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Sahito JH, Zhang H, Gishkori ZGN, Ma C, Wang Z, Ding D, Zhang X, Tang J. Advancements and Prospects of Genome-Wide Association Studies (GWAS) in Maize. Int J Mol Sci 2024; 25:1918. [PMID: 38339196 PMCID: PMC10855973 DOI: 10.3390/ijms25031918] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 01/30/2024] [Accepted: 02/02/2024] [Indexed: 02/12/2024] Open
Abstract
Genome-wide association studies (GWAS) have emerged as a powerful tool for unraveling intricate genotype-phenotype association across various species. Maize (Zea mays L.), renowned for its extensive genetic diversity and rapid linkage disequilibrium (LD), stands as an exemplary candidate for GWAS. In maize, GWAS has made significant advancements by pinpointing numerous genetic loci and potential genes associated with complex traits, including responses to both abiotic and biotic stress. These discoveries hold the promise of enhancing adaptability and yield through effective breeding strategies. Nevertheless, the impact of environmental stress on crop growth and yield is evident in various agronomic traits. Therefore, understanding the complex genetic basis of these traits becomes paramount. This review delves into current and future prospectives aimed at yield, quality, and environmental stress resilience in maize and also addresses the challenges encountered during genomic selection and molecular breeding, all facilitated by the utilization of GWAS. Furthermore, the integration of omics, including genomics, transcriptomics, proteomics, metabolomics, epigenomics, and phenomics has enriched our understanding of intricate traits in maize, thereby enhancing environmental stress tolerance and boosting maize production. Collectively, these insights not only advance our understanding of the genetic mechanism regulating complex traits but also propel the utilization of marker-assisted selection in maize molecular breeding programs, where GWAS plays a pivotal role. Therefore, GWAS provides robust support for delving into the genetic mechanism underlying complex traits in maize and enhancing breeding strategies.
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Affiliation(s)
- Javed Hussain Sahito
- National Key Laboratory of Wheat and Maize Crop Science, College of Agronomy, Henan Agricultural University, Zhengzhou 450002, China
| | - Hao Zhang
- National Key Laboratory of Wheat and Maize Crop Science, College of Agronomy, Henan Agricultural University, Zhengzhou 450002, China
| | - Zeeshan Ghulam Nabi Gishkori
- Institute of Biotechnology, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310058, China
| | - Chenhui Ma
- National Key Laboratory of Wheat and Maize Crop Science, College of Agronomy, Henan Agricultural University, Zhengzhou 450002, China
| | - Zhihao Wang
- National Key Laboratory of Wheat and Maize Crop Science, College of Agronomy, Henan Agricultural University, Zhengzhou 450002, China
| | - Dong Ding
- National Key Laboratory of Wheat and Maize Crop Science, College of Agronomy, Henan Agricultural University, Zhengzhou 450002, China
| | - Xuehai Zhang
- National Key Laboratory of Wheat and Maize Crop Science, College of Agronomy, Henan Agricultural University, Zhengzhou 450002, China
| | - Jihua Tang
- National Key Laboratory of Wheat and Maize Crop Science, College of Agronomy, Henan Agricultural University, Zhengzhou 450002, China
- The Shennong Laboratory, Zhengzhou 450002, China
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Mastrangelo AM, Hartings H, Lanzanova C, Balconi C, Locatelli S, Cassol H, Valoti P, Petruzzino G, Pecchioni N. Genetic Diversity within a Collection of Italian Maize Inbred Lines: A Resource for Maize Genomics and Breeding. PLANTS (BASEL, SWITZERLAND) 2024; 13:336. [PMID: 38337869 PMCID: PMC10857507 DOI: 10.3390/plants13030336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 01/16/2024] [Accepted: 01/17/2024] [Indexed: 02/12/2024]
Abstract
Genetic diversity is fundamental for studying the complex architecture of the traits of agronomic importance, controlled by major and minor loci. Moreover, well-characterized germplasm collections are essential tools for dissecting and analyzing genetic and phenotypic diversity in crops. A panel of 360 entries, a subset of a larger collection maintained within the GenBank at CREA Bergamo, which includes the inbreds derived from traditional Italian maize open-pollinated (OP) varieties and advanced breeding ones (Elite Inbreds), was analyzed to identify SNP markers using the tGBS® genotyping-by-sequencing technology. A total of 797,368 SNPs were found during the initial analysis. Imputation and filtering processes were carried out based on the percentage of missing data, redundant markers, and rarest allele frequencies, resulting in a final dataset of 15,872 SNP markers for which a physical map position was identified. Using this dataset, the inbred panel was characterized for linkage disequilibrium (LD), genetic diversity, population structure, and genetic relationships. LD decay at a genome-wide level indicates that the collection is a suitable resource for association mapping. Population structure analyses, which were carried out with different clustering methods, showed stable grouping statistics for four groups, broadly corresponding to 'Insubria', 'Microsperma', and 'Scagliolino' genotypes, with a fourth group composed prevalently of elite accessions derived from Italian and US breeding programs. Based on these results, the CREA Italian maize collection, genetically characterized in this study, can be considered an important tool for the mapping and characterization of useful traits and associated loci/alleles, to be used in maize breeding programs.
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Affiliation(s)
- Anna Maria Mastrangelo
- CREA-Centro di Ricerca Cerealicoltura e Colture Industriali/Research Centre for Cereal and Industrial Crops, SS 673 Metri 25200, 71122 Foggia, Italy; (G.P.); (N.P.)
| | - Hans Hartings
- CREA-Centro di Ricerca Cerealicoltura e Colture Industriali/Research Centre for Cereal and Industrial Crops, Via Stezzano 24, 24126 Bergamo, Italy; (H.H.); (C.L.); (C.B.); (S.L.); (H.C.); (P.V.)
| | - Chiara Lanzanova
- CREA-Centro di Ricerca Cerealicoltura e Colture Industriali/Research Centre for Cereal and Industrial Crops, Via Stezzano 24, 24126 Bergamo, Italy; (H.H.); (C.L.); (C.B.); (S.L.); (H.C.); (P.V.)
| | - Carlotta Balconi
- CREA-Centro di Ricerca Cerealicoltura e Colture Industriali/Research Centre for Cereal and Industrial Crops, Via Stezzano 24, 24126 Bergamo, Italy; (H.H.); (C.L.); (C.B.); (S.L.); (H.C.); (P.V.)
| | - Sabrina Locatelli
- CREA-Centro di Ricerca Cerealicoltura e Colture Industriali/Research Centre for Cereal and Industrial Crops, Via Stezzano 24, 24126 Bergamo, Italy; (H.H.); (C.L.); (C.B.); (S.L.); (H.C.); (P.V.)
| | - Helga Cassol
- CREA-Centro di Ricerca Cerealicoltura e Colture Industriali/Research Centre for Cereal and Industrial Crops, Via Stezzano 24, 24126 Bergamo, Italy; (H.H.); (C.L.); (C.B.); (S.L.); (H.C.); (P.V.)
| | - Paolo Valoti
- CREA-Centro di Ricerca Cerealicoltura e Colture Industriali/Research Centre for Cereal and Industrial Crops, Via Stezzano 24, 24126 Bergamo, Italy; (H.H.); (C.L.); (C.B.); (S.L.); (H.C.); (P.V.)
| | - Giuseppe Petruzzino
- CREA-Centro di Ricerca Cerealicoltura e Colture Industriali/Research Centre for Cereal and Industrial Crops, SS 673 Metri 25200, 71122 Foggia, Italy; (G.P.); (N.P.)
| | - Nicola Pecchioni
- CREA-Centro di Ricerca Cerealicoltura e Colture Industriali/Research Centre for Cereal and Industrial Crops, SS 673 Metri 25200, 71122 Foggia, Italy; (G.P.); (N.P.)
- CREA-Centro di Ricerca Cerealicoltura e Colture Industriali/Research Centre for Cereal and Industrial Crops, Via Stezzano 24, 24126 Bergamo, Italy; (H.H.); (C.L.); (C.B.); (S.L.); (H.C.); (P.V.)
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Zhang Z, Peng C, Xu W, Li Y, Qi X, Zhao M. Genome-wide association study of agronomic traits related to nitrogen use efficiency in Henan wheat. BMC Genomics 2024; 25:7. [PMID: 38166525 PMCID: PMC10759698 DOI: 10.1186/s12864-023-09922-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 12/18/2023] [Indexed: 01/04/2024] Open
Abstract
BACKGROUND Nitrogen use efficiency (NUE) is closely related to crop yield and nitrogen fertilizer application rate. Although NUE is susceptible to environments, quantitative trait nucleotides (QTNs) for NUE in wheat germplasm populations have been rarely reported in genome-wide associated study. RESULTS In this study, 244 wheat accessions were phenotyped by three NUE-related traits in three environments and genotyped by 203,224 SNPs. All the phenotypes for each trait were used to associate with all the genotypes of these SNP markers for identifying QTNs and QTN-by-environment interactions via 3VmrMLM. Among 279 QTNs and one QTN-by-environment interaction for low nitrogen tolerance, 33 were stably identified, especially, one large QTN (r2 > 10%), qPHR3A.2, was newly identified for plant height ratio in one environment and multi-environment joint analysis. Among 52 genes around qPHR3A.2, four genes (TraesCS3A01G101900, TraesCS3A01G102200, TraesCS3A01G104100, and TraesCS3A01G105400) were found to be differentially expressed in low-nitrogen-tolerant wheat genotypes, while TaCLH2 (TraesCS3A01G101900) was putatively involved in porphyrin metabolism in KEGG enrichment analyses. CONCLUSIONS This study identified valuable candidate gene for low-N-tolerant wheat breeding and provides new insights into the genetic basis of low N tolerance in wheat.
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Affiliation(s)
- Zaicheng Zhang
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, People's Republic of China
- Institute of Crops Molecular Breeding, National Engineering Laboratory of Wheat, Key Laboratory of Wheat Biology and Genetic Breeding in Central Huanghuai Area, Ministry of Agriculture, Henan Key Laboratory of Wheat Germplasm Resources Innovation and Improvement, Henan Academy of Agricultural Sciences, Zhengzhou, 450002, People's Republic of China
| | - Chaojun Peng
- Institute of Crops Molecular Breeding, National Engineering Laboratory of Wheat, Key Laboratory of Wheat Biology and Genetic Breeding in Central Huanghuai Area, Ministry of Agriculture, Henan Key Laboratory of Wheat Germplasm Resources Innovation and Improvement, Henan Academy of Agricultural Sciences, Zhengzhou, 450002, People's Republic of China
- The Shennong Laboratory, Zhengzhou, 450002, People's Republic of China
| | - Weigang Xu
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, People's Republic of China.
- Institute of Crops Molecular Breeding, National Engineering Laboratory of Wheat, Key Laboratory of Wheat Biology and Genetic Breeding in Central Huanghuai Area, Ministry of Agriculture, Henan Key Laboratory of Wheat Germplasm Resources Innovation and Improvement, Henan Academy of Agricultural Sciences, Zhengzhou, 450002, People's Republic of China.
- The Shennong Laboratory, Zhengzhou, 450002, People's Republic of China.
| | - Yan Li
- Institute of Crops Molecular Breeding, National Engineering Laboratory of Wheat, Key Laboratory of Wheat Biology and Genetic Breeding in Central Huanghuai Area, Ministry of Agriculture, Henan Key Laboratory of Wheat Germplasm Resources Innovation and Improvement, Henan Academy of Agricultural Sciences, Zhengzhou, 450002, People's Republic of China
- The Shennong Laboratory, Zhengzhou, 450002, People's Republic of China
| | - Xueli Qi
- Institute of Crops Molecular Breeding, National Engineering Laboratory of Wheat, Key Laboratory of Wheat Biology and Genetic Breeding in Central Huanghuai Area, Ministry of Agriculture, Henan Key Laboratory of Wheat Germplasm Resources Innovation and Improvement, Henan Academy of Agricultural Sciences, Zhengzhou, 450002, People's Republic of China
- The Shennong Laboratory, Zhengzhou, 450002, People's Republic of China
| | - Mingzhong Zhao
- Institute of Crops Molecular Breeding, National Engineering Laboratory of Wheat, Key Laboratory of Wheat Biology and Genetic Breeding in Central Huanghuai Area, Ministry of Agriculture, Henan Key Laboratory of Wheat Germplasm Resources Innovation and Improvement, Henan Academy of Agricultural Sciences, Zhengzhou, 450002, People's Republic of China
- The Shennong Laboratory, Zhengzhou, 450002, People's Republic of China
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Li C, Guo J, Wang D, Chen X, Guan H, Li Y, Zhang D, Liu X, He G, Wang T, Li Y. Genomic insight into changes of root architecture under drought stress in maize. PLANT, CELL & ENVIRONMENT 2023; 46:1860-1872. [PMID: 36785485 DOI: 10.1111/pce.14567] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 02/03/2023] [Accepted: 02/11/2023] [Indexed: 05/04/2023]
Abstract
Drought stress is a central environmental factor that severely limits maize production worldwide. Root architecture plays an important role in drought tolerance and can be targeted in breeding programmes. Here, we conducted phenotyping of root architecture under different water treatments for 373 maize inbred lines, representative germplasm from both China and the United States in different breeding eras. We found that seminal root length in response to drought stress experienced convergent increase during breeding in both countries. Using a genome-wide association study, we identified a total of 221 associated loci underlying 13 root traits under well-watered and water-stressed conditions. These loci harboured many reported root- and abiotic stress-related genes. Furthermore, a total of 75 strong candidate genes were prioritised by integrating candidate genes associated with seminal root length and differentially expressed genes in seminal root. One of high-confidence candidate genes, ZmCIPK3 was functionally characterised and probably plays a role in enhancing drought tolerance through regulating seminal root growth. This study provides valuable information for genetic improvement of root architecture and drought tolerance in maize.
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Affiliation(s)
- Chunhui Li
- State Key Lab of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Jian Guo
- Jiangsu Key Laboratory of Crop Genetics and Physiology, Jiangsu Key Laboratory of Crop Cultivation and Physiology, Agricultural College, Yangzhou University, Yangzhou, China
| | - Dongmei Wang
- State Key Lab of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xiaojing Chen
- State Key Lab of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Honghui Guan
- State Key Lab of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yongxiang Li
- State Key Lab of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Dengfeng Zhang
- State Key Lab of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xuyang Liu
- State Key Lab of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Guanhua He
- State Key Lab of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Tianyu Wang
- State Key Lab of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yu Li
- State Key Lab of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
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5
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Wang Y, Bi Y, Jiang F, Shaw RK, Sun J, Hu C, Guo R, Fan X. Mapping and Functional Analysis of QTL for Kernel Number per Row in Tropical and Temperate-Tropical Introgression Lines of Maize ( Zea mays L.). Curr Issues Mol Biol 2023; 45:4416-4430. [PMID: 37232750 DOI: 10.3390/cimb45050281] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2023] [Revised: 05/10/2023] [Accepted: 05/16/2023] [Indexed: 05/27/2023] Open
Abstract
Kernel number per row (KNR) is an essential component of maize (Zea mays L.) grain yield (GY), and understanding its genetic mechanism is crucial to improve GY. In this study, two F7 recombinant inbred line (RIL) populations were created using a temperate-tropical introgression line TML418 and a tropical inbred line CML312 as female parents and a backbone maize inbred line Ye107 as the common male parent. Bi-parental quantitative trait locus (QTL) mapping and genome-wide association analysis (GWAS) were then performed on 399 lines of the two maize RIL populations for KNR in two different environments using 4118 validated single nucleotide polymorphism (SNP) markers. This study aimed to: (1) detect molecular markers and/or the genomic regions associated with KNR; (2) identify the candidate genes controlling KNR; and (3) analyze whether the candidate genes are useful in improving GY. The authors reported a total of 7 QTLs tightly linked to KNR through bi-parental QTL mapping and identified 21 SNPs significantly associated with KNR through GWAS. Among these, a highly confident locus qKNR7-1 was detected at two locations, Dehong and Baoshan, with both mapping approaches. At this locus, three novel candidate genes (Zm00001d022202, Zm00001d022168, Zm00001d022169) were identified to be associated with KNR. These candidate genes were primarily involved in the processes related to compound metabolism, biosynthesis, protein modification, degradation, and denaturation, all of which were related to the inflorescence development affecting KNR. These three candidate genes were not reported previously and are considered new candidate genes for KNR. The progeny of the hybrid Ye107 × TML418 exhibited strong heterosis for KNR, which the authors believe might be related to qKNR7-1. This study provides a theoretical foundation for future research on the genetic mechanism underlying KNR in maize and the use of heterotic patterns to develop high-yielding hybrids.
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Affiliation(s)
- Yuling Wang
- Institute of Resource Plants, Yunnan University, Kunming 650504, China
| | - Yaqi Bi
- Institute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming 650205, China
| | - Fuyan Jiang
- Institute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming 650205, China
| | - Ranjan Kumar Shaw
- Institute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming 650205, China
| | - Jiachen Sun
- College of Agronomy and Biotechnology, Yunnan Agricultural University, Kunming 650500, China
| | - Can Hu
- Institute of Resource Plants, Yunnan University, Kunming 650504, China
| | - Ruijia Guo
- Institute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming 650205, China
| | - Xingming Fan
- Institute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming 650205, China
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Karnatam KS, Chhabra G, Saini DK, Singh R, Kaur G, Praba UP, Kumar P, Goyal S, Sharma P, Ranjan R, Sandhu SK, Kumar R, Vikal Y. Genome-Wide Meta-Analysis of QTLs Associated with Root Traits and Implications for Maize Breeding. Int J Mol Sci 2023; 24:ijms24076135. [PMID: 37047112 PMCID: PMC10093813 DOI: 10.3390/ijms24076135] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 03/14/2023] [Accepted: 03/17/2023] [Indexed: 04/14/2023] Open
Abstract
Root system architecture (RSA), also known as root morphology, is critical in plant acquisition of soil resources, plant growth, and yield formation. Many QTLs associated with RSA or root traits in maize have been identified using several bi-parental populations, particularly in response to various environmental factors. In the present study, a meta-analysis of QTLs associated with root traits was performed in maize using 917 QTLs retrieved from 43 mapping studies published from 1998 to 2020. A total of 631 QTLs were projected onto a consensus map involving 19,714 markers, which led to the prediction of 68 meta-QTLs (MQTLs). Among these 68 MQTLs, 36 MQTLs were validated with the marker-trait associations available from previous genome-wide association studies for root traits. The use of comparative genomics approaches revealed several gene models conserved among the maize, sorghum, and rice genomes. Among the conserved genomic regions, the ortho-MQTL analysis uncovered 20 maize MQTLs syntenic to 27 rice MQTLs for root traits. Functional analysis of some high-confidence MQTL regions revealed 442 gene models, which were then subjected to in silico expression analysis, yielding 235 gene models with significant expression in various tissues. Furthermore, 16 known genes viz., DXS2, PHT, RTP1, TUA4, YUC3, YUC6, RTCS1, NSA1, EIN2, NHX1, CPPS4, BIGE1, RCP1, SKUS13, YUC5, and AW330564 associated with various root traits were present within or near the MQTL regions. These results could aid in QTL cloning and pyramiding in developing new maize varieties with specific root architecture for proper plant growth and development under optimum and abiotic stress conditions.
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Affiliation(s)
- Krishna Sai Karnatam
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana 141001, India
| | - Gautam Chhabra
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana 141001, India
| | - Dinesh Kumar Saini
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana 141001, India
| | - Rajveer Singh
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana 141001, India
| | - Gurwinder Kaur
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana 141001, India
| | - Umesh Preethi Praba
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana 141001, India
| | - Pankaj Kumar
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana 141001, India
| | - Simran Goyal
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana 141001, India
| | - Priti Sharma
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana 141001, India
| | - Rumesh Ranjan
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana 141001, India
| | - Surinder K Sandhu
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana 141001, India
| | - Ramesh Kumar
- Indian Institute of Maize Research, Ludhiana 141001, India
| | - Yogesh Vikal
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana 141001, India
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Sun D, Chen S, Cui Z, Lin J, Liu M, Jin Y, Zhang A, Gao Y, Cao H, Ruan Y. Genome-wide association study reveals the genetic basis of brace root angle and diameter in maize. Front Genet 2022; 13:963852. [PMID: 36276979 PMCID: PMC9582141 DOI: 10.3389/fgene.2022.963852] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 09/07/2022] [Indexed: 11/26/2022] Open
Abstract
Brace roots are the main organ to support the above-ground part of maize plant. It involves in plant growth and development by water absorption and lodging resistance. The bracing root angle (BRA) and diameter (BRD) are important components of brace root traits. Illuminating the genetic basis of BRA and BRD will contribute the improvement for mechanized harvest and increasing production. A GWAS of BRA and BRD was conducted using an associated panel composed of 508 inbred lines of maize. The broad-sense heritability of BRA and BRD was estimated to be respectively 71% ± 0.19 and 52% ± 0.14. The phenotypic variation of BRA and BRD in the non-stiff stalk subgroup (NSS) and the stiff stalk subgroup (SS) subgroups are significantly higher than that in the tropical/subtropical subgroup (TST) subgroups. In addition, BRA and BRD are significantly positive with plant height (PH), ear length (EL), and kernel number per row (KNPR). GWAS revealed 27 candidate genes within the threshold of p < 1.84 × 10−6 by both MLM and BLINK models. Among them, three genes, GRMZM2G174736, GRMZM2G445169 and GRMZM2G479243 were involved in cell wall function, and GRMZM2G038073 encoded the NAC transcription factor family proteins. These results provide theoretical support for clarifying the genetic basis of brace roots traits.
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Affiliation(s)
- Daqiu Sun
- Shenyang Key Laboratory of Maize Genomic Selection Breeding, Liaoning Province Research Center of Plant Genetic Engineering Technology, College of Biological Science and Technology, Shenyang Agricultural University, Shenyang, China
| | - Sibo Chen
- Shenyang Key Laboratory of Maize Genomic Selection Breeding, Liaoning Province Research Center of Plant Genetic Engineering Technology, College of Biological Science and Technology, Shenyang Agricultural University, Shenyang, China
- Key Laboratory of Northern Geng Super Rice Breeding, Ministry of Education, Rice Research Institute, Shenyang Agricultural University, Shenyang, China
| | - Zhenhai Cui
- Shenyang Key Laboratory of Maize Genomic Selection Breeding, Liaoning Province Research Center of Plant Genetic Engineering Technology, College of Biological Science and Technology, Shenyang Agricultural University, Shenyang, China
- Key Laboratory of Soybean Molecular Design Breeding, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, China
| | - Jingwei Lin
- Shenyang Key Laboratory of Maize Genomic Selection Breeding, Liaoning Province Research Center of Plant Genetic Engineering Technology, College of Biological Science and Technology, Shenyang Agricultural University, Shenyang, China
| | - Meiling Liu
- Shenyang Key Laboratory of Maize Genomic Selection Breeding, Liaoning Province Research Center of Plant Genetic Engineering Technology, College of Biological Science and Technology, Shenyang Agricultural University, Shenyang, China
| | - Yueting Jin
- Shenyang Key Laboratory of Maize Genomic Selection Breeding, Liaoning Province Research Center of Plant Genetic Engineering Technology, College of Biological Science and Technology, Shenyang Agricultural University, Shenyang, China
| | - Ao Zhang
- Shenyang Key Laboratory of Maize Genomic Selection Breeding, Liaoning Province Research Center of Plant Genetic Engineering Technology, College of Biological Science and Technology, Shenyang Agricultural University, Shenyang, China
| | - Yuan Gao
- Shenyang Key Laboratory of Maize Genomic Selection Breeding, Liaoning Province Research Center of Plant Genetic Engineering Technology, College of Biological Science and Technology, Shenyang Agricultural University, Shenyang, China
| | - Huiying Cao
- Shenyang Key Laboratory of Maize Genomic Selection Breeding, Liaoning Province Research Center of Plant Genetic Engineering Technology, College of Biological Science and Technology, Shenyang Agricultural University, Shenyang, China
- *Correspondence: Huiying Cao, ; Yanye Ruan,
| | - Yanye Ruan
- Shenyang Key Laboratory of Maize Genomic Selection Breeding, Liaoning Province Research Center of Plant Genetic Engineering Technology, College of Biological Science and Technology, Shenyang Agricultural University, Shenyang, China
- *Correspondence: Huiying Cao, ; Yanye Ruan,
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Zuffo LT, DeLima RO, Lübberstedt T. Combining datasets for maize root seedling traits increases the power of GWAS and genomic prediction accuracies. JOURNAL OF EXPERIMENTAL BOTANY 2022; 73:5460-5473. [PMID: 35608947 PMCID: PMC9467658 DOI: 10.1093/jxb/erac236] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/11/2021] [Accepted: 06/06/2022] [Indexed: 05/13/2023]
Abstract
The identification of genomic regions associated with root traits and the genomic prediction of untested genotypes can increase the rate of genetic gain in maize breeding programs targeting roots traits. Here, we combined two maize association panels with different genetic backgrounds to identify single nucleotide polymorphisms (SNPs) associated with root traits, and used a genome-wide association study (GWAS) and to assess the potential of genomic prediction for these traits in maize. For this, we evaluated 377 lines from the Ames panel and 302 from the Backcrossed Germplasm Enhancement of Maize (BGEM) panel in a combined panel of 679 lines. The lines were genotyped with 232 460 SNPs, and four root traits were collected from 14-day-old seedlings. We identified 30 SNPs significantly associated with root traits in the combined panel, whereas only two and six SNPs were detected in the Ames and BGEM panels, respectively. Those 38 SNPs were in linkage disequilibrium with 35 candidate genes. In addition, we found higher prediction accuracy in the combined panel than in the Ames or BGEM panel. We conclude that combining association panels appears to be a useful strategy to identify candidate genes associated with root traits in maize and improve the efficiency of genomic prediction.
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Affiliation(s)
- Leandro Tonello Zuffo
- Corteva Agriscience, Rio Verde, GO, Brazil
- Department of Agronomy, Universidade Federal de Viçosa, Viçosa, MG, Brazil
- Department of Agronomy, Iowa State University, Ames, IA, USA
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Ahmad N, Su B, Ibrahim S, Kuang L, Tian Z, Wang X, Wang H, Dun X. Deciphering the Genetic Basis of Root and Biomass Traits in Rapeseed (Brassica napus L.) through the Integration of GWAS and RNA-Seq under Nitrogen Stress. Int J Mol Sci 2022; 23:ijms23147958. [PMID: 35887301 PMCID: PMC9323118 DOI: 10.3390/ijms23147958] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 07/16/2022] [Accepted: 07/16/2022] [Indexed: 02/06/2023] Open
Abstract
An excellent root system is responsible for crops with high nitrogen-use efficiency (NUE). The current study evaluated the natural variations in 13 root- and biomass-related traits under a low nitrogen (LN) treatment in a rapeseed association panel. The studied traits exhibited significant phenotypic differences with heritabilities ranging from 0.53 to 0.66, and most of the traits showed significant correlations with each other. The genome-wide association study (GWAS) found 51 significant and 30 suggestive trait–SNP associations that integrated into 14 valid quantitative trait loci (QTL) clusters and explained 5.7–21.2% phenotypic variance. In addition, RNA sequencing was performed at two time points to examine the differential expression of genes (DEGs) between high and low NUE lines. In total, 245, 540, and 399 DEGs were identified as LN stress-specific, high nitrogen (HN) condition-specific, and HNLN common DEGs, respectively. An integrated analysis of GWAS, weighted gene co-expression network, and DEGs revealed 16 genes involved in rapeseed root development under LN stress. Previous studies have reported that the homologs of seven out of sixteen potential genes control root growth and NUE. These findings revealed the genetic basis underlying nitrogen stress and provided worthwhile SNPs/genes information for the genetic improvement of NUE in rapeseed.
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Affiliation(s)
- Nazir Ahmad
- Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences/Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Wuhan 430062, China; (N.A.); (B.S.); (S.I.); (L.K.); (Z.T.); (X.W.)
| | - Bin Su
- Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences/Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Wuhan 430062, China; (N.A.); (B.S.); (S.I.); (L.K.); (Z.T.); (X.W.)
| | - Sani Ibrahim
- Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences/Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Wuhan 430062, China; (N.A.); (B.S.); (S.I.); (L.K.); (Z.T.); (X.W.)
- Department of Plant Biology, Faculty of Life Sciences, College of Physical and Pharmaceutical Sciences, Bayero University, P.M.B. 3011, Kano 700006, Nigeria
| | - Lieqiong Kuang
- Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences/Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Wuhan 430062, China; (N.A.); (B.S.); (S.I.); (L.K.); (Z.T.); (X.W.)
| | - Ze Tian
- Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences/Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Wuhan 430062, China; (N.A.); (B.S.); (S.I.); (L.K.); (Z.T.); (X.W.)
| | - Xinfa Wang
- Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences/Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Wuhan 430062, China; (N.A.); (B.S.); (S.I.); (L.K.); (Z.T.); (X.W.)
- Hubei Hongshan Laboratory, Wuhan 430070, China
| | - Hanzhong Wang
- Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences/Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Wuhan 430062, China; (N.A.); (B.S.); (S.I.); (L.K.); (Z.T.); (X.W.)
- Hubei Hongshan Laboratory, Wuhan 430070, China
- Correspondence: (H.W.); (X.D.)
| | - Xiaoling Dun
- Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences/Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Wuhan 430062, China; (N.A.); (B.S.); (S.I.); (L.K.); (Z.T.); (X.W.)
- Correspondence: (H.W.); (X.D.)
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