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Goeckeritz CZ, Grabb C, Grumet R, Iezzoni AF, Hollender CA. Genetic factors acting prior to dormancy in sour cherry influence bloom time the following spring. JOURNAL OF EXPERIMENTAL BOTANY 2024; 75:4428-4452. [PMID: 38602443 PMCID: PMC11263489 DOI: 10.1093/jxb/erae157] [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: 11/09/2023] [Accepted: 04/10/2024] [Indexed: 04/12/2024]
Abstract
Understanding the process of Prunus species floral development is crucial for developing strategies to manipulate bloom time and prevent crop loss due to climate change. Here, we present a detailed examination of flower development from initiation until bloom for early- and late-blooming sour cherries (Prunus cerasus) from a population segregating for a major bloom time QTL on chromosome 4. Using a new staging system, we show floral buds from early-blooming trees were persistently more advanced than those from late-blooming siblings. A genomic DNA coverage analysis revealed the late-blooming haplotype of this QTL, k, is located on a subgenome originating from the late-blooming P. fruticosa progenitor. Transcriptome analyses identified many genes within this QTL as differentially expressed between early- and late-blooming trees during the vegetative-to-floral transition. From these, we identified candidate genes for the late bloom phenotype, including multiple transcription factors homologous to Reproductive Meristem B3 domain-containing proteins. Additionally, we determined that the basis of k in sour cherry is likely separate from candidate genes found in sweet cherry-suggesting several major regulators of bloom time are located on Prunus chromosome 4.
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Affiliation(s)
- Charity Z Goeckeritz
- Department of Horticulture, Michigan State University, 1066 Bogue St., East Lansing, MI 48824, USA
| | - Chloe Grabb
- Department of Horticulture, Michigan State University, 1066 Bogue St., East Lansing, MI 48824, USA
| | - Rebecca Grumet
- Department of Horticulture, Michigan State University, 1066 Bogue St., East Lansing, MI 48824, USA
| | - Amy F Iezzoni
- Department of Horticulture, Michigan State University, 1066 Bogue St., East Lansing, MI 48824, USA
| | - Courtney A Hollender
- Department of Horticulture, Michigan State University, 1066 Bogue St., East Lansing, MI 48824, USA
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2
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Khojasteh M, Darzi Ramandi H, Taghavi SM, Taheri A, Rahmanzadeh A, Chen G, Foolad MR, Osdaghi E. Unraveling the genetic basis of quantitative resistance to diseases in tomato: a meta-QTL analysis and mining of transcript profiles. PLANT CELL REPORTS 2024; 43:184. [PMID: 38951262 DOI: 10.1007/s00299-024-03268-x] [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: 11/18/2023] [Accepted: 06/11/2024] [Indexed: 07/03/2024]
Abstract
KEY MESSAGE Whole-genome QTL mining and meta-analysis in tomato for resistance to bacterial and fungal diseases identified 73 meta-QTL regions with significantly refined/reduced confidence intervals. Tomato production is affected by a range of biotic stressors, causing yield losses and quality reductions. While sources of genetic resistance to many tomato diseases have been identified and characterized, stability of the resistance genes or quantitative trait loci (QTLs) across the resources has not been determined. Here, we examined 491 QTLs previously reported for resistance to tomato diseases in 40 independent studies and 54 unique mapping populations. We identified 29 meta-QTLs (MQTLs) for resistance to bacterial pathogens and 44 MQTLs for resistance to fungal pathogens, and were able to reduce the average confidence interval (CI) of the QTLs by 4.1-fold and 6.7-fold, respectively, compared to the average CI of the original QTLs. The corresponding physical length of the CIs of MQTLs ranged from 56 kb to 6.37 Mb, with a median of 921 kb, of which 27% had a CI lower than 500 kb and 53% had a CI lower than 1 Mb. Comparison of defense responses between tomato and Arabidopsis highlighted 73 orthologous genes in the MQTL regions, which were putatively determined to be involved in defense against bacterial and fungal diseases. Intriguingly, multiple genes were identified in some MQTL regions that are implicated in plant defense responses, including PR-P2, NDR1, PDF1.2, Pip1, SNI1, PTI5, NSL1, DND1, CAD1, SlACO, DAD1, SlPAL, Ph-3, EDS5/SID1, CHI-B/PR-3, Ph-5, ETR1, WRKY29, and WRKY25. Further, we identified a number of candidate resistance genes in the MQTL regions that can be useful for both marker/gene-assisted breeding as well as cloning and genetic transformation.
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Affiliation(s)
- Moein Khojasteh
- Department of Plant Protection, School of Agriculture, Shiraz University, Shiraz, 71441-65186, Iran
- School of Agriculture and Biology/State Key Laboratory of Microbial Metabolism, Shanghai Jiao Tong University, Shanghai, 200240, China
- Department of Plant Protection, University of Tehran, Karaj, 31587-77871, Iran
| | - Hadi Darzi Ramandi
- Department of Plant Production and Genetics, Faculty of Agriculture, Bu-Ali Sina University, P.O. Box 657833131, Hamedan, Iran
- Department of Molecular Physiology, Agricultural Biotechnology Research Institute of Iran, Agricultural Research Education and Extension Organization (AREEO), Karaj, Iran
| | - S Mohsen Taghavi
- Department of Plant Protection, School of Agriculture, Shiraz University, Shiraz, 71441-65186, Iran.
| | - Ayat Taheri
- Joint International Research Laboratory of Metabolic and Developmental Sciences, Plant Biotechnology Research Center, Fudan-SJTU-Nottingham Plant Biotechnology R&D Center, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, China
| | - Asma Rahmanzadeh
- Department of Plant Protection, School of Agriculture, Shiraz University, Shiraz, 71441-65186, Iran
- Department of Plant Protection, University of Tehran, Karaj, 31587-77871, Iran
| | - Gongyou Chen
- School of Agriculture and Biology/State Key Laboratory of Microbial Metabolism, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Majid R Foolad
- Department of Plant Science and the Intercollege Graduate Degree Program in Plant Biology, The Pennsylvania State University, University Park, PA, 16802, USA.
| | - Ebrahim Osdaghi
- Department of Plant Protection, University of Tehran, Karaj, 31587-77871, Iran.
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Daryani P, Amirbakhtiar N, Soorni J, Loni F, Darzi Ramandi H, Shobbar ZS. Uncovering the Genomic Regions Associated with Yield Maintenance in Rice Under Drought Stress Using an Integrated Meta-Analysis Approach. RICE (NEW YORK, N.Y.) 2024; 17:7. [PMID: 38227151 DOI: 10.1186/s12284-024-00684-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2023] [Accepted: 01/03/2024] [Indexed: 01/17/2024]
Abstract
The complex trait of yield is controlled by several quantitative trait loci (QTLs). Given the global water deficit issue, the development of rice varieties suitable for non-flooded cultivation holds significant importance in breeding programs. The powerful approach of Meta-QTL (MQTL) analysis can be used for the genetic dissection of complicated quantitative traits. In the current study, a comprehensive MQTL analysis was conducted to identify consistent QTL regions associated with drought tolerance and yield-related traits under water deficit conditions in rice. In total, 1087 QTLs from 134 rice populations, published between 2000 to 2021, were utilized in the analysis. Distinct MQTL analysis of the relevant traits resulted in the identification of 213 stable MQTLs. The confidence interval (CI) for the detected MQTLs was between 0.12 and 19.7 cM. The average CI of the identified MQTLs (4.68 cM) was 2.74 times narrower compared to the average CI of the initial QTLs. Interestingly, 63 MQTLs coincided with SNP peak positions detected by genome-wide association studies for yield and drought tolerance-associated traits under water deficit conditions in rice. Considering the genes located both in the QTL-overview peaks and the SNP peak positions, 19 novel candidate genes were introduced, which are associated with drought response index, plant height, panicle number, biomass, and grain yield. Moreover, an inclusive MQTL analysis was performed on all the traits to obtain "Breeding MQTLs". This analysis resulted in the identification of 96 MQTLs with a CI ranging from 0.01 to 9.0 cM. The mean CI of the obtained MQTLs (2.33 cM) was 4.66 times less than the mean CI of the original QTLs. Thirteen MQTLs fulfilling the criteria of having more than 10 initial QTLs, CI < 1 cM, and an average phenotypic variance explained greater than 10%, were designated as "Breeding MQTLs". These findings hold promise for assisting breeders in enhancing rice yield under drought stress conditions.
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Affiliation(s)
- Parisa Daryani
- Department of Systems Biology, Agricultural Biotechnology Research Institute of Iran (ABRII), Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran
| | - Nazanin Amirbakhtiar
- National Plant Gene Bank of Iran, Seed and Plant Improvement Institute (SPII), Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran
| | - Jahad Soorni
- Department of Systems Biology, Agricultural Biotechnology Research Institute of Iran (ABRII), Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran
| | - Fatemeh Loni
- Department of Systems Biology, Agricultural Biotechnology Research Institute of Iran (ABRII), Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran
| | - Hadi Darzi Ramandi
- Department of Plant Production and Genetics, Faculty of Agriculture, Bu-Ali Sina University, Hamedan, Iran.
| | - Zahra-Sadat Shobbar
- Department of Systems Biology, Agricultural Biotechnology Research Institute of Iran (ABRII), Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran.
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Beugnot A, Mary-Huard T, Bauland C, Combes V, Madur D, Lagardère B, Palaffre C, Charcosset A, Moreau L, Fievet JB. Identifying QTLs involved in hybrid performance and heterotic group complementarity: new GWAS models applied to factorial and admixed diallel maize hybrid panels. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:219. [PMID: 37816986 PMCID: PMC10564676 DOI: 10.1007/s00122-023-04431-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Accepted: 07/25/2023] [Indexed: 10/12/2023]
Abstract
KEY MESSAGE An original GWAS model integrating the ancestry of alleles was proposed and allowed the detection of background specific additive and dominance QTLs involved in heterotic group complementarity and hybrid performance. Maize genetic diversity is structured into genetic groups selected and improved relative to each other. This process increases group complementarity and differentiation over time and ensures that the hybrids produced from inter-group crosses exhibit high performances and heterosis. To identify loci involved in hybrid performance and heterotic group complementarity, we introduced an original association study model that disentangles allelic effects from the heterotic group origin of the alleles and compared it with a conventional additive/dominance model. This new model was applied on a factorial between Dent and Flint lines and a diallel between Dent-Flint admixed lines with two different layers of analysis: within each environment and in a multiple-environment context. We identified several strong additive QTLs for all traits, including some well-known additive QTLs for flowering time (in the region of Vgt1/2 on chromosome 8). Yield trait displayed significant non-additive effects in the diallel panel. Most of the detected Yield QTLs exhibited overdominance or, more likely, pseudo-overdominance effects. Apparent overdominance at these QTLs contributed to a part of the genetic group complementarity. The comparison between environments revealed a higher stability of additive QTL effects than non-additive ones. Several QTLs showed variations of effects according to the local heterotic group origin. We also revealed large chromosomic regions that display genetic group origin effects. Altogether, our results illustrate how admixed panels combined with dedicated GWAS modeling allow the identification of new QTLs that could not be revealed by a classical hybrid panel analyzed with traditional modeling.
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Affiliation(s)
- Aurélien Beugnot
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, UMR GQE-Le Moulon, 91272, Gif-Sur-Yvette, France
| | - Tristan Mary-Huard
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, UMR GQE-Le Moulon, 91272, Gif-Sur-Yvette, France
- Université Paris-Saclay, AgroParisTech, INRAE, UMR MIA Paris-Saclay, 91120, Palaiseau, France
| | - Cyril Bauland
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, UMR GQE-Le Moulon, 91272, Gif-Sur-Yvette, France
| | - Valerie Combes
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, UMR GQE-Le Moulon, 91272, Gif-Sur-Yvette, France
| | - Delphine Madur
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, UMR GQE-Le Moulon, 91272, Gif-Sur-Yvette, France
| | | | | | - Alain Charcosset
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, UMR GQE-Le Moulon, 91272, Gif-Sur-Yvette, France
| | - Laurence Moreau
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, UMR GQE-Le Moulon, 91272, Gif-Sur-Yvette, France
| | - Julie B Fievet
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, UMR GQE-Le Moulon, 91272, Gif-Sur-Yvette, France.
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Adak A, Kang M, Anderson SL, Murray SC, Jarquin D, Wong RKW, Katzfuß M. Phenomic data-driven biological prediction of maize through field-based high-throughput phenotyping integration with genomic data. JOURNAL OF EXPERIMENTAL BOTANY 2023; 74:5307-5326. [PMID: 37279568 DOI: 10.1093/jxb/erad216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 06/02/2023] [Indexed: 06/08/2023]
Abstract
High-throughput phenotyping (HTP) has expanded the dimensionality of data in plant research; however, HTP has resulted in few novel biological discoveries to date. Field-based HTP (FHTP), using small unoccupied aerial vehicles (UAVs) equipped with imaging sensors, can be deployed routinely to monitor segregating plant population interactions with the environment under biologically meaningful conditions. Here, flowering dates and plant height, important phenological fitness traits, were collected on 520 segregating maize recombinant inbred lines (RILs) in both irrigated and drought stress trials in 2018. Using UAV phenomic, single nucleotide polymorphism (SNP) genomic, as well as combined data, flowering times were predicted using several scenarios. Untested genotypes were predicted with 0.58, 0.59, and 0.41 prediction ability for anthesis, silking, and terminal plant height, respectively, using genomic data, but prediction ability increased to 0.77, 0.76, and 0.58 when phenomic and genomic data were used together. Using the phenomic data in a genome-wide association study, a heat-related candidate gene (GRMZM2G083810; hsp18f) was discovered using temporal reflectance phenotypes belonging to flowering times (both irrigated and drought) trials where heat stress also peaked. Thus, a relationship between plants and abiotic stresses belonging to a specific time of growth was revealed only through use of temporal phenomic data. Overall, this study showed that (i) it is possible to predict complex traits using high dimensional phenomic data between different environments, and (ii) temporal phenomic data can reveal a time-dependent association between genotypes and abiotic stresses, which can help understand mechanisms to develop resilient plants.
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Affiliation(s)
- Alper Adak
- Department of Soil and Crop Sciences, Texas A&M University, College Station, TX 77843-2474, USA
| | - Myeongjong Kang
- Department of Statistics, Texas A&M University, College Station, TX 77843, USA
| | | | - Seth C Murray
- Department of Soil and Crop Sciences, Texas A&M University, College Station, TX 77843-2474, USA
| | - Diego Jarquin
- Agronomy Department, University of Florida, Gainesville, FL 32611, USA
| | - Raymond K W Wong
- Department of Statistics, Texas A&M University, College Station, TX 77843, USA
| | - Matthias Katzfuß
- Department of Statistics, Texas A&M University, College Station, TX 77843, USA
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6
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Halladakeri P, Gudi S, Akhtar S, Singh G, Saini DK, Hilli HJ, Sakure A, Macwana S, Mir RR. Meta-analysis of the quantitative trait loci associated with agronomic traits, fertility restoration, disease resistance, and seed quality traits in pigeonpea (Cajanus cajan L.). THE PLANT GENOME 2023; 16:e20342. [PMID: 37328945 DOI: 10.1002/tpg2.20342] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Revised: 03/25/2023] [Accepted: 03/28/2023] [Indexed: 06/18/2023]
Abstract
A meta-analysis of quantitative trait loci (QTLs), associated with agronomic traits, fertility restoration, disease resistance, and seed quality traits was conducted for the first time in pigeonpea (Cajanus cajan L.). Data on 498 QTLs was collected from 9 linkage mapping studies (involving 21 biparental populations). Of these 498, 203 QTLs were projected onto "PigeonPea_ConsensusMap_2022," saturated with 10,522 markers, which resulted in the prediction of 34 meta-QTLs (MQTLs). The average confidence interval (CI) of these MQTLs (2.54 cM) was 3.37 times lower than the CI of the initial QTLs (8.56 cM). Of the 34 MQTLs, 12 high-confidence MQTLs with CI (≤5 cM) and a greater number of initial QTLs (≥5) were utilized to extract 2255 gene models, of which 105 were believed to be associated with different traits under study. Furthermore, eight of these MQTLs were observed to overlap with several marker-trait associations or significant SNPs identified in previous genome-wide association studies. Furthermore, synteny and ortho-MQTL analyses among pigeonpea and four related legumes crops, such as chickpea, pea, cowpea, and French bean, led to the identification of 117 orthologous genes from 20 MQTL regions. Markers associated with MQTLs can be employed for MQTL-assisted breeding as well as to improve the prediction accuracy of genomic selection in pigeonpea. Additionally, MQTLs may be subjected to fine mapping, and some of the promising candidate genes may serve as potential targets for positional cloning and functional analysis to elucidate the molecular mechanisms underlying the target traits.
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Affiliation(s)
- Priyanka Halladakeri
- Department of Genetics and Plant Breeding, Anand Agricultural University, Gujarat, India
| | - Santosh Gudi
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Sabina Akhtar
- College of Education, American University in the Emirates, Dubai, UAE
| | - Gurjeet Singh
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Dinesh Kumar Saini
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Harshavardan J Hilli
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Amar Sakure
- Department of Agricultural Biotechnology, Anand Agricultural University, Gujarat, India
| | - Sneha Macwana
- Department of Genetics and Plant Breeding, Anand Agricultural University, Gujarat, India
| | - Reyazul Rouf Mir
- Division of Genetics and Plant Breeding, Faculty of Agriculture, SKUAST-Kashmir, Wadura, India
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7
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Choquette NE, Weldekidan T, Brewer J, Davis SB, Wisser RJ, Holland JB. Enhancing adaptation of tropical maize to temperate environments using genomic selection. G3 (BETHESDA, MD.) 2023; 13:jkad141. [PMID: 37368984 PMCID: PMC10468305 DOI: 10.1093/g3journal/jkad141] [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: 03/02/2023] [Revised: 05/28/2023] [Accepted: 06/14/2023] [Indexed: 06/29/2023]
Abstract
Tropical maize can be used to diversify the genetic base of temperate germplasm and help create climate-adapted cultivars. However, tropical maize is unadapted to temperate environments, in which sensitivities to long photoperiods and cooler temperatures result in severely delayed flowering times, developmental defects, and little to no yield. Overcoming this maladaptive syndrome can require a decade of phenotypic selection in a targeted, temperate environment. To accelerate the incorporation of tropical diversity in temperate breeding pools, we tested if an additional generation of genomic selection can be used in an off-season nursery where phenotypic selection is not very effective. Prediction models were trained using flowering time recorded on random individuals in separate lineages of a heterogenous population grown at two northern U.S. latitudes. Direct phenotypic selection and genomic prediction model training was performed within each target environment and lineage, followed by genomic prediction of random intermated progenies in the off-season nursery. Performance of genomic prediction models was evaluated on self-fertilized progenies of prediction candidates grown in both target locations in the following summer season. Prediction abilities ranged from 0.30 to 0.40 among populations and evaluation environments. Prediction models with varying marker effect distributions or spatial field effects had similar accuracies. Our results suggest that genomic selection in a single off-season generation could increase genetic gains for flowering time by more than 50% compared to direct selection in summer seasons only, reducing the time required to change the population mean to an acceptably adapted flowering time by about one-third to one-half.
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Affiliation(s)
- Nicole E Choquette
- Department of Crop and Soil Sciences, North Carolina State University, Raleigh, NC 27695, USA
| | | | - Jason Brewer
- USDA-ARS Plant Science Research Unit, Raleigh, NC 27695, USA
| | - Scott B Davis
- Department of Plant and Soil Sciences, University of Delaware, Newark, DE 19716, USA
| | - Randall J Wisser
- Department of Plant and Soil Sciences, University of Delaware, Newark, DE 19716, USA
- Laboratoire d’Ecophysiologie des Plantes sous Stress Environmentaux, INRAE, University of Montpellier, L’Institut Agro, Montpellier, FR 34000, USA
| | - James B Holland
- Department of Crop and Soil Sciences, North Carolina State University, Raleigh, NC 27695, USA
- USDA-ARS Plant Science Research Unit, Raleigh, NC 27695, USA
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8
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Sethi M, Saini DK, Devi V, Kaur C, Singh MP, Singh J, Pruthi G, Kaur A, Singh A, Chaudhary DP. Unravelling the genetic framework associated with grain quality and yield-related traits in maize ( Zea mays L.). Front Genet 2023; 14:1248697. [PMID: 37609038 PMCID: PMC10440565 DOI: 10.3389/fgene.2023.1248697] [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: 06/27/2023] [Accepted: 07/26/2023] [Indexed: 08/24/2023] Open
Abstract
Maize serves as a crucial nutrient reservoir for a significant portion of the global population. However, to effectively address the growing world population's hidden hunger, it is essential to focus on two key aspects: biofortification of maize and improving its yield potential through advanced breeding techniques. Moreover, the coordination of multiple targets within a single breeding program poses a complex challenge. This study compiled mapping studies conducted over the past decade, identifying quantitative trait loci associated with grain quality and yield related traits in maize. Meta-QTL analysis of 2,974 QTLs for 169 component traits (associated with quality and yield related traits) revealed 68 MQTLs across different genetic backgrounds and environments. Most of these MQTLs were further validated using the data from genome-wide association studies (GWAS). Further, ten MQTLs, referred to as breeding-friendly MQTLs (BF-MQTLs), with a significant phenotypic variation explained over 10% and confidence interval less than 2 Mb, were shortlisted. BF-MQTLs were further used to identify potential candidate genes, including 59 genes encoding important proteins/products involved in essential metabolic pathways. Five BF-MQTLs associated with both quality and yield traits were also recommended to be utilized in future breeding programs. Synteny analysis with wheat and rice genomes revealed conserved regions across the genomes, indicating these hotspot regions as validated targets for developing biofortified, high-yielding maize varieties in future breeding programs. After validation, the identified candidate genes can also be utilized to effectively model the plant architecture and enhance desirable quality traits through various approaches such as marker-assisted breeding, genetic engineering, and genome editing.
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Affiliation(s)
- Mehak Sethi
- Division of Biochemistry, Indian Institute of Maize Research, Ludhiana, Punjab, India
| | - Dinesh Kumar Saini
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Veena Devi
- Division of Biochemistry, Indian Institute of Maize Research, Ludhiana, Punjab, India
| | - Charanjeet Kaur
- Department of Basic Sciences and Humanities, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Mohini Prabha Singh
- Department of Floriculture and Landscaping, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Jasneet Singh
- Agricultural and Environmental Sciences, Macdonald Campus, McGill University, Montreal, QC, Canada
| | - Gomsie Pruthi
- Department of Biotechnology, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Amanpreet Kaur
- Division of Biochemistry, Indian Institute of Maize Research, Ludhiana, Punjab, India
| | - Alla Singh
- Division of Biochemistry, Indian Institute of Maize Research, Ludhiana, Punjab, India
| | - Dharam Paul Chaudhary
- Division of Biochemistry, Indian Institute of Maize Research, Ludhiana, Punjab, India
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9
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Baisakh N, Da Silva EA, Pradhan AK, Rajasekaran K. Comprehensive meta-analysis of QTL and gene expression studies identify candidate genes associated with Aspergillus flavus resistance in maize. FRONTIERS IN PLANT SCIENCE 2023; 14:1214907. [PMID: 37534296 PMCID: PMC10392829 DOI: 10.3389/fpls.2023.1214907] [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: 04/30/2023] [Accepted: 06/26/2023] [Indexed: 08/04/2023]
Abstract
Aflatoxin (AF) contamination, caused by Aspergillus flavus, compromises the food safety and marketability of commodities, such as maize, cotton, peanuts, and tree nuts. Multigenic inheritance of AF resistance impedes conventional introgression of resistance traits into high-yielding commercial maize varieties. Several AF resistance-associated quantitative trait loci (QTLs) and markers have been reported from multiple biparental mapping and genome-wide association studies (GWAS) in maize. However, QTLs with large confidence intervals (CI) explaining inconsistent phenotypic variance limit their use in marker-assisted selection. Meta-analysis of published QTLs can identify significant meta-QTLs (MQTLs) with a narrower CI for reliable identification of genes and linked markers for AF resistance. Using 276 out of 356 reported QTLs controlling resistance to A. flavus infection and AF contamination in maize, we identified 58 MQTLs on all 10 chromosomes with a 66.5% reduction in the average CI. Similarly, a meta-analysis of maize genes differentially expressed in response to (a)biotic stresses from the to-date published literature identified 591 genes putatively responding to only A. flavus infection, of which 14 were significantly differentially expressed (-1.0 ≤ Log2Fc ≥ 1.0; p ≤ 0.05). Eight MQTLs were validated by their colocalization with 14 A. flavus resistance-associated SNPs identified from GWAS in maize. A total of 15 genes were physically close between the MQTL intervals and SNPs. Assessment of 12 MQTL-linked SSR markers identified three markers that could discriminate 14 and eight cultivars with resistance and susceptible responses, respectively. A comprehensive meta-analysis of QTLs and differentially expressed genes led to the identification of genes and makers for their potential application in marker-assisted breeding of A. flavus-resistant maize varieties.
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Affiliation(s)
- Niranjan Baisakh
- School of Plant, Environmental and Soil Sciences, Louisiana State University Agricultural Center, Baton Rouge, LA, United States
| | - Eduardo A. Da Silva
- School of Plant, Environmental and Soil Sciences, Louisiana State University Agricultural Center, Baton Rouge, LA, United States
- Department of Agriculture, Federal University of Lavras, Lavras, Brazil
| | - Anjan K. Pradhan
- School of Plant, Environmental and Soil Sciences, Louisiana State University Agricultural Center, Baton Rouge, LA, United States
| | - Kanniah Rajasekaran
- Food and Feed Safety Research Unit, Southern Regional Research Center, United States Department of Agriculture - Agricultural Research Service (USDA-ARS), New Orleans, LA, United States
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10
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Taranto F, Esposito S, De Vita P. Genomics for Yield and Yield Components in Durum Wheat. PLANTS (BASEL, SWITZERLAND) 2023; 12:2571. [PMID: 37447132 DOI: 10.3390/plants12132571] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Revised: 06/29/2023] [Accepted: 07/04/2023] [Indexed: 07/15/2023]
Abstract
In recent years, many efforts have been conducted to dissect the genetic basis of yield and yield components in durum wheat thanks to linkage mapping and genome-wide association studies. In this review, starting from the analysis of the genetic bases that regulate the expression of yield for developing new durum wheat varieties, we have highlighted how, currently, the reductionist approach, i.e., dissecting the yield into its individual components, does not seem capable of ensuring significant yield increases due to diminishing resources, land loss, and ongoing climate change. However, despite the identification of genes and/or chromosomal regions, controlling the grain yield in durum wheat is still a challenge, mainly due to the polyploidy level of this species. In the review, we underline that the next-generation sequencing (NGS) technologies coupled with improved wheat genome assembly and high-throughput genotyping platforms, as well as genome editing technology, will revolutionize plant breeding by providing a great opportunity to capture genetic variation that can be used in breeding programs. To date, genomic selection provides a valuable tool for modeling optimal allelic combinations across the whole genome that maximize the phenotypic potential of an individual under a given environment.
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Affiliation(s)
- Francesca Taranto
- Institute of Biosciences and Bioresources (CNR-IBBR), 70126 Bari, Italy
| | - Salvatore Esposito
- Research Centre for Cereal and Industrial Crops (CREA-CI), CREA-Council for Agricultural Research and Economics, 71122 Foggia, Italy
| | - Pasquale De Vita
- Research Centre for Cereal and Industrial Crops (CREA-CI), CREA-Council for Agricultural Research and Economics, 71122 Foggia, Italy
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11
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Bilgrami S, Darzi Ramandi H, Farokhzadeh S, Rousseau-Gueutin M, Sobhani Najafabadi A, Ghaderian M, Huang P, Liu L. Meta-analysis of seed weight QTLome using a consensus and highly dense genetic map in Brassica napus L. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:161. [PMID: 37354229 DOI: 10.1007/s00122-023-04401-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 06/02/2023] [Indexed: 06/26/2023]
Abstract
KEY MESSAGE We report here the discovery of high-confidence MQTL regions and of putative candidate genes associated with seed weight in B. napus using a highly dense consensus genetic map and by comparing various large-scale multiomics datasets. Seed weight (SW) is a direct determinant of seed yield in Brassica napus and is controlled by many loci. To unravel the main genomic regions associated with this complex trait, we used 13 available genetic maps to construct a consensus and highly dense map, comprising 40,401 polymorphic markers and 9191 genetic bins, harboring a cumulative length of 3047.8 cM. Then, we performed a meta-analysis using 639 projected SW quantitative trait loci (QTLs) obtained from studies conducted since 1999, enabling the identification of 57 meta-QTLS (MQTLs). The confidence intervals of our MQTLs were 9.8 and 4.3 times lower than the average CIs of the original QTLs for the A and C subgenomes, respectively, resulting in the detection of some key genes and several putative novel candidate genes associated with SW. By comparing the genes identified in MQTL intervals with multiomics datasets and coexpression analyses of common genes, we defined a more reliable and shorter list of putative candidate genes potentially involved in the regulation of seed maturation and SW. As an example, we provide a list of promising genes with high expression levels in seeds and embryos (e.g., BnaA03g04230D, BnaC03g08840D, BnaA10g29580D and BnaA03g27410D) that can be more finely studied through functional genetics experiments or that may be useful for MQTL-assisted breeding for SW. The high-density genetic consensus map and the single nucleotide polymorphism (SNP) physical map generated from the latest B. napus cv. Darmor-bzh v10 assembly will be a valuable resource for further mapping and map-based cloning of other important traits.
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Affiliation(s)
- Sayedehsaba Bilgrami
- College of Agronomy and Biotechnology, Southwest University, Beibei, Chongqing, 400715, China
| | - Hadi Darzi Ramandi
- Department of Agronomy and Plant Breeding, Faculty of Agriculture, Bu-Ali Sina University, Hamedan, Iran
| | - Sara Farokhzadeh
- Department of Plant Production, College of Agriculture and Natural Resources of Darab, Shiraz University, Darab, Iran
| | | | - Ahmad Sobhani Najafabadi
- Department of Biotechnology, Agricultural Biotechnology Research Institute of Iran - Isfahan Branch, Agricultural Research, Education and Extension Organization (AREEO), Isfahan, Iran
| | - Mostafa Ghaderian
- Division of Biostatistics and Bioinformatics, Department of Environmental and Public Health Sciences, University of Cincinnati, Cincinnati, OH, 45220, USA
| | - Pu Huang
- College of Agronomy and Biotechnology, Southwest University, Beibei, Chongqing, 400715, China
| | - Liezhao Liu
- College of Agronomy and Biotechnology, Southwest University, Beibei, Chongqing, 400715, China.
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12
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Li N, Miao Y, Ma J, Zhang P, Chen T, Liu Y, Che Z, Shahinnia F, Yang D. Consensus genomic regions for grain quality traits in wheat revealed by Meta-QTL analysis and in silico transcriptome integration. THE PLANT GENOME 2023:e20336. [PMID: 37144681 DOI: 10.1002/tpg2.20336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 03/08/2023] [Accepted: 03/13/2023] [Indexed: 05/06/2023]
Abstract
Grain quality traits are the key factors that determine the economic value of wheat and are largely influenced by genetics and the environment. In this study, using a meta-analysis of quantitative trait loci (QTLs) and a comprehensive in silico transcriptome assessment, we identified key genomic regions and putative candidate genes for the grain quality traits protein content, gluten content, and test weight. A total of 508 original QTLs were collected from 41 articles on QTL mapping for the three quality traits in wheat published from 2003 to 2021. When these original QTLs were projected onto a high-density consensus map consisting of 14,548 markers, 313 QTLs resulted in the identification of 64 MQTLs distributed across 17 of the 21 chromosomes. Most of the meta-QTLs (MQTLs) were distributed on sub-genomes A and B. Compared with the original QTLs, the confidence interval (CI) of the MQTLs was smaller, with an average CI of 4.47 cM, while the projected QTLs CI was 11.13 cM (2.49-fold lower). The corresponding physical length of the MQTL ranged from 0.45 to 239.01 Mb. Thirty-one of these 64 MQTLs were validated in at least one genome-wide association study. In addition, five of the 64 MQTLs were selected and designated as core MQTLs. The 211 quality-related genes from rice were used to identify wheat homologs in MQTLs. In combination with transcriptional and omics analyses, 135 putative candidate genes were identified from 64 MQTL regions. The findings should contribute to a better understanding of the molecular genetic mechanisms underlying grain quality and the improvement of these traits in wheat breeding.
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Affiliation(s)
- Na Li
- State Key Laboratory of Aridland Crop Science, Gansu, China
- College of Life Science and Technology, Gansu Agricultural University, Gansu, China
| | - Yongping Miao
- State Key Laboratory of Aridland Crop Science, Gansu, China
- College of Life Science and Technology, Gansu Agricultural University, Gansu, China
| | - Jingfu Ma
- State Key Laboratory of Aridland Crop Science, Gansu, China
- College of Life Science and Technology, Gansu Agricultural University, Gansu, China
| | - Peipei Zhang
- State Key Laboratory of Aridland Crop Science, Gansu, China
| | - Tao Chen
- State Key Laboratory of Aridland Crop Science, Gansu, China
- College of Life Science and Technology, Gansu Agricultural University, Gansu, China
| | - Yuan Liu
- State Key Laboratory of Aridland Crop Science, Gansu, China
- College of Life Science and Technology, Gansu Agricultural University, Gansu, China
| | - Zhuo Che
- Plant Seed Master Station of Gansu Province, Gansu, China
| | - Fahimeh Shahinnia
- Institute for Crop Science and Plant Breeding, Bavarian State Research Centre for Agriculture, Freising, Germany
| | - Delong Yang
- State Key Laboratory of Aridland Crop Science, Gansu, China
- College of Life Science and Technology, Gansu Agricultural University, Gansu, China
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13
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Shikha K, Madhumal Thayil V, Shahi JP, Zaidi PH, Seetharam K, Nair SK, Singh R, Tosh G, Singamsetti A, Singh S, Sinha B. Genomic-regions associated with cold stress tolerance in Asia-adapted tropical maize germplasm. Sci Rep 2023; 13:6297. [PMID: 37072497 PMCID: PMC10113201 DOI: 10.1038/s41598-023-33250-8] [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: 11/24/2022] [Accepted: 04/10/2023] [Indexed: 05/03/2023] Open
Abstract
Maize is gaining impetus in non-traditional and non-conventional seasons such as off-season, primarily due to higher demand and economic returns. Maize varieties directed for growing in the winter season of South Asia must have cold resilience as an important trait due to the low prevailing temperatures and frequent cold snaps observed during this season in most parts of the lowland tropics of Asia. The current study involved screening of a panel of advanced tropically adapted maize lines to cold stress during vegetative and flowering stage under field conditions. A suite of significant genomic loci (28) associated with grain yield along and agronomic traits such as flowering (15) and plant height (6) under cold stress environments. The haplotype regression revealed 6 significant haplotype blocks for grain yield under cold stress across the test environments. Haplotype blocks particularly on chromosomes 5 (bin5.07), 6 (bin6.02), and 9 (9.03) co-located to regions/bins that have been identified to contain candidate genes involved in membrane transport system that would provide essential tolerance to the plant. The regions on chromosome 1 (bin1.04), 2 (bin 2.07), 3 (bin 3.05-3.06), 5 (bin5.03), 8 (bin8.05-8.06) also harboured significant SNPs for the other agronomic traits. In addition, the study also looked at the plausibility of identifying tropically adapted maize lines from the working germplasm with cold resilience across growth stages and identified four lines that could be used as breeding starts in the tropical maize breeding pipelines.
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Affiliation(s)
- Kumari Shikha
- Department of Genetics and Plant Breeding, Banaras Hindu University (BHU), Varanasi, India
| | - Vinayan Madhumal Thayil
- International Maize and Wheat Improvement Centre (CIMMYT), ICRISAT Campus, Patancheru, Telangana, India.
| | - J P Shahi
- Department of Genetics and Plant Breeding, Banaras Hindu University (BHU), Varanasi, India
| | - P H Zaidi
- International Maize and Wheat Improvement Centre (CIMMYT), ICRISAT Campus, Patancheru, Telangana, India
| | - Kaliyamoorthy Seetharam
- International Maize and Wheat Improvement Centre (CIMMYT), ICRISAT Campus, Patancheru, Telangana, India
| | - Sudha K Nair
- International Maize and Wheat Improvement Centre (CIMMYT), ICRISAT Campus, Patancheru, Telangana, India
| | - Raju Singh
- Borlaug Institute for South Asia (BISA), Ludhiana, Punjab, India
| | - Garg Tosh
- Punjab Agricultural University (PAU), Ludhiana, India
| | - Ashok Singamsetti
- Department of Genetics and Plant Breeding, Banaras Hindu University (BHU), Varanasi, India
| | - Saurabh Singh
- Department of Genetics and Plant Breeding, Banaras Hindu University (BHU), Varanasi, India
| | - B Sinha
- Department of Genetics and Plant Breeding, Banaras Hindu University (BHU), Varanasi, India
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14
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Yannam VRR, Lopes M, Guzman C, Soriano JM. Uncovering the genetic basis for quality traits in the Mediterranean old wheat germplasm and phenotypic and genomic prediction assessment by cross-validation test. FRONTIERS IN PLANT SCIENCE 2023; 14:1127357. [PMID: 36778676 PMCID: PMC9911887 DOI: 10.3389/fpls.2023.1127357] [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: 12/19/2022] [Accepted: 01/16/2023] [Indexed: 06/18/2023]
Abstract
The release of new wheat varieties is based on two main characteristics, grain yield and quality, to meet the consumer's demand. Identifying the genetic architecture for yield and key quality traits has wide attention for genetic improvement to meet the global requirement. In this sense, the use of landraces represents an impressive source of natural allelic variation. In this study, a genome-wide association analysis (GWAS) with PCA and kinship matrix was performed to detect QTLs in bread wheat for fifteen quality and agronomic traits using 170 diverse landraces from 24 Mediterranean countries in two years of field trials. A total of 53 QTL hotspots containing 165 significant marker-trait associations (MTAs) were located across the genome for quality and agronomical traits except for chromosome 2D. The major specific QTL hotspots for quality traits were QTL_3B.3 (13 MTAs with a mean PVE of 8.2%) and QTL_4A.3 (15 MTAs, mean PVE of 11.0%), and for yield-related traits were QTL_2B.1 (8 MTAs, mean PVE of 7.4%) and QTL_4B.2 (5 MTAs, mean PVE of 10.0%). A search for candidate genes (CG) identified 807 gene models within the QTL hotspots. Ten of these CGs were expressed specifically in grain supporting the role of identified QTLs in Landraces, associated to bread wheat quality traits and grain formation. A cross-validation approach within the collection was performed to calculate the accuracies of genomic prediction for quality and agronomical traits, ranging from -0.03 to 0.64 for quality and 0.46 to 0.65 for agronomic traits. In addition, five prediction equations using the phenotypic data were developed to predict bread loaf volume in landraces. The prediction ability varied from 0.67 to 0.82 depending on the complexity of the traits considered to predict loaf volume.
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Affiliation(s)
- Venkata Rami Reddy Yannam
- Sustainable Field Crops Program, Institute for Food and Agricultural Research and Technology (IRTA), Lleida, Spain
| | - Marta Lopes
- Sustainable Field Crops Program, Institute for Food and Agricultural Research and Technology (IRTA), Lleida, Spain
| | - Carlos Guzman
- Departamento de Genética, Escuela Técnica Superior de Ingeniería Agronómica y de Montes, Universidad de Córdoba, Córdoba, Spain
| | - Jose Miguel Soriano
- Sustainable Field Crops Program, Institute for Food and Agricultural Research and Technology (IRTA), Lleida, Spain
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15
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Discovering Loci for Breeding Prospective and Phenology in Wheat Mediterranean Landraces by Environmental and eigenGWAS. Int J Mol Sci 2023; 24:ijms24021700. [PMID: 36675215 PMCID: PMC9863576 DOI: 10.3390/ijms24021700] [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: 11/30/2022] [Revised: 12/27/2022] [Accepted: 01/12/2023] [Indexed: 01/19/2023] Open
Abstract
Knowledge of the genetic basis of traits controlling phenology, differentiation patterns, and environmental adaptation is essential to develop new cultivars under climate change conditions. Landrace collections are an appropriate platform to study the hidden variation caused by crop breeding. The use of genome-wide association analysis for phenology, climatic data and differentiation among Mediterranean landraces led to the identification of 651 marker-trait associations that could be grouped in 46 QTL hotspots. A candidate gene analysis using the annotation of the genome sequence of the wheat cultivar 'Chinese Spring' detected 1097 gene models within 33 selected QTL hotspots. From all the gene models, 42 were shown to be differentially expressed (upregulated) under abiotic stress conditions, and 9 were selected based on their levels of expression. Different gene families previously reported for their involvement in different stress responses were found (protein kinases, ras-like GTP binding proteins and ethylene-responsive transcription factors). Finally, the synteny analysis in the QTL hotspots regions among the genomes of wheat and other cereal species identified 23, 21 and 7 ortho-QTLs for Brachypodium, rice and maize, respectively, confirming the importance of these loci.
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16
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Zhao Y, Zhao B, Xie Y, Jia H, Li Y, Xu M, Wu G, Ma X, Li Q, Hou M, Li C, Xia Z, He G, Xu H, Bai Z, Kong D, Zheng Z, Liu Q, Liu Y, Zhong J, Tian F, Wang B, Wang H. The evening complex promotes maize flowering and adaptation to temperate regions. THE PLANT CELL 2023; 35:369-389. [PMID: 36173348 PMCID: PMC9806612 DOI: 10.1093/plcell/koac296] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Accepted: 09/16/2022] [Indexed: 05/30/2023]
Abstract
Maize (Zea mays) originated in southern Mexico and has spread over a wide latitudinal range. Maize expansion from tropical to temperate regions has necessitated a reduction of its photoperiod sensitivity. In this study, we cloned a quantitative trait locus (QTL) regulating flowering time in maize and show that the maize ortholog of Arabidopsis thaliana EARLY FLOWERING3, ZmELF3.1, is the causal locus. We demonstrate that ZmELF3.1 and ZmELF3.2 proteins can physically interact with ZmELF4.1/4.2 and ZmLUX1/2, to form evening complex(es; ECs) in the maize circadian clock. Loss-of-function mutants for ZmELF3.1/3.2 and ZmLUX1/2 exhibited delayed flowering under long-day and short-day conditions. We show that EC directly represses the expression of several flowering suppressor genes, such as the CONSTANS, CONSTANS-LIKE, TOC1 (CCT) genes ZmCCT9 and ZmCCT10, ZmCONSTANS-LIKE 3, and the PSEUDORESPONSE REGULATOR (PRR) genes ZmPRR37a and ZmPRR73, thus alleviating their inhibition, allowing florigen gene expression and promoting flowering. Further, we identify two closely linked retrotransposons located in the ZmELF3.1 promoter that regulate the expression levels of ZmELF3.1 and may have been positively selected during postdomestication spread of maize from tropical to temperate regions during the pre-Columbian era. These findings provide insights into circadian clock-mediated regulation of photoperiodic flowering in maize and new targets of genetic improvement for breeding.
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Affiliation(s)
- Yongping Zhao
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Binbin Zhao
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Yurong Xie
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
- HainanYazhou Bay Seed Lab, Sanya, 572025, China
| | - Hong Jia
- Department of Plant Genetics and Breeding, State Key Laboratory of Agrobiotechnology and National Maize Improvement Center, China Agricultural University, Beijing, 100193, China
| | - Yongxiang Li
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, 10008, China
| | - Miaoyun Xu
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
- HainanYazhou Bay Seed Lab, Sanya, 572025, China
| | - Guangxia Wu
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Xiaojing Ma
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Quanquan Li
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Mei Hou
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Changyu Li
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Zhanchao Xia
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Gang He
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Hua Xu
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Zhijing Bai
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Dexin Kong
- School of Life Sciences, and State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangzhou, 510642, China
| | - Zhigang Zheng
- School of Life Sciences, and State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangzhou, 510642, China
| | - Qing Liu
- School of Life Sciences, and State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangzhou, 510642, China
| | - Yuting Liu
- School of Life Sciences, and State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangzhou, 510642, China
| | - Jinshun Zhong
- School of Life Sciences, and State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangzhou, 510642, China
| | - Feng Tian
- Department of Plant Genetics and Breeding, State Key Laboratory of Agrobiotechnology and National Maize Improvement Center, China Agricultural University, Beijing, 100193, China
| | - Baobao Wang
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
- HainanYazhou Bay Seed Lab, Sanya, 572025, China
| | - Haiyang Wang
- School of Life Sciences, and State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangzhou, 510642, China
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Arriagada O, Arévalo B, Cabeza RA, Carrasco B, Schwember AR. Meta-QTL Analysis for Yield Components in Common Bean ( Phaseolus vulgaris L.). PLANTS (BASEL, SWITZERLAND) 2022; 12:117. [PMID: 36616246 PMCID: PMC9824219 DOI: 10.3390/plants12010117] [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: 11/30/2022] [Revised: 12/15/2022] [Accepted: 12/17/2022] [Indexed: 06/17/2023]
Abstract
Common bean is one of the most important legumes produced and consumed worldwide because it is a highly valuable food for the human diet. However, its production is mainly carried out by small farmers, who obtain average grain yields below the potential yield of the species. In this sense, numerous mapping studies have been conducted to identify quantitative trait loci (QTL) associated with yield components in common bean. Meta-QTL (MQTL) analysis is a useful approach to combine data sets and for creating consensus positions for the QTL detected in independent studies. Consequently, the objective of this study was to perform a MQTL analysis to identify the most reliable and stable genomic regions associated with yield-related traits of common bean. A total of 667 QTL associated with yield-related traits reported in 21 different studies were collected. A total of 42 MQTL associated with yield-related traits were identified, in which the average confidence interval (CI) of the MQTL was 3.41 times lower than the CIs of the original QTL. Most of the MQTL (28) identified in this study contain QTL associated with yield and phenological traits; therefore, these MQTL can be useful in common bean breeding programs. Finally, a total of 18 candidate genes were identified and associated with grain yield within these MQTL, with functions related to ubiquitin ligase complex, response to auxin, and translation elongation factor activity.
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Affiliation(s)
- Osvin Arriagada
- Departamento de Ciencias Vegetales, Facultad de Agronomía e Ingeniería Forestal, Pontificia Universidad Católica de Chile, Santiago 7820436, Chile
| | - Bárbara Arévalo
- Centro de Estudios en Alimentos Procesados, Talca 3460000, Chile
| | - Ricardo A. Cabeza
- Departamento de Producción Agrícola, Facultad de Ciencias Agrarias, Universidad de Talca, Talca 3460000, Chile
| | - Basilio Carrasco
- Centro de Estudios en Alimentos Procesados, Talca 3460000, Chile
| | - Andrés R. Schwember
- Departamento de Ciencias Vegetales, Facultad de Agronomía e Ingeniería Forestal, Pontificia Universidad Católica de Chile, Santiago 7820436, Chile
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18
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Genetic structure and molecular mechanism underlying the stalk lodging traits in maize ( Zea mays L.). Comput Struct Biotechnol J 2022; 21:485-494. [PMID: 36618981 PMCID: PMC9803694 DOI: 10.1016/j.csbj.2022.12.037] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 12/03/2022] [Accepted: 12/20/2022] [Indexed: 12/24/2022] Open
Abstract
Stalk lodging seriously affects yield and quality of crops, and it can be caused by several factors, such as environments, developmental stages, and internal chemical components of plant stalks. Breeding of stalk lodging-resistant varieties is thus an important task for maize breeders. To better understand the genetic basis underlying stalk lodging resistance, several methods such as quantitative trait locus (QTL) mapping and genome-wide association study (GWAS) have been used to mine potential gene resources. Based on different types of genetic populations and mapping methods, many significant loci associated with stalk lodging resistance have been identified so far. However, few work has been performed to compare and integrate these reported genetic loci. In this study, we first collected hundreds of QTLs and quantitative trait nucleotides (QTNs) related to stalk lodging traits in maize. Then we mapped and integrated the QTLs and QTNs in maize genome to identify overlapped hotspot regions. Based on the genomic confidence intervals harboring these overlapped hotspot regions, we predicted candidate genes related to stalk lodging traits. Meanwhile, we mapped reported genes to these hotspot regions. Finally, we constructed molecular regulatory networks underlying stalk lodging resistance in maize. Collectively, this study provides not only useful genetic loci for deeply exploring molecular mechanisms of stalk lodging resistance traits, but also potential candidate genes and targeted strategies for improving stalk lodging resistance to increase crop yields in future.
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19
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Vidal A, Gauthier F, Rodrigez W, Guiglielmoni N, Leroux D, Chevrolier N, Jasson S, Tourrette E, Martin OC, Falque M. SeSAM: software for automatic construction of order-robust linkage maps. BMC Bioinformatics 2022; 23:499. [PMCID: PMC9675223 DOI: 10.1186/s12859-022-05045-7] [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: 08/03/2022] [Accepted: 11/08/2022] [Indexed: 11/21/2022] Open
Abstract
Background Genotyping and sequencing technologies produce increasingly large numbers of genetic markers with potentially high rates of missing or erroneous data. Therefore, the construction of linkage maps is more and more complex. Moreover, the size of segregating populations remains constrained by cost issues and is less and less commensurate with the numbers of SNPs available. Thus, guaranteeing a statistically robust marker order requires that maps include only a carefully selected subset of SNPs. Results In this context, the SeSAM software allows automatic genetic map construction using seriation and placement approaches, to produce (1) a high-robustness framework map which includes as many markers as possible while keeping the order robustness beyond a given statistical threshold, and (2) a high-density total map including the framework plus almost all polymorphic markers. During this process, care is taken to limit the impact of genotyping errors and of missing data on mapping quality. SeSAM can be used with a wide range of biparental populations including from outcrossing species for which phases are inferred on-the-fly by maximum-likelihood during map elongation. The package also includes functions to simulate data sets, convert data formats, detect putative genotyping errors, visualize data and map quality (including graphical genotypes), and merge several maps into a consensus. SeSAM is also suitable for interactive map construction, by providing lower-level functions for 2-point and multipoint EM analyses. The software is implemented in a R package including functions in C++. Conclusions SeSAM is a fully automatic linkage mapping software designed to (1) produce a framework map as robust as desired by optimizing the selection of a subset of markers, and (2) produce a high-density map including almost all polymorphic markers. The software can be used with a wide range of biparental mapping populations including cases from outcrossing. SeSAM is freely available under a GNU GPL v3 license and works on Linux, Windows, and macOS platforms. It can be downloaded together with its user-manual and quick-start tutorial from ForgeMIA (SeSAM project) at https://forgemia.inra.fr/gqe-acep/sesam/-/releases Supplementary Information The online version contains supplementary material available at 10.1186/s12859-022-05045-7.
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Affiliation(s)
- Adrien Vidal
- grid.460789.40000 0004 4910 6535Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE - Le Moulon, 91190 Gif-sur-Yvette, France
| | - Franck Gauthier
- grid.460789.40000 0004 4910 6535Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE - Le Moulon, 91190 Gif-sur-Yvette, France
| | - Willy Rodrigez
- grid.460789.40000 0004 4910 6535Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE - Le Moulon, 91190 Gif-sur-Yvette, France
| | - Nadège Guiglielmoni
- grid.460789.40000 0004 4910 6535Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE - Le Moulon, 91190 Gif-sur-Yvette, France
| | - Damien Leroux
- grid.507621.7INRAE, Unité de Mathématiques et Informatique Appliquées - Toulouse, Toulouse, France
| | - Nicolas Chevrolier
- grid.460789.40000 0004 4910 6535Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE - Le Moulon, 91190 Gif-sur-Yvette, France
| | - Sylvain Jasson
- grid.507621.7INRAE, Unité de Mathématiques et Informatique Appliquées - Toulouse, Toulouse, France
| | - Elise Tourrette
- grid.460789.40000 0004 4910 6535Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE - Le Moulon, 91190 Gif-sur-Yvette, France
| | - Olivier C. Martin
- grid.460789.40000 0004 4910 6535Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE - Le Moulon, 91190 Gif-sur-Yvette, France ,grid.503243.3Université Paris-Saclay, CNRS, INRAE, Université Evry, Institute of Plant Sciences Paris-Saclay (IPS2), 91190 Gif-sur-Yvette, France ,Université Paris Cité, CNRS, INRAE, Univ Evry, Institute of Plant Sciences Paris-Saclay (IPS2), 91190 Gif-sur-Yvette, France
| | - Matthieu Falque
- grid.460789.40000 0004 4910 6535Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE - Le Moulon, 91190 Gif-sur-Yvette, France
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20
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Aloryi KD, Okpala NE, Amo A, Bello SF, Akaba S, Tian X. A meta-quantitative trait loci analysis identified consensus genomic regions and candidate genes associated with grain yield in rice. FRONTIERS IN PLANT SCIENCE 2022; 13:1035851. [PMID: 36466247 PMCID: PMC9709451 DOI: 10.3389/fpls.2022.1035851] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/03/2022] [Accepted: 10/19/2022] [Indexed: 06/17/2023]
Abstract
Improving grain yield potential in rice is an important step toward addressing global food security challenges. The meta-QTL analysis offers stable and robust QTLs irrespective of the genetic background of mapping populations and phenotype environment and effectively narrows confidence intervals (CI) for candidate gene (CG) mining and marker-assisted selection improvement. To achieve these aims, a comprehensive bibliographic search for grain yield traits (spikelet fertility, number of grains per panicle, panicles number per plant, and 1000-grain weight) QTLs was conducted, and 462 QTLs were retrieved from 47 independent QTL research published between 2002 and 2022. QTL projection was performed using a reference map with a cumulative length of 2,945.67 cM, and MQTL analysis was conducted on 313 QTLs. Consequently, a total of 62 MQTLs were identified with reduced mean CI (up to 3.40 fold) compared to the mean CI of original QTLs. However, 10 of these MQTLs harbored at least six of the initial QTLs from diverse genetic backgrounds and environments and were considered the most stable and robust MQTLs. Also, MQTLs were compared with GWAS studies and resulted in the identification of 16 common significant loci modulating the evaluated traits. Gene annotation, gene ontology (GO) enrichment, and RNA-seq analyses of chromosome regions of the stable MQTLs detected 52 potential CGs including those that have been cloned in previous studies. These genes encode proteins known to be involved in regulating grain yield including cytochrome P450, zinc fingers, MADs-box, AP2/ERF domain, F-box, ubiquitin ligase domain protein, homeobox domain, DEAD-box ATP domain, and U-box domain. This study provides the framework for molecular dissection of grain yield in rice. Moreover, the MQTLs and CGs identified could be useful for fine mapping, gene cloning, and marker-assisted selection to improve rice productivity.
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Affiliation(s)
- Kelvin Dodzi Aloryi
- Hubei Collaborative Innovation Centre for Grain Industry, College of Agriculture, Yangtze University, Jingzhou, China
| | - Nnaemeka Emmanuel Okpala
- Hubei Collaborative Innovation Centre for Grain Industry, College of Agriculture, Yangtze University, Jingzhou, China
| | - Aduragbemi Amo
- Institute of Plant Breeding, Genetics and Genomics University of Georgia, Athens, GA, United States
| | - Semiu Folaniyi Bello
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou, Guangdong, China
| | - Selorm Akaba
- School of Agriculture, University of Cape Coast, Cape Coast, Ghana
| | - Xiaohai Tian
- Hubei Collaborative Innovation Centre for Grain Industry, College of Agriculture, Yangtze University, Jingzhou, China
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21
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Marcotuli I, Soriano JM, Gadaleta A. A consensus map for quality traits in durum wheat based on genome-wide association studies and detection of ortho-meta QTL across cereal species. Front Genet 2022; 13:982418. [PMID: 36110219 PMCID: PMC9468538 DOI: 10.3389/fgene.2022.982418] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 07/21/2022] [Indexed: 11/13/2022] Open
Abstract
The present work focused on the identification of durum wheat QTL hotspots from a collection of genome-wide association studies, for quality traits, such as grain protein content and composition, yellow color, fiber, grain microelement content (iron, magnesium, potassium, selenium, sulfur, calcium, cadmium), kernel vitreousness, semolina, and dough quality test. For the first time a total of 10 GWAS studies, comprising 395 marker-trait associations (MTA) on 57 quality traits, with more than 1,500 genotypes from 9 association panels, were used to investigate consensus QTL hotspots representative of a wide durum wheat genetic variation. MTA were found distributed on all the A and B genomes chromosomes with minimum number of MTA observed on chromosome 5B (15) and a maximum of 45 on chromosome 7A, with an average of 28 MTA per chromosome. The MTA were equally distributed on A (48%) and B (52%) genomes and allowed the identification of 94 QTL hotspots. Synteny maps for QTL were also performed in Zea mays, Brachypodium, and Oryza sativa, and candidate gene identification allowed the association of genes involved in biological processes playing a major role in the control of quality traits.
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Affiliation(s)
- Ilaria Marcotuli
- Department of Agricultural and Environmental Science, University of Bari Aldo Moro, Bari, Italy
- *Correspondence: Ilaria Marcotuli, ; Jose Miguel Soriano,
| | - Jose Miguel Soriano
- Sustainable Field Crops Programme, IRTA (Institute for Food and Agricultural Research and Technology), Lleida, Spain
- *Correspondence: Ilaria Marcotuli, ; Jose Miguel Soriano,
| | - Agata Gadaleta
- Department of Agricultural and Environmental Science, University of Bari Aldo Moro, Bari, Italy
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22
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Tanin MJ, Saini DK, Sandhu KS, Pal N, Gudi S, Chaudhary J, Sharma A. Consensus genomic regions associated with multiple abiotic stress tolerance in wheat and implications for wheat breeding. Sci Rep 2022; 12:13680. [PMID: 35953529 PMCID: PMC9372038 DOI: 10.1038/s41598-022-18149-0] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 08/05/2022] [Indexed: 12/03/2022] Open
Abstract
In wheat, a meta-analysis was performed using previously identified QTLs associated with drought stress (DS), heat stress (HS), salinity stress (SS), water-logging stress (WS), pre-harvest sprouting (PHS), and aluminium stress (AS) which predicted a total of 134 meta-QTLs (MQTLs) that involved at least 28 consistent and stable MQTLs conferring tolerance to five or all six abiotic stresses under study. Seventy-six MQTLs out of the 132 physically anchored MQTLs were also verified with genome-wide association studies. Around 43% of MQTLs had genetic and physical confidence intervals of less than 1 cM and 5 Mb, respectively. Consequently, 539 genes were identified in some selected MQTLs providing tolerance to 5 or all 6 abiotic stresses. Comparative analysis of genes underlying MQTLs with four RNA-seq based transcriptomic datasets unravelled a total of 189 differentially expressed genes which also included at least 11 most promising candidate genes common among different datasets. The promoter analysis showed that the promoters of these genes include many stress responsiveness cis-regulatory elements, such as ARE, MBS, TC-rich repeats, As-1 element, STRE, LTR, WRE3, and WUN-motif among others. Further, some MQTLs also overlapped with as many as 34 known abiotic stress tolerance genes. In addition, numerous ortho-MQTLs among the wheat, maize, and rice genomes were discovered. These findings could help with fine mapping and gene cloning, as well as marker-assisted breeding for multiple abiotic stress tolerances in wheat.
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Affiliation(s)
- Mohammad Jafar Tanin
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India.
| | - Dinesh Kumar Saini
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Karansher Singh Sandhu
- Department of Crop and Soil Sciences, Washington State University, Pullman, WA, 99163, USA
| | - Neeraj Pal
- Department of Molecular Biology and Genetic Engineering, G. B. Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, India
| | - Santosh Gudi
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Jyoti Chaudhary
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, Uttar Pradesh, India
| | - Achla Sharma
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
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23
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Tanin MJ, Saini DK, Sandhu KS, Pal N, Gudi S, Chaudhary J, Sharma A. Consensus genomic regions associated with multiple abiotic stress tolerance in wheat and implications for wheat breeding. Sci Rep 2022; 12:13680. [PMID: 35953529 DOI: 10.1101/2022.06.24.497482] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 08/05/2022] [Indexed: 05/20/2023] Open
Abstract
In wheat, a meta-analysis was performed using previously identified QTLs associated with drought stress (DS), heat stress (HS), salinity stress (SS), water-logging stress (WS), pre-harvest sprouting (PHS), and aluminium stress (AS) which predicted a total of 134 meta-QTLs (MQTLs) that involved at least 28 consistent and stable MQTLs conferring tolerance to five or all six abiotic stresses under study. Seventy-six MQTLs out of the 132 physically anchored MQTLs were also verified with genome-wide association studies. Around 43% of MQTLs had genetic and physical confidence intervals of less than 1 cM and 5 Mb, respectively. Consequently, 539 genes were identified in some selected MQTLs providing tolerance to 5 or all 6 abiotic stresses. Comparative analysis of genes underlying MQTLs with four RNA-seq based transcriptomic datasets unravelled a total of 189 differentially expressed genes which also included at least 11 most promising candidate genes common among different datasets. The promoter analysis showed that the promoters of these genes include many stress responsiveness cis-regulatory elements, such as ARE, MBS, TC-rich repeats, As-1 element, STRE, LTR, WRE3, and WUN-motif among others. Further, some MQTLs also overlapped with as many as 34 known abiotic stress tolerance genes. In addition, numerous ortho-MQTLs among the wheat, maize, and rice genomes were discovered. These findings could help with fine mapping and gene cloning, as well as marker-assisted breeding for multiple abiotic stress tolerances in wheat.
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Affiliation(s)
- Mohammad Jafar Tanin
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India.
| | - Dinesh Kumar Saini
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Karansher Singh Sandhu
- Department of Crop and Soil Sciences, Washington State University, Pullman, WA, 99163, USA
| | - Neeraj Pal
- Department of Molecular Biology and Genetic Engineering, G. B. Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, India
| | - Santosh Gudi
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Jyoti Chaudhary
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, Uttar Pradesh, India
| | - Achla Sharma
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
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Linkage Mapping Reveals QTL for Flowering Time-Related Traits under Multiple Abiotic Stress Conditions in Maize. Int J Mol Sci 2022; 23:ijms23158410. [PMID: 35955541 PMCID: PMC9368988 DOI: 10.3390/ijms23158410] [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: 07/05/2022] [Revised: 07/27/2022] [Accepted: 07/28/2022] [Indexed: 11/17/2022] Open
Abstract
Variation in flowering plays a major role in maize photoperiod adaptation during long-term domestication. It is of high value to investigate the genetic basis of maize flowering under a wide range of environmental conditions in order to overcome photoperiod sensitivity or enhance stress tolerance. A recombinant inbred line (RIL) population derived from a cross between Huangzaosi and Mo17, composed of 121 lines and genotyped by 8329 specifically developed markers, was field evaluated in two consecutive years under two planting densities (67,500 and 120,000 plants ha−1) and two water treatments (normal irrigation and drought stress at the flowering stage). The days to silking (DTS), days to anthesis (DTA), and anthesis to silking interval (ASI) were all evaluated. Within the RIL population, DTS and DTA expanded as planting density and water deficit increased. For DTA, DTS, ASI, and ASI-delay, a total of 22, 17, 21, and 11 QTLs were identified, respectively. More than two significant QTLs were identified in each of the nine chromosomal intervals. Under diverse conditions and locations, six QTLs (quantitative trait locus) for DTS and DTA were discovered in Chr. 8: 118.13–125.31 Mb. Three chromosome regions, Chr. 3: 196.14–199.89 Mb, Chr. 8: 169.02–172.46 Mb, and Chr. 9: 128.12–137.26 Mb, all had QTLs for ASI-delay under normal and stress conditions, suggesting their possible roles in stress tolerance enhancement. These QTL hotspots will promote early-maturing or multiple abiotic stress-tolerant maize breeding, as well as shed light on the development of maize varieties with a broad range of adaptations.
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25
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Wang W, Ren Z, Li L, Du Y, Zhou Y, Zhang M, Li Z, Yi F, Duan L. Meta-QTL analysis explores the key genes, especially hormone related genes, involved in the regulation of grain water content and grain dehydration rate in maize. BMC PLANT BIOLOGY 2022; 22:346. [PMID: 35842577 PMCID: PMC9287936 DOI: 10.1186/s12870-022-03738-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Accepted: 07/06/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Low grain water content (GWC) at harvest of maize (Zea mays L.) is essential for mechanical harvesting, transportation and storage. Grain drying rate (GDR) is a key determinant of GWC. Many quantitative trait locus (QTLs) related to GDR and GWC have been reported, however, the confidence interval (CI) of these QTLs are too large and few QTLs has been fine-mapped or even been cloned. Meta-QTL (MQTL) analysis is an effective method to integrate QTLs information in independent populations, which helps to understand the genetic structure of quantitative traits. RESULTS In this study, MQTL analysis was performed using 282 QTLs from 25 experiments related GDR and GWC. Totally, 11 and 34 MQTLs were found to be associated with GDR and GWC, respectively. The average CI of GDR and GWC MQTLs was 24.44 and 22.13 cM which reduced the 57 and 65% compared to the average QTL interval for initial GDR and GWC QTL, respectively. Finally, 1494 and 5011 candidate genes related to GDR and GWC were identified in MQTL intervals, respectively. Among these genes, there are 48 genes related to hormone metabolism. CONCLUSIONS Our studies combined traditional QTL analyses, genome-wide association study and RNA-seq to analysis major locus for regulating GWC in maize.
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Affiliation(s)
- Wei Wang
- State Key Laboratory of Plant Physiology and Biochemistry, Engineering Research Center of Plant Growth Regulator, Ministry of Education &College of Agronomy and Biotechnology, China Agricultural University, No.2 Yuanmingyuan West Road, Haidian, Beijing, 100193, China
| | - Zhaobin Ren
- State Key Laboratory of Plant Physiology and Biochemistry, Engineering Research Center of Plant Growth Regulator, Ministry of Education &College of Agronomy and Biotechnology, China Agricultural University, No.2 Yuanmingyuan West Road, Haidian, Beijing, 100193, China
| | - Lu Li
- State Key Laboratory of Plant Physiology and Biochemistry, Engineering Research Center of Plant Growth Regulator, Ministry of Education &College of Agronomy and Biotechnology, China Agricultural University, No.2 Yuanmingyuan West Road, Haidian, Beijing, 100193, China
| | - Yiping Du
- State Key Laboratory of Plant Physiology and Biochemistry, Engineering Research Center of Plant Growth Regulator, Ministry of Education &College of Agronomy and Biotechnology, China Agricultural University, No.2 Yuanmingyuan West Road, Haidian, Beijing, 100193, China
| | - Yuyi Zhou
- State Key Laboratory of Plant Physiology and Biochemistry, Engineering Research Center of Plant Growth Regulator, Ministry of Education &College of Agronomy and Biotechnology, China Agricultural University, No.2 Yuanmingyuan West Road, Haidian, Beijing, 100193, China
| | - Mingcai Zhang
- State Key Laboratory of Plant Physiology and Biochemistry, Engineering Research Center of Plant Growth Regulator, Ministry of Education &College of Agronomy and Biotechnology, China Agricultural University, No.2 Yuanmingyuan West Road, Haidian, Beijing, 100193, China
| | - Zhaohu Li
- State Key Laboratory of Plant Physiology and Biochemistry, Engineering Research Center of Plant Growth Regulator, Ministry of Education &College of Agronomy and Biotechnology, China Agricultural University, No.2 Yuanmingyuan West Road, Haidian, Beijing, 100193, China
| | - Fei Yi
- State Key Laboratory of Plant Physiology and Biochemistry, Engineering Research Center of Plant Growth Regulator, Ministry of Education &College of Agronomy and Biotechnology, China Agricultural University, No.2 Yuanmingyuan West Road, Haidian, Beijing, 100193, China.
| | - Liusheng Duan
- State Key Laboratory of Plant Physiology and Biochemistry, Engineering Research Center of Plant Growth Regulator, Ministry of Education &College of Agronomy and Biotechnology, China Agricultural University, No.2 Yuanmingyuan West Road, Haidian, Beijing, 100193, China
- College of Plant Science and Technology, Beijing University of Agriculture, Beijing, 102206, China
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26
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Pal N, Jan I, Saini DK, Kumar K, Kumar A, Sharma PK, Kumar S, Balyan HS, Gupta PK. Meta-QTLs for multiple disease resistance involving three rusts in common wheat (Triticum aestivum L.). TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2022; 135:2385-2405. [PMID: 35699741 DOI: 10.1007/s00122-022-04119-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Accepted: 04/28/2022] [Indexed: 05/20/2023]
Abstract
In wheat, multiple disease resistance meta-QTLs (MDR-MQTLs) and underlying candidate genes for the three rusts were identified which may prove useful for development of resistant cultivars. Rust diseases in wheat are a major threat to global food security. Therefore, development of multiple disease-resistant cultivars (resistant to all three rusts) is a major goal in all wheat breeding programs worldwide. In the present study, meta-QTLs and candidate genes for multiple disease resistance (MDR) involving all three rusts were identified using 152 individual QTL mapping studies for resistance to leaf rust (LR), stem rust (SR), and yellow rust (YR). From these 152 studies, a total of 1,146 QTLs for resistance to three rusts were retrieved, which included 368 QTLs for LR, 291 QTLs for SR, and 487 QTLs for YR. Of these 1,146 QTLs, only 718 QTLs could be projected onto the consensus map saturated with 2, 34,619 markers. Meta-analysis of the projected QTLs resulted in the identification of 86 MQTLs, which included 71 MDR-MQTLs. Ten of these MDR-MQTLs were referred to as the 'Breeders' MQTLs'. Seventy-eight of the 86 MQTLs could also be anchored to the physical map of the wheat genome, and 54 MQTLs were validated by marker-trait associations identified during earlier genome-wide association studies. Twenty MQTLs (including 17 MDR-MQTLs) identified in the present study were co-localized with 44 known R genes. In silico expression analysis allowed identification of several differentially expressed candidate genes (DECGs) encoding proteins carrying different domains including the following: NBS-LRR, WRKY domains, F-box domains, sugar transporters, transferases, etc. The introgression of these MDR loci into high-yielding cultivars should prove useful for developing high yielding cultivars with resistance to all the three rusts.
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Affiliation(s)
- Neeraj Pal
- Department of Molecular Biology and Genetic Engineering, G. B. Pant University of Agriculture and Technology, Pantnagar, Uttrakhand, 263145, India
| | - Irfat Jan
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004, India
| | - Dinesh Kumar Saini
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, 141004, India
| | - Kuldeep Kumar
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004, India
| | - Anuj Kumar
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004, India
| | - P K Sharma
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004, India
| | - Sundip Kumar
- Department of Molecular Biology and Genetic Engineering, G. B. Pant University of Agriculture and Technology, Pantnagar, Uttrakhand, 263145, India
| | - H S Balyan
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004, India
| | - P K Gupta
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004, India.
- Murdoch's Centre for Crop & Food Innovation, Murdoch University, Murdoch, Perth, WA 6150, Australia.
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27
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Chamberlain-Irwin HN, Hufford MB. Convergent domestication: Finding the genes that make crops. Curr Biol 2022; 32:R585-R588. [PMID: 35728534 DOI: 10.1016/j.cub.2022.05.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
A recent study shows that convergent selection of orthologs encoding a WD40 protein in maize and rice occurs during domestication. Knockout of these genes increases yield in both crops with no detectable effects on other agronomic traits. Identification of convergent selection can focus improvement efforts.
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Affiliation(s)
| | - Matthew B Hufford
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA, USA.
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28
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Sheoran S, Gupta M, Kumari S, Kumar S, Rakshit S. Meta-QTL analysis and candidate genes identification for various abiotic stresses in maize ( Zea mays L.) and their implications in breeding programs. MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2022; 42:26. [PMID: 37309532 PMCID: PMC10248626 DOI: 10.1007/s11032-022-01294-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Accepted: 03/26/2022] [Indexed: 06/14/2023]
Abstract
Global climate change leads to the concurrence of a number of abiotic stresses including moisture stress (drought, waterlogging), temperature stress (heat, cold), and salinity stress, which are the major factors affecting maize production. To develop abiotic stress tolerance in maize, many quantitative trait loci (QTL) have been identified, but very few of them have been utilized successfully in breeding programs. In this context, the meta-QTL analysis of the reported QTL will enable the identification of stable/real QTL which will pave a reliable way to introgress these QTL into elite cultivars through marker-assisted selection. In this study, a total of 542 QTL were summarized from 33 published studies for tolerance to different abiotic stresses in maize to conduct meta-QTL analysis using BiomercatorV4.2.3. Among those, only 244 major QTL with more than 10% phenotypic variance were preferably utilised to carry out meta-QTL analysis. In total, 32 meta-QTL possessing 1907 candidate genes were detected for different abiotic stresses over diverse genetic and environmental backgrounds. The MQTL2.1, 5.1, 5.2, 5.6, 7.1, 9.1, and 9.2 control different stress-related traits for combined abiotic stress tolerance. The candidate genes for important transcription factor families such as ERF, MYB, bZIP, bHLH, NAC, LRR, ZF, MAPK, HSP, peroxidase, and WRKY have been detected for different stress tolerances. The identified meta-QTL are valuable for future climate-resilient maize breeding programs and functional validation of candidate genes studies, which will help to deepen our understanding of the complexity of these abiotic stresses. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-022-01294-9.
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Affiliation(s)
- Seema Sheoran
- ICAR-Indian Institute of Maize Research, PAU Campus, Ludhiana, 141004 India
- Present Address: ICAR-Indian Agricultural Research Institute, Regional Station, Karnal, 132001 India
| | - Mamta Gupta
- ICAR-Indian Institute of Maize Research, PAU Campus, Ludhiana, 141004 India
| | - Shweta Kumari
- ICAR-Indian Agricultural Statistics Research Institute, New Delhi, 110012 India
| | - Sandeep Kumar
- Present Address: ICAR-Indian Agricultural Research Institute, Regional Station, Karnal, 132001 India
- ICAR-Indian Institute of Pulses Research, Regional Station, Phanda, Bhopal, 462030 India
| | - Sujay Rakshit
- ICAR-Indian Institute of Maize Research, PAU Campus, Ludhiana, 141004 India
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29
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Odell SG, Hudson AI, Praud S, Dubreuil P, Tixier MH, Ross-Ibarra J, Runcie DE. Modeling allelic diversity of multiparent mapping populations affects detection of quantitative trait loci. G3 (BETHESDA, MD.) 2022; 12:6509518. [PMID: 35100382 PMCID: PMC8895984 DOI: 10.1093/g3journal/jkac011] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Accepted: 10/27/2021] [Indexed: 12/02/2022]
Abstract
The search for quantitative trait loci that explain complex traits such as yield and drought tolerance has been ongoing in all crops. Methods such as biparental quantitative trait loci mapping and genome-wide association studies each have their own advantages and limitations. Multiparent advanced generation intercross populations contain more recombination events and genetic diversity than biparental mapping populations and are better able to estimate effect sizes of rare alleles than association mapping populations. Here, we discuss the results of using a multiparent advanced generation intercross population of doubled haploid maize lines created from 16 diverse founders to perform quantitative trait loci mapping. We compare 3 models that assume bi-allelic, founder, and ancestral haplotype allelic states for quantitative trait loci. The 3 methods have differing power to detect quantitative trait loci for a variety of agronomic traits. Although the founder approach finds the most quantitative trait loci, all methods are able to find unique quantitative trait loci, suggesting that each model has advantages for traits with different genetic architectures. A closer look at a well-characterized flowering time quantitative trait loci, qDTA8, which contains vgt1, highlights the strengths and weaknesses of each method and suggests a potential epistatic interaction. Overall, our results reinforce the importance of considering different approaches to analyzing genotypic datasets, and shows the limitations of binary SNP data for identifying multiallelic quantitative trait loci.
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Affiliation(s)
- Sarah G Odell
- Department of Plant Sciences, University of California, Davis, CA 95616, USA.,Department of Evolution and Ecology, University of California, Davis, CA 95616, USA
| | - Asher I Hudson
- Department of Evolution and Ecology, University of California, Davis, CA 95616, USA.,Center for Population Biology, University of California, Davis, CA 95616, USA
| | - Sébastien Praud
- Limagrain, Centre de Recherche de Chappes, Chappes 63720, France
| | - Pierre Dubreuil
- Limagrain, Centre de Recherche de Chappes, Chappes 63720, France
| | | | - Jeffrey Ross-Ibarra
- Department of Evolution and Ecology, University of California, Davis, CA 95616, USA.,Center for Population Biology, University of California, Davis, CA 95616, USA.,Genome Center, University of California, Davis, CA 95616, USA
| | - Daniel E Runcie
- Department of Plant Sciences, University of California, Davis, CA 95616, USA
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30
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Perez-Limón S, Li M, Cintora-Martinez GC, Aguilar-Rangel MR, Salazar-Vidal MN, González-Segovia E, Blöcher-Juárez K, Guerrero-Zavala A, Barrales-Gamez B, Carcaño-Macias J, Costich DE, Nieto-Sotelo J, Martinez de la Vega O, Simpson J, Hufford MB, Ross-Ibarra J, Flint-Garcia S, Diaz-Garcia L, Rellán-Álvarez R, Sawers RJH. A B73×Palomero Toluqueño mapping population reveals local adaptation in Mexican highland maize. G3 (BETHESDA, MD.) 2022; 12:jkab447. [PMID: 35100386 PMCID: PMC8896015 DOI: 10.1093/g3journal/jkab447] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Accepted: 12/16/2021] [Indexed: 01/31/2023]
Abstract
Generations of farmer selection in the central Mexican highlands have produced unique maize varieties adapted to the challenges of the local environment. In addition to possessing great agronomic and cultural value, Mexican highland maize represents a good system for the study of local adaptation and acquisition of adaptive phenotypes under cultivation. In this study, we characterize a recombinant inbred line population derived from the B73 reference line and the Mexican highland maize variety Palomero Toluqueño. B73 and Palomero Toluqueño showed classic rank-changing differences in performance between lowland and highland field sites, indicative of local adaptation. Quantitative trait mapping identified genomic regions linked to effects on yield components that were conditionally expressed depending on the environment. For the principal genomic regions associated with ear weight and total kernel number, the Palomero Toluqueño allele conferred an advantage specifically in the highland site, consistent with local adaptation. We identified Palomero Toluqueño alleles associated with expression of characteristic highland traits, including reduced tassel branching, increased sheath pigmentation and the presence of sheath macrohairs. The oligogenic architecture of these three morphological traits supports their role in adaptation, suggesting they have arisen from consistent directional selection acting at distinct points across the genome. We discuss these results in the context of the origin of phenotypic novelty during selection, commenting on the role of de novo mutation and the acquisition of adaptive variation by gene flow from endemic wild relatives.
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Affiliation(s)
- Sergio Perez-Limón
- Laboratorio Nacional de Genómica para la Biodiversidad/Unidad de Genómica Avanzada, Centro de Investigación y de Estudios Avanzados, Instituto Politécnico Nacional (CINVESTAV-IPN), Irapuato, Guanajuato 36821, México
- Department of Plant Science, The Pennsylvania State University, State College, PA 16802, USA
| | - Meng Li
- Department of Plant Science, The Pennsylvania State University, State College, PA 16802, USA
| | - G Carolina Cintora-Martinez
- Laboratorio Nacional de Genómica para la Biodiversidad/Unidad de Genómica Avanzada, Centro de Investigación y de Estudios Avanzados, Instituto Politécnico Nacional (CINVESTAV-IPN), Irapuato, Guanajuato 36821, México
| | - M Rocio Aguilar-Rangel
- Laboratorio Nacional de Genómica para la Biodiversidad/Unidad de Genómica Avanzada, Centro de Investigación y de Estudios Avanzados, Instituto Politécnico Nacional (CINVESTAV-IPN), Irapuato, Guanajuato 36821, México
| | - M Nancy Salazar-Vidal
- Laboratorio Nacional de Genómica para la Biodiversidad/Unidad de Genómica Avanzada, Centro de Investigación y de Estudios Avanzados, Instituto Politécnico Nacional (CINVESTAV-IPN), Irapuato, Guanajuato 36821, México
- Department of Evolution and Ecology, UC Davis, CA 95616 USA
| | - Eric González-Segovia
- Laboratorio Nacional de Genómica para la Biodiversidad/Unidad de Genómica Avanzada, Centro de Investigación y de Estudios Avanzados, Instituto Politécnico Nacional (CINVESTAV-IPN), Irapuato, Guanajuato 36821, México
- Department of Botany, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
| | - Karla Blöcher-Juárez
- Laboratorio Nacional de Genómica para la Biodiversidad/Unidad de Genómica Avanzada, Centro de Investigación y de Estudios Avanzados, Instituto Politécnico Nacional (CINVESTAV-IPN), Irapuato, Guanajuato 36821, México
| | - Alejandro Guerrero-Zavala
- Laboratorio Nacional de Genómica para la Biodiversidad/Unidad de Genómica Avanzada, Centro de Investigación y de Estudios Avanzados, Instituto Politécnico Nacional (CINVESTAV-IPN), Irapuato, Guanajuato 36821, México
| | - Benjamin Barrales-Gamez
- Laboratorio Nacional de Genómica para la Biodiversidad/Unidad de Genómica Avanzada, Centro de Investigación y de Estudios Avanzados, Instituto Politécnico Nacional (CINVESTAV-IPN), Irapuato, Guanajuato 36821, México
| | - Jessica Carcaño-Macias
- Laboratorio Nacional de Genómica para la Biodiversidad/Unidad de Genómica Avanzada, Centro de Investigación y de Estudios Avanzados, Instituto Politécnico Nacional (CINVESTAV-IPN), Irapuato, Guanajuato 36821, México
| | - Denise E Costich
- International Center for Maize and Wheat Improvement (CIMMyT), De México 56237, México
| | - Jorge Nieto-Sotelo
- Jardín Botánico, Instituto de Biología, Universidad Nacional Autónoma de México, Ciudad de México 04510, México
| | - Octavio Martinez de la Vega
- Laboratorio Nacional de Genómica para la Biodiversidad/Unidad de Genómica Avanzada, Centro de Investigación y de Estudios Avanzados, Instituto Politécnico Nacional (CINVESTAV-IPN), Irapuato, Guanajuato 36821, México
| | - June Simpson
- Laboratorio Nacional de Genómica para la Biodiversidad/Unidad de Genómica Avanzada, Centro de Investigación y de Estudios Avanzados, Instituto Politécnico Nacional (CINVESTAV-IPN), Irapuato, Guanajuato 36821, México
| | - Matthew B Hufford
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA
| | - Jeffrey Ross-Ibarra
- Department of Evolution and Ecology, UC Davis, CA 95616 USA
- Center for Population Biology, and Genome Center, UC Davis, Davis, CA 95616, USA
| | - Sherry Flint-Garcia
- U.S. Department of Agriculture, Agricultural Research Service Plant Genetics Research Unit, Columbia, MO 65211, USA
| | - Luis Diaz-Garcia
- Campo Experimental Pabellón-INIFAP. Carretera Aguascalientes-Zacatecas, Aguascalientes, CP 20660, México
| | - Rubén Rellán-Álvarez
- Laboratorio Nacional de Genómica para la Biodiversidad/Unidad de Genómica Avanzada, Centro de Investigación y de Estudios Avanzados, Instituto Politécnico Nacional (CINVESTAV-IPN), Irapuato, Guanajuato 36821, México
- Department of Molecular and Structural Biochemistry, North Carolina State University, Raleigh, NC 27695, USA
| | - Ruairidh J H Sawers
- Laboratorio Nacional de Genómica para la Biodiversidad/Unidad de Genómica Avanzada, Centro de Investigación y de Estudios Avanzados, Instituto Politécnico Nacional (CINVESTAV-IPN), Irapuato, Guanajuato 36821, México
- Department of Plant Science, The Pennsylvania State University, State College, PA 16802, USA
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31
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Amo A, Soriano JM. Unravelling consensus genomic regions conferring leaf rust resistance in wheat via meta-QTL analysis. THE PLANT GENOME 2022; 15:e20185. [PMID: 34918873 DOI: 10.1002/tpg2.20185] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Accepted: 11/12/2021] [Indexed: 06/14/2023]
Abstract
Leaf rust, caused by the fungus Puccinia triticina Erikss (Pt), is a destructive disease affecting wheat (Triticum aestivum L.) and a threat to food security. Developing resistant cultivars represents a useful method of disease control, and thus, understanding the genetic basis for leaf rust resistance is required. To this end, a comprehensive bibliographic search for leaf rust resistance quantitative trait loci (QTL) was performed, and 393 QTL were collected from 50 QTL mapping studies. Afterward, a consensus map with a total length of 4,567 cM consisting of different types of markers (simple sequence repeat [SSR], diversity arrays technology [DArT], chip-based single-nucleotide polymorphism [SNP] markers, and SNP markers from genotyping-by-sequencing) was used for QTL projection, and meta-QTL (MQTL) analysis was performed on 320 QTL. A total of 75 MQTL were discovered and refined to 15 high-confidence MQTL (hcmQTL). The candidate genes discovered within the hcmQTL interval were then checked for differential expression using data from three transcriptome studies, resulting in 92 differentially expressed genes (DEGs). The expression of these genes in various leaf tissues during wheat development was explored. This study provides insight into leaf rust resistance in wheat and thereby provides an avenue for developing resistant cultivars by incorporating the most important hcmQTL.
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Affiliation(s)
- Aduragbemi Amo
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F Univ., Yangling, Shaanxi, China
| | - Jose Miguel Soriano
- Sustainable Field Crops Programme, Institute for Food and Agricultural Research and Technology (IRTA), Lleida, 25198, Spain
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32
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Saini DK, Chahal A, Pal N, Srivastava P, Gupta PK. Meta-analysis reveals consensus genomic regions associated with multiple disease resistance in wheat ( Triticum aestivum L.). MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2022; 42:11. [PMID: 37309411 PMCID: PMC10248701 DOI: 10.1007/s11032-022-01282-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Accepted: 02/07/2022] [Indexed: 06/14/2023]
Abstract
In wheat, meta-QTLs (MQTLs) and candidate genes (CGs) were identified for multiple disease resistance (MDR). For this purpose, information was collected from 58 studies for mapping QTLs for resistance to one or more of the five diseases. As many as 493 QTLs were available from these studies, which were distributed in five diseases as follows: septoria tritici blotch (STB) 126 QTLs; septoria nodorum blotch (SNB), 103 QTLs; fusarium head blight (FHB), 184 QTLs; karnal bunt (KB), 66 QTLs; and loose smut (LS), 14 QTLs. Of these 493 QTLs, only 291 QTLs could be projected onto a consensus genetic map, giving 63 MQTLs. The CI of the MQTLs ranged from 0.04 to 15.31 cM with an average of 3.09 cM per MQTL. This is a ~ 4.39 fold reduction from the CI of QTLs, which ranged from 0 to 197.6 cM, with a mean of 13.57 cM. Of 63 MQTLs, 60 were anchored to the reference physical map of wheat (the physical interval of these MQTLs ranged from 0.30 to 726.01 Mb with an average of 74.09 Mb). Thirty-eight (38) of these MQTLs were verified using marker-trait associations (MTAs) derived from genome-wide association studies. As many as 874 CGs were also identified which were further investigated for differential expression using data from five transcriptome studies, resulting in 194 differentially expressed candidate genes (DECGs). Among the DECGs, 85 genes had functions previously reported to be associated with disease resistance. These results should prove useful for fine mapping and cloning of MDR genes and marker-assisted breeding. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-022-01282-z.
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Affiliation(s)
- Dinesh Kumar Saini
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab-141004 India
| | - Amneek Chahal
- College of Agriculture, Punjab Agricultural University, Ludhiana, Punjab-141004 India
| | - Neeraj Pal
- Department of Molecular Biology and Genetic Engineering, G. B. Pant, University of Agriculture and Technology, Pantnagar, Uttrakhand-263145 India
| | - Puja Srivastava
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab-141004 India
| | - Pushpendra Kumar Gupta
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004 India
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Carvalho RF, Aguiar-Perecin MLR, Clarindo WR, Fristche-Neto R, Mondin M. A Heterochromatic Knob Reducing the Flowering Time in Maize. Front Genet 2022; 12:799681. [PMID: 35280927 PMCID: PMC8908004 DOI: 10.3389/fgene.2021.799681] [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: 10/21/2021] [Accepted: 12/22/2021] [Indexed: 11/13/2022] Open
Abstract
Maize flowering time is an important agronomic trait, which has been associated with variations in the genome size and heterochromatic knobs content. We integrated three steps to show this association. Firstly, we selected inbred lines varying for heterochromatic knob composition at specific sites in the homozygous state. Then, we produced homozygous and heterozygous hybrids for knobs. Second, we measured the genome size and flowering time for all materials. Knob composition did not affect the genome size and flowering time. Finally, we developed an association study and identified a knob marker on chromosome 9 showing the strongest association with flowering time. Indeed, modelling allele substitution and dominance effects could offer only one heterochromatic knob locus that could affect flowering time, making it earlier rather than the knob composition.
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Affiliation(s)
- Renata Flávia Carvalho
- “Luiz de Queiroz” College of Agriculture, ESALQ, University of São Paulo, Piracicaba, Brazil
| | | | | | - Roberto Fristche-Neto
- “Luiz de Queiroz” College of Agriculture, ESALQ, University of São Paulo, Piracicaba, Brazil
- International Rice Research Institute (IRRI) - Breeding Analytics and Data, Management Unit, Laguna, Philippines
| | - Mateus Mondin
- “Luiz de Queiroz” College of Agriculture, ESALQ, University of São Paulo, Piracicaba, Brazil
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Daryani P, Darzi Ramandi H, Dezhsetan S, Mirdar Mansuri R, Hosseini Salekdeh G, Shobbar ZS. Pinpointing genomic regions associated with root system architecture in rice through an integrative meta-analysis approach. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2022; 135:81-106. [PMID: 34623472 DOI: 10.1007/s00122-021-03953-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Accepted: 09/20/2021] [Indexed: 06/13/2023]
Abstract
Applying an integrated meta-analysis approach led to identification of meta-QTLs/ candidate genes associated with rice root system architecture, which can be used in MQTL-assisted breeding/ genetic engineering of root traits. Root system architecture (RSA) is an important factor for facilitating water and nutrient uptake from deep soils and adaptation to drought stress conditions. In the present research, an integrated meta-analysis approach was employed to find candidate genes and genomic regions involved in rice RSA traits. A whole-genome meta-analysis was performed for 425 initial QTLs reported in 34 independent experiments controlling RSA traits under control and drought stress conditions in the previous twenty years. Sixty-four consensus meta-QTLs (MQTLs) were detected, unevenly distributed on twelve rice chromosomes. The confidence interval (CI) of the identified MQTLs was obtained as 0.11-14.23 cM with an average of 3.79 cM, which was 3.88 times narrower than the mean CI of the original QTLs. Interestingly, 52 MQTLs were co-located with SNP peak positions reported in rice genome-wide association studies (GWAS) for root morphological traits. The genes located in these RSA-related MQTLs were detected and explored to find the drought-responsive genes in the rice root based on the RNA-seq and microarray data. Multiple RSA and drought tolerance-associated genes were found in the MQTLs including the genes involved in auxin biosynthesis or signaling (e.g. YUCCA, WOX, AUX/IAA, ARF), root angle (DRO1-related genes), lateral root development (e.g. DSR, WRKY), root diameter (e.g. OsNAC5), plant cell wall (e.g. EXPA), and lignification (e.g. C4H, PAL, PRX and CAD). The genes located within both the SNP peak positions and the QTL-overview peaks for RSA are suggested as novel candidate genes for further functional analysis. The promising candidate genes and MQTLs can be used as basis for genetic engineering and MQTL-assisted breeding of root phenotypes to improve yield potential, stability and performance in a water-stressed environment.
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Affiliation(s)
- Parisa Daryani
- Department of Agronomy & Plant Breeding, University of Mohaghegh Ardabili, Ardabil, Iran
- Department of Systems Biology, Agricultural Biotechnology Research Institute of Iran (ABRII), Agricultural Research Education and Extension Organization (AREEO), 31535-1897, Karaj, Iran
| | - Hadi Darzi Ramandi
- Department of Molecular Physiology, Agricultural Biotechnology Research Institute of Iran, Agricultural Research Education and Extension Organization (AREEO), Karaj, Iran
| | - Sara Dezhsetan
- Department of Agronomy & Plant Breeding, University of Mohaghegh Ardabili, Ardabil, Iran.
| | - Raheleh Mirdar Mansuri
- Department of Systems Biology, Agricultural Biotechnology Research Institute of Iran (ABRII), Agricultural Research Education and Extension Organization (AREEO), 31535-1897, Karaj, Iran
| | - Ghasem Hosseini Salekdeh
- Department of Systems Biology, Agricultural Biotechnology Research Institute of Iran (ABRII), Agricultural Research Education and Extension Organization (AREEO), 31535-1897, Karaj, Iran
- Department of Molecular Sciences, Macquarie University, Sydney, NSW, Australia
| | - Zahra-Sadat Shobbar
- Department of Systems Biology, Agricultural Biotechnology Research Institute of Iran (ABRII), Agricultural Research Education and Extension Organization (AREEO), 31535-1897, Karaj, Iran.
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Arriagada O, Gadaleta A, Marcotuli I, Maccaferri M, Campana M, Reveco S, Alfaro C, Matus I, Schwember AR. A comprehensive meta-QTL analysis for yield-related traits of durum wheat ( Triticum turgidum L. var. durum) grown under different water regimes. FRONTIERS IN PLANT SCIENCE 2022; 13:984269. [PMID: 36147234 PMCID: PMC9486101 DOI: 10.3389/fpls.2022.984269] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 08/18/2022] [Indexed: 05/13/2023]
Abstract
Abiotic stress strongly affects yield-related traits in durum wheat, in particular drought is one of the main environmental factors that have effect on grain yield and plant architecture. In order to obtain new genotypes well adapted to stress conditions, the highest number of desirable traits needs to be combined in the same genotype. In this context, hundreds of quantitative trait loci (QTL) have been identified for yield-related traits in different genetic backgrounds and environments. Meta-QTL (MQTL) analysis is a useful approach to combine data sets and for creating consensus positions for the QTL detected in independent studies for the reliability of their location and effects. MQTL analysis is a useful method to dissect the genetic architecture of complex traits, which provide an extensive allelic coverage, a higher mapping resolution and allow the identification of putative molecular markers useful for marker-assisted selection (MAS). In the present study, a complete and comprehensive MQTL analysis was carried out to identify genomic regions associated with grain-yield related traits in durum wheat under different water regimes. A total of 724 QTL on all 14 chromosomes (genomes A and B) were collected for the 19 yield-related traits selected, of which 468 were reported under rainfed conditions, and 256 under irrigated conditions. Out of the 590 QTL projected on the consensus map, 421 were grouped into 76 MQTL associated with yield components under both irrigated and rainfed conditions, 12 genomic regions containing stable MQTL on all chromosomes except 1A, 4A, 5A, and 6B. Candidate genes associated to MQTL were identified and an in-silico expression analysis was carried out for 15 genes selected among those that were differentially expressed under drought. These results can be used to increase durum wheat grain yields under different water regimes and to obtain new genotypes adapted to climate change.
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Affiliation(s)
- Osvin Arriagada
- Departamento de Ciencias Vegetales, Facultad de Agronomía e Ingeniería Forestal, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Agata Gadaleta
- Department of Agricultural and Environmental Science, University of Bari Aldo Moro, Bari, Italy
| | - Ilaria Marcotuli
- Department of Agricultural and Environmental Science, University of Bari Aldo Moro, Bari, Italy
| | - Marco Maccaferri
- Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy
| | - Matteo Campana
- Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy
| | - Samantha Reveco
- Departamento de Ciencias Vegetales, Facultad de Agronomía e Ingeniería Forestal, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Christian Alfaro
- Centro Regional Rayentue, Instituto de Investigaciones Agropecuarias (INIA), Rengo, Chile
| | - Iván Matus
- Centro Regional Quilamapu, Instituto de Investigaciones Agropecuarias (INIA), Chillán, Chile
| | - Andrés R. Schwember
- Departamento de Ciencias Vegetales, Facultad de Agronomía e Ingeniería Forestal, Pontificia Universidad Católica de Chile, Santiago, Chile
- *Correspondence: Andrés R. Schwember,
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Li FF, Niu JH, Yu X, Kong QH, Wang RF, Qin L, Chen EY, Yang YB, Liu ZY, Lang LN, Zhang HW, Wang HL, Guan YA. Isolation and identification of SiCOL5, which is involved in photoperiod response, based on the quantitative trait locus mapping of Setaria italica. FRONTIERS IN PLANT SCIENCE 2022; 13:969604. [PMID: 36204051 PMCID: PMC9530826 DOI: 10.3389/fpls.2022.969604] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 08/16/2022] [Indexed: 05/13/2023]
Abstract
Foxtail millet (Setaria italica) is a versatile grain and fodder crop grown in arid and semi-arid regions. It is an especially important crop for combating malnutrition in certain poverty-stricken areas of the world. Photoperiod sensitivity is a major constraint to the distribution and utilization of foxtail millet germplasm resources. Foxtail millet may be suitable as a model species for studying the photoperiod sensitivity of C4 crops. However, the genetic basis of the photoperiod response of foxtail millet remains poorly studied. To detect the genetic basis of photoperiod sensitivity-related traits, a recombinant inbred line (RIL) population consisting of 313 lines derived from a cross between the spring-sown cultivar "Longgu 3" and the summer-sown cultivar "Canggu 3" was established. The RIL population was genotyped using whole-genome re-sequencing and was phenotyped in four environments. A high-density genetic linkage map was constructed with an average distance between adjacent markers of 0.69 cM. A total of 21 quantitative trait loci (QTLs) were identified by composite interval mapping, and 116 candidate genes were predicted according to gene annotations and variations between parents, among which three genes were considered important candidate genes by the integration and overall consideration of the results from gene annotation, SNP and indel analysis, cis-element analysis, and the expression pattern of different genes in different varieties, which have different photoperiod sensitivities. A putative candidate gene, SiCOL5, was isolated based on QTL mapping analysis. The expression of SiCOL5 was sensitive to photoperiod and was regulated by biological rhythm-related genes. Function analysis suggested that SiCOL5 positively regulated flowering time. Yeast two-hybrid and bimolecular fluorescence complementation assays showed that SiCOL5 was capable of interacting with SiNF-YA1 in the nucleus.
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Affiliation(s)
- Fei-fei Li
- Featured Crops Engineering Laboratory of Shandong Province, National Engineering Research Center of Wheat and Maize, Shandong Technology Innovation Center of Wheat, Crop Research Institute, Shandong Academy of Agricultural Sciences, Jinan, China
| | - Jia-hong Niu
- College of Life Science, Shandong Normal University, Jinan, China
| | - Xiao Yu
- College of Life Science, Shandong Normal University, Jinan, China
| | - Qing-hua Kong
- College of Life Science, Shandong Normal University, Jinan, China
| | - Run-feng Wang
- Featured Crops Engineering Laboratory of Shandong Province, National Engineering Research Center of Wheat and Maize, Shandong Technology Innovation Center of Wheat, Crop Research Institute, Shandong Academy of Agricultural Sciences, Jinan, China
| | - Ling Qin
- Featured Crops Engineering Laboratory of Shandong Province, National Engineering Research Center of Wheat and Maize, Shandong Technology Innovation Center of Wheat, Crop Research Institute, Shandong Academy of Agricultural Sciences, Jinan, China
| | - Er-ying Chen
- Featured Crops Engineering Laboratory of Shandong Province, National Engineering Research Center of Wheat and Maize, Shandong Technology Innovation Center of Wheat, Crop Research Institute, Shandong Academy of Agricultural Sciences, Jinan, China
| | - Yan-bing Yang
- Featured Crops Engineering Laboratory of Shandong Province, National Engineering Research Center of Wheat and Maize, Shandong Technology Innovation Center of Wheat, Crop Research Institute, Shandong Academy of Agricultural Sciences, Jinan, China
| | - Zhen-yu Liu
- Featured Crops Engineering Laboratory of Shandong Province, National Engineering Research Center of Wheat and Maize, Shandong Technology Innovation Center of Wheat, Crop Research Institute, Shandong Academy of Agricultural Sciences, Jinan, China
| | - Li-na Lang
- Shandong Seed Administration Station, Jinan, China
| | - Hua-wen Zhang
- Featured Crops Engineering Laboratory of Shandong Province, National Engineering Research Center of Wheat and Maize, Shandong Technology Innovation Center of Wheat, Crop Research Institute, Shandong Academy of Agricultural Sciences, Jinan, China
| | - Hai-lian Wang
- Featured Crops Engineering Laboratory of Shandong Province, National Engineering Research Center of Wheat and Maize, Shandong Technology Innovation Center of Wheat, Crop Research Institute, Shandong Academy of Agricultural Sciences, Jinan, China
| | - Yan-an Guan
- Featured Crops Engineering Laboratory of Shandong Province, National Engineering Research Center of Wheat and Maize, Shandong Technology Innovation Center of Wheat, Crop Research Institute, Shandong Academy of Agricultural Sciences, Jinan, China
- *Correspondence: Yan-an Guan,
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37
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Sandhu N, Pruthi G, Prakash Raigar O, Singh MP, Phagna K, Kumar A, Sethi M, Singh J, Ade PA, Saini DK. Meta-QTL Analysis in Rice and Cross-Genome Talk of the Genomic Regions Controlling Nitrogen Use Efficiency in Cereal Crops Revealing Phylogenetic Relationship. Front Genet 2021; 12:807210. [PMID: 34992638 PMCID: PMC8724540 DOI: 10.3389/fgene.2021.807210] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Accepted: 11/30/2021] [Indexed: 11/13/2022] Open
Abstract
The phenomenal increase in the use of nitrogenous fertilizers coupled with poor nitrogen use efficiency is among the most important threats to the environment, economic, and social health. During the last 2 decades, a number of genomic regions associated with nitrogen use efficiency (NUE) and related traits have been reported by different research groups, but none of the stable and major effect QTL have been utilized in the marker-assisted introgression/pyramiding program. Compiling the data available in the literature could be very useful in identifying stable and major effect genomic regions associated with the root and NUE-related trait improving the rice grain yield. In the present study, we performed meta-QTL analysis on 1,330 QTL from 29 studies published in the past 2 decades. A total of 76 MQTL with a stable effect over different genetic backgrounds and environments were identified. The significant reduction in the confidence interval of the MQTL compared to the initial QTL resulted in the identification of annotated and putative candidate genes related to the traits considered in the present study. A hot spot region associated with correlated traits on chr 1, 4, and 8 and candidate genes associated with nitrate transporters, nitrogen content, and ammonium uptake on chromosomes 2, 4, 6, and 8 have been identified. The identified MQTL, putative candidate genes, and their orthologues were validated on our previous studies conducted on rice and wheat. The research-based interventions such as improving nitrogen use efficiency via identification of major genomic regions and candidate genes can be a plausible, simple, and low-cost solution to address the challenges of the crop improvement program.
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Affiliation(s)
| | | | | | | | - Kanika Phagna
- Indian Institute of Science Education and Research, Berhampur, India
| | - Aman Kumar
- Punjab Agricultural University, Ludhiana, India
| | - Mehak Sethi
- Punjab Agricultural University, Ludhiana, India
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Kumar S, Singh VP, Saini DK, Sharma H, Saripalli G, Kumar S, Balyan HS, Gupta PK. Meta-QTLs, ortho-MQTLs, and candidate genes for thermotolerance in wheat ( Triticum aestivum L.). MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2021; 41:69. [PMID: 37309361 PMCID: PMC10236124 DOI: 10.1007/s11032-021-01264-7] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 11/04/2021] [Indexed: 06/14/2023]
Abstract
Meta-QTL analysis for thermotolerance in wheat was conducted to identify robust meta-QTLs (MQTLs). In this study, 441 QTLs related to 31 heat-responsive traits were projected on the consensus map with 50,310 markers. This exercise resulted in the identification of 85 MQTLs with confidence interval (CI) ranging from 0.11 to 34.9 cM with an average of 5.6 cM. This amounted to a 2.96-fold reduction relative to the mean CI (16.5 cM) of the QTLs used. Seventy-seven (77) of these MQTLs were also compared and verified with the results of recent genome-wide association studies (GWAS). The 85 MQTLs included seven MQTLs that are particularly useful for breeding purposes (we called them breeders' MQTLs). Seven ortho-MQTLs between wheat and rice genomes were also identified using synteny and collinearity. The MQTLs were used for the identification of 1,704 candidate genes (CGs). In silico expression analysis of these CGs permitted identification of 182 differentially expressed genes (DEGs), which included 36 high confidence CGs with known functions previously reported to be important for thermotolerance. These high confidence CGs encoded proteins belonging to the following families: protein kinase, WD40 repeat, glycosyltransferase, ribosomal protein, SNARE associated Golgi protein, GDSL lipase/esterase, SANT/Myb domain, K homology domain, etc. Thus, the present study resulted in the identification of MQTLs (including breeders' MQTLs), ortho-MQTLs, and underlying CGs, which could prove useful not only for molecular breeding for the development of thermotolerant wheat cultivars but also for future studies focused on understanding the molecular basis of thermotolerance. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-021-01264-7.
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Affiliation(s)
- Sourabh Kumar
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, UP India
| | - Vivudh Pratap Singh
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, UP India
| | - Dinesh Kumar Saini
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab India
| | - Hemant Sharma
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, UP India
| | - Gautam Saripalli
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, UP India
| | - Sachin Kumar
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, UP India
| | - Harindra Singh Balyan
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, UP India
| | - Pushpendra Kumar Gupta
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, UP India
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Rufo R, López A, Lopes MS, Bellvert J, Soriano JM. Identification of Quantitative Trait Loci Hotspots Affecting Agronomic Traits and High-Throughput Vegetation Indices in Rainfed Wheat. FRONTIERS IN PLANT SCIENCE 2021; 12:735192. [PMID: 34616417 PMCID: PMC8489662 DOI: 10.3389/fpls.2021.735192] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Accepted: 08/20/2021] [Indexed: 06/13/2023]
Abstract
Understanding the genetic basis of agronomic traits is essential for wheat breeding programs to develop new cultivars with enhanced grain yield under climate change conditions. The use of high-throughput phenotyping (HTP) technologies for the assessment of agronomic performance through drought-adaptive traits opens new possibilities in plant breeding. HTP together with a genome-wide association study (GWAS) mapping approach can be a useful method to dissect the genetic control of complex traits in wheat to enhance grain yield under drought stress. This study aimed to identify molecular markers associated with agronomic and remotely sensed vegetation index (VI)-related traits under rainfed conditions in bread wheat and to use an in silico candidate gene (CG) approach to search for upregulated CGs under abiotic stress. The plant material consisted of 170 landraces and 184 modern cultivars from the Mediterranean basin. The collection was phenotyped for agronomic and VI traits derived from multispectral images over 3 and 2 years, respectively. The GWAS identified 2,579 marker-trait associations (MTAs). The quantitative trait loci (QTL) overview index statistic detected 11 QTL hotspots involving more than one trait in at least 2 years. A CG analysis detected 12 CGs upregulated under abiotic stress in six QTL hotspots and 46 downregulated CGs in 10 QTL hotspots. The current study highlights the utility of VI to identify chromosome regions that contribute to yield and drought tolerance under rainfed Mediterranean conditions.
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Affiliation(s)
- Rubén Rufo
- Sustainable Field Crops Programme, Institute for Food and Agricultural Research and Technology (IRTA), Lleida, Spain
| | - Andrea López
- Sustainable Field Crops Programme, Institute for Food and Agricultural Research and Technology (IRTA), Lleida, Spain
| | - Marta S. Lopes
- Sustainable Field Crops Programme, Institute for Food and Agricultural Research and Technology (IRTA), Lleida, Spain
| | - Joaquim Bellvert
- Efficient Use of Water in Agriculture Program, Institute for Food and Agricultural Research and Technology (IRTA), Parc Científici TecnològicAgroalimentari de Gardeny (PCiTAL), Fruitcentre, Lleida, Spain
| | - Jose M. Soriano
- Sustainable Field Crops Programme, Institute for Food and Agricultural Research and Technology (IRTA), Lleida, Spain
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Wu PY, Yang MH, Kao CH. A statistical framework for QTL hotspot detection. G3-GENES GENOMES GENETICS 2021; 11:6151767. [PMID: 33638985 PMCID: PMC8049418 DOI: 10.1093/g3journal/jkab056] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/04/2021] [Accepted: 02/11/2021] [Indexed: 11/13/2022]
Abstract
Quantitative trait loci (QTL) hotspots (genomic locations enriched in QTL) are a common and notable feature when collecting many QTL for various traits in many areas of biological studies. The QTL hotspots are important and attractive since they are highly informative and may harbor genes for the quantitative traits. So far, the current statistical methods for QTL hotspot detection use either the individual-level data from the genetical genomics experiments or the summarized data from public QTL databases to proceed with the detection analysis. These methods may suffer from the problems of ignoring the correlation structure among traits, neglecting the magnitude of LOD scores for the QTL, or paying a very high computational cost, which often lead to the detection of excessive spurious hotspots, failure to discover biologically interesting hotspots composed of a small-to-moderate number of QTL with strong LOD scores, and computational intractability, respectively, during the detection process. In this article, we describe a statistical framework that can handle both types of data as well as address all the problems at a time for QTL hotspot detection. Our statistical framework directly operates on the QTL matrix and hence has a very cheap computational cost and is deployed to take advantage of the QTL mapping results for assisting the detection analysis. Two special devices, trait grouping and top γn,α profile, are introduced into the framework. The trait grouping attempts to group the traits controlled by closely linked or pleiotropic QTL together into the same trait groups and randomly allocates these QTL together across the genomic positions separately by trait group to account for the correlation structure among traits, so as to have the ability to obtain much stricter thresholds and dismiss spurious hotspots. The top γn,α profile is designed to outline the LOD-score pattern of QTL in a hotspot across the different hotspot architectures, so that it can serve to identify and characterize the types of QTL hotspots with varying sizes and LOD-score distributions. Real examples, numerical analysis, and simulation study are performed to validate our statistical framework, investigate the detection properties, and also compare with the current methods in QTL hotspot detection. The results demonstrate that the proposed statistical framework can effectively accommodate the correlation structure among traits, identify the types of hotspots, and still keep the notable features of easy implementation and fast computation for practical QTL hotspot detection.
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Affiliation(s)
- Po-Ya Wu
- Institute of Statistical Science, Academia Sinica, Taipei 11529, Taiwan, Republic of China
| | - Man-Hsia Yang
- Crop Science Division, Taiwan Agricultural Research Institute, Council of Agriculture, Taichung 41362, Taiwan, Republic of China
| | - Chen-Hung Kao
- Institute of Statistical Science, Academia Sinica, Taipei 11529, Taiwan, Republic of China.,Department of Agronomy, National Taiwan University, Taipei 10617, Taiwan, Republic of China
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41
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Soriano JM, Colasuonno P, Marcotuli I, Gadaleta A. Meta-QTL analysis and identification of candidate genes for quality, abiotic and biotic stress in durum wheat. Sci Rep 2021; 11:11877. [PMID: 34088972 PMCID: PMC8178383 DOI: 10.1038/s41598-021-91446-2] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Accepted: 05/25/2021] [Indexed: 11/15/2022] Open
Abstract
The genetic improvement of durum wheat and enhancement of plant performance often depend on the identification of stable quantitative trait loci (QTL) and closely linked molecular markers. This is essential for better understanding the genetic basis of important agronomic traits and identifying an effective method for improving selection efficiency in breeding programmes. Meta-QTL analysis is a useful approach for dissecting the genetic basis of complex traits, providing broader allelic coverage and higher mapping resolution for the identification of putative molecular markers to be used in marker-assisted selection. In the present study, extensive QTL meta-analysis was conducted on 45 traits of durum wheat, including quality and biotic and abiotic stress-related traits. A total of 368 QTL distributed on all 14 chromosomes of genomes A and B were projected: 171 corresponded to quality-related traits, 127 to abiotic stress and 71 to biotic stress, of which 318 were grouped in 85 meta-QTL (MQTL), 24 remained as single QTL and 26 were not assigned to any MQTL. The number of MQTL per chromosome ranged from 4 in chromosomes 1A and 6A to 9 in chromosome 7B; chromosomes 3A and 7A showed the highest number of individual QTL (4), and chromosome 7B the highest number of undefined QTL (4). The recently published genome sequence of durum wheat was used to search for candidate genes within the MQTL peaks. This work will facilitate cloning and pyramiding of QTL to develop new cultivars with specific quantitative traits and speed up breeding programs.
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Affiliation(s)
- Jose Miguel Soriano
- Sustainable Field Crops Programme, IRTA (Institute for Food and Agricultural Research and Technology), 25198, Lleida, Spain.
| | - Pasqualina Colasuonno
- Department of Agricultural and Environmental Science, University of Bari 'Aldo Moro', Via G. Amendola 165/A, 70126, Bari, Italy
| | - Ilaria Marcotuli
- Department of Agricultural and Environmental Science, University of Bari 'Aldo Moro', Via G. Amendola 165/A, 70126, Bari, Italy.
| | - Agata Gadaleta
- Department of Agricultural and Environmental Science, University of Bari 'Aldo Moro', Via G. Amendola 165/A, 70126, Bari, Italy
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Joint analysis of days to flowering reveals independent temperate adaptations in maize. Heredity (Edinb) 2021; 126:929-941. [PMID: 33888874 PMCID: PMC8178344 DOI: 10.1038/s41437-021-00422-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2020] [Revised: 02/07/2021] [Accepted: 02/25/2021] [Indexed: 02/02/2023] Open
Abstract
Domesticates are an excellent model for understanding biological consequences of rapid climate change. Maize (Zea mays ssp. mays) was domesticated from a tropical grass yet is widespread across temperate regions today. We investigate the biological basis of temperate adaptation in diverse structured nested association mapping (NAM) populations from China, Europe (Dent and Flint) and the United States as well as in the Ames inbred diversity panel, using days to flowering as a proxy. Using cross-population prediction, where high prediction accuracy derives from overall genomic relatedness, shared genetic architecture, and sufficient diversity in the training population, we identify patterns in predictive ability across the five populations. To identify the source of temperate adapted alleles in these populations, we predict top associated genome-wide association study (GWAS) identified loci in a Random Forest Classifier using independent temperate-tropical North American populations based on lines selected from Hapmap3 as predictors. We find that North American populations are well predicted (AUC equals 0.89 and 0.85 for Ames and USNAM, respectively), European populations somewhat well predicted (AUC equals 0.59 and 0.67 for the Dent and Flint panels, respectively) and that the Chinese population is not predicted well at all (AUC is 0.47), suggesting an independent adaptation process for early flowering in China. Multiple adaptations for the complex trait days to flowering in maize provide hope for similar natural systems under climate change.
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Jung H, Lee A, Jo SH, Park HJ, Jung WY, Kim HS, Lee HJ, Jeong SG, Kim YS, Cho HS. Nitrogen Signaling Genes and SOC1 Determine the Flowering Time in a Reciprocal Negative Feedback Loop in Chinese Cabbage ( Brassica rapa L.) Based on CRISPR/Cas9-Mediated Mutagenesis of Multiple BrSOC1 Homologs. Int J Mol Sci 2021; 22:ijms22094631. [PMID: 33924895 PMCID: PMC8124421 DOI: 10.3390/ijms22094631] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Revised: 04/23/2021] [Accepted: 04/26/2021] [Indexed: 11/29/2022] Open
Abstract
Precise flowering timing is critical for the plant life cycle. Here, we examined the molecular mechanisms and regulatory network associated with flowering in Chinese cabbage (Brassica rapa L.) by comparative transcriptome profiling of two Chinese cabbage inbred lines, “4004” (early bolting) and “50” (late bolting). RNA-Seq and quantitative reverse transcription PCR (qPCR) analyses showed that two positive nitric oxide (NO) signaling regulator genes, nitrite reductase (BrNIR) and nitrate reductase (BrNIA), were up-regulated in line “50” with or without vernalization. In agreement with the transcription analysis, the shoots in line “50” had substantially higher nitrogen levels than those in “4004”. Upon vernalization, the flowering repressor gene Circadian 1 (BrCIR1) was significantly up-regulated in line “50”, whereas the flowering enhancer genes named SUPPRESSOR OF OVEREXPRESSION OF CONSTANCE 1 homologs (BrSOC1s) were substantially up-regulated in line “4004”. CRISPR/Cas9-mediated mutagenesis in Chinese cabbage demonstrated that the BrSOC1-1/1-2/1-3 genes were involved in late flowering, and their expression was mutually exclusive with that of the nitrogen signaling genes. Thus, we identified two flowering mechanisms in Chinese cabbage: a reciprocal negative feedback loop between nitrogen signaling genes (BrNIA1 and BrNIR1) and BrSOC1s to control flowering time and positive feedback control of the expression of BrSOC1s.
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Affiliation(s)
- Haemyeong Jung
- Plant Systems Engineering Research Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Korea; (H.J.); (A.L.); (S.H.J.); (H.J.P.); (W.Y.J.); (H.-S.K.); (H.-J.L.)
- Department of Biosystems and Bioengineering, KRIBB School of Biotechnology, Korea University of Science and Technology (UST), Daejeon 34113, Korea
| | - Areum Lee
- Plant Systems Engineering Research Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Korea; (H.J.); (A.L.); (S.H.J.); (H.J.P.); (W.Y.J.); (H.-S.K.); (H.-J.L.)
- Department of Biosystems and Bioengineering, KRIBB School of Biotechnology, Korea University of Science and Technology (UST), Daejeon 34113, Korea
| | - Seung Hee Jo
- Plant Systems Engineering Research Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Korea; (H.J.); (A.L.); (S.H.J.); (H.J.P.); (W.Y.J.); (H.-S.K.); (H.-J.L.)
- Department of Biosystems and Bioengineering, KRIBB School of Biotechnology, Korea University of Science and Technology (UST), Daejeon 34113, Korea
| | - Hyun Ji Park
- Plant Systems Engineering Research Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Korea; (H.J.); (A.L.); (S.H.J.); (H.J.P.); (W.Y.J.); (H.-S.K.); (H.-J.L.)
| | - Won Yong Jung
- Plant Systems Engineering Research Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Korea; (H.J.); (A.L.); (S.H.J.); (H.J.P.); (W.Y.J.); (H.-S.K.); (H.-J.L.)
| | - Hyun-Soon Kim
- Plant Systems Engineering Research Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Korea; (H.J.); (A.L.); (S.H.J.); (H.J.P.); (W.Y.J.); (H.-S.K.); (H.-J.L.)
- Department of Biosystems and Bioengineering, KRIBB School of Biotechnology, Korea University of Science and Technology (UST), Daejeon 34113, Korea
| | - Hyo-Jun Lee
- Plant Systems Engineering Research Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Korea; (H.J.); (A.L.); (S.H.J.); (H.J.P.); (W.Y.J.); (H.-S.K.); (H.-J.L.)
- Department of Functional Genomics, KRIBB School of Biotechnology, Korea University of Science and Technology (UST), Daejeon 34113, Korea
| | - Seon-Geum Jeong
- Department of Biotechnology, NongWoo Bio, Anseong 17558, Korea;
| | - Youn-Sung Kim
- Department of Biotechnology, NongWoo Bio, Anseong 17558, Korea;
- Correspondence: (Y.-S.K.); (H.S.C.); Tel.: +82-31-652-5526 (Y.-S.K.); +82-42-860-4469 (H.S.C.)
| | - Hye Sun Cho
- Plant Systems Engineering Research Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Korea; (H.J.); (A.L.); (S.H.J.); (H.J.P.); (W.Y.J.); (H.-S.K.); (H.-J.L.)
- Department of Biosystems and Bioengineering, KRIBB School of Biotechnology, Korea University of Science and Technology (UST), Daejeon 34113, Korea
- Correspondence: (Y.-S.K.); (H.S.C.); Tel.: +82-31-652-5526 (Y.-S.K.); +82-42-860-4469 (H.S.C.)
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Colasuonno P, Marcotuli I, Gadaleta A, Soriano JM. From Genetic Maps to QTL Cloning: An Overview for Durum Wheat. PLANTS (BASEL, SWITZERLAND) 2021; 10:315. [PMID: 33562160 PMCID: PMC7914919 DOI: 10.3390/plants10020315] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Revised: 01/26/2021] [Accepted: 02/02/2021] [Indexed: 12/17/2022]
Abstract
Durum wheat is one of the most important cultivated cereal crops, providing nutrients to humans and domestic animals. Durum breeding programs prioritize the improvement of its main agronomic traits; however, the majority of these traits involve complex characteristics with a quantitative inheritance (quantitative trait loci, QTL). This can be solved with the use of genetic maps, new molecular markers, phenotyping data of segregating populations, and increased accessibility to sequences from next-generation sequencing (NGS) technologies. This allows for high-density genetic maps to be developed for localizing candidate loci within a few Kb in a complex genome, such as durum wheat. Here, we review the identified QTL, fine mapping, and cloning of QTL or candidate genes involved in the main traits regarding the quality and biotic and abiotic stresses of durum wheat. The current knowledge on the used molecular markers, sequence data, and how they changed the development of genetic maps and the characterization of QTL is summarized. A deeper understanding of the trait architecture useful in accelerating durum wheat breeding programs is envisioned.
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Affiliation(s)
- Pasqualina Colasuonno
- Department of Agricultural and Environmental Science, University of Bari ‘Aldo Moro’, Via G. Amendola 165/A, 70126 Bari, Italy; (P.C.); (I.M.)
| | - Ilaria Marcotuli
- Department of Agricultural and Environmental Science, University of Bari ‘Aldo Moro’, Via G. Amendola 165/A, 70126 Bari, Italy; (P.C.); (I.M.)
| | - Agata Gadaleta
- Department of Agricultural and Environmental Science, University of Bari ‘Aldo Moro’, Via G. Amendola 165/A, 70126 Bari, Italy; (P.C.); (I.M.)
| | - Jose Miguel Soriano
- Sustainable Field Crops Programme, IRTA (Institute for Food and Agricultural Research and Technology), 25198 Lleida, Spain
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Jensen E, Shafiei R, Ma X, Serba DD, Smith DP, Slavov GT, Robson P, Farrar K, Thomas Jones S, Swaller T, Flavell R, Clifton‐Brown J, Saha MC, Donnison I. Linkage mapping evidence for a syntenic QTL associated with flowering time in perennial C 4 rhizomatous grasses Miscanthus and switchgrass. GLOBAL CHANGE BIOLOGY. BIOENERGY 2021; 13:98-111. [PMID: 33381230 PMCID: PMC7756372 DOI: 10.1111/gcbb.12755] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Accepted: 08/10/2020] [Indexed: 06/12/2023]
Abstract
Flowering in perennial species is directed via complex signalling pathways that adjust to developmental regulations and environmental cues. Synchronized flowering in certain environments is a prerequisite to commercial seed production, and so the elucidation of the genetic architecture of flowering time in Miscanthus and switchgrass could aid breeding in these underdeveloped species. In this context, we assessed a mapping population in Miscanthus and two ecologically diverse switchgrass mapping populations over 3 years from planting. Multiple flowering time quantitative trait loci (QTL) were identified in both species. Remarkably, the most significant Miscanthus and switchgrass QTL proved to be syntenic, located on linkage groups 4 and 2, with logarithm of odds scores of 17.05 and 21.8 respectively. These QTL regions contained three flowering time transcription factors: Squamosa Promoter-binding protein-Like, MADS-box SEPELLATA2 and gibberellin-responsive bHLH137. The former is emerging as a key component of the age-related flowering time pathway.
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Affiliation(s)
- Elaine Jensen
- Institute of Biological, Environmental and Rural SciencesAberystwyth UniversityAberystwythUK
| | - Reza Shafiei
- Institute of Biological, Environmental and Rural SciencesAberystwyth UniversityAberystwythUK
- University of Dundee at JHIDundeeUK
| | - Xue‐Feng Ma
- Ceres, Inc.Thousand OaksCAUSA
- Noble Research Institute, LLC.ArdmoreOKUSA
| | - Desalegn D. Serba
- Noble Research Institute, LLC.ArdmoreOKUSA
- Agricultural Research Center‐HaysKansas State UniversityHaysKSUSA
| | - Daniel P. Smith
- Institute of Biological, Environmental and Rural SciencesAberystwyth UniversityAberystwythUK
- ScionRotoruaNew Zealand
| | - Gancho T. Slavov
- Institute of Biological, Environmental and Rural SciencesAberystwyth UniversityAberystwythUK
- ScionRotoruaNew Zealand
| | - Paul Robson
- Institute of Biological, Environmental and Rural SciencesAberystwyth UniversityAberystwythUK
| | - Kerrie Farrar
- Institute of Biological, Environmental and Rural SciencesAberystwyth UniversityAberystwythUK
| | - Sian Thomas Jones
- Institute of Biological, Environmental and Rural SciencesAberystwyth UniversityAberystwythUK
| | - Timothy Swaller
- Ceres, Inc.Thousand OaksCAUSA
- Genomics Institute of the Novartis Research FoundationSan DiegoCAUSA
| | - Richard Flavell
- Ceres, Inc.Thousand OaksCAUSA
- International Wheat Yield PartnershipTexas A&M UniversityCollege StationTXUSA
| | - John Clifton‐Brown
- Institute of Biological, Environmental and Rural SciencesAberystwyth UniversityAberystwythUK
| | | | - Iain Donnison
- Institute of Biological, Environmental and Rural SciencesAberystwyth UniversityAberystwythUK
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Li Q, Wu G, Zhao Y, Wang B, Zhao B, Kong D, Wei H, Chen C, Wang H. CRISPR/Cas9-mediated knockout and overexpression studies reveal a role of maize phytochrome C in regulating flowering time and plant height. PLANT BIOTECHNOLOGY JOURNAL 2020; 18:2520-2532. [PMID: 32531863 PMCID: PMC7680541 DOI: 10.1111/pbi.13429] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2020] [Revised: 03/30/2020] [Accepted: 04/20/2020] [Indexed: 05/18/2023]
Abstract
Maize is a major staple crop widely used for food, feedstocks and industrial products. Shade-avoidance syndrome (SAS), which is triggered when plants sense competition of light from neighbouring vegetation, is detrimental for maize yield production under high-density planting conditions. Previous studies have shown that the red and far-red photoreceptor phytochromes are responsible for perceiving the shading signals and triggering SAS in Arabidopsis; however, their roles in maize are less clear. In this study, we examined the expression patterns of ZmPHYC1 and ZmPHYC2 and found that ZmPHYC1, but not ZmPHYC2, is highly expressed in leaves and is regulated by the circadian clock. Both ZmPHYC1 and ZmPHYC2 proteins are localized to both the nucleus and cytoplasm under light conditions and both of them can interact with themselves or with ZmPHYBs. Heterologous expression of ZmPHYCs can complement the Arabidopsis phyC-2 mutant under constant red light conditions and confer an attenuated SAS in Arabidopsis in response to shading. Double knockout mutants of ZmPHYC1 and ZmPHYC2 created using the CRISPR/Cas9 technology display a moderate early-flowering phenotype under long-day conditions, whereas ZmPHYC2 overexpression plants exhibit a moderately reduced plant height and ear height. Together, these results provided new insight into the function of ZmPHYCs and guidance for breeding high-density tolerant maize cultivars.
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Affiliation(s)
- Quanquan Li
- State Key Laboratory of Crop BiologyCollege of AgronomyShandong Agricultural UniversityTai’anChina
| | - Guangxia Wu
- Biotechnology Research InstituteChinese Academy of Agricultural SciencesBeijingChina
| | - Yongping Zhao
- Biotechnology Research InstituteChinese Academy of Agricultural SciencesBeijingChina
| | - Baobao Wang
- Biotechnology Research InstituteChinese Academy of Agricultural SciencesBeijingChina
| | - Binbin Zhao
- Biotechnology Research InstituteChinese Academy of Agricultural SciencesBeijingChina
| | - Dexin Kong
- State Key Laboratory for Conservation and Utilization of Subtropical Agro‐BioresourcesSouth China Agricultural UniversityGuangzhouChina
| | - Hongbin Wei
- State Key Laboratory for Conservation and Utilization of Subtropical Agro‐BioresourcesSouth China Agricultural UniversityGuangzhouChina
| | - Cuixia Chen
- State Key Laboratory of Crop BiologyCollege of AgronomyShandong Agricultural UniversityTai’anChina
| | - Haiyang Wang
- State Key Laboratory for Conservation and Utilization of Subtropical Agro‐BioresourcesSouth China Agricultural UniversityGuangzhouChina
- Guangdong Laboratory for Lingnan Modern AgricultureGuangzhouChina
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Bilgrami SS, Ramandi HD, Shariati V, Razavi K, Tavakol E, Fakheri BA, Mahdi Nezhad N, Ghaderian M. Detection of genomic regions associated with tiller number in Iranian bread wheat under different water regimes using genome-wide association study. Sci Rep 2020; 10:14034. [PMID: 32820220 PMCID: PMC7441066 DOI: 10.1038/s41598-020-69442-9] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2019] [Accepted: 07/09/2020] [Indexed: 11/09/2022] Open
Abstract
Two of the important traits for wheat yield are tiller and fertile tiller number, both of which have been thought to increase cereal yield in favorable and unfavorable environments. A total of 6,349 single nucleotide polymorphism (SNP) markers from the 15 K wheat Infinium array were employed for genome-wide association study (GWAS) of tillering number traits, generating a physical distance of 14,041.6 Mb based on the IWGSC wheat genome sequence. GWAS analysis using Fixed and random model Circulating Probability Unification (FarmCPU) identified a total of 47 significant marker-trait associations (MTAs) for total tiller number (TTN) and fertile tiller number (FTN) in Iranian bread wheat under different water regimes. After applying a 5% false discovery rate (FDR) threshold, a total of 13 and 11 MTAs distributed on 10 chromosomes were found to be significantly associated with TTN and FTN, respectively. Linked single nucleotide polymorphisms for IWB39005 (2A) and IWB44377 (7A) were highly significantly associated (FDR < 0.01) with TTN and FTN traits. Moreover, to validate GWAS results, meta-analysis was performed and 30 meta-QTL regions were identified on 11 chromosomes. The integration of GWAS and meta-QTLs revealed that tillering trait in wheat is a complex trait which is conditioned by the combined effects of minor changes in multiple genes. The information provided by this study can enrich the currently available candidate genes and genetic resources pools, offering evidence for subsequent analysis of genetic adaptation of wheat to different climatic conditions of Iran and other countries.
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Affiliation(s)
- Sayedeh Saba Bilgrami
- Department of Plant Molecular Biotechnology, National Institute of Genetic Engineering and Biotechnology (NIGEB), Tehran, Iran.,College of Agronomy and Biotechnology, Southwest University, Beibei, 400715, Chongqing, China
| | - Hadi Darzi Ramandi
- Department of Molecular Physiology, Agricultural Biotechnology Research Institute of Iran, Research, Education and Extension Organization (AREEO), Karaj, Iran
| | - Vahid Shariati
- Department of Plant Molecular Biotechnology, National Institute of Genetic Engineering and Biotechnology (NIGEB), Tehran, Iran.
| | - Khadijeh Razavi
- Department of Plant Molecular Biotechnology, National Institute of Genetic Engineering and Biotechnology (NIGEB), Tehran, Iran.
| | - Elahe Tavakol
- Department of Plant Production and Genetics, Shiraz University, Shiraz, Iran
| | - Barat Ali Fakheri
- Department of Plant Breeding and Biotechnology, Faculty of Agriculture, University of Zabol, Zabol, Iran
| | - Nafiseh Mahdi Nezhad
- Department of Plant Breeding and Biotechnology, Faculty of Agriculture, University of Zabol, Zabol, Iran
| | - Mostafa Ghaderian
- Department of Plant Breeding and Biotechnology, Faculty of Agriculture, Isfahan University of Technology, Isfahan, Iran
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48
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Kumar A, Saripalli G, Jan I, Kumar K, Sharma PK, Balyan HS, Gupta PK. Meta-QTL analysis and identification of candidate genes for drought tolerance in bread wheat ( Triticum aestivum L.). PHYSIOLOGY AND MOLECULAR BIOLOGY OF PLANTS : AN INTERNATIONAL JOURNAL OF FUNCTIONAL PLANT BIOLOGY 2020; 26:1713-1725. [PMID: 32801498 PMCID: PMC7415061 DOI: 10.1007/s12298-020-00847-6] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/22/2020] [Revised: 06/30/2020] [Accepted: 07/03/2020] [Indexed: 05/18/2023]
Abstract
Meta-QTL (MQTL) analysis for drought tolerance was undertaken in bread wheat to identify consensus and robust MQTLs using 340 known QTLs from 11 earlier studies; 13 MQTLs located on 6 chromosomes (1D, 3B, 5A, 6D, 7A and 7D) were identified, with maximum of 4 MQTLs on chromosome 5A. Mean confidence intervals for MQTLs were much narrower (mean, 6.01 cM; range 2.07-19.46 cM), relative to those in original QTLs (mean, 13.6 cM; range, 1.0-119.1 cM). Two MQTLs, namely MQTL4 and MQTL12, were major MQTLs with potential for use in marker-assisting breeding. As many as 228 candidate genes (CGs) were also identified using 6 of the 13 MQTLs. In-silico expression analysis of these 228 CGs allowed identification of 14 important CGs, with + 3 to - 8 fold change in expression under drought (relative to normal conditions) in a tolerant cv. named TAM107. These CGs encoded proteins belonging to the following families: NAD-dependent epimerase/dehydratase, protein kinase, NAD(P)-binding domain protein, heat shock protein 70 (Hsp70), glycosyltransferase 2-like, etc. Important MQTLs and CGs identified in the present study should prove useful for future molecular breeding and for the study of molecular basis of drought tolerance in cereals in general and wheat in particular.
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Affiliation(s)
- Anuj Kumar
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004 India
| | - Gautam Saripalli
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004 India
| | - Irfat Jan
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004 India
| | - Kuldeep Kumar
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004 India
| | - P. K. Sharma
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004 India
| | - H. S. Balyan
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004 India
| | - P. K. Gupta
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004 India
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49
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Maize adaptation across temperate climates was obtained via expression of two florigen genes. PLoS Genet 2020; 16:e1008882. [PMID: 32673315 DOI: 10.1371/journal.pgen.1008882] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2019] [Revised: 07/28/2020] [Accepted: 05/22/2020] [Indexed: 11/19/2022] Open
Abstract
Expansion of the maize growing area was central for food security in temperate regions. In addition to the suppression of the short-day requirement for floral induction, it required breeding for a large range of flowering time that compensates the effect of South-North gradients of temperatures. Here we show the role of a novel florigen gene, ZCN12, in the latter adaptation in cooperation with ZCN8. Strong eQTLs of ZCN8 and ZCN12, measured in 327 maize lines, accounted for most of the genetic variance of flowering time in platform and field experiments. ZCN12 had a strong effect on flowering time of transgenic Arabidopsis thaliana plants; a path analysis showed that it directly affected maize flowering time together with ZCN8. The allelic composition at ZCN QTLs showed clear signs of selection by breeders. This suggests that florigens played a central role in ensuring a large range of flowering time, necessary for adaptation to temperate areas.
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50
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Rio S, Mary-Huard T, Moreau L, Bauland C, Palaffre C, Madur D, Combes V, Charcosset A. Disentangling group specific QTL allele effects from genetic background epistasis using admixed individuals in GWAS: An application to maize flowering. PLoS Genet 2020; 16:e1008241. [PMID: 32130208 PMCID: PMC7075643 DOI: 10.1371/journal.pgen.1008241] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2019] [Revised: 03/16/2020] [Accepted: 01/29/2020] [Indexed: 12/21/2022] Open
Abstract
When handling a structured population in association mapping, group-specific allele effects may be observed at quantitative trait loci (QTLs) for several reasons: (i) a different linkage disequilibrium (LD) between SNPs and QTLs across groups, (ii) group-specific genetic mutations in QTL regions, and/or (iii) epistatic interactions between QTLs and other loci that have differentiated allele frequencies between groups. We present here a new genome-wide association (GWAS) approach to identify QTLs exhibiting such group-specific allele effects. We developed genetic materials including admixed progeny from different genetic groups with known genome-wide ancestries (local admixture). A dedicated statistical methodology was developed to analyze pure and admixed individuals jointly, allowing one to disentangle the factors causing the heterogeneity of allele effects across groups. This approach was applied to maize by developing an inbred "Flint-Dent" panel including admixed individuals that was evaluated for flowering time. Several associations were detected revealing a wide range of configurations of allele effects, both at known flowering QTLs (Vgt1, Vgt2 and Vgt3) and new loci. We found several QTLs whose effect depended on the group ancestry of alleles while others interacted with the genetic background. Our GWAS approach provides useful information on the stability of QTL effects across genetic groups and can be applied to a wide range of species.
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Affiliation(s)
- Simon Rio
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE - Le Moulon, 91190, Gif-sur-Yvette, France
| | - Tristan Mary-Huard
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE - Le Moulon, 91190, Gif-sur-Yvette, France
- MIA, INRAE, AgroParisTech, Université Paris-Saclay, 75005, Paris, France
| | - Laurence Moreau
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE - Le Moulon, 91190, Gif-sur-Yvette, France
| | - Cyril Bauland
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE - Le Moulon, 91190, Gif-sur-Yvette, France
| | - Carine Palaffre
- UE 0394 SMH, INRAE, 2297 Route de l’INRA, 40390, Saint-Martin-de-Hinx, France
| | - Delphine Madur
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE - Le Moulon, 91190, Gif-sur-Yvette, France
| | - Valérie Combes
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE - Le Moulon, 91190, Gif-sur-Yvette, France
| | - Alain Charcosset
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE - Le Moulon, 91190, Gif-sur-Yvette, France
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