.; Li, X.; Yang, X.; Yan, J.; Nagato, Y.; Sakai, H.; Shen, B.; Li, J A transposable element insertion within ZmGE2 gene is associated with increase in embryo to endosperm ratio in maize. Theor. Appl. Genet. 2012, 125 (7), 1463–1471, 10.1007/s00122-012-1926-3
Hu, Y.; Colantonio, V.; Muller, B. S. F.; Leach, K. A.; Nanni, A.; Finegan, C.; Wang, B.; Baseggio, M.; Newton, C. J.; Juhl, E. M.; Hislop, L.; Gonzalez, J. M.; Rios, E. F.; Hannah, L. C.; Swarts, K.; Gore, M. A.; Hennen-Bierwagen, T. A.; Myers, A. M.; Settles, A. M.; Tracy, W. F.; Resende, M. F. R. Genome assembly and population genomic analysis provide insights into the evolution of modern sweet corn. Nat. Commun. 2021, 12 (1), 1227, 10.1038/s41467-021-21380-4
Guo, Y.; Yang, X.; Chander, S.; Yan, J.; Zhang, J.; Song, T.; Li, J. Identification of unconditional and conditional QTL for oil, protein and starch content in maize. Crop Journal 2013, 1 (1), 34–42, 10.1016/j.cj.2013.07.010
Alrefai, R.; Berke, T. G.; Rocheford, T. R. Quantitative trait locus analysis of fatty acid concentrations in maize. Genome 1995, 38 (5), 894–901, 10.1139/g95-118
Mangolin, C.; de Souza, C., Jr; Garcia, A. A. F.; Garcia, A.; Sibov, S.; De Souza, A. Mapping QTLs for kernel oil content in a tropical maize population. Euphytica 2004, 137 (2), 251–259, 10.1023/B:EUPH.0000041588.95689.47
Yang, Z.; Li, X.; Zhang, N.; Zhang, Y. N.; Jiang, H. W.; Gao, J.; Kuai, B. K.; Ding, Y. L.; Huang, X. Q. Detection of quantitative trait loci for kernel oil and protein concentration in a B73 and Zheng58 maize cross. Genet Mol. Res. 2016, 15, (3)10.4238/gmr.15038951.
Zhang, X.; Ren, Z.; Luo, B.; Zhong, H.; Ma, P.; Zhang, H.; Hu, H.; Wang, Y.; Zhang, H.; Liu, D.; Wu, L.; Nie, Z.; Zhu, Y.; He, W.; Zhang, S.; Su, S.; Shen, Y.; Gao, S. Genetic architecture of maize yield traits dissected by QTL mapping and GWAS in maize. Crop Journal 2022, 10 (2), 436–446, 10.1016/j.cj.2021.07.008
Luo, X.; Wang, B.; Gao, S.; Zhang, F.; Terzaghi, W.; Dai, M. Genome-wide association study dissects the genetic bases of salt tolerance in maize seedlings. J. Integr Plant Biol. 2019, 61 (6), 658–674, 10.1111/jipb.12797
Liu, N.; Xue, Y.; Guo, Z.; Li, W.; Tang, J. Genome-wide association study identifies candidate genes for starch content regulation in maize kernels. Front Plant Sci. 2016, 7, 1046, 10.3389/fpls.2016.01046
Zhu, X. M.; Shao, X. Y.; Pei, Y. H.; Guo, X. M.; Li, J.; Song, X. Y.; Zhao, M. A. Genetic diversity and genome-wide association study of major ear quantitative traits using high-density SNPs in maize. Front Plant Sci. 2018, 9, 966, 10.3389/fpls.2018.00966
Li, H.; Peng, Z.; Yang, X.; Wang, W.; Fu, J.; Wang, J.; Han, Y.; Chai, Y.; Guo, T.; Yang, N.; Liu, J.; Warburton, M. L; Cheng, Y.; Hao, X.; Zhang, P.; Zhao, J.; Liu, Y.; Wang, G.; Li, J.; Yan, J. Genome-wide association study dissects the genetic architecture of oil biosynthesis in maize kernels. Nat. Genet. 2013, 45 (1), 43–50, 10.1038/ng.2484
Li, C.; Jia, Y.; Zhou, R.; Liu, L.; Cao, M.; Zhou, Y.; Wang, Z.; Di, H. GWAS and RNA-seq analysis uncover candidate genes associated with alkaline stress tolerance in maize (Zea mays L.) seedlings. Front Plant Sci. 2022, 13, 963874 10.3389/fpls.2022.963874
Wan, X.; Liu, Q.; Dong, B.; Vibhakaran Pillai, S.; Huang, F. H.; Singh, S. P.; Zhou, X. R. Molecular and biochemical analysis of the castor caruncle reveals a set of unique genes involved in oil accumulation in non-seed tissues. Biotechnol Biofuels 2019, 12, 158, 10.1186/s13068-019-1496-6
Furuhashi, M.; Hiramitsu, S.; Mita, T.; Omori, A.; Fuseya, T.; Ishimura, S.; Watanabe, Y.; Hoshina, K.; Matsumoto, M.; Tanaka, M.; Moniwa, N.; Yoshida, H.; Ishii, J.; Miura, T. Reduction of circulating FABP4 level by treatment with omega-3 fatty acid ethyl esters. Lipids Health Dis 2016, 15, 5, 10.1186/s12944-016-0177-8
Ruan, Y.; Yu, B.; Knox, R. E.; Zhang, W.; Singh, A. K.; Cuthbert, R.; Fobert, P.; DePauw, R.; Berraies, S.; Sharpe, A.; Fu, B. X.; Sangha, J. Conditional mapping identified quantitative trait loci for grain protein concentration expressing independently of grain yield in Canadian Durum wheat. Front. Plant Sci. 2021, 12, 642955 10.3389/fpls.2021.642955
Sandhu, K. S.; You, F. M.; Conner, R. L.; Balasubramanian, P. M.; Hou, A. Genetic analysis and QTL mapping of the seed hardness trait in a black common bean (Phaseolus vulgaris) recombinant inbred line (RIL) population. Mol. Breed 2018, 38 (3), 34, 10.1007/s11032-018-0789-y
Zhang, L.; Wang, W.; Chen, M.; Wang, Z.; Yang, H.; Duan, Y.; Hu, C.; Tang, S.; Liu, P.; Zhou, X.; Yang, X. Deciphering the genetic basis of sugar cane (Saccharum spontaneum L) root system and related traits under nitrogen stress through the integration of genome-wide association studies and RNA-seq. J. Agric. Food Chem. 2025, 73 (5), 3246–3256, 10.1021/acs.jafc.4c08169
Zhou, X.; Stephens, M. Genome-wide efficient mixed-model analysis for association studies. Nat. Genet. 2012, 44 (7), 821–824, 10.1038/ng.2310
Turner, S. D. qqman: an R package for visualizing GWAS results using QQ and manhattan plots. Biorxiv Preprint, 2014. https://doi.org/10.1101/005165 (2024-8-15).
Zhang, B.; Huang, Y.; Zhang, L.; Zhou, Z.; Zhou, S.; Duan, W.; Yang, C.; Gao, Y.; Li, S.; Chen, M.; Li, Y.; Yang, X.; Zhang, G.; Huang, D. Genome-wide association study unravels quantitative trait loci and genes associated with yield-related traits in sugarcane. J. Agric. Food Chem. 2023, 71 (44), 16815–16826, 10.1021/acs.jafc.3c02935
Zhang, C.; Dong, S. S.; Xu, J. Y.; He, W. M.; Yang, T. L. PopLDdecay: a fast and effective tool for linkage disequilibrium decay analysis based on variant call format files. Bioinformatics 2019, 35 (10), 1786–1788, 10.1093/bioinformatics/bty875
Qin, M. F.; Li, L. T.; Singh, J.; Sun, M. Y.; Bai, B.; Li, S. W.; Ni, J. P.; Zhang, J. Y.; Zhang, X.; Wei, W. L. Construction of a high-density bin-map and identification of fruit quality-related quantitative trait loci and functional genes in pear. Horticulture Research 2022, 9, uhac141, 10.1093/hr/uhac141
Broman, K. W.; Wu, H.; Sen, S.; Churchill, G. A. R/qtl: QTL mapping in experimental crosses. Bioinformatics 2003, 19 (7), 889–890, 10.1093/bioinformatics/btg112
González-Thuillier, I.; Pellny, T. K.; Tosi, P.; Mitchell, R. A. C.; Haslam, R.; Shewry, P. R. Accumulation and deposition of triacylglycerols in the starchy endosperm of wheat grain. J. Cereal Sci. 2021, 98, 103167 10.1016/j.jcs.2021.103167
Kibe, M.; Nyaga, C.; Nair, S. K.; Beyene, Y.; Das, B.; M, S. L.; Bright, J. M.; Makumbi, D.; Kinyua, J.; Olsen, M. S. Combination of linkage mapping, GWAS, and GP to dissect the genetic basis of common rust resistance in tropical maize germplasm. Int. J. Mol. Sci. 2020, 21 (18), 6518, 10.3390/ijms21186518
Wei, Y.; Lin, M.; Oliver, D. J.; Schnable, P. S. The roles of aldehyde dehydrogenases (ALDHs) in the PDH bypass of Arabidopsis. BMC Biochem 2009, 10, 7, 10.1186/1471-2091-10-7
Hirayama, T.; Oka, A. Novel protein kinase of Arabidopsis thaliana (APK1) that phosphorylates tyrosine, serine and threonine. Plant Mol. Biol. 1992, 20 (4), 653–662, 10.1007/BF00046450
Li, P.; Li, Z.; Xie, G.; Zhang, J. Trihelix transcription factor ZmThx20 is required for kernel development in maize. Int. J. Mol. Sci. 2021, 22 (22), 12137, 10.3390/ijms222212137
Jiao, P.; Jiang, Z.; Wei, X.; Liu, S.; Qu, J.; Guan, S.; Ma, Y. Overexpression of the homeobox-leucine zipper protein ATHB-6 improves the drought tolerance of maize (Zea mays L.). Plant Sci. 2022, 316, 111159 10.1016/j.plantsci.2021.111159
Jia, H.; Li, M.; Li, W.; Liu, L.; Jian, Y.; Yang, Z.; Shen, X.; Ning, Q.; Du, Y.; Zhao, R.; Jackson, D.; Yang, X.; Zhang, Z. A serine/threonine protein kinase encoding gene KERNEL NUMBER PER ROW6 regulates maize grain yield. Nat. Commun. 2020, 11 (1), 988, 10.1038/s41467-020-14746-7
Li, C.; Song, Y.; Zhu, Y.; Cao, M.; Han, X.; Fan, J.; Lu, Z.; Xu, Y.; Zhou, Y.; Zeng, X.; Zhang, Z.; Dong, L.; Sun, D.; Wang, Z.; Di, H. GWAS analysis reveals candidate genes associated with density tolerance (ear leaf structure) in maize (Zea mays L.). Journal of Integrative Agriculture 2025, 24 (6), 2046–2062, 10.1016/j.jia.2024.01.023
Wu, X.; Feng, H.; Wu, D.; Yan, S.; Zhang, P.; Wang, W.; Zhang, J.; Ye, J.; Dai, G.; Fan, Y.; Li, W.; Song, B.; Geng, Z.; Yang, W.; Chen, G.; Qin, F.; Terzaghi, W.; Stitzer, M.; Li, L.; Xiong, L.; Yan, J.; Buckler, E.; Yang, W.; Dai, M. Using high-throughput multiple optical phenotyping to decipher the genetic architecture of maize drought tolerance. Genome Biol. 2021, 22 (1), 185, 10.1186/s13059-021-02377-0
Li, C.; Huang, Y.; Huang, R.; Wu, Y.; Wang, W. The genetic architecture of amylose biosynthesis in maize kernel. Plant Biotechnol J. 2018, 16 (2), 688–695, 10.1111/pbi.12821
Borrego-Benjumea, A.; Carter, A.; Zhu, M.; Tucker, J. R.; Zhou, M.; Badea, A. Genome-wide association study of waterlogging tolerance in barley (Hordeum vulgare L.) under controlled field conditions. Front Plant Sci. 2021, 12, 711654 10.3389/fpls.2021.711654
Duan, H.; Li, J.; Sun, Y.; Xiong, X.; Sun, L.; Li, W.; Gao, J.; Li, N.; Zhang, J.; Cui, J.; Fu, Z.; Zhang, X.; Tang, J. Candidate loci for leaf angle in maize revealed by a combination of genome-wide association study and meta-analysis. Front Genet 2022, 13, 1004211 10.3389/fgene.2022.1004211
Sharma, S. K.; MacKenzie, K.; McLean, K.; Dale, F.; Daniels, S.; Bryan, G. J. Linkage disequilibrium and evaluation of genome-wide association mapping models in tetraploid potato. G3 (Bethesda) 2018, 8 (10), 3185–3202, 10.1534/g3.118.200377
Pasam, R. K.; Sharma, R.; Malosetti, M.; van Eeuwijk, F. A.; Haseneyer, G.; Kilian, B.; Graner, A. Genome-wide association studies for agronomical traits in a world wide spring barley collection. BMC Plant Biol. 2012, 12, 16, 10.1186/1471-2229-12-16
Kaler, A. S.; Gillman, J. D.; Beissinger, T.; Purcell, L. C. Comparing different statistical models and multiple testing corrections for association mapping in soybean and maize. Front Plant Sci. 2020, 10, 1794, 10.3389/fpls.2019.01794
Zhao, Z.; Zhang, H.; Fu, Z.; Chen, H.; Lin, Y.; Yan, P.; Li, W.; Xie, H.; Guo, Z.; Zhang, X.; Tang, J. Genetic-based dissection of arsenic accumulation in maize using a genome-wide association analysis method. Plant Biotechnol. J. 2018, 16 (5), 1085–1093, 10.1111/pbi.12853
Yu, J.; Pressoir, G.; Briggs, W. H.; Vroh Bi, I.; Yamasaki, M.; Doebley, J. F.; McMullen, M. D.; Gaut, B. S.; Nielsen, D. M.; Holland, J. B.; Kresovich, S.; Buckler, E. S. A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nat. Genet. 2006, 38 (2), 203–208, 10.1038/ng1702
Wang, Y.; Ran, F.; Yin, X.; Jiang, F.; Bi, Y.; Shaw, R. K.; Fan, X. Genome-wide association studies on the kernel row number in a multi-parent maize population. Int. J. Mol. Sci. 2024, 25 (6), 3377, 10.3390/ijms25063377
Yang, Y.; Zhao, T.; Wang, F.; Liu, L.; Liu, B.; Zhang, K.; Qin, J.; Yang, C.; Qiao, Y. Identification of candidate genes for soybean seed coat-related traits using QTL mapping and GWAS. Front Plant Sci. 2023, 14, 1190503 10.3389/fpls.2023.1190503
Hu, D.; Kan, G.; Hu, W.; Li, Y.; Hao, D.; Li, X.; Yang, H.; Yang, Z.; He, X.; Huang, F.; Yu, D. Identification of loci and candidate genes responsible for pod dehiscence in soybean via genome-wide association analysis across multiple environments. Front. Plant Sci. 2019, 10, 811, 10.3389/fpls.2019.00811
Guo, T.; Yang, J.; Li, D.; Sun, K.; Luo, L.; Xiao, W.; Wang, J.; Liu, Y.; Wang, S.; Wang, H.; Chen, Z. Integrating GWAS, QTL, mapping and RNA-seq to identify candidate genes for seed vigor in rice (Oryza sativa L.). Molecular Breeding 2019, 39 (6), 87, 10.1007/s11032-019-0993-4
Zhong, Y.; Zhao, Y.; Wang, Y.; Niu, J.; Sun, Z.; Chen, J.; Luan, M. Transcriptome analysis and GC-MS profiling of key fatty acid biosynthesis genes in Akebia trifoliata (Thunb.) Koidz Seeds. Biology (Basel) 2022, 11 (6), 855, 10.3390/biology11060855
Pushkova, E. N.; Povkhova, L. V.; Dvorianinova, E. M.; Novakovskiy, R. O.; Rozhmina, T. A.; Gryzunov, A. A.; Sigova, E. A.; Zhernova, D. A.; Borkhert, E. V.; Turba, A. A.; Yablokov, A. G.; Bolsheva, N. L.; Dmitriev, A. A.; Melnikova, N. V. Expression of FAD and SAD genes in developing seeds of flax varieties under different growth conditions. Plants (Basel) 2024, 13 (7), 956, 10.3390/plants13070956
Yan, B.; Xu, X.; Gu, Y.; Zhao, Y.; Zhao, X.; He, L.; Zhao, C.; Li, Z.; Xu, J. Genome-wide characterization and expression profiling of diacylglycerol acyltransferase genes from maize. Genome 2018, 61 (10), 735–743, 10.1139/gen-2018-0029
Zhu, T.; Wu, S.; Zhang, D.; Li, Z.; Xie, K.; An, X.; Ma, B.; Hou, Q.; Dong, Z.; Tian, Y.; Li, J.; Wan, X. Genome-wide analysis of maize GPAT gene family and cytological characterization and breeding application of ZmMs33/ZmGPAT6 gene. Theor. Appl. Genet. 2019, 132 (7), 2137–2154, 10.1007/s00122-019-03343-y
Mustiga, G. M.; Morrissey, J.; Stack, J. C.; DuVal, A.; Royaert, S.; Jansen, J.; Bizzotto, C.; Villela-Dias, C.; Mei, L.; Cahoon, E. B.; Seguine, E.; Marelli, J. P.; Motamayor, J. C. Identification of climate and genetic factors that control fat content and fatty acid composition of Theobroma cacao L. Beans. Front. Plant Sci. 2019, 10, 1159, 10.3389/fpls.2019.01159
Lindqvist, Y.; Huang, W.; Schneider, G.; Shanklin, J. Crystal structure of delta9 stearoyl-acyl carrier protein desaturase from castor seed and its relationship to other di-iron proteins. Embo j 1996, 15 (16), 4081–4092, 10.1002/j.1460-2075.1996.tb00783.x
Haslam, T. M.; Kunst, L. Extending the story of very-long-chain fatty acid elongation. Plant Sci. 2013, 210, 93–107, 10.1016/j.plantsci.2013.05.008
Ma, L.; Li, G. FAR1-RELATED SEQUENCE (FRS) and FRS-RELATED FACTOR (FRF) family proteins in Arabidopsis growth and development. Front Plant Sci. 2018, 9, 692, 10.3389/fpls.2018.00692
