1
|
Cai Y, Zhou X, Wang C, Liu A, Sun Z, Li S, Shi X, Yang S, Guan Y, Cheng J, Wu Y, Qin R, Sun H, Zhao C, Li J, Cui F. Quantitative trait loci detection for three tiller-related traits and the effects on wheat (Triticum aestivum L.) yields. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2024; 137:87. [PMID: 38512468 DOI: 10.1007/s00122-024-04589-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Accepted: 02/23/2024] [Indexed: 03/23/2024]
Abstract
KEY MESSAGE A total of 38 putative additive QTLs and 55 pairwise putative epistatic QTLs for tiller-related traits were reported, and the candidate genes underlying qMtn-KJ-5D, a novel major and stable QTL for maximum tiller number, were characterized. Tiller-related traits play an important role in determining the yield potential of wheat. Therefore, it is important to elucidate the genetic basis for tiller number when attempting to use genetic improvement as a tool for enhancing wheat yields. In this study, a quantitative trait locus (QTL) analysis of three tiller-related traits was performed on the recombinant inbred lines (RILs) of a mapping population, referred to as KJ-RILs, that was derived from a cross between the Kenong 9204 (KN9204) and Jing 411 (J411) lines. A total of 38 putative additive QTLs and 55 pairwise putative epistatic QTLs for spike number per plant (SNPP), maximum tiller number (MTN), and ear-bearing tiller rate (EBTR) were detected in eight different environments. Among these QTLs with additive effects, three major and stable QTLs were first documented herein. Almost all but two pairwise epistatic QTLs showed minor interaction effects accounting for no more than 3.0% of the phenotypic variance. The genetic effects of two colocated major and stable QTLs, i.e., qSnpp-KJ-5D.1 and qMtn-KJ-5D, for yield-related traits were characterized. The breeding selection effect of the beneficial allele for the two QTLs was characterized, and its genetic effects on yield-related traits were evaluated. The candidate genes underlying qMtn-KJ-5D were predicted based on multi-omics data, and TraesKN5D01HG00080 was identified as a likely candidate gene. Overall, our results will help elucidate the genetic architecture of tiller-related traits and can be used to develop novel wheat varieties with high yields.
Collapse
Affiliation(s)
- 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, People's Republic of China
| | - Xiaohan Zhou
- 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, People's Republic of China
| | - Chenyang Wang
- 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, People's Republic of China
| | - Aifeng Liu
- Crop Research Institute, Shandong Academy of Agricultural Science, Jinan, 250100, People's Republic of China
| | - Zhencang Sun
- Jingbo Agrochemicals Technology Co., Ltd., Binzhou, 256500, People's Republic of China
| | - Shihui Li
- 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, People's Republic of China
| | - Xinyao Shi
- 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, People's Republic of China
| | - Shuang 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, People's Republic of China
| | - Yuxiang Guan
- 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, People's Republic of China
| | - Jiajia Cheng
- 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, People's Republic of 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, People's Republic of China
| | - 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, People's Republic of 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, People's Republic of 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, People's Republic of China.
| | - Junming Li
- Ministry of Education Key Laboratory of Molecular and Cellular Biology, Hebei Collaboration Innovation Center for Cell SignalingHebei Key Laboratory of Molecular and Cellular Biology, College of Life Sciences, Hebei Normal University, Shijiazhuang, 050024, People's Republic of 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, People's Republic of China.
| |
Collapse
|
2
|
Wang J, Wang E, Cheng S, Ma A. Identification of molecular markers and candidate regions associated with grain number per spike in Pubing3228 using SLAF-BSA. FRONTIERS IN PLANT SCIENCE 2024; 15:1361621. [PMID: 38504905 PMCID: PMC10948542 DOI: 10.3389/fpls.2024.1361621] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Accepted: 01/30/2024] [Indexed: 03/21/2024]
Abstract
Grain number per spike, a pivotal agronomic trait dictating wheat yield, lacks a comprehensive understanding of its underlying mechanism in Pubing3228, despite the identification of certain pertinent genes. Thus, our investigation sought to ascertain molecular markers and candidate regions associated with grain number per spike through a high-density genetic mapping approach that amalgamates site-specific amplified fragment sequencing (SLAF-seq) and bulked segregation analysis (BSA). To facilitate this, we conducted a comparative analysis of two wheat germplasms, Pubing3228 and Jing4839, known to exhibit marked discrepancies in spike shape. By leveraging this methodology, we successfully procured 2,810,474 SLAF tags, subsequently resulting in the identification of 187,489 single nucleotide polymorphisms (SNPs) between the parental strains. We subsequently employed the SNP-index association algorithm alongside the extended distribution (ED) association algorithm to detect regions associated with the trait. The former algorithm identified 24 trait-associated regions, whereas the latter yielded 70. Remarkably, the intersection of these two algorithms led to the identification of 25 trait-associated regions. Amongst these regions, we identified 399 annotated genes, including three genes harboring non-synonymous mutant SNP loci. Notably, the APETALA2 (AP2) transcription factor families, which exhibited a strong correlation with spike type, were also annotated. Given these findings, it is plausible to hypothesize that these genes play a critical role in determining spike shape. In summation, our study contributes significant insights into the genetic foundation of grain number per spike. The molecular markers and candidate regions we have identified can be readily employed for marker-assisted breeding endeavors, ultimately leading to the development of novel wheat cultivars possessing enhanced yield potential. Furthermore, conducting further functional analyses on the identified genes will undoubtedly facilitate a comprehensive elucidation of the underlying mechanisms governing spike development in wheat.
Collapse
Affiliation(s)
- Jiansheng Wang
- College of Chemistry and Environment Engineering, Pingdingshan University, Pingdingshan, Henan, 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, China
| | - Shiping Cheng
- College of Chemistry and Environment Engineering, Pingdingshan University, Pingdingshan, Henan, 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, China
| |
Collapse
|
3
|
Wang D, Zhao Y, Zhao X, Ji M, Guo X, Tian J, Chen G, Deng Z. Genome-wide association analysis of type II resistance to Fusarium head blight in common wheat. PeerJ 2023; 11:e15906. [PMID: 37750077 PMCID: PMC10518165 DOI: 10.7717/peerj.15906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Accepted: 07/26/2023] [Indexed: 09/27/2023] Open
Abstract
Background Fusarium head blight (FHB) is a disease affecting wheat spikes caused by some Fusarium species and leads to cases of severe yield reduction and seed contamination. Identifying resistance genes/QTLs from wheat germplasm may help to improve FHB resistance in wheat production. Methods Our study evaluated 205 elite winter wheat cultivars for FHB resistance. A high-density 90K SNP array was used for genotyping the panel. A genome-wide association study (GWAS) from cultivars from three different environments was performed using a mixed linear model (MLM). Results Sixty-six significant marker-trait associations (MTAs) were identified (P < 0.001) on fifteen chromosomes that explained the phenotypic variation ranging from 5.4 to 11.2%. Some important new MTAs in genomic regions involving FHB resistance were found on chromosomes 2A, 3B, 5B, 6A, and 7B. Six MTAs at 92 cM on chromosome 7B were found in cultivars from two different environments. Moreover, there were 11 MTAs consistently associated with diseased spikelet rate and diseased rachis rate as pleiotropic effect loci and D_contig74317_533 on chromosome 5D was novel for FHB resistance. Eight new candidate genes of FHB resistance were predicated in wheat in this study. Three candidate genes, TraesCS5D02G006700, TraesCS6A02G013600, and TraesCS7B02G370700 on chromosome 5DS, 6AS, and 7BL, respectively, were perhaps important in defending against FHB by regulating intramolecular transferase activity, GTP binding, or chitinase activity in wheat, but further validation in needed. In addition, a total of five favorable alleles associated with wheat FHB resistance were discovered. These results provide important genes/loci for enhancing FHB resistance in wheat breeding by marker-assisted selection.
Collapse
Affiliation(s)
- Dehua Wang
- State Key Laboratory of Crop Biology, Shandong Agricultural University, Tai’an, Shandong, China
| | - Yunzhe Zhao
- State Key Laboratory of Crop Biology, Shandong Agricultural University, Tai’an, Shandong, China
| | - Xinying Zhao
- State Key Laboratory of Crop Biology, Shandong Agricultural University, Tai’an, Shandong, China
| | - Mengqi Ji
- State Key Laboratory of Crop Biology, Shandong Agricultural University, Tai’an, Shandong, China
| | - Xin Guo
- Taiyuan Agro-Tech Extension and Service Center, Taiyuan, Shanxi, China
| | - Jichun Tian
- State Key Laboratory of Crop Biology, Shandong Agricultural University, Tai’an, Shandong, China
- Shandong Huatian Agricultural Technology Co., Ltd, Tai’an, Shandong, China
| | - Guangfeng Chen
- College of Ecology and Garden Architecture, Dezhou University, Dezhou, Shandong, China
| | - Zhiying Deng
- State Key Laboratory of Crop Biology, Shandong Agricultural University, Tai’an, Shandong, China
| |
Collapse
|
4
|
Rahimi Y, Khahani B, Jamali A, Alipour H, Bihamta MR, Ingvarsson PK. Genome-wide association study to identify genomic loci associated with early vigor in bread wheat under simulated water deficit complemented with quantitative trait loci meta-analysis. G3 (BETHESDA, MD.) 2023; 13:jkac320. [PMID: 36458966 PMCID: PMC10248217 DOI: 10.1093/g3journal/jkac320] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/10/2022] [Revised: 11/16/2022] [Accepted: 11/17/2022] [Indexed: 12/05/2022]
Abstract
A genome-wide association study (GWAS) was used to identify associated loci with early vigor under simulated water deficit and grain yield under field drought in a diverse collection of Iranian bread wheat landraces. In addition, a meta-quantitative trait loci (MQTL) analysis was used to further expand our approach by retrieving already published quantitative trait loci (QTL) from recombinant inbred lines, double haploids, back-crosses, and F2 mapping populations. In the current study, around 16%, 14%, and 16% of SNPs were in significant linkage disequilibrium (LD) in the A, B, and D genomes, respectively, and varied between 5.44% (4A) and 21.85% (6A). Three main subgroups were identified among the landraces with different degrees of admixture, and population structure was further explored through principal component analysis. Our GWAS identified 54 marker-trait associations (MTAs) that were located across the wheat genome but with the highest number found in the B sub-genome. The gene ontology (GO) analysis of MTAs revealed that around 75% were located within or closed to protein-coding genes. In the MQTL analysis, 23 MQTLs, from a total of 215 QTLs, were identified and successfully projected onto the reference map. MQT-YLD4, MQT-YLD9, MQT-YLD13, MQT-YLD17, MQT-YLD18, MQT-YLD19, and MQTL-RL1 contributed to the highest number of projected QTLs and were therefore regarded as the most reliable and stable QTLs under water deficit conditions. These MQTLs greatly facilitate the identification of putative candidate genes underlying at each MQTL interval due to the reduced confidence of intervals associated with MQTLs. These findings provide important information on the genetic basis of early vigor traits and grain yield under water deficit conditions and set the foundation for future investigations into adaptation to water deficit in bread wheat.
Collapse
Affiliation(s)
- Yousef Rahimi
- Department of Plant Biology, Uppsala BioCenter, Linnean Centre for Plant Biology in Uppsala, Swedish University of Agricultural Sciences, 75007 Uppsala, Sweden
| | - Bahman Khahani
- Department of Plant Genetics and Production, College of Agriculture, Shiraz University, 71441-65186 Shiraz, Iran
| | - Ali Jamali
- Department of Agronomy and Plant Breeding, Faculty of Agriculture, University of Tehran, 31587-77871 Karaj, Iran
| | - Hadi Alipour
- Department of Plant Breeding and Biotechnology, Faculty of Agriculture, Urmia University, 5756151818 Urmia, Iran
| | - Mohammad Reza Bihamta
- Department of Agronomy and Plant Breeding, Faculty of Agriculture, University of Tehran, 31587-77871 Karaj, Iran
| | - Pär K Ingvarsson
- Department of Plant Biology, Uppsala BioCenter, Linnean Centre for Plant Biology in Uppsala, Swedish University of Agricultural Sciences, 75007 Uppsala, Sweden
| |
Collapse
|
5
|
Liu X, Xu Z, Feng B, Zhou Q, Ji G, Guo S, Liao S, Lin D, Fan X, Wang T. Quantitative trait loci identification and breeding value estimation of grain weight-related traits based on a new wheat 50K single nucleotide polymorphism array-derived genetic map. FRONTIERS IN PLANT SCIENCE 2022; 13:967432. [PMID: 36110352 PMCID: PMC9468616 DOI: 10.3389/fpls.2022.967432] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2022] [Accepted: 08/04/2022] [Indexed: 06/01/2023]
Abstract
Mining novel and less utilized thousand grain weight (TGW) related genes are useful for improving wheat yield. In this study, a recombinant inbred line population from a cross between Zhongkemai 138 (ZKM138, high TGW) and Chuanmai 44 (CM44, low TGW) was used to construct a new Wheat 50K SNP array-derived genetic map that spanned 1,936.59 cM and contained 4, 139 markers. Based on this map, ninety-one quantitative trait loci (QTL) were detected for eight grain-related traits in six environments. Among 58 QTLs, whose superior alleles were contributed by ZKM138, QTgw.cib-6A was a noticeable major stable QTL and was also highlighted by bulked segregant analysis with RNA sequencing (BSR-Seq). It had a pyramiding effect on TGW enhancement but no significant trade-off effect on grain number per spike or tiller number, with two other QTLs (QTgw.cib-2A.2 and QTgw.cib-6D), possibly explaining the excellent grain performance of ZKM138. After comparison with known loci, QTgw.cib-6A was deduced to be a novel locus that differed from nearby TaGW2 and TaBT1. Seven simple sequence repeat (SSR) and thirty-nine kompetitive allele-specific PCR (KASP) markers were finally developed to narrow the candidate interval of QTgw.cib-6A to 4.1 Mb. Only six genes in this interval were regarded as the most likely candidate genes. QTgw.cib-6A was further validated in different genetic backgrounds and presented 88.6% transmissibility of the ZKM138-genotype and a 16.4% increase of TGW in ZKM138 derivatives. And the geographic pattern of this locus revealed that its superior allele is present in only 6.47% of 433 Chinese modern wheat varieties, indicating its potential contribution to further high-yield breeding.
Collapse
Affiliation(s)
- Xiaofeng Liu
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Zhibin Xu
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Bo Feng
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Qiang Zhou
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Guangsi Ji
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Shaodan Guo
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Simin Liao
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Dian Lin
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Xiaoli Fan
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Tao Wang
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
- Innovative Academy for Seed Design, Chinese Academy of Sciences, Beijing, China
| |
Collapse
|
6
|
Che Y, He Y, Song N, Yang Y, Wei L, Yang X, Zhang Y, Zhang J, Han H, Li X, Zhou S, Liu W, Li L. Four-Year and Five-Developing-Stage Dynamic QTL Mapping for Tiller Number in the Hybrid Population of Agropyron Gaertn. FRONTIERS IN PLANT SCIENCE 2022; 13:835437. [PMID: 35283893 PMCID: PMC8907830 DOI: 10.3389/fpls.2022.835437] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Accepted: 01/24/2022] [Indexed: 06/14/2023]
Abstract
Tiller number (TN) is an important agronomic trait affecting gramineous crop yield. To understand the static and dynamic information of quantitative trait locus (QTLs) controlling TN of Agropyron Gaertn., both the unconditional and conditional quantitative trait loci (QTL) mapping of TN were conducted using a cross-pollinated (CP) hybrid population with a total of 113 plant lines from the cross between Agropyron cristatum (L.) Gaertn. Z1842 and Allium mongolicum Keng Z2098, based on the phenotypic data of TN at five developmental stages [i.e., recovering stage (RS), jointing stage (JS), heading stage (HS), flowering stage (FS), and maturity stage (MS)] in 4 years (i.e., 2017, 2018, 2020, and 2021) and the genetic map constructed of 1,023 single-nucleotide polymorphism (SNP) markers. Thirty-seven QTLs controlling TN were detected using two analysis methods in 4 years, which were distributed in six linkage groups. Each QTL explained 2.96-31.11% of the phenotypic variation, with a logarithum of odds (LOD) value of 2.51-13.95. Nine of these loci detected both unconditional and conditional QTLs. Twelve unconditional major QTLs and sixteen conditional major QTLs were detected. Three relatively major stable conditional QTLs, namely, cQTN1-3, cQTN1-5, and cQTN4-1, were expressed in 2020 and 2021. Meantime, two pairs of major QTLs cQTN1-5 and qTN1-4 and also cQTN2-4 and qTN2-3 were located at the same interval but in different years. Except for qTN2-2 and qTN3-5/cQTN3-5, other thirty-four QTLs were first detected in this study. This study provides a better interpretation of genetic factors that selectively control tiller at different developmental stages and a reference for molecular marker-assisted selection in the related plant improvement.
Collapse
Affiliation(s)
- Yonghe Che
- Hebei Key Laboratory of Crop Stress Biology, Qinhuangdao, China
- College of Agronomy and Biotechnology, Hebei Normal University of Science and Technology, Qinhuangdao, China
| | - Yutong He
- Hebei Key Laboratory of Crop Stress Biology, Qinhuangdao, China
- College of Agronomy and Biotechnology, Hebei Normal University of Science and Technology, Qinhuangdao, China
| | - Nan Song
- Hebei Key Laboratory of Crop Stress Biology, Qinhuangdao, China
- College of Agronomy and Biotechnology, Hebei Normal University of Science and Technology, Qinhuangdao, China
| | - Yanping Yang
- Hebei Key Laboratory of Crop Stress Biology, Qinhuangdao, China
- College of Agronomy and Biotechnology, Hebei Normal University of Science and Technology, Qinhuangdao, China
| | - Lai Wei
- Hebei Key Laboratory of Crop Stress Biology, Qinhuangdao, China
- College of Agronomy and Biotechnology, Hebei Normal University of Science and Technology, Qinhuangdao, China
| | - Xinming Yang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yan Zhang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Jinpeng Zhang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Haiming Han
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xiuquan Li
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Shenghui Zhou
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Weihua Liu
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Lihui Li
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| |
Collapse
|
7
|
Saini DK, Chopra Y, Singh J, Sandhu KS, Kumar A, Bazzer S, Srivastava P. Comprehensive evaluation of mapping complex traits in wheat using genome-wide association studies. MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2022; 42:1. [PMID: 37309486 PMCID: PMC10248672 DOI: 10.1007/s11032-021-01272-7] [Citation(s) in RCA: 49] [Impact Index Per Article: 24.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Accepted: 12/10/2021] [Indexed: 06/14/2023]
Abstract
Genome-wide association studies (GWAS) are effectively applied to detect the marker trait associations (MTAs) using whole genome-wide variants for complex quantitative traits in different crop species. GWAS has been applied in wheat for different quality, biotic and abiotic stresses, and agronomic and yield-related traits. Predictions for marker-trait associations are controlled with the development of better statistical models taking population structure and familial relatedness into account. In this review, we have provided a detailed overview of the importance of association mapping, population design, high-throughput genotyping and phenotyping platforms, advancements in statistical models and multiple threshold comparisons, and recent GWA studies conducted in wheat. The information about MTAs utilized for gene characterization and adopted in breeding programs is also provided. In the literature that we surveyed, as many as 86,122 wheat lines have been studied under various GWA studies reporting 46,940 loci. However, further utilization of these is largely limited. The future breakthroughs in area of genomic selection, multi-omics-based approaches, machine, and deep learning models in wheat breeding after exploring the complex genetic structure with the GWAS are also discussed. This is a most comprehensive study of a large number of reports on wheat GWAS and gives a comparison and timeline of technological developments in this area. This will be useful to new researchers or groups who wish to invest in GWAS.
Collapse
Affiliation(s)
- Dinesh K. Saini
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, 141004 India
| | - Yuvraj Chopra
- College of Agriculture, Punjab Agricultural University, Ludhiana, 141004 India
| | - Jagmohan Singh
- Division of Plant Pathology, Indian Agricultural Research Institute, New Delhi, 110012 India
| | - Karansher S. Sandhu
- Department of Crop and Soil Sciences, Washington State University, Pullman, WA 99163 USA
| | - Anand Kumar
- Department of Genetics and Plant Breeding, Chandra Shekhar Azad University of Agriculture and Technology, Kanpur, 202002 India
| | - Sumandeep Bazzer
- Division of Plant Sciences, University of Missouri, Columbia, MO 65211 USA
| | - Puja Srivastava
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, 141004 India
| |
Collapse
|
8
|
Bai Y, Zhao X, Yao X, Yao Y, An L, Li X, Wang Y, Gao X, Jia Y, Guan L, Li M, Wu K, Wang Z. Genome wide association study of plant height and tiller number in hulless barley. PLoS One 2021; 16:e0260723. [PMID: 34855842 PMCID: PMC8639095 DOI: 10.1371/journal.pone.0260723] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Accepted: 11/15/2021] [Indexed: 11/18/2022] Open
Abstract
Hulless barley (Hordeum vulgare L. var. nudum), also called naked barley, is a unique variety of cultivated barley. The genome-wide specific length amplified fragment sequencing (SLAF-seq) method is a rapid deep sequencing technology that is used for the selection and identification of genetic loci or markers. In this study, we collected 300 hulless barley accessions and used the SLAF-seq method to identify candidate genes involved in plant height (PH) and tiller number (TN). We obtained a total of 1407 M paired-end reads, and 228,227 SLAF tags were developed. After filtering using an integrity threshold of >0.8 and a minor allele frequency of >0.05, 14,504,892 single-nucleotide polymorphisms (SNP) loci were screened out. The remaining SNPs were used for the construction of a neighbour-joining phylogenetic tree, and the three subcluster members showed no obvious differentiation among regional varieties. We used a genome wide association study approach to identify 1006 and 113 SNPs associated with TN and PH, respectively. Based on best linear unbiased predictors (BLUP), 41 and 29 SNPs associated with TN and PH, respectively. Thus, several of genes, including Hd3a and CKX5, may be useful candidates for the future genetic breeding of hulless barley. Taken together, our results provide insight into the molecular mechanisms controlling barley architecture, which is important for breeding and yield.
Collapse
Affiliation(s)
- Yixiong Bai
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, Shaanxi, China
- Qinghai University, Qinghai Academy of Agricultural and Forestry Sciences, Qinghai Key Laboratory of Hulless Barley Genetics and Breeding, Xining, Qinghai Province, China
| | - Xiaohong Zhao
- Qinghai University, Qinghai Academy of Agricultural and Forestry Sciences, Qinghai Key Laboratory of Hulless Barley Genetics and Breeding, Xining, Qinghai Province, China
- Good Agricultural Practices Research Center of Traditional, Chongqing Institute of Medicinal Plant Cultivation, Chongqing, China
| | - Xiaohua Yao
- Qinghai University, Qinghai Academy of Agricultural and Forestry Sciences, Qinghai Key Laboratory of Hulless Barley Genetics and Breeding, Xining, Qinghai Province, China
| | - Youhua Yao
- Qinghai University, Qinghai Academy of Agricultural and Forestry Sciences, Qinghai Key Laboratory of Hulless Barley Genetics and Breeding, Xining, Qinghai Province, China
| | - Likun An
- Qinghai University, Qinghai Academy of Agricultural and Forestry Sciences, Qinghai Key Laboratory of Hulless Barley Genetics and Breeding, Xining, Qinghai Province, China
| | - Xin Li
- Qinghai University, Qinghai Academy of Agricultural and Forestry Sciences, Qinghai Key Laboratory of Hulless Barley Genetics and Breeding, Xining, Qinghai Province, China
| | - Yong Wang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, Shaanxi, China
| | - Xin Gao
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, Shaanxi, China
| | - Yatao Jia
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, Shaanxi, China
| | - Lulu Guan
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, Shaanxi, China
| | - Man Li
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, Shaanxi, China
| | - Kunlun Wu
- Qinghai University, Qinghai Academy of Agricultural and Forestry Sciences, Qinghai Key Laboratory of Hulless Barley Genetics and Breeding, Xining, Qinghai Province, China
- * E-mail: (KW); (ZW)
| | - Zhonghua Wang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, Shaanxi, China
- * E-mail: (KW); (ZW)
| |
Collapse
|
9
|
Semagn K, Iqbal M, Chen H, Perez-Lara E, Bemister DH, Xiang R, Zou J, Asif M, Kamran A, N'Diaye A, Randhawa H, Beres BL, Pozniak C, Spaner D. Physical mapping of QTL associated with agronomic and end-use quality traits in spring wheat under conventional and organic management systems. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2021; 134:3699-3719. [PMID: 34333664 DOI: 10.1007/s00122-021-03923-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Accepted: 07/20/2021] [Indexed: 06/13/2023]
Abstract
Using phenotypic data of four biparental spring wheat populations evaluated at multiple environments under two management systems, we discovered 152 QTL and 22 QTL hotspots, of which two QTL accounted for up to 37% and 58% of the phenotypic variance, consistently detected in all environments, and fell within genomic regions harboring known genes. Identification of the physical positions of quantitative trait loci (QTL) would be highly useful for developing functional markers and comparing QTL results across multiple independent studies. The objectives of the present study were to map and characterize QTL associated with nine agronomic and end-use quality traits (tillering ability, plant height, lodging, grain yield, grain protein content, thousand kernel weight, test weight, sedimentation volume, and falling number) in hard red spring wheat recombinant inbred lines (RILs) using the International Wheat Genome Sequencing Consortium (IWGSC) RefSeq v2.0 physical map. We evaluated a total of 698 RILs from four populations derived from crosses involving seven parents at 3-8 conventionally (high N) and organically (low N) managed field environments. Using the phenotypic data combined across all environments per management, and the physical map between 1058 and 6526 markers per population, we identified 152 QTL associated with the nine traits, of which 29 had moderate and 2 with major effects. Forty-nine of the 152 QTL mapped across 22 QTL hotspot regions with each region coincident to 2-6 traits. Some of the QTL hotspots were physically located close to known genes. QSv.dms-1A and QPht.dms-4B.1 individually explained up to 37% and 58% of the variation in sedimentation volume and plant height, respectively, and had very large LOD scores that varied from 19.0 to 35.7 and from 16.7 to 55.9, respectively. We consistently detected both QTL in the combined and all individual environments, laying solid ground for further characterization and possibly for cloning.
Collapse
Affiliation(s)
- Kassa Semagn
- Department of Agricultural, Food and Nutritional Science, 4-10 Agriculture-Forestry Centre, University of Alberta, Edmonton, AB, T6G 2P5, Canada
| | - Muhammad Iqbal
- Department of Agricultural, Food and Nutritional Science, 4-10 Agriculture-Forestry Centre, University of Alberta, Edmonton, AB, T6G 2P5, Canada
| | - Hua Chen
- Department of Agricultural, Food and Nutritional Science, 4-10 Agriculture-Forestry Centre, University of Alberta, Edmonton, AB, T6G 2P5, Canada
- Department of Agronomy, School of Life Science and Engineering, Southwest University of Science and Technology, 59 Qinglong Road, Mianyang, 621010, Sichuan, China
| | - Enid Perez-Lara
- Department of Agricultural, Food and Nutritional Science, 4-10 Agriculture-Forestry Centre, University of Alberta, Edmonton, AB, T6G 2P5, Canada
| | - Darcy H Bemister
- Department of Agricultural, Food and Nutritional Science, 4-10 Agriculture-Forestry Centre, University of Alberta, Edmonton, AB, T6G 2P5, Canada
| | - Rongrong Xiang
- Department of Agricultural, Food and Nutritional Science, 4-10 Agriculture-Forestry Centre, University of Alberta, Edmonton, AB, T6G 2P5, Canada
| | - Jun Zou
- Department of Agricultural, Food and Nutritional Science, 4-10 Agriculture-Forestry Centre, University of Alberta, Edmonton, AB, T6G 2P5, Canada
| | - Muhammad Asif
- Department of Agricultural, Food and Nutritional Science, 4-10 Agriculture-Forestry Centre, University of Alberta, Edmonton, AB, T6G 2P5, Canada
- Department of Agronomy, 2004 Throckmorton Plant Science Center, Kansas State University, Manhattan, KS, 66506, USA
- Heartland Plant Innovations, Kansas Wheat Innovation Center, 1990 Kimball Avenue, Manhattan, KS, 66502, USA
| | - Atif Kamran
- Department of Agricultural, Food and Nutritional Science, 4-10 Agriculture-Forestry Centre, University of Alberta, Edmonton, AB, T6G 2P5, Canada
- Department of Botany, Seed Centre, The University of Punjab, New Campus, Lahore, 54590, Pakistan
| | - Amidou N'Diaye
- Crop Development Centre and Department of Plant Sciences, University of Saskatchewan, 51 Campus Drive, Saskatoon, SK, S7N 5A8, Canada
| | - Harpinder Randhawa
- Agriculture, and Agri-Food Canada, 5403-1st Avenue South, Lethbridge, AB, T1J 4B1, Canada
| | - Brian L Beres
- Agriculture, and Agri-Food Canada, 5403-1st Avenue South, Lethbridge, AB, T1J 4B1, Canada
| | - Curtis Pozniak
- Crop Development Centre and Department of Plant Sciences, University of Saskatchewan, 51 Campus Drive, Saskatoon, SK, S7N 5A8, Canada
| | - Dean Spaner
- Department of Agricultural, Food and Nutritional Science, 4-10 Agriculture-Forestry Centre, University of Alberta, Edmonton, AB, T6G 2P5, Canada.
| |
Collapse
|
10
|
Wang W, Guo H, Wu C, Yu H, Li X, Chen G, Tian J, Deng Z. Identification of novel genomic regions associated with nine mineral elements in Chinese winter wheat grain. BMC PLANT BIOLOGY 2021; 21:311. [PMID: 34210282 PMCID: PMC8252321 DOI: 10.1186/s12870-021-03105-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Accepted: 06/14/2021] [Indexed: 05/08/2023]
Abstract
BACKGROUND Mineral elements are important for maintaining good human health besides heavy metals. Mining genes that control mineral elements are paramount for improving their accumulation in the wheat grain. Although previous studies have reported some loci for beneficial trace elements, they have mainly focused on Zn and Fe content. However, little information is available regarding the genetic loci differences in dissecting synchronous accumulation of multiple mineral elements in wheat grains, including beneficial and heavy elements. Therefore, a genome-wide association study (GWAS) was conducted on 205 wheat accessions with 24,355 single nucleotide polymorphisms (SNPs) to identify important loci and candidate genes for controlling Ca, Fe, Zn, Se, Cu, Mn, Cd, As, and Pb accumulation in wheat grains. RESULTS A total of 101 marker-trait associations (MTAs) (P < 10-5) loci affecting the content of nine mineral elements was identified on chromosomes 1B, 1D, 2A, 2B, 3A, 3B, 3D, 4A, 4B, 5A, 5B, 5D, 6B, 7A, 7B, and 7D. Among these, 17 major MTAs loci for the nine mineral elements were located, and four MTAs loci (P < 10-5) were found on chromosomes 1B, 6B, 7B, and 7D. Eight multi-effect MTAs loci were detected that are responsible for the control of more than one trait, mainly distributed on chromosomes 3B, 7B, and 5A. Furthermore, sixteen candidate genes controlling Ca, Fe, Zn, Se, Cd, and Pb were predicted, whose functions were primarily related to ion binding, including metals, Fe, Ca, Cu, Mg, and Zn, ATP binding, ATPase activity, DNA binding, RNA binding, and protein kinase activity. CONCLUSIONS Our study indicated the existence of gene interactions among mineral elements based on multi-effect MTAs loci and candidate genes. Meanwhile this study provided new insights into the genetic control of mineral element concentrations, and the important loci and genes identified may contribute to the rapid development of beneficial mineral elements and a reduced content of harmful heavy metals in wheat grain.
Collapse
Affiliation(s)
- Wei Wang
- State Key Laboratory of Crop Biology, Key Laboratory of Crop Biology of Shandong Province, Group of Wheat Quality and Molecular Breeding, College of Agronomy, Shandong Agricultural University, Tai'an, Shandong, 271000, P.R. China
| | - Hong Guo
- State Key Laboratory of Crop Biology, Key Laboratory of Crop Biology of Shandong Province, Group of Wheat Quality and Molecular Breeding, College of Agronomy, Shandong Agricultural University, Tai'an, Shandong, 271000, P.R. China
| | - Chongning Wu
- State Key Laboratory of Crop Biology, Key Laboratory of Crop Biology of Shandong Province, Group of Wheat Quality and Molecular Breeding, College of Agronomy, Shandong Agricultural University, Tai'an, Shandong, 271000, P.R. China
| | - Hui Yu
- State Key Laboratory of Crop Biology, Key Laboratory of Crop Biology of Shandong Province, Group of Wheat Quality and Molecular Breeding, College of Agronomy, Shandong Agricultural University, Tai'an, Shandong, 271000, P.R. China
| | - Xiaokang Li
- Handan Academy of Agricultural Sciences, Handan, Hebei, 056000, P.R. China
| | - Guangfeng Chen
- College of Ecology and Garden Architecture, Dezhou University, Dezhou, Shandong, 253023, P.R. China
| | - Jichun Tian
- State Key Laboratory of Crop Biology, Key Laboratory of Crop Biology of Shandong Province, Group of Wheat Quality and Molecular Breeding, College of Agronomy, Shandong Agricultural University, Tai'an, Shandong, 271000, P.R. China
| | - Zhiying Deng
- State Key Laboratory of Crop Biology, Key Laboratory of Crop Biology of Shandong Province, Group of Wheat Quality and Molecular Breeding, College of Agronomy, Shandong Agricultural University, Tai'an, Shandong, 271000, P.R. China.
| |
Collapse
|
11
|
Genome wide association study of the whiteness and colour related traits of flour and dough sheets in common wheat. Sci Rep 2021; 11:8790. [PMID: 33888831 PMCID: PMC8062544 DOI: 10.1038/s41598-021-88241-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Accepted: 04/08/2021] [Indexed: 11/09/2022] Open
Abstract
Flour whiteness and colour are important factors that influence the quality of wheat flour and end-use products. In this study, a genome wide association study focusing on flour and dough sheet colour using a high density genetic map constructed with 90K single nucleotide polymorphism arrays in a panel of 205 elite winter wheat accessions was conducted in two different locations in 2 years. Eighty-six significant marker-trait associations (MTAs) were detected for flour whiteness and the brightness index (L* value), the redness index (a* value), and the yellowness index (b* value) of flour and dough sheets (P < 10-4) on homologous group 1, 2, 5 and 7, and chromosomes 3A, 3B, 4A, 6A and 6B. Four, three, eleven, eleven MTAs for the flour whiteness, L* value, a* value, b* value, and one MTA for the dough sheet L* value were identified in more than one environment. Based on MATs, some important new candidate genes were identified. Of these, two candidate genes, TraesCS5D01G004300 and Gsp-1D, for BS00000020_51 were found in wheat, relating to grain hardness. Other candidate genes were associated with proteins, the fatty acid biosynthetic process, the ketone body biosynthetic process, etc.
Collapse
|
12
|
Vitale P, Fania F, Esposito S, Pecorella I, Pecchioni N, Palombieri S, Sestili F, Lafiandra D, Taranto F, De Vita P. QTL Analysis of Five Morpho-Physiological Traits in Bread Wheat Using Two Mapping Populations Derived from Common Parents. Genes (Basel) 2021; 12:genes12040604. [PMID: 33923933 PMCID: PMC8074140 DOI: 10.3390/genes12040604] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Revised: 04/15/2021] [Accepted: 04/17/2021] [Indexed: 01/20/2023] Open
Abstract
Traits such as plant height (PH), juvenile growth habit (GH), heading date (HD), and tiller number are important for both increasing yield potential and improving crop adaptation to climate change. In the present study, these traits were investigated by using the same bi-parental population at early (F2 and F2-derived F3 families) and late (F6 and F7, recombinant inbred lines, RILs) generations to detect quantitative trait loci (QTLs) and search for candidate genes. A total of 176 and 178 lines were genotyped by the wheat Illumina 25K Infinium SNP array. The two genetic maps spanned 2486.97 cM and 3732.84 cM in length, for the F2 and RILs, respectively. QTLs explaining the highest phenotypic variation were found on chromosomes 2B, 2D, 5A, and 7D for HD and GH, whereas those for PH were found on chromosomes 4B and 4D. Several QTL detected in the early generations (i.e., PH and tiller number) were not detected in the late generations as they were due to dominance effects. Some of the identified QTLs co-mapped to well-known adaptive genes (i.e., Ppd-1, Vrn-1, and Rht-1). Other putative candidate genes were identified for each trait, of which PINE1 and PIF4 may be considered new for GH and TTN in wheat. The use of a large F2 mapping population combined with NGS-based genotyping techniques could improve map resolution and allow closer QTL tagging.
Collapse
Affiliation(s)
- Paolo Vitale
- Department of Agriculture, Food, Natural Science, Engineering, University of Foggia, Via Napoli 25, 71122 Foggia, Italy; (P.V.); (F.F.)
- Research Centre for Cereal and Industrial Crops (CREA-CI), CREA—Council for Agricultural Research and Economics, 71122 Foggia, Italy; (S.E.); (I.P.); (N.P.)
| | - Fabio Fania
- Department of Agriculture, Food, Natural Science, Engineering, University of Foggia, Via Napoli 25, 71122 Foggia, Italy; (P.V.); (F.F.)
| | - Salvatore Esposito
- Research Centre for Cereal and Industrial Crops (CREA-CI), CREA—Council for Agricultural Research and Economics, 71122 Foggia, Italy; (S.E.); (I.P.); (N.P.)
| | - Ivano Pecorella
- Research Centre for Cereal and Industrial Crops (CREA-CI), CREA—Council for Agricultural Research and Economics, 71122 Foggia, Italy; (S.E.); (I.P.); (N.P.)
| | - Nicola Pecchioni
- Research Centre for Cereal and Industrial Crops (CREA-CI), CREA—Council for Agricultural Research and Economics, 71122 Foggia, Italy; (S.E.); (I.P.); (N.P.)
| | - Samuela Palombieri
- Department of Agriculture and Forest Sciences (DAFNE), University of Tuscia, 01100 Viterbo, Italy; (S.P.); (F.S.); (D.L.)
| | - Francesco Sestili
- Department of Agriculture and Forest Sciences (DAFNE), University of Tuscia, 01100 Viterbo, Italy; (S.P.); (F.S.); (D.L.)
| | - Domenico Lafiandra
- Department of Agriculture and Forest Sciences (DAFNE), University of Tuscia, 01100 Viterbo, Italy; (S.P.); (F.S.); (D.L.)
| | - Francesca Taranto
- Institute of Biosciences and Bioresources (CNR-IBBR), 80055 Portici, Italy
- Correspondence: (F.T.); (P.D.V.)
| | - Pasquale De Vita
- Research Centre for Cereal and Industrial Crops (CREA-CI), CREA—Council for Agricultural Research and Economics, 71122 Foggia, Italy; (S.E.); (I.P.); (N.P.)
- Correspondence: (F.T.); (P.D.V.)
| |
Collapse
|
13
|
Gupta S, Akhatar J, Kaur P, Sharma A, Sharma P, Mittal M, Bharti B, Banga SS. Genetic analyses of nitrogen assimilation enzymes in Brassica juncea (L.) Czern & Coss. Mol Biol Rep 2019; 46:4235-4244. [PMID: 31115836 DOI: 10.1007/s11033-019-04878-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2018] [Accepted: 05/14/2019] [Indexed: 12/11/2022]
Abstract
Nitrogen (N) is a critical input for plant growth and development. A better understanding of N uptake and utilization is important to develop plant breeding strategies for improving nitrogen use efficiency (NUE). With that objective in mind, we assayed a SNP-genotyped association panel comprising 92 inbred lines for the activities of nitrate reductase (NR), nitrite reductase (NIR), glutamine synthetase (GS) and glutamate synthase (GOGAT). All these enzymes are associated with N assimilation. The experiments were carried out at two levels of N application: no added N (N0) and agrnomically recommened dose (100 kg/ha) of N application (N100). Genome wide association studies (GWAS) helped to identify several marker-trait associations (MTAs), involving chromosomes A01, A06, A08, B02, B04, B05 and B08. These explained high phenotypic variation (up to 32%). Annotation of the genomic region(s) in or around significant SNPs allowed prediction of genes encoding high affinity nitrate transporters, glutamine synthetase 1.3, myb-like transcription factor family protein, bidirectional amino acid transporter 1, auxin signaling F-box 3 and oxidoreductases. This is the first attempt to use GWAS for identification of enzyme QTLs to explain variation for nitrogen assimilation enzymes in Brassica juncea.
Collapse
Affiliation(s)
- Shilpa Gupta
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, 141001, India
| | - Javed Akhatar
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, 141001, India
| | - Palminder Kaur
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, 141001, India
| | - Anju Sharma
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, 141001, India
| | - Pushp Sharma
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, 141001, India
| | - Meenakshi Mittal
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, 141001, India
| | - Baudh Bharti
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, 141001, India
| | - Surinder Singh Banga
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, 141001, India.
| |
Collapse
|
14
|
Jamil M, Ali A, Gul A, Ghafoor A, Napar AA, Ibrahim AMH, Naveed NH, Yasin NA, Mujeeb-Kazi A. Genome-wide association studies of seven agronomic traits under two sowing conditions in bread wheat. BMC PLANT BIOLOGY 2019; 19:149. [PMID: 31003597 PMCID: PMC6475106 DOI: 10.1186/s12870-019-1754-6] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2018] [Accepted: 04/02/2019] [Indexed: 05/18/2023]
Abstract
BACKGROUND Wheat is a cool seasoned crop requiring low temperature during grain filling duration and therefore increased temperature causes significant yield reduction. A set of 125 spring wheat genotypes from International Maize and Wheat Improvement Centre (CIMMYT-Mexico) was evaluated for phenological and yield related traits at three locations in Pakistan under normal sowing time and late sowing time for expose to prolonged high temperature. With the help of genome-wide association study using genotyping-by-sequencing, marker trait associations (MTAs) were observed separately for the traits under normal and late sown conditions. RESULTS Significant reduction ranging from 9 to 74% was observed in all traits under high temperature. Especially 30, 25, 41 and 66% reduction was observed for days to heading (DH), plant height (PH), spikes per plant (SPP) and yield respectively. We identified 55,954 single nucleotide polymorphisms (SNPs) using genotyping by sequencing of these 125 hexaploid spring wheat genotypes and conducted genome-wide association studies (GWAS) for days to heading (DH), grain filled duration (GFD), plant height (PH), spikes per plant (SPP), grain number per spike (GNS), thousand kernel weight (TKW) and grain yield per plot (GY). Genomic regions identified through GWAS explained up to 13% of the phenotypic variance, on average. A total of 139 marker-trait associations (MTAs) across three wheat genomes (56 on genome A, 55 on B and 28 on D) were identified for all the seven traits studied. For days to heading, 20; grain filled duration, 21; plant height, 23; spikes per plant, 13; grain numbers per spike, 8; thousand kernel weight, 21 and for grain yield, 33 MTAs were detected under normal and late sown conditions. CONCLUSIONS This study identifies the essential resource of genetics research and underpins the chromosomal regions of seven agronomic traits under normal and high temperature. Significant relationship was observed between the number of favored alleles and trait observations. Fourteen protein coding genes with their respective annotations have been searched with the sequence of seven MTAs which were identified in this study. These findings will be helpful in the development of a breeder friendly platform for the selection of high yielding wheat lines at high temperature areas.
Collapse
Affiliation(s)
- Muhammad Jamil
- Department of Botany, University of Sargodha, Sargodha, Punjab Pakistan
| | - Aamir Ali
- Department of Botany, University of Sargodha, Sargodha, Punjab Pakistan
| | - Alvina Gul
- Atta-ur-Rehman School of Applied Biosciences (ASAB), National University of Science and Technology (NUST), Islamabad, Pakistan
| | - Abdul Ghafoor
- Plant Genetic Resources Institute (PGRI), National Agriculture Research Center (NARC), Islamabad, Pakistan
| | - Abdul Aziz Napar
- Institute of Plant Sciences, University of Sind Jamshoro, Sind, Pakistan
| | - Amir M. H. Ibrahim
- Soil and Crop Sciences Department, Texas A&M University, College Station, USA
| | - Naima Huma Naveed
- Department of Botany, University of Sargodha, Sargodha, Punjab Pakistan
| | | | | |
Collapse
|
15
|
Ren T, Hu Y, Tang Y, Li C, Yan B, Ren Z, Tan F, Tang Z, Fu S, Li Z. Utilization of a Wheat55K SNP Array for Mapping of Major QTL for Temporal Expression of the Tiller Number. FRONTIERS IN PLANT SCIENCE 2018; 9:333. [PMID: 29599793 PMCID: PMC5862827 DOI: 10.3389/fpls.2018.00333] [Citation(s) in RCA: 48] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/20/2017] [Accepted: 02/28/2018] [Indexed: 05/19/2023]
Abstract
Maximum tiller number and productive tiller number are important traits for wheat grain yield, but research involving the temporal expression of tiller number at different quantitative trait loci (QTL) levels is limited. In the present study, a population set of 371 recombined inbred lines derived from a cross between Chuan-Nong18 and T1208 was used to construct a high-density genetic map using a Wheat55K SNP Array and to perform dynamic QTL analysis of the tiller number at four growth stages. A high-density genetic map containing 11,583 SNP markers and 59 SSR markers that spanned 4,513.95 cM and was distributed across 21 wheat chromosomes was constructed. A total of 28 single environmental QTL were identified in the recombined inbred lines population, and among these, seven QTL were stable and used for multi-environmental and dynamic analysis. These QTL were mapped to chromosomes 2D, 4A, 4D, 5A, 5D, and 7D, respectively. Each QTL explained 1.63-21.22% of the observed phenotypic variation, with an additive effect from -20.51 to 11.59. Dynamic analysis showed that cqTN-2D.2 can be detected at four growth stages of tillering, explaining 4.92-17.16% of the observed phenotypic variations and spanning 13.71 Mb (AX-109283238-AX-110544009: 82189047-95895626) according to the physical location of the flanking markers. The effects of the stable QTL were validated in the recombined inbred lines population, and the beneficial alleles could be utilized in future marker-assisted selection. Several candidate genes for MTN and PTN were predicted. The results provide a better understanding of the QTL selectively expressing the control of tiller number and will facilitate future map-based cloning. 9.17% SNP markers showed best hits to the Chinese Spring contigs. It was indicated that Wheat55K Array was efficient and valid to construct a high-density wheat genetic map.
Collapse
Affiliation(s)
- Tianheng Ren
- College of Agronomy, Sichuan Agricultural University, Chengdu, China
| | - Yangshan Hu
- College of Life Science, Sichuan Agricultural University, Ya’an, China
| | - Yingzi Tang
- College of Agronomy, Sichuan Agricultural University, Chengdu, China
| | - Chunsheng Li
- College of Agronomy, Sichuan Agricultural University, Chengdu, China
| | - Benju Yan
- College of Life Science, Sichuan Agricultural University, Ya’an, China
| | - Zhenglong Ren
- College of Agronomy, Sichuan Agricultural University, Chengdu, China
| | - Feiquan Tan
- College of Agronomy, Sichuan Agricultural University, Chengdu, China
| | - Zongxiang Tang
- College of Agronomy, Sichuan Agricultural University, Chengdu, China
| | - Shulan Fu
- College of Agronomy, Sichuan Agricultural University, Chengdu, China
| | - Zhi Li
- College of Life Science, Sichuan Agricultural University, Ya’an, China
| |
Collapse
|