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Li Y, Hu J, Qu Y, Qiu D, Lin H, Du J, Hou L, Ma L, Wu Q, Zhou Y, Zhang H, Yang L, Liu H, Liu Z, Zhou Y, Li H. Alleles on locus chromosome 4B from different parents confer tiller number and the yield-associated traits in wheat. BMC PLANT BIOLOGY 2024; 24:454. [PMID: 38789943 PMCID: PMC11127307 DOI: 10.1186/s12870-024-05079-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Accepted: 04/28/2024] [Indexed: 05/26/2024]
Abstract
Pleiotropy is frequently detected in agronomic traits of wheat (Triticum aestivum). A locus on chromosome 4B, QTn/Ptn/Sl/Sns/Al/Tgw/Gl/Gw.caas-4B, proved to show pleiotropic effects on tiller, spike, and grain traits using a recombinant inbred line (RIL) population of Qingxinmai × 041133. The allele from Qingxinmai increased tiller numbers, and the allele from line 041133 produced better performances of spike traits and grain traits. Another 52 QTL for the eight traits investigated were detected on 18 chromosomes, except for chromosomes 5D, 6D, and 7B. Several genes in the genomic interval of the locus on chromosome 4B were differentially expressed in crown and inflorescence samples between Qingxinmai and line 041133. The development of the KASP marker specific for the locus on chromosome 4B is useful for molecular marker-assisted selection in wheat breeding.
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Affiliation(s)
- Yahui Li
- College of Life and Environmental Sciences, Minzu University of China, Beijing, 100081, China
- The National Engineering Laboratory of Crop Molecular Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Jinghuang Hu
- The National Engineering Laboratory of Crop Molecular Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Yunfeng Qu
- State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng, 475001, China
| | - Dan Qiu
- Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Huailong Lin
- Jiushenghe Seed Industry Co. Ltd, Changji, 831100, China
| | - Jiuyuan Du
- Wheat Research Institute, Gansu Academy of Agricultural Sciences, Lanzhou, 730070, China
| | - Lu Hou
- Key Laboratory of Agricultural Integrated Pest Management, Qinghai Academy of Agricultural and Forestry Sciences, Qinghai University, Xining, 810016, China
| | - Lin Ma
- Datong Hui and Tu Autonomous County Agricultural Technology Extension Center, Xining, 810100, China
| | - Qiuhong Wu
- Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Yang Zhou
- The National Engineering Laboratory of Crop Molecular Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Hongjun Zhang
- The National Engineering Laboratory of Crop Molecular Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Li Yang
- The National Engineering Laboratory of Crop Molecular Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Hongwei Liu
- The National Engineering Laboratory of Crop Molecular Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Zhiyong Liu
- Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Yijun Zhou
- College of Life and Environmental Sciences, Minzu University of China, Beijing, 100081, China.
| | - Hongjie Li
- The National Engineering Laboratory of Crop Molecular Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
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Zhang L, Zhou H, Fu X, Zhou N, Liu M, Bai S, Zhao X, Cheng R, Li S, Zhang D. Identification and map-based cloning of an EMS-induced mutation in wheat gene TaSP1 related to spike architecture. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2024; 137:119. [PMID: 38709271 DOI: 10.1007/s00122-024-04621-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2024] [Accepted: 04/10/2024] [Indexed: 05/07/2024]
Abstract
KEY MESSAGE A candidate gene TaSP1 related to spike shape was cloned, and the gene-specific marker was developed to efficiently track the superior haplotype in common wheat. Spike shape, an important factor that affects wheat grain yield, is mainly defined by spike length (SPL), spikelet number (SPN), and compactness. Zhoumai32 mutant 1160 (ZM1160), a mutant obtained from ethyl methane sulfonate (EMS) treatment of hexaploid wheat variety Zhoumai32, was used to identify and clone the candidate gene that conditioned the spike shape. Genetic analysis of an F2 population derived from a cross of ZM1160 and Bainong207 suggested that the compact spike shape in ZM1160 was controlled by a single recessive gene, and therefore, the mutated gene was designated as Tasp1. With polymorphic markers identified through bulked segregant analysis (BSA), the gene was mapped to a 2.65-cM interval flanked by markers YZU0852 and MIS46239 on chromosome 7D, corresponding to a 0.42-Mb physical interval of Chinese spring (CS) reference sequences (RefSeq v1.0). To fine map TaSP1, 15 and seven recombinants were, respectively, screened from 1599 and 1903 F3 plants derived from the heterozygous F2 plants. Finally, TaSP1 was delimited to a 21.9 Kb (4,870,562 to 4,892,493 bp) Xmis48123-Xmis48104 interval. Only one high-confidence gene TraesCS7D02G010200 was annotated in this region, which encodes an unknown protein with a putative vWA domain. Quantitative reverse transcription PCR (qRT-PCR) analysis showed that TraesCS7D02G010200 was mainly expressed in the spike. Haplotype analysis of 655 wheat cultivars using the candidate gene-specific marker Xg010200p2 identified a superior haplotype TaSP1b with longer spike and more spikelet number. TaSP1 is beneficial to the improvement in wheat spike shape.
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Affiliation(s)
- Lin Zhang
- School of Life Sciences, Henan University, Kaifeng, 475001, China
| | - Huidan Zhou
- State Key Laboratory of Crop Stress Adaptation and Improvement, College of Agricultural Sciences, Henan University, Kaifeng, 475001, Henan, China
| | - Xian Fu
- School of Life Sciences, Henan University, Kaifeng, 475001, China
| | - Niuniu Zhou
- School of Life Sciences, Henan University, Kaifeng, 475001, China
| | - Mengjie Liu
- School of Life Sciences, Henan University, Kaifeng, 475001, China
| | - Shenglong Bai
- State Key Laboratory of Crop Stress Adaptation and Improvement, College of Agricultural Sciences, Henan University, Kaifeng, 475001, Henan, China
| | - Xinpeng Zhao
- State Key Laboratory of Crop Stress Adaptation and Improvement, College of Agricultural Sciences, Henan University, Kaifeng, 475001, Henan, China
| | - Ruiru Cheng
- State Key Laboratory of Crop Stress Adaptation and Improvement, College of Agricultural Sciences, Henan University, Kaifeng, 475001, Henan, China.
| | - Suoping Li
- State Key Laboratory of Crop Stress Adaptation and Improvement, College of Agricultural Sciences, Henan University, Kaifeng, 475001, Henan, China.
| | - Dale Zhang
- State Key Laboratory of Crop Stress Adaptation and Improvement, College of Agricultural Sciences, Henan University, Kaifeng, 475001, Henan, China.
- The Zhongzhou Laboratory for Integrative Biology, Zhengzhou, 450000, Henan, China.
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Wang J, Wang E, Cheng S, Ma A. Genetic insights into superior grain number traits: a QTL analysis of wheat-Agropyron cristatum derivative pubing3228. BMC PLANT BIOLOGY 2024; 24:271. [PMID: 38605289 PMCID: PMC11008026 DOI: 10.1186/s12870-024-04913-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/25/2023] [Accepted: 03/15/2024] [Indexed: 04/13/2024]
Abstract
BACKGROUND Agropyron cristatum (L.) is a valuable genetic resource for expanding the genetic diversity of common wheat. Pubing3228, a novel wheat-A. cristatum hybrid germplasm, exhibits several desirable agricultural traits, including high grain number per spike (GNS). Understanding the genetic architecture of GNS in Pubing3228 is crucial for enhancing wheat yield. This study aims to analyze the specific genetic regions and alleles associated with high GNS in Pubing3228. METHODS The study employed a recombination inbred line (RIL) population derived from a cross between Pubing3228 and Jing4839 to investigate the genetic regions and alleles linked to high GNS. Quantitative Trait Loci (QTL) analysis and candidate gene investigation were utilized to explore these traits. RESULTS A total of 40 QTLs associated with GNS were identified across 16 chromosomes, accounting for 4.25-17.17% of the total phenotypic variation. Five QTLs (QGns.wa-1D, QGns.wa-5 A, QGns.wa-7Da.1, QGns.wa-7Da.2 and QGns.wa-7Da.3) accounter for over 10% of the phenotypic variation in at least two environments. Furthermore, 94.67% of the GNS QTL with positive effects originated from Pubing3228. Candidate gene analysis of stable QTLs identified 11 candidate genes for GNS, including a senescence-associated protein gene (TraesCS7D01G148000) linked to the most significant SNP (AX-108,748,734) on chromosome 7D, potentially involved in reallocating nutrients from senescing tissues to developing seeds. CONCLUSION This study provides new insights into the genetic mechanisms underlying high GNS in Pubing3228, offering valuable resources for marker-assisted selection in wheat breeding to enhance yield.
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Affiliation(s)
- Jiansheng Wang
- College of Chemistry and Environment Engineering, Pingdingshan University, North to Weilailu road, New district, Pingdingshan, Henan, 467000, China.
- Henan Key Laboratory of Germplasm Innovation and Utilization of Eco-economic Woody Plant, Pingdingshan, Henan, China.
| | - Erwei Wang
- Pingdingshan Academy of Agricultural Science, Pingdingshan, Henan, 467001, China
| | - Shiping Cheng
- College of Chemistry and Environment Engineering, Pingdingshan University, North to Weilailu road, New district, Pingdingshan, Henan, 467000, China
- Henan Key Laboratory of Germplasm Innovation and Utilization of Eco-economic Woody Plant, Pingdingshan, Henan, China
| | - Aichu Ma
- Pingdingshan Academy of Agricultural Science, Pingdingshan, Henan, 467001, China
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Zhang L, Luo Y, Zhong X, Jia G, Chen H, Wang Y, Zhou J, Ma C, Li X, Huang K, Yang S, Wang J, Han D, Ren Y, Cai L, Zhou X. Genome-wide QTL mapping for agronomic traits in the winter wheat cultivar Pindong 34 based on 90K SNP array. FRONTIERS IN PLANT SCIENCE 2024; 15:1369440. [PMID: 38638350 PMCID: PMC11024375 DOI: 10.3389/fpls.2024.1369440] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Accepted: 03/11/2024] [Indexed: 04/20/2024]
Abstract
Introduction Agronomic traits are key components of wheat yield. Exploitation of the major underlying quantitative trait loci (QTLs) can improve the yield potential in wheat breeding. Methods In this study, we constructed a recombinant inbred line (RIL) population from Mingxian 169 (MX169) and Pindong 34 (PD34) to determine the QTLs for grain length (GL), grain width (GW), grain length-to-width ratio (LWR), plant height (PH), spike length (SL), grain number per spike (GNS), and the thousand grain weight (TGW) across four environments using wheat 90K SNP array. Results A QTL associated with TGW, i.e., QTGWpd.swust-6BS, was identified on chromosome 6B, which explained approximately 14.1%-16.2% of the phenotypic variation. In addition, eight QTLs associated with GL were detected across six chromosomes in four different test environments. These were QGLpd.swust-1BL, QGLpd.swust-2BL, QGLpd.swust-3BL.1, QGLpd.swust-3BL.2, QGLpd.swust-5DL, QGLpd.swust-6AL, QGLpd.swust-6DL.1, and QGLpd.swust-6DL.2. They accounted for 9.0%-21.3% of the phenotypic variation. Two QTLs, namely, QGWpd.swust-3BS and QGWpd.swust-6DL, were detected for GW on chromosomes 3B and 6D, respectively. These QTLs explained 12.8%-14.6% and 10.8%-15.2% of the phenotypic variation, respectively. In addition, two QTLs, i.e., QLWRpd.swust-7AS.1 and QLWRpd.swust-7AS.2, were detected on chromosome 7A for the grain LWR, which explained 10.9%-11.6% and 11.6%-11.2% of the phenotypic variation, respectively. Another QTL, named QGNSpd-swust-6DS, was discovered on chromosome 6D, which determines the GNS and which accounted for 11.4%-13.8% of the phenotypic variation. Furthermore, five QTLs associated with PH were mapped on chromosomes 2D, 3A, 5A, 6B, and 7B. These QTLs were QPHpd.swust-2DL, QPHpd.swust-3AL, QPHpd.swust-5AL, QPHpd.swust-6BL, and QPHpd.swust-7BS, which accounted for 11.3%-19.3% of the phenotypic variation. Lastly, a QTL named QSLpd.swust-3AL, conferring SL, was detected on chromosome 3A and explained 16.1%-17.6% of the phenotypic variation. All of these QTLs were defined within the physical interval of the Chinese spring reference genome. Discussion The findings of this study have significant implications for the development of fine genetic maps, for genomic breeding, and for marker-assisted selection to enhance wheat grain yield.
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Affiliation(s)
- Liangqi Zhang
- Wheat Research Institute, School of Life Sciences and Engineering, Southwest University of Science and Technology, Mianyang, Sichuan, China
| | - Yuqi Luo
- Wheat Research Institute, School of Life Sciences and Engineering, Southwest University of Science and Technology, Mianyang, Sichuan, China
| | - Xiao Zhong
- Chongqing Banan District Agricultural Technology Promoting Station, Chongqing, China
| | - Guoyun Jia
- Wheat Research Institute, School of Life Sciences and Engineering, Southwest University of Science and Technology, Mianyang, Sichuan, China
| | - Hao Chen
- Wheat Research Institute, School of Life Sciences and Engineering, Southwest University of Science and Technology, Mianyang, Sichuan, China
| | - Yuqi Wang
- Wheat Research Institute, School of Life Sciences and Engineering, Southwest University of Science and Technology, Mianyang, Sichuan, China
| | - Jianian Zhou
- Wheat Research Institute, School of Life Sciences and Engineering, Southwest University of Science and Technology, Mianyang, Sichuan, China
| | - Chunhua Ma
- Wheat Research Institute, School of Life Sciences and Engineering, Southwest University of Science and Technology, Mianyang, Sichuan, China
| | - Xin Li
- Wheat Research Institute, School of Life Sciences and Engineering, Southwest University of Science and Technology, Mianyang, Sichuan, China
| | - Kebing Huang
- Wheat Research Institute, School of Life Sciences and Engineering, Southwest University of Science and Technology, Mianyang, Sichuan, China
| | - Suizhuang Yang
- Wheat Research Institute, School of Life Sciences and Engineering, Southwest University of Science and Technology, Mianyang, Sichuan, China
| | - Jianfeng Wang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Plant Protection, Northwest A&F University, Yangling, Shanxi, China
| | - Dejun Han
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Plant Protection, Northwest A&F University, Yangling, Shanxi, China
| | - Yong Ren
- Crop Characteristic Resources Creation and Utilization Key Laboratory of Sichuan Province, Mianyang Institute of Agricultural Science, Mianyang, Sichuan, China
| | - Lin Cai
- College of Tobacco Science of Guizhou University, Key Laboratory of Plant Resource Conservation and Germplasm Innovation in Mountainous Region (Ministry of Education), Guizhou Key Lab of Agro-Bioengineering, Guiyang, China
| | - Xinli Zhou
- Wheat Research Institute, School of Life Sciences and Engineering, Southwest University of Science and Technology, Mianyang, Sichuan, China
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Qin R, Cao M, Dong J, Chen L, Guo H, Guo Q, Cai Y, Han L, Huang Z, Xu N, Yang A, Xu H, Wu Y, Sun H, Liu X, Ling H, Zhao C, Li J, Cui F. Fine mapping of a major QTL, qKl-1BL controlling kernel length in common wheat. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2024; 137:67. [PMID: 38441674 DOI: 10.1007/s00122-024-04574-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 02/03/2024] [Indexed: 03/07/2024]
Abstract
KEY MESSAGE A major stable QTL, qKl-1BL, for kernel length of wheat was narrowed down to a 2.04-Mb interval on chromosome 1BL; the candidate genes were predicated and the genetic effects on yield-related traits were characterized. As a key factor influencing kernel weight, wheat kernel shape is closely related to yield formation, and in turn affects both wheat processing quality and market value. Fine mapping of the major quantitative trait loci (QTL) for kernel shape could provide genetic resources and a theoretical basis for the genetic improvement of wheat yield-related traits. In this study, a major QTL for kernel length (KL) on 1BL, named qKl-1BL, was identified from the recombinant inbred lines (RIL) in multiple environments based on the genetic map and physical map, with 4.76-21.15% of the phenotypic variation explained. To fine map qKl-1BL, the map-based cloning strategy was used. By using developed InDel markers, the near-isogenic line (NIL) pairs and eight key recombinants were identified from a segregating population containing 3621 individuals derived from residual heterozygous lines (RHLs) self-crossing. In combination with phenotype identification, qKl-1BL was finely positioned into a 2.04-Mb interval, KN1B:698.15-700.19 Mb, with eight differentially expressed genes enriched at the key period of kernel elongation. Based on transcriptome analysis and functional annotation information, two candidate genes for qKl-1BL controlling kernel elongation were identified. Additionally, genetic effect analysis showed that the superior allele of qKl-1BL from Jing411 could increase KL, thousand kernel weight (TKW), and yield per plant (YPP) significantly, as well as kernel bulk density and stability time. Taken together, this study identified a QTL interval for controlling kernel length with two possible candidate genes, which provides an important basis for qKl-1BL cloning, functional analysis, and application in molecular breeding programs.
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Affiliation(s)
- Ran Qin
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Mingsu Cao
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Jizi Dong
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Linqu Chen
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Haoru Guo
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Qingjie Guo
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Yibiao Cai
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Lei Han
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Zhenjie Huang
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Ninghao Xu
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Aoyu Yang
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Huiyuan Xu
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Yongzhen Wu
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Han Sun
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China
| | - Xigang Liu
- Ministry of Education Key Laboratory of Molecular and Cellular Biology, Hebei Collaboration Innovation Center for Cell Signaling and Environmental Adaptation, Hebei Key Laboratory of Molecular and Cellular Biology, College of Life Sciences, Hebei Normal University, Shijiazhuang, 050000, China
| | - Hongqing Ling
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing, 100101, China
| | - Chunhua Zhao
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China.
| | - Junming Li
- Ministry of Education Key Laboratory of Molecular and Cellular Biology, Hebei Collaboration Innovation Center for Cell Signaling and Environmental Adaptation, Hebei Key Laboratory of Molecular and Cellular Biology, College of Life Sciences, Hebei Normal University, Shijiazhuang, 050000, China.
| | - Fa Cui
- Key Laboratory of Molecular Module-Based Breeding of High Yield and Abiotic Resistant Plants in Universities of Shandong, College of Agriculture, Ludong University, Yantai, 264025, China.
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Zhang H, Li Y, Liu W, Sun Y, Tang J, Che J, Yang S, Wang X, Zhang R. Genetic Analysis of Adaptive Traits in Spring Wheat in Northeast China. Life (Basel) 2024; 14:168. [PMID: 38398677 PMCID: PMC10890535 DOI: 10.3390/life14020168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Revised: 01/13/2024] [Accepted: 01/17/2024] [Indexed: 02/25/2024] Open
Abstract
The dissection of the genetic architecture and the detection of the loci for adaptive traits are important for marker-assisted selection (MAS) for breeding. A spring wheat diversity panel with 251 cultivars, mainly from China, was obtained to conduct a genome-wide association study (GWAS) to detect the new loci, including the heading date (HD), maturating date (MD), plant height (PH), and lodging resistance (LR). In total, 41 loci existing in all 21 chromosomes, except for 4A and 6B, were identified, and each explained 4.3-18.9% of the phenotypic variations existing in two or more environments. Of these, 13 loci are overlapped with the known genes or quantitative trait loci (QTLs), whereas the other 28 are likely to be novel. The 1A locus (296.9-297.7 Mb) is a multi-effect locus for LR and PH, whereas the locus on chromosome 6D (464.5-471.0 Mb) affects both the HD and MD. Furthermore, four candidate genes for adaptive traits were identified, involved in cell division, signal transduction, and plant development. Additionally, two competitive, allele-specific PCR (KASP) markers, Kasp_2D_PH for PH and Kasp_6D_HD for HD, were developed and validated in another 162 spring wheat accessions. Our study uncovered the genetic basis of adaptive traits and provided the associated SNPs and varieties with more favorable alleles for wheat MAS breeding.
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Affiliation(s)
- Hongji Zhang
- Crop Resources Institute, Heilongjiang Academy of Agricultural Sciences, Harbin 150086, China; (W.L.); (Y.S.); (J.T.); (S.Y.); (X.W.)
| | - Yuyao Li
- Heilongjiang Academy of Agricultural Sciences, Harbin 150086, China;
| | - Wenlin Liu
- Crop Resources Institute, Heilongjiang Academy of Agricultural Sciences, Harbin 150086, China; (W.L.); (Y.S.); (J.T.); (S.Y.); (X.W.)
| | - Yan Sun
- Crop Resources Institute, Heilongjiang Academy of Agricultural Sciences, Harbin 150086, China; (W.L.); (Y.S.); (J.T.); (S.Y.); (X.W.)
| | - Jingquan Tang
- Crop Resources Institute, Heilongjiang Academy of Agricultural Sciences, Harbin 150086, China; (W.L.); (Y.S.); (J.T.); (S.Y.); (X.W.)
| | - Jingyu Che
- Keshan Branch of Heilongjiang Academy of Agricultural Sciences, Qiqihar 161600, China;
| | - Shuping Yang
- Crop Resources Institute, Heilongjiang Academy of Agricultural Sciences, Harbin 150086, China; (W.L.); (Y.S.); (J.T.); (S.Y.); (X.W.)
| | - Xiangyu Wang
- Crop Resources Institute, Heilongjiang Academy of Agricultural Sciences, Harbin 150086, China; (W.L.); (Y.S.); (J.T.); (S.Y.); (X.W.)
| | - Rui Zhang
- Institute of Forage and Grassland Sciences, Heilongjiang Academy of Agricultural Sciences, Harbin 150086, China;
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Bian Y, Li L, Tian X, Xu D, Sun M, Li F, Xie L, Liu S, Liu B, Xia X, He Z, Cao S. Rht12b, a widely used ancient allele of TaGA2oxA13, reduces plant height and enhances yield potential in wheat. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:253. [PMID: 37989964 DOI: 10.1007/s00122-023-04502-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/13/2023] [Accepted: 11/10/2023] [Indexed: 11/23/2023]
Abstract
KEY MESSAGE We identified a new wheat dwarfing allele Rht12b conferring reduced height and higher grain yield, pinpointed its causal variations, developed a breeding-applicable marker, and traced its origin and worldwide distribution. Plant height control is essential to optimize lodging resistance and yield gain in crops. RHT12 is a reduced height (Rht) locus that is identified in a mutationally induced dwarfing mutant and encodes a gibberellin 2-oxidase TaGA2oxA13. However, the artificial dwarfing allele is not used in wheat breeding due to excessive height reduction. Here, we confirmed a stable Rht locus, overlapping with RHT12, in a panel of wheat cultivars and its dwarfing allele reduced plant height by 5.4-8.2 cm, equivalent to Rht12b, a new allele of RHT12. We validated the effect of Rht12b on plant height in a bi-parent mapping population. Importantly, wheat cultivars carrying Rht12b had higher grain yield than those with the contrasting Rht12a allele. Rht12b conferred higher expression level of TaGA2oxA13. Transient activation assays defined SNP-390(C/A) in the promoter of TaGA2oxA13 as the causal variation. An efficient kompetitive allele-specific PCR marker was developed to diagnose Rht12b. Conjoint analysis showed that Rht12b plus the widely used Rht-D1b, Rht8 and Rht24b was the predominant Rht combination and conferred a moderate plant height in tested wheat cultivars. Evolutionary tracking uncovered that RHT12 locus arose from a tandem duplication event with Rht12b firstly appearing in wild emmer. The frequency of Rht12b was approximately 70% (700/1005) in a worldwide wheat panel and comparable to or higher than those of other widely used Rht genes, suggesting it had been subjected to positive selection. These findings not only identify a valuable Rht gene for wheat improvement but also develop a functionally diagnostic tool for marker-assisted breeding.
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Affiliation(s)
- Yingjie Bian
- National Wheat Improvement Center, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Lingli Li
- National Wheat Improvement Center, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Xiuling Tian
- National Wheat Improvement Center, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Dengan Xu
- National Wheat Improvement Center, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
- College of Agronomy, Qingdao Agricultural University, Qingdao, 266109, China
| | - Mengjing Sun
- National Wheat Improvement Center, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Faji Li
- Crop Research Institute, Shandong Academy of Agricultural Sciences, 202 Gongye North Road, Jinan, 250100, Shandong, China
| | - Lina Xie
- National Wheat Improvement Center, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Siyang Liu
- National Wheat Improvement Center, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Bingyan Liu
- National Wheat Improvement Center, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Xianchun Xia
- National Wheat Improvement Center, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Zhonghu He
- National Wheat Improvement Center, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China.
- International Maize and Wheat Improvement Center China Office, c/o Chinese Academy Agricultural Sciences, Beijing, 100081, China.
| | - Shuanghe Cao
- National Wheat Improvement Center, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China.
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8
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Joshi B, Singh S, Tiwari GJ, Kumar H, Boopathi NM, Jaiswal S, Adhikari D, Kumar D, Sawant SV, Iquebal MA, Jena SN. Genome-wide association study of fiber yield-related traits uncovers the novel genomic regions and candidate genes in Indian upland cotton ( Gossypium hirsutum L.). FRONTIERS IN PLANT SCIENCE 2023; 14:1252746. [PMID: 37941674 PMCID: PMC10630025 DOI: 10.3389/fpls.2023.1252746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Accepted: 09/11/2023] [Indexed: 11/10/2023]
Abstract
Upland cotton (Gossypium hirsutum L.) is a major fiber crop that is cultivated worldwide and has significant economic importance. India harbors the largest area for cotton cultivation, but its fiber yield is still compromised and ranks 22nd in terms of productivity. Genetic improvement of cotton fiber yield traits is one of the major goals of cotton breeding, but the understanding of the genetic architecture underlying cotton fiber yield traits remains limited and unclear. To better decipher the genetic variation associated with fiber yield traits, we conducted a comprehensive genome-wide association mapping study using 117 Indian cotton germplasm for six yield-related traits. To accomplish this, we generated 2,41,086 high-quality single nucleotide polymorphism (SNP) markers using genotyping-by-sequencing (GBS) methods. Population structure, PCA, kinship, and phylogenetic analyses divided the germplasm into two sub-populations, showing weak relatedness among the germplasms. Through association analysis, 205 SNPs and 134 QTLs were identified to be significantly associated with the six fiber yield traits. In total, 39 novel QTLs were identified in the current study, whereas 95 QTLs overlapped with existing public domain data in a comparative analysis. Eight QTLs, qGhBN_SCY_D6-1, qGhBN_SCY_D6-2, qGhBN_SCY_D6-3, qGhSI_LI_A5, qGhLI_SI_A13, qGhLI_SI_D9, qGhBW_SCY_A10, and qGhLP_BN_A8 were identified. Gene annotation of these fiber yield QTLs revealed 2,509 unique genes. These genes were predominantly enriched for different biological processes, such as plant cell wall synthesis, nutrient metabolism, and vegetative growth development in the gene ontology (GO) enrichment study. Furthermore, gene expression analysis using RNAseq data from 12 diverse cotton tissues identified 40 candidate genes (23 stable and 17 novel genes) to be transcriptionally active in different stages of fiber, ovule, and seed development. These findings have revealed a rich tapestry of genetic elements, including SNPs, QTLs, and candidate genes, and may have a high potential for improving fiber yield in future breeding programs for Indian cotton.
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Affiliation(s)
- Babita Joshi
- Plant Genetic Resources and Improvement, CSIR-National Botanical Research Institute, Lucknow, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
| | - Sanjay Singh
- Division of Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Gopal Ji Tiwari
- Plant Genetic Resources and Improvement, CSIR-National Botanical Research Institute, Lucknow, India
| | - Harish Kumar
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Regional Research Station, Faridkot, Punjab, India
| | - Narayanan Manikanda Boopathi
- Department of Plant Biotechnology, Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, India
| | - Sarika Jaiswal
- Division of Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Dibyendu Adhikari
- Plant Ecology and Climate Change Science, CSIR-National Botanical Research Institute, Lucknow, India
| | - Dinesh Kumar
- Division of Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Samir V. Sawant
- Molecular Biology & Biotechnology, CSIR-National Botanical Research Institute, Lucknow, India
| | - Mir Asif Iquebal
- Division of Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Satya Narayan Jena
- Plant Genetic Resources and Improvement, CSIR-National Botanical Research Institute, Lucknow, India
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9
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Jin Y, Wang Y, Liu J, Wang F, Qiu X, Liu P. Genome-wide linkage mapping of root system architecture-related traits in common wheat ( Triticum aestivum L.). FRONTIERS IN PLANT SCIENCE 2023; 14:1274392. [PMID: 37900737 PMCID: PMC10612324 DOI: 10.3389/fpls.2023.1274392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Accepted: 09/22/2023] [Indexed: 10/31/2023]
Abstract
Identifying loci for root system architecture (RSA) traits and developing available markers are crucial for wheat breeding. In this study, RSA-related traits, including total root length (TRL), total root area (TRA), and number of root tips (NRT), were evaluated in the Doumai/Shi4185 recombinant inbred line (RIL) population under hydroponics. In addition, both the RILs and parents were genotyped using the wheat 90K single-nucleotide polymorphism (SNP) array. In total, two quantitative trait loci (QTLs) each for TRL (QTRL.caas-4A.1 and QTRL.caas-4A.2), TRA (QTRA.caas-4A and QTRA.caas-4D), and NRT (QNRT.caas-5B and QNRT.caas-5D) were identified and each explaining 5.94%-9.47%, 6.85%-7.10%, and 5.91%-10.16% phenotypic variances, respectively. Among these, QTRL.caas-4A.1 and QTRA.caas-4A overlapped with previous reports, while QTRL.caas-4A.2, QTRA.caas-4D, QNRT.caas-5B, and QNRT.caas-5D were novel. The favorable alleles of QTRL.caas-4A.1, QTRA.caas-4A, and QTRA.caas-5B were contributed by Doumai, whereas the favorable alleles of QTRL.caas-4A.2, QTRA.caas-4D, and QTRA.caas-5D originated from Shi 4185. Additionally, two competitive allele-specific PCR (KASP) markers, Kasp_4A_RL (QTRA.caas-4A) and Kasp_5D_RT (QNRT.caas-5D), were developed and validated in 165 wheat accessions. This study provides new loci and available KASP markers, accelerating wheat breeding for higher yields.
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Affiliation(s)
- Yirong Jin
- Wheat Research Institute, Dezhou Academy of Agricultural Sciences, Dezhou, China
| | - Yamei Wang
- School of Agriculture, Sun Yat-sen University, Shenzhen, China
| | - Jindong Liu
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Fuyan Wang
- Wheat Research Institute, Dezhou Academy of Agricultural Sciences, Dezhou, China
| | - Xiaodong Qiu
- Department of Science and Technology of Shandong Province, Jinan, China
| | - Peng Liu
- Wheat Research Institute, Dezhou Academy of Agricultural Sciences, Dezhou, China
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10
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Yang X, Cai L, Wang M, Zhu W, Xu L, Wang Y, Zeng J, Fan X, Sha L, Wu D, Cheng Y, Zhang H, Jiang Y, Chen G, Zhou Y, Kang H. Genome-Wide Association Study of Asian and European Common Wheat Accessions for Yield-Related Traits and Stripe Rust Resistance. PLANT DISEASE 2023; 107:3085-3095. [PMID: 37079013 DOI: 10.1094/pdis-03-22-0702-re] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Identifying novel loci of yield-related traits and resistance to stripe rust (caused by Puccinia striiformis f. sp. tritici) in wheat will help in breeding wheat that can meet projected demands in diverse environmental and agricultural practices. We performed a genome-wide association study with 24,767 single nucleotide polymorphisms (SNPs) in 180 wheat accessions that originated in 16 Asian or European countries between latitudes 30°N and 45°N. We detected seven accessions with desirable yield-related traits and 42 accessions that showed stable, high degrees of stripe rust resistance in multienvironment field assessments. A marker-trait association analysis of yield-related traits detected 18 quantitative trait loci (QTLs) in at least two test environments and two QTLs related to stripe rust resistance in at least three test environments. Five of these QTLs were identified as potentially novel QTLs by comparing their physical locations with those of known QTLs in the Chinese Spring (CS) reference genome RefSeq v1.1 published by the International Wheat Genome Sequencing Consortium; two were for spike length, one was for grain number per spike, one was for spike number, and one was for stripe rust resistance at the adult plant stage. We also identified 14 candidate genes associated with the five novel QTLs. These QTLs and candidate genes will provide breeders with new germplasm and can be used to conduct marker-assisted selection in breeding wheat with improved yield and stripe rust resistance.
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Affiliation(s)
- Xiu Yang
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Li Cai
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Miaomiao Wang
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Wei Zhu
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Lili Xu
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Yi Wang
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Jian Zeng
- College of Resources, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Xing Fan
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Lina Sha
- College of Grassland Science and Technology, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Dandan Wu
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Yiran Cheng
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Haiqin Zhang
- College of Grassland Science and Technology, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Yunfeng Jiang
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Guoyue Chen
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Yonghong Zhou
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
| | - Houyang Kang
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China
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11
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Liu Y, Chen J, Yin C, Wang Z, Wu H, Shen K, Zhang Z, Kang L, Xu S, Bi A, Zhao X, Xu D, He Z, Zhang X, Hao C, Wu J, Gong Y, Yu X, Sun Z, Ye B, Liu D, Zhang L, Shen L, Hao Y, Ma Y, Lu F, Guo Z. A high-resolution genotype-phenotype map identifies the TaSPL17 controlling grain number and size in wheat. Genome Biol 2023; 24:196. [PMID: 37641093 PMCID: PMC10463835 DOI: 10.1186/s13059-023-03044-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Accepted: 08/21/2023] [Indexed: 08/31/2023] Open
Abstract
BACKGROUND Large-scale genotype-phenotype association studies of crop germplasm are important for identifying alleles associated with favorable traits. The limited number of single-nucleotide polymorphisms (SNPs) in most wheat genome-wide association studies (GWASs) restricts their power to detect marker-trait associations. Additionally, only a few genes regulating grain number per spikelet have been reported due to sensitivity of this trait to variable environments. RESULTS We perform a large-scale GWAS using approximately 40 million filtered SNPs for 27 spike morphology traits. We detect 132,086 significant marker-trait associations and the associated SNP markers are located within 590 associated peaks. We detect additional and stronger peaks by dividing spike morphology into sub-traits relative to GWAS results of spike morphology traits. We propose that the genetic dissection of spike morphology is a powerful strategy to detect signals for grain yield traits in wheat. The GWAS results reveal that TaSPL17 positively controls grain size and number by regulating spikelet and floret meristem development, which in turn leads to enhanced grain yield per plant. The haplotypes at TaSPL17 indicate geographical differentiation, domestication effects, and breeding selection. CONCLUSION Our study provides valuable resources for genetic improvement of spike morphology and a fast-forward genetic solution for candidate gene detection and cloning in wheat.
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Affiliation(s)
- Yangyang Liu
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Jun Chen
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China
| | - Changbin Yin
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, 10011, China
| | - Ziying Wang
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - He Wu
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Kuocheng Shen
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Zhiliang Zhang
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, 10011, China
| | - Lipeng Kang
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, 10011, China
| | - Song Xu
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, 10011, China
| | - Aoyue Bi
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, 10011, China
| | - Xuebo Zhao
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, 10011, China
| | - Daxing Xu
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, 10011, China
| | - Zhonghu He
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China
- International Maize and Wheat Improvement Center (CIMMYT) China Office, c/o CAAS, Beijing, 100081, China
| | - Xueyong Zhang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China
| | - Chenyang Hao
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China
| | - Jianhui Wu
- State Key Laboratory of Crop Stress Biology for Arid Areas, Northwest A&F University, Yangling, 712100, Shaanxi, China
| | - Yan Gong
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China
| | - Xuchang Yu
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Zhiwen Sun
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Botao Ye
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Danni Liu
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Lili Zhang
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China
| | - Liping Shen
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China
| | - Yuanfeng Hao
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China.
| | - Youzhi Ma
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China.
| | - Fei Lu
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, 10011, China.
- CAS-JIC Centre of Excellence for Plant and Microbial Science (CEPAMS), Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, 100093, China.
| | - Zifeng Guo
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
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12
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Zhang Y, Miao H, Xiao Y, Wang C, Zhang J, Shi X, Xie S, Wang C, Li T, Deng P, Chen C, Zhang H, Ji W. An intron-located single nucleotide variation of TaGS5-3D is related to wheat grain size through accumulating intron retention transcripts. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:193. [PMID: 37606787 DOI: 10.1007/s00122-023-04439-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Accepted: 07/31/2023] [Indexed: 08/23/2023]
Abstract
KEY MESSAGE Thirty-three stable QTL for 13 yield-related traits across ten environments were identified in the PD34/MY47 RIL population, and a candidate gene TaGS5-3D in Qmt.nwafu.3D was preliminarily identified to affect grain-related traits through accumulation of specific transcripts. Dissecting the genetic basis of yield-related traits is pivotal for improvement of wheat yield potential. In this study, a recombinant inbred line (RIL) population genotyped by SNP markers was used to detect quantitative trait loci (QTL) related to yield-related traits in ten environments. A total of 102 QTL were detected, including 33 environmentally stable QTL and 69 putative QTL. Among them, Qmt.nwafu.3D was identified as a pleiotropic QTL in the physical interval of 149.77-154.11 Mb containing a potential candidate gene TaGS5-3D. An SNP (T > C) was detected in its ninth intron, and TaGS5-3D-C was validated as a superior allele associated with larger grains using a CAPS marker. Interestingly, we found that TaGS5-3D-C was closely related to significantly up-regulated expression of intron-retained transcript (TaGS5-3D-PD34.1), while TaGS5-3D-T was related to dominant expression of normal splicing transcript (TaGS5-3D-MY47.1). Our results indicated that alternative splicing associated with the SNP T/C could be involved in the regulation of grain-related traits, laying a foundation for the functional analysis of TaGS5-3D and its greater potential application in high-yield wheat breeding.
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Affiliation(s)
- Yaoyuan Zhang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, China
| | - Hanxiao Miao
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, China
| | - Yi Xiao
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, China
| | - Chao Wang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, China
| | - Junjie Zhang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, China
| | - Xiaoxi Shi
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, China
| | - Songfeng Xie
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, China
| | - Changyou Wang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, China
- Shaanxi Research Station of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs, Yangling, 712100, China
| | - Tingdong Li
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, China
- Shaanxi Research Station of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs, Yangling, 712100, China
| | - Pingchuan Deng
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, China
- Shaanxi Research Station of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs, Yangling, 712100, China
| | - Chunhuan Chen
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, China
- Shaanxi Research Station of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs, Yangling, 712100, China
| | - Hong Zhang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, China.
- Shaanxi Research Station of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs, Yangling, 712100, China.
| | - Wanquan Ji
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, China.
- Shaanxi Research Station of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs, Yangling, 712100, China.
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13
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Li L, Xu D, Bian Y, Liu B, Zeng J, Xie L, Liu S, Tian X, Liu J, Xia X, He Z, Zhang Y, Zhang Y, Cao S. Fine mapping and characterization of a major QTL for plant height on chromosome 5A in wheat. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:167. [PMID: 37402103 DOI: 10.1007/s00122-023-04416-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Accepted: 06/23/2023] [Indexed: 07/05/2023]
Abstract
KEY MESSAGE We precisely mapped QPH.caas-5AL for plant height in wheat, predicted candidate genes and confirmed genetic effects in a panel of wheat cultivars. Plant height is an important agronomic trait, and appropriately reduced height can improve yield potential and stability in wheat, usually combined with sufficient water and fertilizer. We previously detected a stable major-effect quantitative trait locus QPH.caas-5AL for plant height on chromosome 5A in a recombinant inbred line population of the cross 'Doumai × Shi 4185' using the wheat 90 K SNP assay. Here , QPH.caas-5AL was confirmed using new phenotypic data in additional environment and new-developed markers. We identified nine heterozygous recombinant plants for fine mapping of QPH.caas-5AL and developed 14 breeder-friendly kompetitive allele-specific PCR markers in the region of QPH.caas-5AL based on the genome re-sequencing data of parents. Phenotyping and genotyping analyses of secondary populations derived from the self-pollinated heterozygous recombinant plants delimited QPH.caas-5AL into an approximate 3.0 Mb physical region (521.0-524.0 Mb) according to the Chinese Spring reference genome. This region contains 45 annotated genes, and six of them were predicted as the candidates of QPH.caas-5AL based on genome and transcriptome sequencing analyses. We further validated that QPH.caas-5AL has significant effects on plant height but not yield component traits in a diverse panel of wheat cultivars; its dwarfing allele is frequently used in modern wheat cultivars. These findings lay a solid foundation for the map-based cloning of QPH.caas-5AL and also provide a breeding-applicable tool for its marker-assisted selection. Keymessage We precisely mapped QPH.caas-5AL for plant height in wheat, predicted candidate genes and confirmed genetic effects in a panel of wheat cultivars.
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Affiliation(s)
- Lingli Li
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Dengan Xu
- Shandong Provincial Key Laboratory of Dryland Farming Technology, College of Agronomy, Qingdao Agricultural University, Qingdao, 266109, Shandong, China
| | - Yingjie Bian
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Bingyan Liu
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Jianqi Zeng
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Lina Xie
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Siyang Liu
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Xiuling Tian
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Jindong Liu
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Xianchun Xia
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Zhonghu He
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
- International Maize and Wheat Improvement Center (CIMMYT) China Office, c/o CAAS, 12 Zhongguancun South Street, Beijing, 100081, China
| | - Yan Zhang
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Yong Zhang
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China.
| | - Shuanghe Cao
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China.
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14
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Song C, Xie K, Hu X, Zhou Z, Liu A, Zhang Y, Du J, Jia J, Gao L, Mao H. Genome wide association and haplotype analyses for the crease depth trait in bread wheat ( Triticum aestivum L.). FRONTIERS IN PLANT SCIENCE 2023; 14:1203253. [PMID: 37465391 PMCID: PMC10350514 DOI: 10.3389/fpls.2023.1203253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Accepted: 06/14/2023] [Indexed: 07/20/2023]
Abstract
Wheat grain has a complex structure that includes a crease on one side, and tissues within the crease region play an important role in nutrient transportation during wheat grain development. However, the genetic architecture of the crease region is still unclear. In this study, 413 global wheat accessions were resequenced and a method was developed for evaluating the phenotypic data of crease depth (CD). The CD values exhibited continuous and considerable large variation in the population, and the broad-sense heritability was 84.09%. CD was found to be positively correlated with grain-related traits and negatively with quality-related traits. Analysis of differentiation of traits between landraces and cultivars revealed that grain-related traits and CD were simultaneously improved during breeding improvement. Moreover, 2,150.8-Mb genetic segments were identified to fall within the selective sweeps between the landraces and cultivars; they contained some known functional genes for quality- and grain-related traits. Genome-wide association study (GWAS) was performed using around 10 million SNPs generated by genome resequencing and 551 significant SNPs and 18 QTLs were detected significantly associated with CD. Combined with cluster analysis of gene expression, haplotype analysis, and annotated information of candidate genes, two promising genes TraesCS3D02G197700 and TraesCS5A02G292900 were identified to potentially regulate CD. To the best of our knowledge, this is the first study to provide the genetic basis of CD, and the genetic loci identified in this study may ultimately assist in wheat breeding programs.
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Affiliation(s)
- Chengxiang Song
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Kaidi Xie
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Xin Hu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Zhihua Zhou
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Ankui Liu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Yuwei Zhang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Jiale Du
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Jizeng Jia
- Institute of Crop Sciences, Chinese Academy of Agriculture Sciences, Beijing, China
| | - Lifeng Gao
- Institute of Crop Sciences, Chinese Academy of Agriculture Sciences, Beijing, China
| | - Hailiang Mao
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
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15
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Cabral AL, Ruan Y, Cuthbert RD, Li L, Zhang W, Boyle K, Berraies S, Henriquez MA, Burt A, Kumar S, Fobert P, Piche I, Bokore FE, Meyer B, Sangha J, Knox RE. Multi-locus genome-wide association study of fusarium head blight in relation to days to anthesis and plant height in a spring wheat association panel. FRONTIERS IN PLANT SCIENCE 2023; 14:1166282. [PMID: 37457352 PMCID: PMC10346453 DOI: 10.3389/fpls.2023.1166282] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Accepted: 05/03/2023] [Indexed: 07/18/2023]
Abstract
Fusarium head blight (FHB) is a highly destructive fungal disease of wheat to which host resistance is quantitatively inherited and largely influenced by the environment. Resistance to FHB has been associated with taller height and later maturity; however, a further understanding of these relationships is needed. An association mapping panel (AMP) of 192 predominantly Canadian spring wheat was genotyped with the wheat 90K single-nucleotide polymorphism (SNP) array. The AMP was assessed for FHB incidence (INC), severity (SEV) and index (IND), days to anthesis (DTA), and plant height (PLHT) between 2015 and 2017 at three Canadian FHB-inoculated nurseries. Seven multi-environment trial (MET) datasets were deployed in a genome-wide association study (GWAS) using a single-locus mixed linear model (MLM) and a multi-locus random SNP-effect mixed linear model (mrMLM). MLM detected four quantitative trait nucleotides (QTNs) for INC on chromosomes 2D and 3D and for SEV and IND on chromosome 3B. Further, mrMLM identified 291 QTNs: 50 (INC), 72 (SEV), 90 (IND), 41 (DTA), and 38 (PLHT). At two or more environments, 17 QTNs for FHB, DTA, and PLHT were detected. Of these 17, 12 QTNs were pleiotropic for FHB traits, DTA, and PLHT on chromosomes 1A, 1D, 2D, 3B, 5A, 6B, 7A, and 7B; two QTNs for DTA were detected on chromosomes 1B and 7A; and three PLHT QTNs were located on chromosomes 4B and 6B. The 1B DTA QTN and the three pleiotropic QTNs on chromosomes 1A, 3B, and 6B are potentially identical to corresponding quantitative trait loci (QTLs) in durum wheat. Further, the 3B pleiotropic QTN for FHB INC, SEV, and IND co-locates with TraesCS3B02G024900 within the Fhb1 region on chromosome 3B and is ~3 Mb from a cloned Fhb1 candidate gene TaHRC. While the PLHT QTN on chromosome 6B is putatively novel, the 1B DTA QTN co-locates with a disease resistance protein located ~10 Mb from a Flowering Locus T1-like gene TaFT3-B1, and the 7A DTA QTN is ~5 Mb away from a maturity QTL QMat.dms-7A.3 of another study. GWAS and QTN candidate genes enabled the characterization of FHB resistance in relation to DTA and PLHT. This approach should eventually generate additional and reliable trait-specific markers for breeding selection, in addition to providing useful information for FHB trait discovery.
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Affiliation(s)
- Adrian L. Cabral
- Swift Current Research and Development Centre, Agriculture and Agri-Food Canada, Swift Current, SK, Canada
| | - Yuefeng Ruan
- Swift Current Research and Development Centre, Agriculture and Agri-Food Canada, Swift Current, SK, Canada
| | - Richard D. Cuthbert
- Swift Current Research and Development Centre, Agriculture and Agri-Food Canada, Swift Current, SK, Canada
| | - Lin Li
- Swift Current Research and Development Centre, Agriculture and Agri-Food Canada, Swift Current, SK, Canada
| | - Wentao Zhang
- Aquatic and Crop Resource Development Research Centre, National Research Council of Canada, Saskatoon, SK, Canada
| | - Kerry Boyle
- Aquatic and Crop Resource Development Research Centre, National Research Council of Canada, Saskatoon, SK, Canada
| | - Samia Berraies
- Swift Current Research and Development Centre, Agriculture and Agri-Food Canada, Swift Current, SK, Canada
| | - Maria Antonia Henriquez
- Morden Research and Development Centre, Agriculture and Agri-Food Canada, Morden, MB, Canada
| | - Andrew Burt
- Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON, Canada
| | - Santosh Kumar
- Brandon Research and Development Centre, Agriculture and Agri-Food Canada, Brandon, MB, Canada
| | - Pierre Fobert
- Aquatic and Crop Resource Development Research Centre, National Research Council of Canada, Ottawa, ON, Canada
| | - Isabelle Piche
- Swift Current Research and Development Centre, Agriculture and Agri-Food Canada, Swift Current, SK, Canada
| | - Firdissa E. Bokore
- Swift Current Research and Development Centre, Agriculture and Agri-Food Canada, Swift Current, SK, Canada
| | - Brad Meyer
- Swift Current Research and Development Centre, Agriculture and Agri-Food Canada, Swift Current, SK, Canada
| | - Jatinder Sangha
- Swift Current Research and Development Centre, Agriculture and Agri-Food Canada, Swift Current, SK, Canada
| | - Ron E. Knox
- Swift Current Research and Development Centre, Agriculture and Agri-Food Canada, Swift Current, SK, Canada
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16
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Wang X, Zhang J, Mao W, Guan P, Wang Y, Chen Y, Liu W, Guo W, Yao Y, Hu Z, Xin M, Ni Z, Sun Q, Peng H. Association mapping identifies loci and candidate genes for grain-related traits in spring wheat in response to heat stress. PLANT SCIENCE : AN INTERNATIONAL JOURNAL OF EXPERIMENTAL PLANT BIOLOGY 2023; 331:111676. [PMID: 36933836 DOI: 10.1016/j.plantsci.2023.111676] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Revised: 02/05/2023] [Accepted: 03/14/2023] [Indexed: 06/18/2023]
Abstract
Heat stress is a limiting factor in wheat production along with global warming. Development of heat-tolerant wheat varieties and generation of suitable pre-breeding materials are the major goals in current wheat breeding programs. Our understanding on the genetic basis of thermotolerance remains sparse. In this study, we genotyped a collection of 211 core spring wheat accessions and conducted field trials to evaluate the grain-related traits under heat stress and non-stress conditions in two different locations for three consecutive years. Based on SNP datasets and grain-related traits, we performed genome-wide association study (GWAS) to detect stable loci related to thermotolerance. Thirty-three quantitative trait loci (QTL) were identified, nine of them are the same loci as previous studies, and 24 are potentially novel loci. Functional candidate genes at these QTL are predicted and proved to be relevant to heat stress and grain-related traits such as TaELF3-A1 (1A) for earliness per se (Eps), TaHSFA1-B1 (5B) influencing heat tolerance and TaVIN2-A1 (6A) for grain size. Functional markers of TaELF3-A1 were detected and converted to KASP markers, with their function and genetic diversity being analyzed in the natural populations. In addition, our results unveiled favor alleles controlling agronomic traits and/or heat stress tolerance. In summary, we provide insights into heritable correlation between yield and heat stress tolerance, which will accelerate the development of new cultivars with high and stable yield of wheat in the future.
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Affiliation(s)
- Xiaobo Wang
- Frontiers Science Center for Molecular Design Breeding (MOE), Key Laboratory of Crop Heterosis and Utilization, Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
| | - Jinbo Zhang
- Frontiers Science Center for Molecular Design Breeding (MOE), Key Laboratory of Crop Heterosis and Utilization, Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, China; Institute of Crop Germplasm Resource, Xinjiang Academy of Agricultural Sciences, Urumqi, China
| | - Weiwei Mao
- Frontiers Science Center for Molecular Design Breeding (MOE), Key Laboratory of Crop Heterosis and Utilization, Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
| | - Panfeng Guan
- Frontiers Science Center for Molecular Design Breeding (MOE), Key Laboratory of Crop Heterosis and Utilization, Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
| | - Yongfa Wang
- Frontiers Science Center for Molecular Design Breeding (MOE), Key Laboratory of Crop Heterosis and Utilization, Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
| | - Yongming Chen
- Frontiers Science Center for Molecular Design Breeding (MOE), Key Laboratory of Crop Heterosis and Utilization, Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
| | - Wangqing Liu
- Crop Research Institute of Ningxia Academy of Agriculture and Forestry Sciences, Ningxia, China
| | - Weilong Guo
- Frontiers Science Center for Molecular Design Breeding (MOE), Key Laboratory of Crop Heterosis and Utilization, Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
| | - Yingyin Yao
- Frontiers Science Center for Molecular Design Breeding (MOE), Key Laboratory of Crop Heterosis and Utilization, Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
| | - Zhaorong Hu
- Frontiers Science Center for Molecular Design Breeding (MOE), Key Laboratory of Crop Heterosis and Utilization, Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
| | - Mingming Xin
- Frontiers Science Center for Molecular Design Breeding (MOE), Key Laboratory of Crop Heterosis and Utilization, Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
| | - Zhongfu Ni
- Frontiers Science Center for Molecular Design Breeding (MOE), Key Laboratory of Crop Heterosis and Utilization, Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
| | - Qixin Sun
- Frontiers Science Center for Molecular Design Breeding (MOE), Key Laboratory of Crop Heterosis and Utilization, Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, China.
| | - Huiru Peng
- Frontiers Science Center for Molecular Design Breeding (MOE), Key Laboratory of Crop Heterosis and Utilization, Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, China.
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17
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Li Y, Tao F, Hao Y, Tong J, Xiao Y, He Z, Reynolds M. Variations in phenological, physiological, plant architectural and yield-related traits, their associations with grain yield and genetic basis. ANNALS OF BOTANY 2023; 131:503-519. [PMID: 36655618 PMCID: PMC10072080 DOI: 10.1093/aob/mcad003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Accepted: 01/09/2023] [Indexed: 06/17/2023]
Abstract
BACKGROUND AND AIMS Physiological and morphological traits play essential roles in wheat (Triticum aestivum) growth and development. In particular, photosynthesis is a limitation to yield. Increasing photosynthesis in wheat has been identified as an important strategy to increase yield. However, the genotypic variations and the genomic regions governing morphological, architectural and photosynthesis traits remain unexplored. METHODS Here, we conducted a large-scale investigation of the phenological, physiological, plant architectural and yield-related traits, involving 32 traits for 166 wheat lines during 2018-2020 in four environments, and performed a genome-wide association study with wheat 90K and 660K single nucleotide polymorphism (SNP) arrays. KEY RESULTS These traits exhibited considerable genotypic variations in the wheat diversity panel. Higher yield was associated with higher net photosynthetic rate (r = 0.41, P < 0.01), thousand-grain weight (r = 0.36, P < 0.01) and truncated and lanceolate shape, but shorter plant height (r = -0.63, P < 0.01), flag leaf angle (r = -0.49, P < 0.01) and spike number per square metre (r = -0.22, P < 0.01). Genome-wide association mapping discovered 1236 significant stable loci detected in the four environments among the 32 traits using SNP markers. Trait values have a cumulative effect as the number of the favourable alleles increases, and significant progress has been made in determining phenotypic values and favourable alleles over the years. Eleven elite cultivars and 14 traits associated with grain yield per plot (GY) were identified as potential parental lines and as target traits to develop high-yielding cultivars. CONCLUSIONS This study provides new insights into the phenotypic and genetic elucidation of physiological and morphological traits in wheat and their associations with GY, paving the way for discovering their underlying gene control and for developing enhanced ideotypes in wheat breeding.
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Affiliation(s)
- Yibo Li
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | | | - Yuanfeng Hao
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Jingyang Tong
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Yonggui Xiao
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | | | - Matthew Reynolds
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
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18
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Halder T, Liu H, Chen Y, Yan G, Siddique KHM. Chromosome groups 5, 6 and 7 harbor major quantitative trait loci controlling root traits in bread wheat ( Triticum aestivum L.). FRONTIERS IN PLANT SCIENCE 2023; 14:1092992. [PMID: 37021301 PMCID: PMC10067626 DOI: 10.3389/fpls.2023.1092992] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Accepted: 02/27/2023] [Indexed: 06/19/2023]
Abstract
Identifying genomic regions for root traits in bread wheat can help breeders develop climate-resilient and high-yielding wheat varieties with desirable root traits. This study used the recombinant inbred line (RIL) population of Synthetic W7984 × Opata M85 to identify quantitative trait loci (QTL) for different root traits such as rooting depth (RD), root dry mass (RM), total root length (RL), root diameter (Rdia) and root surface areas (RSA1 for coarse roots and RSA2 for fine roots) under controlled conditions in a semi-hydroponic system. We detected 14 QTL for eight root traits on nine wheat chromosomes; we discovered three QTL each for RD and RSA1, two QTL each for RM and RSA2, and one QTL each for RL, Rdia, specific root length and nodal root number per plant. The detected QTL were concentrated on chromosome groups 5, 6 and 7. The QTL for shallow RD (Q.rd.uwa.7BL: Xbarc50) and high RM (Q.rm.uwa.6AS: Xgwm334) were validated in two independent F2 populations of Synthetic W7984 × Chara and Opata M85 × Cascade, respectively. Genotypes containing negative alleles for Q.rd.uwa.7BL had 52% shallower RD than other Synthetic W7984 × Chara population lines. Genotypes with the positive alleles for Q.rm.uwa.6AS had 31.58% higher RM than other Opata M85 × Cascade population lines. Further, we identified 21 putative candidate genes for RD (Q.rd.uwa.7BL) and 13 for RM (Q.rm.uwa.6AS); TraesCS6A01G020400, TraesCS6A01G024400 and TraesCS6A01G021000 identified from Q.rm.uwa.6AS, and TraesCS7B01G404000, TraesCS7B01G254900 and TraesCS7B01G446200 identified from Q.rd.uwa.7BL encoded important proteins for root traits. We found germin-like protein encoding genes in both Q.rd.uwa.7BL and Q.rm.uwa.6AS regions. These genes may play an important role in RM and RD improvement. The identified QTL, especially the validated QTL and putative candidate genes are valuable genetic resources for future root trait improvement in wheat.
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Affiliation(s)
- Tanushree Halder
- UWA School of Agriculture and Environment, The University of Western Australia, Crawley, WA, Australia
- The UWA Institute of Agriculture, The University of Western Australia, Crawley, WA, Australia
- Department of Genetics and Plant Breeding, Faculty of Agriculture, Sher-e-Bangla Agricultural University, Dhaka, Bangladesh
| | - Hui Liu
- UWA School of Agriculture and Environment, The University of Western Australia, Crawley, WA, Australia
- The UWA Institute of Agriculture, The University of Western Australia, Crawley, WA, Australia
| | - Yinglong Chen
- UWA School of Agriculture and Environment, The University of Western Australia, Crawley, WA, Australia
- The UWA Institute of Agriculture, The University of Western Australia, Crawley, WA, Australia
| | - Guijun Yan
- UWA School of Agriculture and Environment, The University of Western Australia, Crawley, WA, Australia
- The UWA Institute of Agriculture, The University of Western Australia, Crawley, WA, Australia
| | - Kadambot H. M. Siddique
- UWA School of Agriculture and Environment, The University of Western Australia, Crawley, WA, Australia
- The UWA Institute of Agriculture, The University of Western Australia, Crawley, WA, Australia
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19
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Ma F, Xu Y, Wang R, Tong Y, Zhang A, Liu D, An D. Identification of major QTLs for yield-related traits with improved genetic map in wheat. FRONTIERS IN PLANT SCIENCE 2023; 14:1138696. [PMID: 37008504 PMCID: PMC10063875 DOI: 10.3389/fpls.2023.1138696] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Accepted: 03/08/2023] [Indexed: 06/19/2023]
Abstract
INTRODUCTION Identification of stable major quantitative trait loci (QTLs) for yield-related traits is important for yield potential improvement in wheat breeding. METHODS In the present study, we genotyped a recombinant inbred line (RIL) population using the Wheat 660K SNP array and constructed a high-density genetic map. The genetic map showed high collinearity with the wheat genome assembly. Fourteen yield-related traits were evaluated in six environments for QTL analysis. RESULTS AND DISCUSSION A total of 12 environmentally stable QTLs were identified in at least three environments, explaining up to 34.7% of the phenotypic variation. Of these, QTkw-1B.2 for thousand kernel weight (TKW), QPh-2D.1 (QSl-2D.2/QScn-2D.1) for plant height (PH), spike length (SL) and spikelet compactness (SCN), QPh-4B.1 for PH, and QTss-7A.3 for total spikelet number per spike (TSS) were detected in at least five environments. A set of Kompetitive Allele Specific PCR (KASP) markers were converted based on the above QTLs and used to genotype a diversity panel comprising of 190 wheat accessions across four growing seasons. QPh-2D.1 (QSl-2D.2/QScn-2D.1), QPh-4B.1 and QTss-7A.3 were successfully validated. Compared with previous studies, QTkw-1B.2 and QPh-4B.1 should be novel QTLs. These results provided a solid foundation for further positional cloning and marker-assisted selection of the targeted QTLs in wheat breeding programs.
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Affiliation(s)
- Feifei Ma
- Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, China
| | - Yunfeng Xu
- Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, China
| | - Ruifang Wang
- Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, China
| | - Yiping Tong
- State Key Laboratory of Plant Cell and Chromosome Engineering, National Center for Plant Gene Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
| | - Aimin Zhang
- State Key Laboratory of North China Crop Improvement and Regulation, College of Agronomy, Hebei Agricultural University, Baoding, Hebei, China
- State Key Laboratory of Plant Cell and Chromosome Engineering, National Center for Plant Gene Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
| | - Dongcheng Liu
- State Key Laboratory of North China Crop Improvement and Regulation, College of Agronomy, Hebei Agricultural University, Baoding, Hebei, China
| | - Diaoguo An
- Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, China
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20
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Song J, Li L, Liu B, Dong Y, Dong Y, Li F, Liu S, Luo X, Sun M, Ni Z, Fei S, Xia X, Ni Z, He Z, Cao S. Fine mapping of reduced height locus RHT26 in common wheat. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:62. [PMID: 36914894 DOI: 10.1007/s00122-023-04331-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Accepted: 02/23/2023] [Indexed: 06/18/2023]
Abstract
We fine mapped RHT26 for plant height in wheat, confirmed its genetic effects in a panel of wheat cultivars and predicted candidate genes. Development of wheat cultivars with appropriate plant height (PH) is an important goal in breeding. Utilization of semi-dwarfing genes Rht-B1b and Rht-D1b triggered wheat Green Resolution in the 1960s. Since these genes also bring unfavorable features, such as reduced coleoptile length and grain weight, it is necessary to identify alternative reduced height genes without yield penalty. Here we constructed a high-density genetic map of a recombinant inbred line population derived from the cross of Zhongmai175 and Lunxuan987 and detected a stable genetic locus for PH, designated RHT26, on chromosome arm 3DL in all of six environments, accounting for 6.8-14.0% of the phenotypic variances. RHT26 was delimited to an approximate 1.4 Mb physical interval (517.1-518.5 Mb) using secondary mapping populations derived from 22 heterozygous recombinant plants and 24 kompetitive allele-specific PCR markers. Eleven high-confidence genes were annotated in the physical interval according to the Chinese Spring reference genome, and four of them were predicted as candidates for RHT26 based on genome and transcriptome sequencing analyses. We also confirmed that RHT26 had significant effects on PH, but not grain yield in a panel of wheat cultivars; its dwarfing allele has been frequently used in wheat breeding. These findings lay a sound foundation for map-based cloning of RHT26 and provide a breeding-applicable tool for marker-assisted selection.
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Affiliation(s)
- Jie Song
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Lei Li
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Bingyan Liu
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Yachao Dong
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Yan Dong
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Faji Li
- Crop Research Institute, Shandong Academy of Agricultural Sciences, 202 Gongye North Road, Jinan, 250100, Shandong, China
| | - Siyang Liu
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Xumei Luo
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Mengjing Sun
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Zhongqiu Ni
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Shuaipeng Fei
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Xianchun Xia
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Zhongfu Ni
- State Key Laboratory of Agrobiotechnology, Key Laboratory of Crop Heterosis and Utilization, Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy, China Agricultural University, 2 Yuanmingyuan West Road, Beijing, 100094, China
| | - Zhonghu He
- International Maize and Wheat Improvement Center (CIMMYT) China Office, c/o, CAAS, 12 Zhongguancun South Street, Beijing, 100081, China.
| | - Shuanghe Cao
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China.
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Zeng Z, Zhao D, Wang C, Yan X, Song J, Chen P, Lan C, Singh RP. QTL cluster analysis and marker development for kernel traits based on DArT markers in spring bread wheat ( Triticum aestivum L.). FRONTIERS IN PLANT SCIENCE 2023; 14:1072233. [PMID: 36844075 PMCID: PMC9951491 DOI: 10.3389/fpls.2023.1072233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Accepted: 01/23/2023] [Indexed: 06/18/2023]
Abstract
Genetic dissection of yield component traits including kernel characteristics is essential for the continuous improvement in wheat yield. In the present study, one recombinant inbred line (RIL) F6 population derived from a cross between Avocet and Chilero was used to evaluate the phenotypes of kernel traits of thousand-kernel weight (TKW), kernel length (KL), and kernel width (KW) in four environments at three experimental stations during the 2018-2020 wheat growing seasons. The high-density genetic linkage map was constructed with the diversity arrays technology (DArT) markers and the inclusive composite interval mapping (ICIM) method to identify the quantitative trait loci (QTLs) for TKW, KL, and KW. A total of 48 QTLs for three traits were identified in the RIL population on the 21 chromosomes besides 2A, 4D, and 5B, accounting for 3.00%-33.85% of the phenotypic variances. Based on the physical positions of each QTL, nine stable QTL clusters were identified in the RILs, and among these QTL clusters, TaTKW-1A was tightly linked to the DArT marker interval 3950546-1213099, explaining 10.31%-33.85% of the phenotypic variances. A total of 347 high-confidence genes were identified in a 34.74-Mb physical interval. TraesCS1A02G045300 and TraesCS1A02G058400 were among the putative candidate genes associated with kernel traits, and they were expressed during grain development. Moreover, we also developed high-throughput kompetitive allele-specific PCR (KASP) markers of TaTKW-1A, validated in a natural population of 114 wheat varieties. The study provides a basis for cloning the functional genes underlying the QTL for kernel traits and a practical and accurate marker for molecular breeding.
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Affiliation(s)
- Zhankui Zeng
- College of Agronomy, Henan University of Science and Technology, Luoyang, Henan, China
- The Shennong Laboratory, Zhengzhou, Henan, China
| | - Dehui Zhao
- College of Agronomy, Henan University of Science and Technology, Luoyang, Henan, China
- The Shennong Laboratory, Zhengzhou, Henan, China
| | - Chunping Wang
- College of Agronomy, Henan University of Science and Technology, Luoyang, Henan, China
- The Shennong Laboratory, Zhengzhou, Henan, China
| | - Xuefang Yan
- College of Agronomy, Henan University of Science and Technology, Luoyang, Henan, China
- The Shennong Laboratory, Zhengzhou, Henan, China
| | - Junqiao Song
- College of Agronomy, Henan University of Science and Technology, Luoyang, Henan, China
- The Shennong Laboratory, Zhengzhou, Henan, China
| | - Peng Chen
- College of Agronomy, Henan University of Science and Technology, Luoyang, Henan, China
- The Shennong Laboratory, Zhengzhou, Henan, China
| | - Caixia Lan
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, Hubei, China
| | - Ravi P. Singh
- Global Wheat Program, International Maize and Wheat Improvement Center (CIMMYT), Mexico, Mexico
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22
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Kong B, Ma J, Zhang P, Chen T, Liu Y, Che Z, Shahinnia F, Yang D. Deciphering key genomic regions controlling flag leaf size in wheat via integration of meta-QTL and in silico transcriptome assessment. BMC Genomics 2023; 24:33. [PMID: 36658498 PMCID: PMC9854125 DOI: 10.1186/s12864-023-09119-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Accepted: 01/05/2023] [Indexed: 01/20/2023] Open
Abstract
BACKGROUND Grain yield is a complex and polygenic trait influenced by the photosynthetic source-sink relationship in wheat. The top three leaves, especially the flag leaf, are considered the major sources of photo-assimilates accumulated in the grain. Determination of significant genomic regions and candidate genes affecting flag leaf size can be used in breeding for grain yield improvement. RESULTS With the final purpose of understanding key genomic regions for flag leaf size, a meta-analysis of 521 initial quantitative trait loci (QTLs) from 31 independent QTL mapping studies over the past decades was performed, where 333 loci eventually were refined into 64 meta-QTLs (MQTLs). The average confidence interval (CI) of these MQTLs was 5.28 times less than that of the initial QTLs. Thirty-three MQTLs overlapped the marker trait associations (MTAs) previously reported in genome-wide association studies (GWAS) for flag leaf traits in wheat. A total of 2262 candidate genes for flag leaf size, which were involved in the peroxisome, basal transcription factor, and tyrosine metabolism pathways were identified in MQTL regions by the in silico transcriptome assessment. Of these, the expression analysis of the available genes revealed that 134 genes with > 2 transcripts per million (TPM) were highly and specifically expressed in the leaf. These candidate genes could be critical to affect flag leaf size in wheat. CONCLUSIONS The findings will make further insight into the genetic determinants of flag leaf size and provide some reliable MQTLs and putative candidate genes for the genetic improvement of flag leaf size in wheat.
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Affiliation(s)
- Binxue Kong
- State Key Laboratory of Aridland Crop Science, Lanzhou, 730070, China
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China
| | - Jingfu Ma
- State Key Laboratory of Aridland Crop Science, Lanzhou, 730070, China
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China
| | - Peipei Zhang
- State Key Laboratory of Aridland Crop Science, Lanzhou, 730070, China
| | - Tao Chen
- State Key Laboratory of Aridland Crop Science, Lanzhou, 730070, China
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China
| | - Yuan Liu
- State Key Laboratory of Aridland Crop Science, Lanzhou, 730070, China
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China
| | - Zhuo Che
- Plant Seed Master Station of Gansu Province, Lanzhou, 730000, China
| | - Fahimeh Shahinnia
- Bavarian State Research Centre for Agriculture, Institute for Crop Science and Plant Breeding, 85354, Freising, Germany
| | - Delong Yang
- State Key Laboratory of Aridland Crop Science, Lanzhou, 730070, China.
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China.
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23
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Ahmed HGMD, Zeng Y, Khan MA, Rashid MAR, Ameen M, Akrem A, Saeed A. Genome-wide association mapping of bread wheat genotypes using yield and grain morphology-related traits under different environments. Front Genet 2023; 13:1008024. [PMID: 36733942 PMCID: PMC9887163 DOI: 10.3389/fgene.2022.1008024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Accepted: 11/22/2022] [Indexed: 01/18/2023] Open
Abstract
Depleting water resources and increasing global temperature due to climate change are major challenges to agriculture and food security worldwide. Deciphering the underlying mechanisms of traits contributing to grain development and yield is essential for the development of climate-resilient cultivars. Therefore, this study assessed 105 bread wheat genotypes grown under control, drought, and heat-stress conditions for two crop seasons and performed a genome-wide association study (GWAS) using a 90k SNP array. The genotypes showed significant trait differences under all environmental conditions. Highly significant variation was observed, with moderate (50.09%) to high (76.19%) heritability in the studied germplasms. The studied traits were all also significantly positively correlated. A total of 541 significant associations (p ≤ 10-3) between marker and trait (MTAs) were observed after crossing the FDR <0.05 threshold for all traits. Among these, 195, 179, and 167 significant MTAs were detected under control, drought, and heat-stress conditions, respectively. Under the control and drought conditions, pleiotropic loci BS00010616_51 and BS00010868_51 were observed on chromosomes 7B and 1B situated at 186.24 cM and 35.47 cM, respectively. Pleiotropic loci BS00010868_51, Kukri_c11154_1723, and Ex_c10068_1509 were identified on chromosomes 1B, 5B, and 2A, respectively, under control and heat stress conditions. A stable and consistent locus (Excalibur_c20796_395) on chromosome 7A, located at 372.34 cM, was also linked to grain morphology and yield-related attributes in control, drought, and heat-stress conditions. The results of the current study confirmed several previously reported MTAs for the traits under consideration and identified new MTAs under harsh climatic conditions. These SNPs will aid in the discovery of novel genes in wheat. SNPs showing significant associations may be used in marker-assisted selection and allow the development of drought- and heat-tolerant genotypes with high yields to address global food security concerns.
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Affiliation(s)
- Hafiz Ghulam Muhu-Din Ahmed
- Department of Plant Breeding and Genetics, Faculty of Agriculture and Environment, The Islamia University of Bahawalpur, Bahawalpur, Pakistan,*Correspondence: Hafiz Ghulam Muhu-Din Ahmed, ; Yawen Zeng,
| | - Yawen Zeng
- Biotechnology and Germplasm Resources Institute, Yunnan Academy of Agricultural Sciences, Kunming, China,*Correspondence: Hafiz Ghulam Muhu-Din Ahmed, ; Yawen Zeng,
| | - Muhammad Ahsan Khan
- Department of Plant Breeding and Genetics, University of Agriculture, Faisalabad, Pakistan
| | - Muhammad Abdul Rehman Rashid
- Department of Agricultural Sciences, Government College University Faisalabad, Faisalabad, Pakistan,Department of Bioinformatics and Biotechnology, Government College University Faisalabad, Faisalabad, Pakistan
| | - Muhammad Ameen
- Department of Soil Science, Faculty of Agriculture and Environment, The Islamia University of Bahawalpur, Bahawalpur, Pakistan
| | - Ahmed Akrem
- Institute of Botany, Bahauddin Zakariya University, Multan, Pakistan
| | - Amjad Saeed
- Institute of Forest Sciences Faculty of Agriculture and Environment, The Islamia University of Bahawalpur, Bahawalpur, Pakistan
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Zhao J, Sun L, Gao H, Hu M, Mu L, Cheng X, Wang J, Zhao Y, Li Q, Wang P, Li H, Zhang Y. Genome-wide association study of yield-related traits in common wheat ( Triticum aestivum L.) under normal and drought treatment conditions. FRONTIERS IN PLANT SCIENCE 2023; 13:1098560. [PMID: 36684753 PMCID: PMC9846334 DOI: 10.3389/fpls.2022.1098560] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 12/13/2022] [Indexed: 06/17/2023]
Abstract
The primary goal of modern wheat breeding is to develop new high-yielding and widely adaptable varieties. We analyzed four yield-related agronomic traits in 502 wheat accessions under normal conditions (NC) and drought treatment (DT) conditions over three years. The genome-wide association analysis identified 51 yield-related and nine drought-resistance-related QTL, including 13 for the thousand-grain weight (TGW), 30 for grain length (GL), three for grain width (GW), five for spike length (SL) and nine for stress tolerance index (STI) QTL in wheat. These QTL, containing 72 single nucleotide polymorphisms (SNPs), explained 2.23 - 7.35% of the phenotypic variation across multiple environments. Eight stable SNPs on chromosomes 2A, 2D, 3B, 4A, 5B, 5D, and 7D were associated with phenotypic stability under NC and DT conditions. Two of these stable SNPs had association with TGW and STI. Several novel QTL for TGW, GL and SL were identified on different chromosomes. Three linked SNPs were transformed into kompetitive allele-specific PCR (KASP) markers. These results will facilitate the discovery of promising SNPs for yield-related traits and/or drought stress tolerance and will accelerate the development of new wheat varieties with desirable alleles.
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Affiliation(s)
- Jie Zhao
- Institute of Cereal and Oil Crops, Laboratory of Crop Genetics and Breeding of Hebei, Hebei Academy of Agriculture and Forestry Sciences, Shijiazhuang, China
| | - Lijing Sun
- Institute of Cereal and Oil Crops, Laboratory of Crop Genetics and Breeding of Hebei, Hebei Academy of Agriculture and Forestry Sciences, Shijiazhuang, China
| | - Huimin Gao
- Institute of Cash Crops, Hebei Academy of Agriculture and Forestry Sciences, Shijiazhuang, China
| | - Mengyun Hu
- Institute of Cereal and Oil Crops, Laboratory of Crop Genetics and Breeding of Hebei, Hebei Academy of Agriculture and Forestry Sciences, Shijiazhuang, China
| | - Liming Mu
- Institute of Cereal Crops, Dingxi Academy of Agricultural Sciences, Dingxi, China
| | - Xiaohu Cheng
- Institute of Cereal Crops, Dingxi Academy of Agricultural Sciences, Dingxi, China
| | - Jianbing Wang
- Institute of Cereal Crops, Dingxi Academy of Agricultural Sciences, Dingxi, China
| | - Yun Zhao
- Institute of Cereal and Oil Crops, Laboratory of Crop Genetics and Breeding of Hebei, Hebei Academy of Agriculture and Forestry Sciences, Shijiazhuang, China
| | - Qianying Li
- Institute of Cereal and Oil Crops, Laboratory of Crop Genetics and Breeding of Hebei, Hebei Academy of Agriculture and Forestry Sciences, Shijiazhuang, China
| | - Peinan Wang
- Institute of Cereal and Oil Crops, Laboratory of Crop Genetics and Breeding of Hebei, Hebei Academy of Agriculture and Forestry Sciences, Shijiazhuang, China
| | - Hui Li
- Institute of Cereal and Oil Crops, Laboratory of Crop Genetics and Breeding of Hebei, Hebei Academy of Agriculture and Forestry Sciences, Shijiazhuang, China
| | - Yingjun Zhang
- Institute of Cereal and Oil Crops, Laboratory of Crop Genetics and Breeding of Hebei, Hebei Academy of Agriculture and Forestry Sciences, Shijiazhuang, China
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25
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Rathan ND, Krishnappa G, Singh AM, Govindan V. Mapping QTL for Phenological and Grain-Related Traits in a Mapping Population Derived from High-Zinc-Biofortified Wheat. PLANTS (BASEL, SWITZERLAND) 2023; 12:220. [PMID: 36616350 PMCID: PMC9823887 DOI: 10.3390/plants12010220] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/13/2022] [Revised: 12/27/2022] [Accepted: 12/29/2022] [Indexed: 06/17/2023]
Abstract
Genomic regions governing days to heading (DH), days to maturity (DM), plant height (PH), thousand-kernel weight (TKW), and test weight (TW) were investigated in a set of 190 RILs derived from a cross between a widely cultivated wheat-variety, Kachu (DPW-621-50), and a high-zinc variety, Zinc-Shakti. The RIL population was genotyped using 909 DArTseq markers and phenotyped in three environments. The constructed genetic map had a total genetic length of 4665 cM, with an average marker density of 5.13 cM. A total of thirty-seven novel quantitative trait loci (QTL), including twelve for PH, six for DH, five for DM, eight for TKW and six for TW were identified. A set of 20 stable QTLs associated with the expression of DH, DM, PH, TKW, and TW were identified in two or more environments. Three novel pleiotropic genomic-regions harboring co-localized QTLs governing two or more traits were also identified. In silico analysis revealed that the DArTseq markers were located on important putative candidate genes such as MLO-like protein, Phytochrome, Zinc finger and RING-type, Cytochrome P450 and pentatricopeptide repeat, involved in the regulation of pollen maturity, the photoperiodic modulation of flowering-time, abiotic-stress tolerance, grain-filling duration, thousand-kernel weight, seed morphology, and plant growth and development. The identified novel QTLs, particularly stable and co-localized QTLs, will be validated to estimate their effects in different genetic backgrounds for subsequent use in marker-assisted selection (MAS).
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Affiliation(s)
| | | | | | - Velu Govindan
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco 56237, Mexico
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26
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Lisker A, Maurer A, Schmutzer T, Kazman E, Cöster H, Holzapfel J, Ebmeyer E, Alqudah AM, Sannemann W, Pillen K. A Haplotype-Based GWAS Identified Trait-Improving QTL Alleles Controlling Agronomic Traits under Contrasting Nitrogen Fertilization Treatments in the MAGIC Wheat Population WM-800. PLANTS (BASEL, SWITZERLAND) 2022; 11:3508. [PMID: 36559621 PMCID: PMC9784842 DOI: 10.3390/plants11243508] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Revised: 11/27/2022] [Accepted: 12/07/2022] [Indexed: 06/17/2023]
Abstract
The multi-parent-advanced-generation-intercross (MAGIC) population WM-800 was developed by intercrossing eight modern winter wheat cultivars to enhance the genetic diversity present in breeding populations. We cultivated WM-800 during two seasons in seven environments under two contrasting nitrogen fertilization treatments. WM-800 lines exhibited highly significant differences between treatments, as well as high heritabilities among the seven agronomic traits studied. The highest-yielding WM-line achieved an average yield increase of 4.40 dt/ha (5.2%) compared to the best founder cultivar Tobak. The subsequent genome-wide-association-study (GWAS), which was based on haplotypes, located QTL for seven agronomic traits including grain yield. In total, 40, 51, and 46 QTL were detected under low, high, and across nitrogen treatments, respectively. For example, the effect of QYLD_3A could be associated with the haplotype allele of cultivar Julius increasing yield by an average of 4.47 dt/ha (5.2%). A novel QTL on chromosome 2B exhibited pleiotropic effects, acting simultaneously on three-grain yield components (ears-per-square-meter, grains-per-ear, and thousand-grain-weight) and plant-height. These effects may be explained by a member of the nitrate-transporter-1 (NRT1)/peptide-family, TaNPF5.34, located 1.05 Mb apart. The WM-800 lines and favorable QTL haplotypes, associated with yield improvements, are currently implemented in wheat breeding programs to develop advanced nitrogen-use efficient wheat cultivars.
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Affiliation(s)
- Antonia Lisker
- Institute of Agricultural and Nutritional Sciences, Martin-Luther-University Halle-Wittenberg, Betty-Heimann-Str. 3, 06120 Halle, Germany
| | - Andreas Maurer
- Institute of Agricultural and Nutritional Sciences, Martin-Luther-University Halle-Wittenberg, Betty-Heimann-Str. 3, 06120 Halle, Germany
| | - Thomas Schmutzer
- Institute of Agricultural and Nutritional Sciences, Martin-Luther-University Halle-Wittenberg, Betty-Heimann-Str. 3, 06120 Halle, Germany
| | - Ebrahim Kazman
- Syngenta Seeds GmbH, Kroppenstedter Str. 4, 39387 Oschersleben, Germany
| | | | - Josef Holzapfel
- Secobra Saatzucht GmbH, Feldkirchen 3, 85368 Moosburg an der Isar, Germany
| | - Erhard Ebmeyer
- KWS Lochow GMBH, Ferdinand-Lochow-Str. 5, 29303 Bergen, Germany
| | - Ahmad M. Alqudah
- Biological Science Program, Department of Biological and Environmental Sciences, College of Art and Science, Qatar University, Doha P.O. Box 2713, Qatar
| | - Wiebke Sannemann
- Institute of Agricultural and Nutritional Sciences, Martin-Luther-University Halle-Wittenberg, Betty-Heimann-Str. 3, 06120 Halle, Germany
| | - Klaus Pillen
- Institute of Agricultural and Nutritional Sciences, Martin-Luther-University Halle-Wittenberg, Betty-Heimann-Str. 3, 06120 Halle, Germany
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27
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Wang Z, Dhakal S, Cerit M, Wang S, Rauf Y, Yu S, Maulana F, Huang W, Anderson JD, Ma XF, Rudd JC, Ibrahim AMH, Xue Q, Hays DB, Bernardo A, St. Amand P, Bai G, Baker J, Baker S, Liu S. QTL mapping of yield components and kernel traits in wheat cultivars TAM 112 and Duster. FRONTIERS IN PLANT SCIENCE 2022; 13:1057701. [PMID: 36570880 PMCID: PMC9768232 DOI: 10.3389/fpls.2022.1057701] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Accepted: 11/04/2022] [Indexed: 06/17/2023]
Abstract
In the Southern Great Plains, wheat cultivars have been selected for a combination of outstanding yield and drought tolerance as a long-term breeding goal. To understand the underlying genetic mechanisms, this study aimed to dissect the quantitative trait loci (QTL) associated with yield components and kernel traits in two wheat cultivars `TAM 112' and `Duster' under both irrigated and dryland environments. A set of 182 recombined inbred lines (RIL) derived from the cross of TAM 112/Duster were planted in 13 diverse environments for evaluation of 18 yield and kernel related traits. High-density genetic linkage map was constructed using 5,081 single nucleotide polymorphisms (SNPs) from genotyping-by-sequencing (GBS). QTL mapping analysis detected 134 QTL regions on all 21 wheat chromosomes, including 30 pleiotropic QTL regions and 21 consistent QTL regions, with 10 QTL regions in common. Three major pleiotropic QTL on the short arms of chromosomes 2B (57.5 - 61.6 Mbps), 2D (37.1 - 38.7 Mbps), and 7D (66.0 - 69.2 Mbps) colocalized with genes Ppd-B1, Ppd-D1, and FT-D1, respectively. And four consistent QTL associated with kernel length (KLEN), thousand kernel weight (TKW), plot grain yield (YLD), and kernel spike-1 (KPS) (Qklen.tamu.1A.325, Qtkw.tamu.2B.137, Qyld.tamu.2D.3, and Qkps.tamu.6A.113) explained more than 5% of the phenotypic variation. QTL Qklen.tamu.1A.325 is a novel QTL with consistent effects under all tested environments. Marker haplotype analysis indicated the QTL combinations significantly increased yield and kernel traits. QTL and the linked markers identified in this study will facilitate future marker-assisted selection (MAS) for pyramiding the favorable alleles and QTL map-based cloning.
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Affiliation(s)
- Zhen Wang
- Texas A&M AgriLife Research and Extension Center, Amarillo, TX, United States
| | - Smit Dhakal
- Texas A&M AgriLife Research and Extension Center, Amarillo, TX, United States
| | - Mustafa Cerit
- Texas A&M AgriLife Research and Extension Center, Amarillo, TX, United States
| | - Shichen Wang
- Genomics and Bioinformatics Service Center, Texas A&M AgriLife Research, College Station, TX, United States
| | - Yahya Rauf
- Texas A&M AgriLife Research and Extension Center, Amarillo, TX, United States
| | - Shuhao Yu
- Texas A&M AgriLife Research and Extension Center, Amarillo, TX, United States
| | - Frank Maulana
- Noble Research Institute, Ardmore, OK, United States
| | - Wangqi Huang
- Noble Research Institute, Ardmore, OK, United States
| | | | - Xue-Feng Ma
- Noble Research Institute, Ardmore, OK, United States
| | - Jackie C. Rudd
- Texas A&M AgriLife Research and Extension Center, Amarillo, TX, United States
| | - Amir M. H. Ibrahim
- Department of Soil and Crop Science, Texas A&M University, College Station, TX, United States
| | - Qingwu Xue
- Texas A&M AgriLife Research and Extension Center, Amarillo, TX, United States
| | - Dirk B. Hays
- Department of Soil and Crop Science, Texas A&M University, College Station, TX, United States
| | - Amy Bernardo
- Central Small Grain Genotyping Lab and Hard Winter Wheat Genetics Research Unit, U.S. Department of Agriculture-Agricultural Research Service, Manhattan, KS, United States
| | - Paul St. Amand
- Central Small Grain Genotyping Lab and Hard Winter Wheat Genetics Research Unit, U.S. Department of Agriculture-Agricultural Research Service, Manhattan, KS, United States
| | - Guihua Bai
- Central Small Grain Genotyping Lab and Hard Winter Wheat Genetics Research Unit, U.S. Department of Agriculture-Agricultural Research Service, Manhattan, KS, United States
| | - Jason Baker
- Texas A&M AgriLife Research and Extension Center, Amarillo, TX, United States
| | - Shannon Baker
- Texas A&M AgriLife Research and Extension Center, Amarillo, TX, United States
| | - Shuyu Liu
- Texas A&M AgriLife Research and Extension Center, Amarillo, TX, United States
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28
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Liu H, Shi Z, Ma F, Xu Y, Han G, Zhang J, Liu D, An D. Identification and validation of plant height, spike length and spike compactness loci in common wheat (Triticum aestivum L.). BMC PLANT BIOLOGY 2022; 22:568. [PMID: 36471256 PMCID: PMC9724413 DOI: 10.1186/s12870-022-03968-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 11/28/2022] [Indexed: 06/17/2023]
Abstract
BACKGROUND Plant height (PH), spike length (SL) and spike compactness (SCN) are important agronomic traits in wheat due to their strong correlations with lodging and yield. Thus, dissection of their genetic basis is essential for the improvement of plant architecture and yield potential in wheat breeding. The objective of this study was to map quantitative trait loci (QTL) for PH, SL and SCN in a recombinant inbred line (RIL) population derived from the cross 'PuBing3228 × Gao8901' (PG-RIL) and to evaluate the potential values of these QTL to improve yield. RESULTS In the current study, Five, six and ten stable QTL for PH, SL, and SCN, respectively, were identified in at least two individual environments. Five major QTL QPh.cas-5A.3, QPh.cas-6A, QSl.cas-6B.2, QScn.cas-2B.2 and QScn.cas-6B explained 5.58-25.68% of the phenotypic variation. Notably, two, three and three novel stable QTL for PH, SL and SCN were identified in this study, which could provide further insights into the genetic factors that shape PH and spike morphology in wheat. Conditional QTL analysis revealed that QTL for SCN were mainly affected by SL. Moreover, a Kompetitive Allele Specific PCR (KASP) marker tightly linked to stable major QTL QPh.cas-5A.3 was developed and verified using the PG-RIL population and a natural population. CONCLUSIONS Twenty-one stable QTL related to PH, SL, and SCN were identified. These stable QTL and the user-friendly marker KASP8750 will facilitate future studies involving positional cloning and marker-assisted selection in breeding.
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Affiliation(s)
- Hong Liu
- Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, Hebei, 050022, China
| | - Zhipeng Shi
- Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, Hebei, 050022, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Feifei Ma
- Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, Hebei, 050022, China
| | - Yunfeng Xu
- Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, Hebei, 050022, China
| | - Guohao Han
- Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, Hebei, 050022, China
| | - Jinpeng Zhang
- The National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Dongcheng Liu
- State Key Laboratory of North China Crop Improvement and Regulation, College of Agronomy, Hebei Agricultural University, Baoding, 071000, Hebei, China.
| | - Diaoguo An
- Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, Hebei, 050022, China.
- The Innovative Academy for Seed Design, Chinese Academy of Sciences, Beijing, 100101, China.
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29
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Genome-Wide Association Analysis for Hybrid Breeding in Wheat. Int J Mol Sci 2022; 23:ijms232315321. [PMID: 36499647 PMCID: PMC9740285 DOI: 10.3390/ijms232315321] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Revised: 11/24/2022] [Accepted: 11/27/2022] [Indexed: 12/12/2022] Open
Abstract
Disclosure of markers that are significantly associated with plant traits can help develop new varieties with desirable properties. This study determined the genome-wide associations based on DArTseq markers for six agronomic traits assessed in eight environments for wheat. Moreover, the association study for heterosis and analysis of the effects of markers grouped by linkage disequilibrium were performed based on mean values over all experiments. All results were validated using data from post-registration trials. GWAS revealed 1273 single nucleotide polymorphisms with biologically significant effects. Most polymorphisms were predicted to be modifiers of protein translation, with only two having a more pronounced effect. Markers significantly associated with the considered set of features were clustered within chromosomes based on linkage disequilibrium in 327 LD blocks. A GWAS for heterosis revealed 1261 markers with significant effects.
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Peters Haugrud AR, Zhang Q, Green AJ, Xu SS, Faris JD. Identification of stable QTL controlling multiple yield components in a durum × cultivated emmer wheat population under field and greenhouse conditions. G3 (BETHESDA, MD.) 2022; 13:6762085. [PMID: 36250796 PMCID: PMC9911061 DOI: 10.1093/g3journal/jkac281] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 09/27/2022] [Indexed: 11/09/2022]
Abstract
Crop yield gains are needed to keep pace with a growing global population and decreasing resources to produce food. Cultivated emmer wheat is a progenitor of durum wheat and a useful source of genetic variation for trait improvement in durum. Here, we evaluated a recombinant inbred line population derived from a cross between the North Dakota durum wheat variety Divide and the cultivated emmer wheat accession PI 272527 consisting of 219 lines. The population was evaluated in 3 field environments and 2 greenhouse experiments to identify quantitative trait locus associated with 11 yield-related traits that were expressed in a consistent manner over multiple environments. We identified 27 quantitative trait locus expressed in at least 2 field environments, 17 of which were also expressed under greenhouse conditions. Seven quantitative trait locus regions on chromosomes 1B, 2A, 2B, 3A, 3B, 6A, and 7B had pleiotropic effects on multiple yield-related traits. The previously cloned genes Q and FT-B1, which are known to be associated with development and morphology, were found to consistently be associated with multiple traits across environments. PI 272527 contributed beneficial alleles for quantitative trait locus associated with multiple traits, especially for seed morphology quantitative trait locus on chromosomes 1B, 2B, and 6A. Three recombinant inbred lines with increased grain size and weight compared to Divide were identified and demonstrated the potential for improvement of durum wheat through deployment of beneficial alleles from the cultivated emmer parent. The findings from this study provide knowledge regarding stable and robust quantitative trait locus that breeders can use for improving yield in durum wheat.
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Affiliation(s)
| | - Qijun Zhang
- Department of Plant Sciences, North Dakota State University, Fargo, ND 58102, USA
| | - Andrew J Green
- Department of Plant Sciences, North Dakota State University, Fargo, ND 58102, USA
| | - Steven S Xu
- USDA-ARS Western Regional Research Center, Albany, CA 94710, USA
| | - Justin D Faris
- Corresponding author: Cereal Crops Research Unit, Edward T. Schafer Agricultural Research Center, Agricultural Research Service, United States Department of Agriculture, Fargo, ND 58102, USA.
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High-Density Linkage Mapping of Agronomic Trait QTLs in Wheat under Water Deficit Condition using Genotyping by Sequencing (GBS). PLANTS 2022; 11:plants11192533. [PMID: 36235399 PMCID: PMC9571144 DOI: 10.3390/plants11192533] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 09/05/2022] [Accepted: 09/15/2022] [Indexed: 11/17/2022]
Abstract
Improvement of grain yield is the ultimate goal for wheat breeding under water-limited environments. In the present study, a high-density linkage map was developed by using genotyping-by-sequencing (GBS) of a recombinant inbred line (RIL) population derived from the cross between Iranian landrace #49 and cultivar Yecora Rojo. The population was evaluated in three locations in Iran during two years under irrigated and water deficit conditions for the agronomic traits grain yield (GY), plant height (PH), spike number per square meter (SM), 1000 kernel weight (TKW), grain number per spike (GNS), spike length (SL), biomass (BIO) and harvest index (HI). A linkage map was constructed using 5831 SNPs assigned to 21 chromosomes, spanning 3642.14 cM of the hexaploid wheat genome with an average marker density of 0.62 (markers/cM). In total, 85 QTLs were identified on 19 chromosomes (all except 5D and 6D) explaining 6.06–19.25% of the traits phenotypic variance. We could identify 20 novel QTLs explaining 8.87–19.18% of phenotypic variance on chromosomes 1A, 1B, 1D, 2B, 3A, 3B, 6A, 6B and 7A. For 35 out of 85 mapped QTLs functionally annotated genes were identified which could be related to a potential role in drought stress.
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Song J, Xu D, Dong Y, Li F, Bian Y, Li L, Luo X, Fei S, Li L, Zhao C, Zhang Y, Xia X, Ni Z, He Z, Cao S. Fine mapping and characterization of a major QTL for grain weight on wheat chromosome arm 5DL. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2022; 135:3237-3246. [PMID: 35904627 DOI: 10.1007/s00122-022-04182-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Accepted: 07/14/2022] [Indexed: 06/15/2023]
Abstract
We fine mapped QTL QTKW.caas-5DL for thousand kernel weight in wheat, predicted candidate genes and developed a breeding-applicable marker. Thousand kernel weight (TKW) is an important yield component trait in wheat, and identification of the underlying genetic loci is helpful for yield improvement. We previously identified a stable quantitative trait locus (QTL) QTKW.caas-5DL for TKW in a Doumai/Shi4185 recombinant inbred line (RIL) population. Here we performed fine mapping of QTKW.caas-5DL using secondary populations derived from 15 heterozygous recombinants and delimited the QTL to an approximate 3.9 Mb physical interval from 409.9 to 413.8 Mb according to the Chinese Spring (CS) reference genome. Analysis of genomic synteny showed that annotated genes in the physical interval had high collinearity among CS and eight other wheat genomes. Seven genes with sequence variation and/or differential expression between parents were predicted as candidates for QTKW.caas-5DL based on whole-genome resequencing and transcriptome assays. A kompetitive allele-specific PCR (KASP) marker for QTKW.caas-5DL was developed, and genotyping confirmed a significant association with TKW but not with other yield component traits in a panel of elite wheat cultivars. The superior allele of QTKW.caas-5DL was frequent in a panel of cultivars, suggesting that it had undergone positive selection. These findings not only lay a foundation for map-based cloning of QTKW.caas-5DL but also provide an efficient tool for marker-assisted selection.
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Affiliation(s)
- Jie Song
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
- State Key Laboratory of Agrobiotechnology, Key Laboratory of Crop Heterosis and Utilization, Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy, China Agricultural University, 2 Yuanmingyuan West Road, Beijing, 100094, China
| | - Dengan Xu
- Shandong Province Key Laboratory of Dryland Farming Technology, College of Agronomy, Qingdao Agricultural University, Qingdao, 266109, Shandong, China
| | - Yan Dong
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Faji Li
- Crop Research Institute, Shandong Academy of Agricultural Sciences, 202 Gongye North Road, Jinan, 250100, Shandong, China
| | - Yingjie Bian
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Lingli Li
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Xumei Luo
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Shuaipeng Fei
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Lei Li
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Cong Zhao
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Yong Zhang
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Xianchun Xia
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Zhongfu Ni
- State Key Laboratory of Agrobiotechnology, Key Laboratory of Crop Heterosis and Utilization, Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy, China Agricultural University, 2 Yuanmingyuan West Road, Beijing, 100094, China
| | - Zhonghu He
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China.
- International Maize and Wheat Improvement Center (CIMMYT) China Office, c/o CAAS, 12 Zhongguancun South Street, Beijing, 100081, China.
| | - Shuanghe Cao
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China.
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Gill HS, Halder J, Zhang J, Rana A, Kleinjan J, Amand PS, Bernardo A, Bai G, Sehgal SK. Whole-genome analysis of hard winter wheat germplasm identifies genomic regions associated with spike and kernel traits. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2022; 135:2953-2967. [PMID: 35939073 DOI: 10.1007/s00122-022-04160-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 06/22/2022] [Indexed: 06/15/2023]
Abstract
Genetic dissection of yield component traits including spike and kernel characteristics is essential for the continuous improvement in wheat yield. Genome-wide association studies (GWAS) have been frequently used to identify genetic determinants for spike and kernel-related traits in wheat, though none have been employed in hard winter wheat (HWW) which represents a major class in US wheat acreage. Further, most of these studies relied on assembled diversity panels instead of adapted breeding lines, limiting the transferability of results to practical wheat breeding. Here we assembled a population of advanced/elite breeding lines and well-adapted cultivars and evaluated over four environments for phenotypic analysis of spike and kernel traits. GWAS identified 17 significant multi-environment marker-trait associations (MTAs) for various traits, representing 12 putative quantitative trait loci (QTLs), with five QTLs affecting multiple traits. Four of these QTLs mapped on three chromosomes 1A, 5B, and 7A for spike length, number of spikelets per spike (NSPS), and kernel length are likely novel. Further, a highly significant QTL was detected on chromosome 7AS that has not been previously associated with NSPS and putative candidate genes were identified in this region. The allelic frequencies of important quantitative trait nucleotides (QTNs) were deduced in a larger set of 1,124 accessions which revealed the importance of identified MTAs in the US HWW breeding programs. The results from this study could be directly used by the breeders to select the lines with favorable alleles for making crosses, and reported markers will facilitate marker-assisted selection of stable QTLs for yield components in wheat breeding.
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Affiliation(s)
- Harsimardeep S Gill
- Department of Agronomy, Horticulture & Plant Science, South Dakota State University, Brookings, SD, 57007, USA
| | - Jyotirmoy Halder
- Department of Agronomy, Horticulture & Plant Science, South Dakota State University, Brookings, SD, 57007, USA
| | - Jinfeng Zhang
- Department of Agronomy, Horticulture & Plant Science, South Dakota State University, Brookings, SD, 57007, USA
| | - Anshul Rana
- Department of Agronomy, Horticulture & Plant Science, South Dakota State University, Brookings, SD, 57007, USA
| | - Jonathan Kleinjan
- Department of Agronomy, Horticulture & Plant Science, South Dakota State University, Brookings, SD, 57007, USA
| | - Paul St Amand
- USDA-ARS, Hard Winter Wheat Genetics Research Unit, Manhattan, KS, 66506, USA
| | - Amy Bernardo
- USDA-ARS, Hard Winter Wheat Genetics Research Unit, Manhattan, KS, 66506, USA
| | - Guihua Bai
- USDA-ARS, Hard Winter Wheat Genetics Research Unit, Manhattan, KS, 66506, USA
| | - Sunish K Sehgal
- Department of Agronomy, Horticulture & Plant Science, South Dakota State University, Brookings, SD, 57007, USA.
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Morgounov A, Li H, Shepelev S, Ali M, Flis P, Koksel H, Savin T, Shamanin V. Genetic Characterization of Spring Wheat Germplasm for Macro-, Microelements and Trace Metals. PLANTS (BASEL, SWITZERLAND) 2022; 11:plants11162173. [PMID: 36015476 PMCID: PMC9412593 DOI: 10.3390/plants11162173] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 08/15/2022] [Accepted: 08/17/2022] [Indexed: 06/12/2023]
Abstract
Wheat as a staple food crop is the main source of micro- and macronutrients for most people of the world and is recognized as an attractive crop for biofortification. This study presents a comprehensive investigation of genomic regions governing grain micro- and macroelements concentrations in a panel of 135 diverse wheat accessions through a genome-wide association study. The genetic diversity panel was genotyped using the genotyping-by-sequencing (GBS) method and phenotyped in two environments during 2017−2018. Wide ranges of variation in nutrient element concentrations in grain were detected among the accessions. Based on 33,808 high-quality single nucleotide polymorphisms (SNPs), 2997 marker-element associations (MEAs) with −log10(p-value) > 3.5 were identified, representing all three subgenomes of wheat for 15-grain concentration elements. The highest numbers of MEAs were identified for Mg (499), followed by S (399), P (394), Ni (381), Cd (243), Ca (229), Mn (224), Zn (212), Sr (212), Cu (111), Rb (78), Fe (63), Mo (43), K (32) and Co (19). Further, MEAs associated with multiple elements and referred to as pleiotropic SNPs were identified for Mg, P, Cd, Mn, and Zn on chromosomes 1B, 2B, and 6B. Fifty MEAs were subjected to validation using KASIB multilocational trial at six sites in two years using 39 genotypes. Gene annotation of MEAs identified putative candidate genes that potentially encode different types of proteins related to disease, metal transportation, and metabolism. The MEAs identified in the present study could be potential targets for further validation and may be used in marker-assisted breeding to improve nutrient element concentrations in wheat grain.
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Affiliation(s)
- Alexey Morgounov
- Agronomy Department, Omsk State Agrarian University, 644008 Omsk, Russia
| | - Huihui Li
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences & CIMMYT-China, Beijing 100081, China
- Nanfan Research Institute, Chinese Academy of Agricultural Sciences (CAAS), Sanya 572024, China
| | - Sergey Shepelev
- Agronomy Department, Omsk State Agrarian University, 644008 Omsk, Russia
| | - Mohsin Ali
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences & CIMMYT-China, Beijing 100081, China
- Nanfan Research Institute, Chinese Academy of Agricultural Sciences (CAAS), Sanya 572024, China
| | - Paulina Flis
- Future Food Beacon of Excellence and the School of Biosciences, University of Nottingham, Nottingham LE12 5RD, UK
| | - Hamit Koksel
- Agronomy Department, Omsk State Agrarian University, 644008 Omsk, Russia
- Department of Nutrition and Dietetics, Istinye University, Istanbul 34010, Turkey
| | - Timur Savin
- Department of Research, S. Seifullin Kazakh Agro Technical University, Nur-Sultan 010011, Kazakhstan
| | - Vladimir Shamanin
- Agronomy Department, Omsk State Agrarian University, 644008 Omsk, Russia
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Liu W, Li Y, Sun Y, Tang J, Che J, Yang S, Wang X, Zhang R, Zhang H. Genetic analysis of morphological traits in spring wheat from the Northeast of China by a genome-wide association study. Front Genet 2022; 13:934757. [PMID: 36061191 PMCID: PMC9434797 DOI: 10.3389/fgene.2022.934757] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Accepted: 07/15/2022] [Indexed: 11/13/2022] Open
Abstract
Identification of the gene for agronomic traits is important for the wheat marker-assisted selection (MAS) breeding. To identify the new and stable loci for agronomic traits, including flag leaf length (FLL), flag leaf width (FLW), uppermost internode length (UIL), and plant morphology (PM, including prostrate, semi-prostrate, and erect). A total of 251 spring wheat accessions collected from the Northeast of China were used to conduct genome-wide association study (GWAS) by 55K SNP arrays. A total of 30 loci for morphological traits were detected, and each explained 4.8–17.9% of the phenotypic variations. Of these, 13 loci have been reported by previous studies, and the other 17 are novel. We have identified seven genes involved in the signal transduction, cell-cycle progression, and plant development pathway as candidate genes. This study provides new insights into the genetic basis of morphological traits. The associated SNPs and accessions with more of favorable alleles identified in this study could be used to promote the wheat breeding progresses.
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Affiliation(s)
- Wenlin Liu
- Crop Resources Institute, Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Yuyao Li
- Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Yan Sun
- Crop Resources Institute, Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Jingquan Tang
- Crop Resources Institute, Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Jingyu Che
- KeShan Branch of Heilongjiang Academy of Agricultural Sciences, Qiqihaer, China
| | - Shuping Yang
- Crop Resources Institute, Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Xiangyu Wang
- Crop Resources Institute, Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Rui Zhang
- Institute of Forage and Grassland Sciences, Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Hongji Zhang
- Crop Resources Institute, Heilongjiang Academy of Agricultural Sciences, Harbin, China
- *Correspondence: Hongji Zhang,
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Yang F, Zhang J, Zhao Y, Liu Q, Islam S, Yang W, Ma W. Wheat glutamine synthetase TaGSr-4B is a candidate gene for a QTL of thousand grain weight on chromosome 4B. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2022; 135:2369-2384. [PMID: 35588016 PMCID: PMC9271121 DOI: 10.1007/s00122-022-04118-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Accepted: 04/25/2022] [Indexed: 06/14/2023]
Abstract
KEY MESSAGE Glutamine synthetase TaGSr-4B is a candidate gene for a QTL of thousand grain weight on 4B, and the gene marker is ready for wheat breeding. A QTL for thousand grain weight (TGW) in wheat was previously mapped on chromosome 4B in a DH population of Westonia × Kauz. For identifying the candidate genes of the QTL, wheat 90 K SNP array was used to saturate the existing linkage map, and four field trials plus one glasshouse experiment over five locations were conducted to refine the QTL. Three nitrogen levels were applied to two of those field trials, resulting in a TGW phenotype data set from nine environments. A robust TGW QTL cluster including 773 genes was detected in six environments with the highest LOD value of 13.4. Based on differentiate gene expression within the QTL cluster in an RNAseq data of Westonia and Kauz during grain filling, a glutamine synthesis gene (GS: TaGSr-4B) was selected as a potential candidate gene for the QTL. A SNP on the promoter region between Westonia and Kauz was used to develop a cleaved amplified polymorphic marker for TaGSr-4B gene mapping and QTL reanalysing. As results, TGW QTL appeared in seven environments, and in four out of seven environments, the TGW QTL were localized on the TaGSr-4B locus and showed significant contributions to the phenotype. Based on the marker, two allele groups of Westonia and Kauz formed showed significant differences on TGW in eight environments. In agreement with the roles of GS genes on nitrogen and carbon remobilizations, TaGSr-4B is likely the candidate gene of the TGW QTL on 4B and the TaGSr-4B gene marker is ready for wheat breeding.
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Affiliation(s)
- Fan Yang
- Australian-China Joint Centre for Wheat Improvement, Food Futures Institute, College of Science, Health, Engineering and Education, Murdoch University, 90 South Street, Murdoch, WA, 6150, Australia
- Crop Research Institute, Sichuan Academy of Agricultural Sciences, 4 Shizishan Road, Chengdu, 610066, China
| | - Jingjuan Zhang
- Australian-China Joint Centre for Wheat Improvement, Food Futures Institute, College of Science, Health, Engineering and Education, Murdoch University, 90 South Street, Murdoch, WA, 6150, Australia.
| | - Yun Zhao
- Australian-China Joint Centre for Wheat Improvement, Food Futures Institute, College of Science, Health, Engineering and Education, Murdoch University, 90 South Street, Murdoch, WA, 6150, Australia
- College of Agronomy, Qingdao Agriculture University, Qingdao, 266109, China
| | - Qier Liu
- Australian-China Joint Centre for Wheat Improvement, Food Futures Institute, College of Science, Health, Engineering and Education, Murdoch University, 90 South Street, Murdoch, WA, 6150, Australia
| | - Shahidul Islam
- Australian-China Joint Centre for Wheat Improvement, Food Futures Institute, College of Science, Health, Engineering and Education, Murdoch University, 90 South Street, Murdoch, WA, 6150, Australia
| | - Wuyun Yang
- Crop Research Institute, Sichuan Academy of Agricultural Sciences, 4 Shizishan Road, Chengdu, 610066, China
| | - Wujun Ma
- Australian-China Joint Centre for Wheat Improvement, Food Futures Institute, College of Science, Health, Engineering and Education, Murdoch University, 90 South Street, Murdoch, WA, 6150, Australia.
- College of Agronomy, Qingdao Agriculture University, Qingdao, 266109, China.
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InDels Identification and Association Analysis with Spike and Awn Length in Chinese Wheat Mini-Core Collection. Int J Mol Sci 2022; 23:ijms23105587. [PMID: 35628397 PMCID: PMC9146729 DOI: 10.3390/ijms23105587] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 05/12/2022] [Accepted: 05/13/2022] [Indexed: 11/17/2022] Open
Abstract
Diversity surveys of germplasm are important for gaining insight into the genomic basis for crop improvement; especially InDels, which are poorly understood in hexaploid common wheat. Here, we describe a map of 89,923 InDels from exome sequencing of 262 accessions of a Chinese wheat mini-core collection. Population structure analysis, principal component analysis and selective sweep analysis between landraces and cultivars were performed. Further genome-wide association study (GWAS) identified five QTL (Quantitative Trait Loci) that were associated with spike length, two of them, on chromosomes 2B and 6A, were detected in 10 phenotypic data sets. Assisted with RNA-seq data, we identified 14 and 21 genes, respectively that expressed in spike and rachis within the two QTL regions that can be further investigated for candidate genes discovery. Moreover, InDels were found to be associated with awn length on chromosomes 5A, 6B and 4A, which overlapped with previously reported genetic loci B1 (Tipped 1), B2 (Tipped 2) and Hd (Hooded). One of the genes TaAGL6 that was previously shown to affect floral organ development was found at the B2 locus to affect awn length development. Our study shows that trait-associated InDels may contribute to wheat improvement and may be valuable molecular markers for future wheat breeding.
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Li T, Li Q, Wang J, Yang Z, Tang Y, Su Y, Zhang J, Qiu X, Pu X, Pan Z, Zhang H, Liang J, Liu Z, Li J, Yan W, Yu M, Long H, Wei Y, Deng G. High-resolution detection of quantitative trait loci for seven important yield-related traits in wheat (Triticum aestivum L.) using a high-density SLAF-seq genetic map. BMC Genom Data 2022; 23:37. [PMID: 35562674 PMCID: PMC9107147 DOI: 10.1186/s12863-022-01050-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Accepted: 04/06/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Yield-related traits including thousand grain weight (TGW), grain number per spike (GNS), grain width (GW), grain length (GL), plant height (PH), spike length (SL), and spikelet number per spike (SNS) are greatly associated with grain yield of wheat (Triticum aestivum L.). To detect quantitative trait loci (QTL) associated with them, 193 recombinant inbred lines derived from two elite winter wheat varieties Chuanmai42 and Chuanmai39 were employed to perform QTL mapping in six/eight environments. RESULTS A total of 30 QTLs on chromosomes 1A, 1B, 1D, 2A, 2B, 2D, 3A, 4A, 5A, 5B, 6A, 6D, 7A, 7B and 7D were identified. Among them, six major QTLs QTgw.cib-6A.1, QTgw.cib-6A.2, QGw.cib-6A, QGl.cib-3A, QGl.cib-6A, and QSl.cib-2D explaining 5.96-23.75% of the phenotypic variance were detected in multi-environments and showed strong and stable effects on corresponding traits. Three QTL clusters on chromosomes 2D and 6A containing 10 QTLs were also detected, which showed significant pleiotropic effects on multiple traits. Additionally, three Kompetitive Allele Specific PCR (KASP) markers linked with five of these major QTLs were developed. Candidate genes of QTgw.cib-6A.1/QGl.cib-6A and QGl.cib-3A were analyzed based on the spatiotemporal expression patterns, gene annotation, and orthologous search. CONCLUSIONS Six major QTLs for TGW, GL, GW and SL were detected. Three KASP markers linked with five of these major QTLs were developed. These QTLs and KASP markers will be useful for elucidating the genetic architecture of grain yield and developing new wheat varieties with high and stable yield in wheat.
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Affiliation(s)
- Tao Li
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China.,Triticeae Research Institute, Sichuan Agricultural University, Chengdu, 611130, China.,State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Chengdu, 611130, China
| | - Qiao Li
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Jinhui Wang
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Zhao Yang
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Yanyan Tang
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Yan Su
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Juanyu Zhang
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Xvebing Qiu
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Xi Pu
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Zhifen Pan
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Haili Zhang
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Junjun Liang
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Zehou Liu
- Crop Research Institute, Sichuan Academy of Agricultural Sciences, Chengdu, 610066, Sichuan, China
| | - Jun Li
- Crop Research Institute, Sichuan Academy of Agricultural Sciences, Chengdu, 610066, Sichuan, China
| | - Wuyun Yan
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Chengdu, 611130, China
| | - Maoqun Yu
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Hai Long
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Yuming Wei
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, 611130, China.,State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Chengdu, 611130, China
| | - Guangbing Deng
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China.
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39
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Qiao L, Li H, Wang J, Zhao J, Zheng X, Wu B, Du W, Wang J, Zheng J. Analysis of Genetic Regions Related to Field Grain Number per Spike From Chinese Wheat Founder Parent Linfen 5064. FRONTIERS IN PLANT SCIENCE 2022; 12:808136. [PMID: 35069666 PMCID: PMC8769526 DOI: 10.3389/fpls.2021.808136] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Accepted: 11/29/2021] [Indexed: 06/14/2023]
Abstract
Wheat founder parents have been important in the development of new wheat cultivars. Understanding the effects of specific genome regions on yield-related traits in founder variety derivatives can enable more efficient use of these genetic resources through molecular breeding. In this study, the genetic regions related to field grain number per spike (GNS) from the founder parent Linfen 5064 were analyzed using a doubled haploid (DH) population developed from a cross between Linfen 5064 and Nongda 3338. Quantitative trait loci (QTL) for five spike-related traits over nine experimental locations/years were identified, namely, total spikelet number per spike (TSS), base sterile spikelet number per spike (BSSS), top sterile spikelet number per spike (TSSS), fertile spikelet number per spike (FSS), and GNS. A total of 13 stable QTL explaining 3.91-19.51% of the phenotypic variation were found. The effect of six of these QTL, Qtss.saw-2B.1, Qtss.saw-2B.2, Qtss.saw-3B, Qfss.saw-2B.2, Qbsss.saw-5A.1, and Qgns.saw-1A, were verified by another DH population (Linfen 5064/Jinmai 47), which showed extreme significance (P < 0.05) in more than three environments. No homologs of reported grain number-related from grass species were found in the physical regions of Qtss.saw-2B.1 and Qtss.saw-3B, that indicating both of them are novel QTL, or possess novel-related genes. The positive alleles of Qtss.saw-2B.2 from Linfen 5064 have the larger effect on TSS (3.30%, 0.62) and have 66.89% in Chinese cultivars under long-term artificial selection. This study revealed three key regions for GNS in Linfen 5064 and provides insights into molecular marker-assisted breeding.
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Affiliation(s)
- Ling Qiao
- College of Agronomy, State Key Laboratory of Sustainable Dryland Agriculture (in Preparation), Shanxi Agricultural University, Jinzhong, China
- Institute of Wheat Research, Shanxi Agricultural University, Linfen, China
| | - Hanlin Li
- College of Agronomy, State Key Laboratory of Sustainable Dryland Agriculture (in Preparation), Shanxi Agricultural University, Jinzhong, China
- Institute of Wheat Research, Shanxi Agricultural University, Linfen, China
| | - Jie Wang
- Institute of Wheat Research, Shanxi Agricultural University, Linfen, China
| | - Jiajia Zhao
- Institute of Wheat Research, Shanxi Agricultural University, Linfen, China
| | - Xingwei Zheng
- Institute of Wheat Research, Shanxi Agricultural University, Linfen, China
| | - Bangbang Wu
- Institute of Wheat Research, Shanxi Agricultural University, Linfen, China
| | - Weijun Du
- College of Agronomy, State Key Laboratory of Sustainable Dryland Agriculture (in Preparation), Shanxi Agricultural University, Jinzhong, China
| | - Juanling Wang
- College of Agronomy, State Key Laboratory of Sustainable Dryland Agriculture (in Preparation), Shanxi Agricultural University, Jinzhong, China
| | - Jun Zheng
- Institute of Wheat Research, Shanxi Agricultural University, Linfen, China
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40
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Li T, Deng G, Su Y, Yang Z, Tang Y, Wang J, Zhang J, Qiu X, Pu X, Yang W, Li J, Liu Z, Zhang H, Liang J, Yu M, Wei Y, Long H. Genetic dissection of quantitative trait loci for grain size and weight by high-resolution genetic mapping in bread wheat (Triticum aestivum L.). TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2022; 135:257-271. [PMID: 34647130 DOI: 10.1007/s00122-021-03964-2] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Accepted: 09/29/2021] [Indexed: 06/13/2023]
Abstract
Six major QTLs for wheat grain size and weight were identified on chromosomes 4A, 4B, 5A and 6A across multiple environments, and were validated in different genetic backgrounds. Grain size and weight are crucial components of wheat yield. Dissection of their genetic control is thus essential for the improvement of yield potential in wheat breeding. We used a doubled haploid (DH) population to detect quantitative trait loci (QTLs) for grain width (GW), grain length (GL), and thousand grain weight (TGW) in five environments. Six major QTLs, QGw.cib-4B.2, QGl.cib-4A, QGl.cib-5A.1, QGl.cib-6A, QTgw.cib-4B, and QTgw.cib-5A, were consistently identified in at least three individual environments and in best linear unbiased prediction (BLUP) datasets, and explained 5.65-34.06% of phenotypic variation. QGw.cib-4B.2, QTgw.cib-4B, QGl.cib-5A.1 and QGl.cib-6A had no effect on grain number per spike (GNS). In addition to QGl.cib-4A, the other major QTLs were further validated by using Kompetitive Allele Specific PCR (KASP) markers in different genetic backgrounds. Moreover, significant interactions between the three major GL QTLs and two major TGW QTLs were observed. Comparison analysis showed that QGl.cib-5A.1 and QGl.cib-6A are likely new loci. Notably, QGw.cib-4B.2 and QTgw.cib-4B were co-located on chromosome 4B and improved TGW by increasing only GW, unlike nearby or overlapped loci reported previously. Three genes associated with grain development within the QGw.cib-4B.2/QTgw.cib-4B interval were identified by searches on sequence similarity, spatial expression patterns, and orthologs. The major QTLs and KASP markers reported here will be useful for elucidating the genetic architecture of grain size and weight and for developing new wheat cultivars with high and stable yield.
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Affiliation(s)
- Tao Li
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Chengdu, 611130, China
| | - Guangbing Deng
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Yan Su
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Zhao Yang
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Yanyan Tang
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Jinhui Wang
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Juanyu Zhang
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Xvebing Qiu
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Xi Pu
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Wuyun Yang
- Crop Research Institute, Sichuan Academy of Agricultural Sciences, Chengdu, 610066, Sichuan, China
| | - Jun Li
- Crop Research Institute, Sichuan Academy of Agricultural Sciences, Chengdu, 610066, Sichuan, China
| | - Zehou Liu
- Crop Research Institute, Sichuan Academy of Agricultural Sciences, Chengdu, 610066, Sichuan, China
| | - Haili Zhang
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Junjun Liang
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Maoqun Yu
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Yuming Wei
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, 611130, China.
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Chengdu, 611130, China.
| | - Hai Long
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China.
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41
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Tian X, Xia X, Xu D, Liu Y, Xie L, Hassan MA, Song J, Li F, Wang D, Zhang Y, Hao Y, Li G, Chu C, He Z, Cao S. Rht24b
, an ancient variation of
TaGA2ox‐A9
, reduces plant height without yield penalty in wheat. NEW PHYTOLOGIST 2022; 233:738-750. [PMID: 0 DOI: 10.1111/nph.17808] [Citation(s) in RCA: 39] [Impact Index Per Article: 19.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Accepted: 09/13/2021] [Indexed: 05/22/2023]
Affiliation(s)
- Xiuling Tian
- Institute of Crop Sciences National Wheat Improvement Center Chinese Academy of Agricultural Sciences (CAAS) 12 Zhongguancun South Street Beijing 100081 China
| | - Xianchun Xia
- Institute of Crop Sciences National Wheat Improvement Center Chinese Academy of Agricultural Sciences (CAAS) 12 Zhongguancun South Street Beijing 100081 China
| | - Dengan Xu
- Institute of Crop Sciences National Wheat Improvement Center Chinese Academy of Agricultural Sciences (CAAS) 12 Zhongguancun South Street Beijing 100081 China
| | - Yongqiang Liu
- State Key Laboratory of Plant Genomics Institute of Genetics and Developmental Biology The Innovative Academy for Seed Design Chinese Academy of Sciences 1 West Beichen Road Beijing 100101 China
| | - Li Xie
- Institute of Crop Sciences National Wheat Improvement Center Chinese Academy of Agricultural Sciences (CAAS) 12 Zhongguancun South Street Beijing 100081 China
| | - Muhammad Adeel Hassan
- Institute of Crop Sciences National Wheat Improvement Center Chinese Academy of Agricultural Sciences (CAAS) 12 Zhongguancun South Street Beijing 100081 China
| | - Jie Song
- Institute of Crop Sciences National Wheat Improvement Center Chinese Academy of Agricultural Sciences (CAAS) 12 Zhongguancun South Street Beijing 100081 China
| | - Faji Li
- Crop Research Institute Shandong Academy of Agricultural Sciences 202 Industry North Road Jinan 250100 China
| | - Desen Wang
- Institute of Crop Sciences National Wheat Improvement Center Chinese Academy of Agricultural Sciences (CAAS) 12 Zhongguancun South Street Beijing 100081 China
| | - Yong Zhang
- Institute of Crop Sciences National Wheat Improvement Center Chinese Academy of Agricultural Sciences (CAAS) 12 Zhongguancun South Street Beijing 100081 China
| | - Yuanfeng Hao
- Institute of Crop Sciences National Wheat Improvement Center Chinese Academy of Agricultural Sciences (CAAS) 12 Zhongguancun South Street Beijing 100081 China
| | - Genying Li
- Crop Research Institute Shandong Academy of Agricultural Sciences 202 Industry North Road Jinan 250100 China
| | - Chengcai Chu
- State Key Laboratory of Plant Genomics Institute of Genetics and Developmental Biology The Innovative Academy for Seed Design Chinese Academy of Sciences 1 West Beichen Road Beijing 100101 China
| | - Zhonghu He
- Institute of Crop Sciences National Wheat Improvement Center Chinese Academy of Agricultural Sciences (CAAS) 12 Zhongguancun South Street Beijing 100081 China
- International Maize and Wheat Improvement Center (CIMMYT) China Office c/o CAAS 12 Zhongguancun South Street Beijing 100081 China
| | - Shuanghe Cao
- Institute of Crop Sciences National Wheat Improvement Center Chinese Academy of Agricultural Sciences (CAAS) 12 Zhongguancun South Street Beijing 100081 China
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42
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Li Y, Tang J, Liu W, Yan W, Sun Y, Che J, Tian C, Zhang H, Yu L. The Genetic Architecture of Grain Yield in Spring Wheat Based on Genome-Wide Association Study. Front Genet 2021; 12:728472. [PMID: 34868206 PMCID: PMC8634730 DOI: 10.3389/fgene.2021.728472] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Accepted: 08/30/2021] [Indexed: 11/24/2022] Open
Abstract
Uncovering the genetic architecture for grain yield (GY)–related traits is important for wheat breeding. To detect stable loci for GY-related traits, a genome-wide association study (GWAS) was conducted in a diverse panel, which included 251 elite spring wheat accessions mainly from the Northeast of China. In total, 52,503 single nucleotide polymorphisms (SNPs) from the wheat 55 K SNP arrays were used. Thirty-eight loci for GY-related traits were detected and each explained 6.5–16.7% of the phenotypic variations among which 12 are at similar locations with the known genes or quantitative trait loci and 26 are likely to be new. Furthermore, six genes possibly involved in cell division, signal transduction, and plant development are candidate genes for GY-related traits. This study provides new insights into the genetic architecture of GY and the significantly associated SNPs and accessions with a larger number of favorable alleles could be used to further enhance GY in breeding.
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Affiliation(s)
- Yuyao Li
- Heilongjiang Bayi Agricultural University, Daqing, China.,Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Jingquan Tang
- Crop Resources Institute, Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Wenlin Liu
- Crop Resources Institute, Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Wenyi Yan
- Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Yan Sun
- Crop Resources Institute, Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Jingyu Che
- Keshan Branch, Heilongjiang Academy of Agricultural Sciences, Qiqihar, China
| | - Chao Tian
- Keshan Branch, Heilongjiang Academy of Agricultural Sciences, Qiqihar, China
| | - Hongji Zhang
- Crop Resources Institute, Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Lihe Yu
- Heilongjiang Bayi Agricultural University, Daqing, China.,Heilongjiang Academy of Agricultural Sciences, Harbin, China
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43
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Arif MAR, Shokat S, Plieske J, Ganal M, Lohwasser U, Chesnokov YV, Kocherina NV, Kulwal P, Kumar N, McGuire PE, Sorrells ME, Qualset CO, Börner A. A SNP-based genetic dissection of versatile traits in bread wheat (Triticum aestivum L.). THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2021; 108:960-976. [PMID: 34218494 DOI: 10.1111/tpj.15407] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Accepted: 06/14/2021] [Indexed: 05/20/2023]
Abstract
The continuous increase in global population prompts increased wheat production. Future wheat (Triticum aestivum L.) breeding will heavily rely on dissecting molecular and genetic bases of wheat yield and related traits which is possible through the discovery of quantitative trait loci (QTLs) in constructed populations, such as recombinant inbred lines (RILs). Here, we present an evaluation of 92 RILs in a bi-parental RIL mapping population (the International Triticeae Mapping Initiative Mapping Population [ITMI/MP]) using newly generated phenotypic data in 3-year experiments (2015), older phenotypic data (1997-2009), and newly created single nucleotide polymorphism (SNP) marker data based on 92 of the original RILs to search for novel and stable QTLs. Our analyses of more than 15 unique traits observed in multiple experiments included analyses of 46 traits in three environments in the USA, 69 traits in eight environments in Germany, 149 traits in 10 environments in Russia, and 28 traits in four environments in India (292 traits in 25 environments) with 7584 SNPs (292 × 7584 = 2 214 528 data points). A total of 874 QTLs were detected with limit of detection (LOD) scores of 2.01-3.0 and 432 QTLs were detected with LOD > 3.0. Moreover, 769 QTLs could be assigned to 183 clusters based on the common markers and relative proximity of related QTLs, indicating gene-rich regions throughout the A, B, and D genomes of common wheat. This upgraded genotype-phenotype information of ITMI/MP can assist breeders and geneticists who can make crosses with suitable RILs to improve or investigate traits of interest.
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Affiliation(s)
- Mian Abdur Rehman Arif
- Wheat Breeding Group, Plant Breeding and Genetics Division, Nuclear Institute for Agriculture and Biology (NIAB), Faisalabad, Pakistan
| | - Sajid Shokat
- Wheat Breeding Group, Plant Breeding and Genetics Division, Nuclear Institute for Agriculture and Biology (NIAB), Faisalabad, Pakistan
| | - Jörg Plieske
- SGS Institut Fresenius GmbH TraitGenetics Section, Am Schwabeplan 1b, Stadt Seeland, OT Gatersleben, 06466, Germany
| | - Martin Ganal
- SGS Institut Fresenius GmbH TraitGenetics Section, Am Schwabeplan 1b, Stadt Seeland, OT Gatersleben, 06466, Germany
| | - Ulrike Lohwasser
- Resources Genetics and Reproduction Group, Leibniz Institute of Plant Genetics and Crop Plant Research, Corrensstr. 3, Seeland, OT Gatersleben, 06466, Germany
| | - Yuriy V Chesnokov
- Laboratory of Ecological Genetics and Plant Breeding, Agrophysical Research Institute, Grazhdanskiy pr. 14, St. Petersburg, 195220, Russia
| | - Nataliya V Kocherina
- Laboratory of Ecological Genetics and Plant Breeding, Agrophysical Research Institute, Grazhdanskiy pr. 14, St. Petersburg, 195220, Russia
| | - Pawan Kulwal
- State Level Biotechnology Centre, Mahatma Phule Krishi Vidyapeeth, Rahuri, Ahmednagar, Maharashtra, 413 722, India
| | - Neeraj Kumar
- Department of Plant and Environmental Sciences, Clemson University, 100C Biosystems Research Complex 105 Collings Street, Clemson, SC, 29634-0141, USA
| | - Patrick E McGuire
- Plant Sciences Department, University of California, Mail Stop 3, One Shields Avenue, Davis, CA, 95616, USA
| | - Mark E Sorrells
- Department of Plant Breeding and Genetics, Cornell University, Ithaca, NY, 14853, USA
| | - Calvin O Qualset
- Plant Sciences Department, University of California, Mail Stop 3, One Shields Avenue, Davis, CA, 95616, USA
| | - Andreas Börner
- Resources Genetics and Reproduction Group, Leibniz Institute of Plant Genetics and Crop Plant Research, Corrensstr. 3, Seeland, OT Gatersleben, 06466, Germany
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44
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Yan H, Li G, Shi J, Tian S, Zhang X, Cheng R, Wang X, Yuan Y, Cao S, Zhou J, Kong Z, Jia H, Ma Z. Genetic control of Fusarium head blight resistance in two Yangmai 158-derived recombinant inbred line populations. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2021; 134:3037-3049. [PMID: 34110431 DOI: 10.1007/s00122-021-03876-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Accepted: 05/28/2021] [Indexed: 06/12/2023]
Abstract
Stably expressed type I and type II resistance QTL were identified using two Yangmai 158-derived RIL populations, and plant-height and flowering-time QTL intervals detected did not contribute to the FHB resistance variations. Yangmai 158 (Y158) is an elite wheat cultivar widely grown in China with stable Fusarium head blight (FHB) resistance. To enrich the genetic basis underlying FHB resistance, QTL mapping was conducted using two recombinant inbred line (RIL) populations derived from crosses of Y158 with susceptible lines Annong 8455 and Veery. Survey with makers linked to Fhb1, Fhb2, Fhb4 and Fhb5 in resistance cultivar Wangshuibai indicated that both Y158 and the susceptible lines do not contain these QTL. The RIL populations were surveyed with 65 PCR markers and 55 K chip, which generated 23,159 valid marker data, to produce genetic maps for whole genome scanning of quantitative trait loci (QTL). A total of six QTL, all with the Y158 alleles for better resistance and including one stably expressed QTL for type I resistance (Qfhi.nau-2D) and one stably expressed QTL for type II resistance (Qfhs.nau-2A), were identified. Moreover, taking advantage of the great genetic variations in plant height and flowering time, QTL conditioning these two traits were determined. Of six plant-height QTL and three flowering-time QTL intervals detected, none were associated with FHB resistance. The FHB resistance QTL in Y158 were shown to be useful alternatives in FHB resistance breeding programs. The SNP markers flanking Qfhs.nau-2A and Qfhi.nau-2D have been converted to breeder-friendly PCR-based markers to facilitate their applications.
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Affiliation(s)
- Haisheng Yan
- Crop Genomics and Bioinformatics Center and National Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
| | - Guoqiang Li
- Crop Genomics and Bioinformatics Center and National Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
| | - Jinxing Shi
- Crop Genomics and Bioinformatics Center and National Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
| | - ShunShun Tian
- Crop Genomics and Bioinformatics Center and National Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
| | - Xiaoqiu Zhang
- Crop Genomics and Bioinformatics Center and National Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
| | - Rui Cheng
- Crop Genomics and Bioinformatics Center and National Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
| | - Xin Wang
- Crop Genomics and Bioinformatics Center and National Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
| | - Yang Yuan
- Crop Genomics and Bioinformatics Center and National Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
| | - Shouyang Cao
- Crop Genomics and Bioinformatics Center and National Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
| | - Jiyang Zhou
- College of Life Science and Technology, Xinjiang University, Urumqi, 830046, Xinjiang, China
| | - Zhongxin Kong
- Crop Genomics and Bioinformatics Center and National Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
| | - Haiyan Jia
- Crop Genomics and Bioinformatics Center and National Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China.
| | - Zhengqiang Ma
- Crop Genomics and Bioinformatics Center and National Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China.
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45
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Ji G, Xu Z, Fan X, Zhou Q, Yu Q, Liu X, Liao S, Feng B, Wang T. Identification of a major and stable QTL on chromosome 5A confers spike length in wheat ( Triticum aestivum L.). MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2021; 41:56. [PMID: 37309397 PMCID: PMC10236030 DOI: 10.1007/s11032-021-01249-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Accepted: 08/29/2021] [Indexed: 06/14/2023]
Abstract
Spike length (SL) is the key determinant of plant architecture and yield potential. In this study, 193 recombinant inbred lines (RILs) derived from a cross between 13F10 and Chuanmai 42 (CM42) were evaluated for spike length in six environments. Sixty RILs consisting of 30 high and 30 low SLs were genotyped using the bulked segregant analysis exome sequencing (BSE-Seq) analysis for preliminary quantitative trait locus (QTL) mapping. A 6.69 Mb (518.43-525.12 Mb) region on chromosome 5AL was found to have a significant effect on the SL trait. Fifteen competitive allele-specific PCR (KASP) markers were successfully converted from the single nucleotide polymorphisms (SNPs) in the SL target region. Combined with four novel simple sequence repeat (SSR) markers, a genetic linkage map spanning 21.159 cM was constructed. The mapping result confirmed the identity of a major and stable QTL named QSl.cib-5A in the targeted region that explained 7.88-26.60% of the phenotypic variation in SL. QSl.cib-5A was narrowed to a region of 4.84 cM interval corresponding to a 4.67 Mb (516.60-521.27 Mb) physical region in the Chinese Spring RefSeq v2.0 containing 17 high-confidence genes with 25 transcripts. In addition, this QTL exhibited pleiotropic effects on spikelet density (SD), with the phenotypic variances proportion ranging from 11.34 to 19.92%. This study provides a foundational step for cloning the QSl.cib-5A, which is involved in the regulation of spike morphology in common wheat. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-021-01249-6.
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Affiliation(s)
- Guangsi Ji
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041 China
- University of Chinese Academy of Sciences, Beijing, 100049 China
| | - Zhibin Xu
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041 China
| | - Xiaoli Fan
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041 China
| | - Qiang Zhou
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041 China
| | - Qin Yu
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041 China
- University of Chinese Academy of Sciences, Beijing, 100049 China
| | - Xiaofeng Liu
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041 China
- University of Chinese Academy of Sciences, Beijing, 100049 China
| | - Simin Liao
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041 China
- University of Chinese Academy of Sciences, Beijing, 100049 China
| | - Bo Feng
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041 China
| | - Tao Wang
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041 China
- The Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, 100101 China
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46
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Qu P, Wang J, Wen W, Gao F, Liu J, Xia X, Peng H, Zhang L. Construction of Consensus Genetic Map With Applications in Gene Mapping of Wheat ( Triticum aestivum L.) Using 90K SNP Array. FRONTIERS IN PLANT SCIENCE 2021; 12:727077. [PMID: 34512703 PMCID: PMC8424075 DOI: 10.3389/fpls.2021.727077] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Accepted: 07/28/2021] [Indexed: 06/02/2023]
Abstract
Wheat is one of the most important cereal crops worldwide. A consensus map combines genetic information from multiple populations, providing an effective alternative to improve the genome coverage and marker density. In this study, we constructed a consensus map from three populations of recombinant inbred lines (RILs) of wheat using a 90K single nucleotide polymorphism (SNP) array. Phenotypic data on plant height (PH), spike length (SL), and thousand-kernel weight (TKW) was collected in six, four, and four environments in the three populations, and then used for quantitative trait locus (QTL) mapping. The mapping results obtained using the constructed consensus map were compared with previous results obtained using individual maps and previous studies on other populations. A simulation experiment was also conducted to assess the performance of QTL mapping with the consensus map. The constructed consensus map from the three populations spanned 4558.55 cM in length, with 25,667 SNPs, having high collinearity with physical map and individual maps. Based on the consensus map, 21, 27, and 19 stable QTLs were identified for PH, SL, and TKW, much more than those detected with individual maps. Four PH QTLs and six SL QTLs were likely to be novel. A putative gene called TraesCS4D02G076400 encoding gibberellin-regulated protein was identified to be the candidate gene for one major PH QTL located on 4DS, which may enrich genetic resources in wheat semi-dwarfing breeding. The simulation results indicated that the length of the confidence interval and standard errors of the QTLs detected using the consensus map were much smaller than those detected using individual maps. The consensus map constructed in this study provides the underlying genetic information for systematic mapping, comparison, and clustering of QTL, and gene discovery in wheat genetic study. The QTLs detected in this study had stable effects across environments and can be used to improve the wide adaptation of wheat cultivars through marker-assisted breeding.
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Affiliation(s)
- Pingping Qu
- The National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
- State Key Laboratory of Agrobiotechnology, Key Laboratory of Crop Heterosis and Utilization, Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
| | - Jiankang Wang
- The National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Weie Wen
- Department of Cell Biology, Zunyi Medical University, Zunyi, China
| | - Fengmei Gao
- Crop Research Institute, Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Jindong Liu
- The National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xianchun Xia
- The National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Huiru Peng
- State Key Laboratory of Agrobiotechnology, Key Laboratory of Crop Heterosis and Utilization, Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
| | - Luyan Zhang
- The National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
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Pretini N, Vanzetti LS, Terrile II, Donaire G, González FG. Mapping QTL for spike fertility and related traits in two doubled haploid wheat (Triticum aestivum L.) populations. BMC PLANT BIOLOGY 2021; 21:353. [PMID: 34311707 PMCID: PMC8314532 DOI: 10.1186/s12870-021-03061-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Accepted: 05/23/2021] [Indexed: 06/02/2023]
Abstract
BACKGROUND In breeding programs, the selection of cultivars with the highest yield potential consisted in the selection of the yield per se, which resulted in cultivars with higher grains per spike (GN) and occasionally increased grain weight (GW) (main numerical components of the yield). In this study, quantitative trait loci (QTL) for GW, GN and spike fertility traits related to GN determination were mapped using two doubled haploid (DH) populations (Baguette Premium 11 × BioINTA 2002 and Baguette 19 × BioINTA 2002). RESULTS In total 305 QTL were identified for 14 traits, out of which 12 QTL were identified in more than three environments and explained more than 10% of the phenotypic variation in at least one environment. Eight hotspot regions were detected on chromosomes 1A, 2B, 3A, 5A, 5B, 7A and 7B in which at least two major and stable QTL sheared confidence intervals. QTL on two of these regions (R5A.1 and R5A.2) have previously been described, but the other six regions are novel. CONCLUSIONS Based on the pleiotropic analysis within a robust physiological model we conclude that two hotspot genomic regions (R5A.1 and R5A.2) together with the QGW.perg-6B are of high relevance to be used in marker assisted selection in order to improve the spike yield potential. All the QTL identified for the spike related traits are the first step to search for their candidate genes, which will allow their better manipulation in the future.
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Affiliation(s)
- Nicole Pretini
- Centro de Investigaciones y Transferencia del Noroeste de la Provincia de Buenos Aires (CITNOBA, CONICET-UNNOBA-UNSADA), Monteagudo 2772 CP 2700, Pergamino, Buenos Aires, Argentina.
| | - Leonardo S Vanzetti
- Instituto Nacional de Tecnología Agropecuaria (INTA), EEA INTA Marcos Juárez. Ruta 12 s/n CP 2850, Marcos Juárez, Córdoba, Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Godoy Cruz 2290 CP C1425FQB, Buenos Aires, Argentina
| | - Ignacio I Terrile
- Instituto Nacional de Tecnología Agropecuaria (INTA), EEA INTA Pergamino. Ruta 32, km 4,5 CP 2700, Pergamino, Buenos Aires, Argentina
| | - Guillermo Donaire
- Instituto Nacional de Tecnología Agropecuaria (INTA), EEA INTA Marcos Juárez. Ruta 12 s/n CP 2850, Marcos Juárez, Córdoba, Argentina
| | - Fernanda G González
- Centro de Investigaciones y Transferencia del Noroeste de la Provincia de Buenos Aires (CITNOBA, CONICET-UNNOBA-UNSADA), Monteagudo 2772 CP 2700, Pergamino, Buenos Aires, Argentina
- Instituto Nacional de Tecnología Agropecuaria (INTA), EEA INTA Pergamino. Ruta 32, km 4,5 CP 2700, Pergamino, Buenos Aires, Argentina
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Xie Q, Sparkes DL. Dissecting the trade-off of grain number and size in wheat. PLANTA 2021; 254:3. [PMID: 34117927 DOI: 10.1007/s00425-021-03658-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Accepted: 06/06/2021] [Indexed: 05/21/2023]
Abstract
Principal component and meta-QTL analyses identified genetic loci affecting the trade-off of wheat grain number and size, which could provide opportunities to optimize local breeding strategies for further yield improvement. Grain yield of wheat is complex, and its physiological and genetic bases remain largely unknown. Using the Forno/Oberkulmer recombinant inbred lines, this study validated the negative phenotypic relationships between thousand grain weight (TGW) and grain number components. This trade-off might be alleviated at the population level by early anthesis and at the shoot level by higher shoot biomass. Principal component (PC) analysis revealed three useful PCs, of which both PC1 and PC3 were positively associated with grain yield and grains m-2 through increased spikes m-2 (for PC1) or grains per spike (for PC3), while PC2 primarily reflected the trade-off of grain number and TGW. Quantitative trait locus (QTL) mapping detected eight and seven loci for PC1 and PC2, respectively, on chromosomes 1D, 2A, 3A, 3B, 4A, 4B, 5A and 7B, individually explaining 11.7‒29.3% of phenotypic variations. Using the 1203 QTLs published previously, a meta-analysis was performed to reveal 12, 21, 37 and 54 genomic regions (MQTLs) affecting grains m-2, spikes m-2, grains per spike and TGW, respectively. Moreover, 67 MQTLs (96%) for grain number were coincided with the TGW MQTLs, with reverse phenotypic effects, suggesting intensive genetic trade-off between grain number and size. The AGP2 gene, which encodes ADP-glucose pyrophosphorylase determining TGW, was found by haplotype analysis in the Forno/Oberkulmer population to affect grain number oppositely, indicating this trade-off at the gene level. Appropriate combinations of the QTLs/genes for local breeding targets, such as higher grain number or larger grains, therefore, would be critical to achieve future yield gains.
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Affiliation(s)
- Quan Xie
- College of Agriculture, Nanjing Agricultural University, Nanjing, 210 095, Jiangsu, China.
| | - Debbie L Sparkes
- Division of Plant and Crop Sciences, School of Biosciences, University of Nottingham Sutton Bonington Campus, Loughborough, LE12 5RD, Leicestershire, UK
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49
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Utilization of a Wheat50K SNP Microarray-Derived High-Density Genetic Map for QTL Mapping of Plant Height and Grain Traits in Wheat. PLANTS 2021; 10:plants10061167. [PMID: 34201388 PMCID: PMC8229693 DOI: 10.3390/plants10061167] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/17/2021] [Revised: 05/18/2021] [Accepted: 05/26/2021] [Indexed: 11/22/2022]
Abstract
Plant height is significantly correlated with grain traits, which is a component of wheat yield. The purpose of this study is to investigate the main quantitative trait loci (QTLs) that control plant height and grain-related traits in multiple environments. In this study, we constructed a high-density genetic linkage map using the Wheat50K SNP Array to map QTLs for these traits in 198 recombinant inbred lines (RILs). The two ends of the chromosome were identified as recombination-rich areas in all chromosomes except chromosome 1B. Both the genetic map and the physical map showed a significant correlation, with a correlation coefficient between 0.63 and 0.99. However, there was almost no recombination between 1RS and 1BS. In terms of plant height, 1RS contributed to the reduction of plant height by 3.43 cm. In terms of grain length, 1RS contributed to the elongation of grain by 0.11 mm. A total of 43 QTLs were identified, including eight QTLs for plant height (PH), 11 QTLs for thousand grain weight (TGW), 15 QTLs for grain length (GL), and nine QTLs for grain width (GW), which explained 1.36–33.08% of the phenotypic variation. Seven were environment-stable QTLs, including two loci (Qph.nwafu-4B and Qph.nwafu-4D) that determined plant height. The explanation rates of phenotypic variation were 7.39–12.26% and 20.11–27.08%, respectively. One QTL, Qtgw.nwafu-4B, which influenced TGW, showed an explanation rate of 3.43–6.85% for phenotypic variation. Two co-segregating KASP markers were developed, and the physical locations corresponding to KASP_AX-109316968 and KASP_AX-109519968 were 25.888344 MB and 25.847691 MB, respectively. Qph.nwafu-4B, controlling plant height, and Qtgw.nwafu-4B, controlling TGW, had an obvious linkage relationship, with a distance of 7–8 cM. Breeding is based on molecular markers that control plant height and thousand-grain weight by selecting strains with low plant height and large grain weight. Another QTL, Qgw.nwafu-4D, which determined grain width, had an explanation rate of 3.43–6.85%. Three loci that affected grain length were Qgl.nwafu-5A, Qgl.nwafu-5D.2, and Qgl.nwafu-6B, illustrating the explanation rates of phenotypic variation as 6.72–9.59%, 5.62–7.75%, and 6.68–10.73%, respectively. Two QTL clusters were identified on chromosomes 4B and 4D.
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50
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Pretini N, Alonso MP, Vanzetti LS, Pontaroli AC, González FG. The physiology and genetics behind fruiting efficiency: a promising spike trait to improve wheat yield potential. JOURNAL OF EXPERIMENTAL BOTANY 2021; 72:3987-4004. [PMID: 33681978 DOI: 10.1093/jxb/erab080] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Accepted: 02/17/2021] [Indexed: 06/12/2023]
Abstract
Fruiting efficiency (FE, grains per g of spike dry weight at anthesis) was proposed as a promising spike trait to improve wheat yield potential, based on its functional relationship with grain number determination and the evidence of trait variability in elite germplasm. During the last few years, we have witnessed great advances in the understanding of the physiological and genetic basis of this trait. The present review summarizes the recent heritability estimations and the genetic gains obtained when fruiting efficiency was measured at maturity (FEm, grains per g of chaff) and used as selection criterion. In addition, we propose spike ideotypes for contrasting fruiting efficiencies based on the fertile floret efficiency (FFE, fertile florets per g of spike dry weight at anthesis) and grain set (grains per fertile floret), together with other spike fertility-related traits. We also review novel genes and quantitative trait loci available for using marker-assisted selection for fruiting efficiency and other spike fertility traits. The possible trade-off between FE and grain weight and the genes reported to alter this relation are also considered. Finally, we discuss the benefits and future steps towards the use of fruiting efficiency as a selection criterion in breeding programs.
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Affiliation(s)
- Nicole Pretini
- Centro de Investigaciones y Transferencia del Noroeste de la Provincia de Buenos Aires (CITNOBA, CONICET-UNNOBA-UNSADA), Monteagudo 2772 CP 2700, Pergamino, Buenos Aires, Argentina
| | - María P Alonso
- Unidad Integrada Balcarce [Facultad de Ciencias Agrarias, Universidad Nacional de Mar del Plata -Instituto Nacional de Tecnología Agropecuaria (INTA), EEA INTA Balcarce], Ruta 226 km 73.5 CP 7620, Balcarce, Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Godoy Cruz 2290 CP C1425FQB, Buenos Aires, Argentina
| | - Leonardo S Vanzetti
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Godoy Cruz 2290 CP C1425FQB, Buenos Aires, Argentina
- Instituto Nacional de Tecnología Agropecuaria (INTA). EEA INTA Marcos Juárez, Ruta 12 s/n CP 2850, Marcos Juárez, Córdoba, Argentina
| | - Ana C Pontaroli
- Unidad Integrada Balcarce [Facultad de Ciencias Agrarias, Universidad Nacional de Mar del Plata -Instituto Nacional de Tecnología Agropecuaria (INTA), EEA INTA Balcarce], Ruta 226 km 73.5 CP 7620, Balcarce, Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Godoy Cruz 2290 CP C1425FQB, Buenos Aires, Argentina
| | - Fernanda G González
- Centro de Investigaciones y Transferencia del Noroeste de la Provincia de Buenos Aires (CITNOBA, CONICET-UNNOBA-UNSADA), Monteagudo 2772 CP 2700, Pergamino, Buenos Aires, Argentina
- Instituto Nacional de Tecnología Agropecuaria (INTA). EEA INTA Pergamino, Ruta 32, km 4,5 CP 2700, Pergamino, Buenos Aires, Argentina
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