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Gesteiro N, Ordás B, Butrón A, de la Fuente M, Jiménez-Galindo JC, Samayoa LF, Cao A, Malvar RA. Genomic versus phenotypic selection to improve corn borer resistance and grain yield in maize. FRONTIERS IN PLANT SCIENCE 2023; 14:1162440. [PMID: 37484478 PMCID: PMC10360656 DOI: 10.3389/fpls.2023.1162440] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Accepted: 06/22/2023] [Indexed: 07/25/2023]
Abstract
Introduction The study of yield and resistance/tolerance to pest are related traits fundamental for maize breeding programs. Genomic selection (GS), which uses all marker information to calculate genomic breeding values, is presented as an emerging alternative to phenotypic and marker-assisted selections for improving complex traits controlled by many genes with small effects. Therefore, although phenotypic selection (PS) has been effective for increasing resistance and yield under high infestation with maize stem borers, higher genetic gains are expected to be obtained through GS based on the complex architecture of both traits. Our objective was to test whether GS is more effective than PS for improving resistance and/or tolerance to maize stem borers and grain yield. Methods For this, we compared different selection programs based on phenotype and genotypic value for a single trait, resistance or yield, and for both traits together. Results and discussion We obtained that GS achieved the highest genetic gain for yield, meanwhile phenotypic selection for yield was the program that achieved the highest reduction of tunnel length, but was ineffective for increasing yield. However, phenotypic or genomic selection for increased resistance may be more effective in improving both traits together; although the gains per cycle would be small for both traits.
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Affiliation(s)
| | | | - Ana Butrón
- Mision Biologica de Galicia (CSIC), Pontevedra, Spain
| | | | | | - Luis Fernando Samayoa
- Department of Crop Science, North Carolina State University, Raleigh, NC, United States
| | - Ana Cao
- Mision Biologica de Galicia (CSIC), Pontevedra, Spain
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Wani SH, Choudhary M, Barmukh R, Bagaria PK, Samantara K, Razzaq A, Jaba J, Ba MN, Varshney RK. Molecular mechanisms, genetic mapping, and genome editing for insect pest resistance in field crops. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2022; 135:3875-3895. [PMID: 35267056 PMCID: PMC9729161 DOI: 10.1007/s00122-022-04060-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Accepted: 02/11/2022] [Indexed: 05/03/2023]
Abstract
Improving crop resistance against insect pests is crucial for ensuring future food security. Integrating genomics with modern breeding methods holds enormous potential in dissecting the genetic architecture of this complex trait and accelerating crop improvement. Insect resistance in crops has been a major research objective in several crop improvement programs. However, the use of conventional breeding methods to develop high-yielding cultivars with sustainable and durable insect pest resistance has been largely unsuccessful. The use of molecular markers for identification and deployment of insect resistance quantitative trait loci (QTLs) can fastrack traditional breeding methods. Till date, several QTLs for insect pest resistance have been identified in field-grown crops, and a few of them have been cloned by positional cloning approaches. Genome editing technologies, such as CRISPR/Cas9, are paving the way to tailor insect pest resistance loci for designing crops for the future. Here, we provide an overview of diverse defense mechanisms exerted by plants in response to insect pest attack, and review recent advances in genomics research and genetic improvements for insect pest resistance in major field crops. Finally, we discuss the scope for genomic breeding strategies to develop more durable insect pest resistant crops.
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Affiliation(s)
- Shabir H Wani
- Mountain Research Center for Field Crops, Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir, Khudwani, J&K, 192101, India.
| | - Mukesh Choudhary
- ICAR-Indian Institute of Maize Research (ICAR-IIMR), PAU Campus, Ludhiana, Punjab, 141001, India
| | - Rutwik Barmukh
- Center of Excellence in Genomics and Systems Biology (CEGSB), International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, 502324, India
| | - Pravin K Bagaria
- ICAR-Indian Institute of Maize Research (ICAR-IIMR), PAU Campus, Ludhiana, Punjab, 141001, India
| | - Kajal Samantara
- Department of Genetics and Plant Breeding, Centurion University of Technology and Management, Paralakhemundi, Odisha, 761211, India
| | - Ali Razzaq
- Centre of Agricultural Biochemistry and Biotechnology, University of Agriculture Faisalabad, Faisalabad, 38040, Pakistan
| | - Jagdish Jaba
- Intergated Crop Management, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, 502324, India
| | - Malick Niango Ba
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), BP 12404, Niamey, Niger
| | - Rajeev K Varshney
- Center of Excellence in Genomics and Systems Biology (CEGSB), International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, 502324, India.
- State Agricultural Biotechnology Centre, Centre for Crop and Food Innovation, Food Futures Institute, Murdoch University, Murdoch, WA, 6150, Australia.
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Jadhav KP, Saykhedkar GR, Tamilarasi PM, Devasree S, Ranjani RV, Sarankumar C, Bharathi P, Karthikeyan A, Arulselvi S, Vijayagowri E, Ganesan KN, Paranidharan V, Nair SK, Babu R, Ramalingam J, Raveendran M, Senthil N. GBS-Based SNP Map Pinpoints the QTL Associated With Sorghum Downy Mildew Resistance in Maize (Zea mays L.). Front Genet 2022; 13:890133. [PMID: 35937985 PMCID: PMC9348272 DOI: 10.3389/fgene.2022.890133] [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: 03/05/2022] [Accepted: 06/13/2022] [Indexed: 12/04/2022] Open
Abstract
Sorghum downy mildew (SDM), caused by the biotrophic fungi Peronosclerospora sorghi, threatens maize production worldwide, including India. To identify quantitative trait loci (QTL) associated with resistance to SDM, we used a recombinant inbred line (RIL) population derived from a cross between resistant inbred line UMI936 (w) and susceptible inbred line UMI79. The RIL population was phenotyped for SDM resistance in three environments [E1-field (Coimbatore), E2-greenhouse (Coimbatore), and E3-field (Mandya)] and also utilized to construct the genetic linkage map by genotyping by sequencing (GBS) approach. The map comprises 1516 SNP markers in 10 linkage groups (LGs) with a total length of 6924.7 cM and an average marker distance of 4.57 cM. The QTL analysis with the phenotype and marker data detected nine QTL on chromosome 1, 2, 3, 5, 6, and 7 across three environments. Of these, QTL namely qDMR1.2, qDMR3.1, qDMR5.1, and qDMR6.1 were notable due to their high phenotypic variance. qDMR3.1 from chromosome 3 was detected in more than one environment (E1 and E2), explaining the 10.3% and 13.1% phenotypic variance. Three QTL, qDMR1.2, qDMR5.1, and qDMR6.1 from chromosomes 1, 5, and 6 were identified in either E1 or E3, explaining 15.2%–18% phenotypic variance. Moreover, genome mining on three QTL (qDMR3.1, qDMR5.1, and qDMR6.1) reveals the putative candidate genes related to SDM resistance. The information generated in this study will be helpful for map-based cloning and marker-assisted selection in maize breeding programs.
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Affiliation(s)
- Kashmiri Prakash Jadhav
- Department of Plant Biotechnology, Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore, India
| | - Gajanan R. Saykhedkar
- Asian Regional Maize Program, International Maize and Wheat Improvement Center (CIMMYT), ICRISAT Campus, Patancheru, India
| | | | - Subramani Devasree
- Department of Millets, Centre for Plant Breeding and Genetics, Tamil Nadu Agricultural University, Coimbatore, India
| | - Rajagopalan Veera Ranjani
- Department of Plant Biotechnology, Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore, India
| | - Chandran Sarankumar
- Department of Plant Breeding and Genetics, Agricultural College and Research Institute, Tamil Nadu Agricultural University, Madurai, India
| | - Pukalenthy Bharathi
- Department of Plant Breeding and Genetics, Agricultural College and Research Institute, Tamil Nadu Agricultural University, Madurai, India
| | - Adhimoolam Karthikeyan
- Department of Biotechnology, Centre of Innovation, Agricultural College and Research Institute, Tamil Nadu Agricultural University, Madurai, India
| | - Soosai Arulselvi
- Agricultural College and Research Institute, Thanjavur, Tamil Nadu Agricultural University, Thanjavur, India
| | - Esvaran Vijayagowri
- Department of Plant Biotechnology, Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore, India
| | - Kalipatty Nalliappan Ganesan
- Department of Forage Crops, Centre for Plant Breeding and Genetics, Tamil Nadu Agricultural University, Coimbatore, India
| | - Vaikuntavasan Paranidharan
- Department of Plant Pathology, Centre for Plant Protection Studies, Tamil Nadu Agricultural University, Coimbatore, India
| | - Sudha K. Nair
- Asian Regional Maize Program, International Maize and Wheat Improvement Center (CIMMYT), ICRISAT Campus, Patancheru, India
| | - Raman Babu
- Corteva Agrisciences, Multi Crop Research Centre, Hyderabad, India
| | - Jegadeesan Ramalingam
- Department of Plant Biotechnology, Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore, India
| | - Muthurajan Raveendran
- Department of Plant Biotechnology, Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore, India
| | - Natesan Senthil
- Department of Biotechnology, Centre of Innovation, Agricultural College and Research Institute, Tamil Nadu Agricultural University, Madurai, India
- Department of Plant Molecular Biology and Bioinformatics, Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore, India
- *Correspondence: Natesan Senthil,
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Yacoubou A, Zoumarou Wallis N, Menkir A, Zinsou VA, Onzo A, Garcia‐Oliveira AL, Meseka S, Wende M, Gedil M, Agre P. Breeding maize ( Zea mays) for Striga resistance: Past, current and prospects in sub-saharan africa. PLANT BREEDING = ZEITSCHRIFT FUR PFLANZENZUCHTUNG 2021; 140:195-210. [PMID: 34239217 PMCID: PMC8248382 DOI: 10.1111/pbr.12896] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/06/2020] [Accepted: 12/21/2020] [Indexed: 05/21/2023]
Abstract
Striga hermonthica, causes up to 100% yield loss in maize production in Sub-Saharan Africa. Developing Striga-resistant maize cultivars could be a major component of integrated Striga management strategies. This paper presents a comprehensive overview of maize breeding activities related to Striga resistance and its management. Scientific surveys have revealed that conventional breeding strategies have been used more than molecular breeding strategies in maize improvement for Striga resistance. Striga resistance genes are still under study in the International Institute for Tropical Agriculture (IITA) maize breeding programme. There is also a need to discover QTL and molecular markers associated with such genes to improve Striga resistance in maize. Marker Assistance Breeding is expected to increase maize breeding efficiency with complex traits such as resistance towards Striga because of the complex nature of the host-parasite relationship and its intersection with other environmental factors. Conventional alongside molecular tools and technical controls are promising methods to effectively assess Striga in Sub-Saharan Africa.
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Affiliation(s)
- Abdoul‐Madjidou Yacoubou
- Laboratoire de Phytotechnie, d’Amélioration et de Protection des Plantes (LaPAPP)Département des Sciences et Techniques de Production Végétale (STPV)Faculté d’AgronomieUniversité de ParakouParakouBénin
- International Institute of Tropical Agriculture (IITA)Oyo RoadPMB 5320IbadanNigeria
- Institut National des Recherches Agricoles du Bénin01 BP 884CotonouBénin
| | - Nouhoun Zoumarou Wallis
- Laboratoire de Phytotechnie, d’Amélioration et de Protection des Plantes (LaPAPP)Département des Sciences et Techniques de Production Végétale (STPV)Faculté d’AgronomieUniversité de ParakouParakouBénin
| | - Abebe Menkir
- International Institute of Tropical Agriculture (IITA)Oyo RoadPMB 5320IbadanNigeria
| | - Valerien A. Zinsou
- Laboratoire de Phytotechnie, d’Amélioration et de Protection des Plantes (LaPAPP)Département des Sciences et Techniques de Production Végétale (STPV)Faculté d’AgronomieUniversité de ParakouParakouBénin
| | - Alexis Onzo
- Laboratoire de Phytotechnie, d’Amélioration et de Protection des Plantes (LaPAPP)Département des Sciences et Techniques de Production Végétale (STPV)Faculté d’AgronomieUniversité de ParakouParakouBénin
| | | | - Silvestro Meseka
- International Institute of Tropical Agriculture (IITA)Oyo RoadPMB 5320IbadanNigeria
| | - Mengesha Wende
- International Institute of Tropical Agriculture (IITA)Oyo RoadPMB 5320IbadanNigeria
| | - Melaku Gedil
- International Institute of Tropical Agriculture (IITA)Oyo RoadPMB 5320IbadanNigeria
| | - Paterne Agre
- International Institute of Tropical Agriculture (IITA)Oyo RoadPMB 5320IbadanNigeria
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López-Malvar A, Butron A, Malvar RA, McQueen-Mason SJ, Faas L, Gómez LD, Revilla P, Figueroa-Garrido DJ, Santiago R. Association mapping for maize stover yield and saccharification efficiency using a multiparent advanced generation intercross (MAGIC) population. Sci Rep 2021; 11:3425. [PMID: 33564080 PMCID: PMC7873224 DOI: 10.1038/s41598-021-83107-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Accepted: 01/13/2021] [Indexed: 11/08/2022] Open
Abstract
Cellulosic ethanol derived from fast growing C4 grasses could become an alternative to finite fossil fuels. With the potential to generate a major source of lignocellulosic biomass, maize has gained importance as an outstanding model plant for studying the complex cell wall network and also to optimize crop breeding strategies in bioenergy grasses. A genome-wide association study (GWAS) was conducted using a subset of 408 Recombinant Inbred Lines (RILs) from a Multi-Parent Advanced Generation Intercross (MAGIC) Population in order to identify single nucleotide polymorphisms (SNPs) associated with yield and saccharification efficiency of maize stover. We identified 13 SNPs significantly associated with increased stover yield that corresponded to 13 QTL, and 2 SNPs significantly associated with improved saccharification efficiency, that could be clustered into 2 QTL. We have pointed out the most interesting SNPs to be implemented in breeding programs based on results from analyses of averaged and yearly data. Association mapping in this MAGIC population highlight genomic regions directly linked to traits that influence the final use of maize. Markers linked to these QTL could be used in genomic or marker-assisted selection programs to improve biomass quality for ethanol production. This study opens a possible optimisation path for improving the viability of second-generation biofuels.
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Affiliation(s)
- A López-Malvar
- Facultad de Biología, Departamento de Biología Vegetal y Ciencias del Suelo, Universidad de Vigo, As Lagoas Marcosende, 36310, Vigo, Spain.
- Agrobiología Ambiental, Calidad de Suelos y Plantas (UVIGO), Unidad Asociada a la MBG (CSIC), Pontevedra, Spain.
| | - A Butron
- Misión Biológica de Galicia (CSIC), Pazo de Salcedo, Carballeira 8, 36143, Pontevedra, Spain
| | - R A Malvar
- Misión Biológica de Galicia (CSIC), Pazo de Salcedo, Carballeira 8, 36143, Pontevedra, Spain
| | - S J McQueen-Mason
- Department of Biology, Centre for Novel Agricultural Products, CNAP, University of York, York, YO10 5DD, UK
| | - L Faas
- Department of Biology, Centre for Novel Agricultural Products, CNAP, University of York, York, YO10 5DD, UK
| | - L D Gómez
- Department of Biology, Centre for Novel Agricultural Products, CNAP, University of York, York, YO10 5DD, UK
| | - P Revilla
- Misión Biológica de Galicia (CSIC), Pazo de Salcedo, Carballeira 8, 36143, Pontevedra, Spain
| | - D J Figueroa-Garrido
- Facultad de Biología, Departamento de Biología Vegetal y Ciencias del Suelo, Universidad de Vigo, As Lagoas Marcosende, 36310, Vigo, Spain
- Agrobiología Ambiental, Calidad de Suelos y Plantas (UVIGO), Unidad Asociada a la MBG (CSIC), Pontevedra, Spain
| | - R Santiago
- Facultad de Biología, Departamento de Biología Vegetal y Ciencias del Suelo, Universidad de Vigo, As Lagoas Marcosende, 36310, Vigo, Spain
- Agrobiología Ambiental, Calidad de Suelos y Plantas (UVIGO), Unidad Asociada a la MBG (CSIC), Pontevedra, Spain
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Muturi PW, Mgonja M, Rubaihayo P, Mwololo JK. QTL Mapping of Traits Associated with Dual Resistance to the African Stem Borer ( Busseola fusca) and Spotted Stem Borer ( Chilo partellus) in Sorghum ( Sorghum bicolor). Int J Genomics 2021; 2021:7016712. [PMID: 33532486 PMCID: PMC7834829 DOI: 10.1155/2021/7016712] [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: 07/17/2020] [Revised: 10/14/2020] [Accepted: 11/16/2020] [Indexed: 11/21/2022] Open
Abstract
Sorghum (Sorghum bicolor (L.) Moench) is an important food crop in semi-arid tropics. The crop grain yield ranges from 0.5 t/ha to 0.8 t/ha compared to potential yields of 10 t/ha. The African stem borer Busseola fusca Fuller (Noctuidae) and the spotted stem borer Chilo partellus Swinhoe (Crambidae), are among the most economically important insect pests of sorghum. The two borers can cause 15% - 80% grain yield loss in sorghum. Mapping of QTLs associated with resistance traits to the two stem borers is important towards marker-assisted breeding. The objective of this study was to map QTLs associated with resistance traits to B. fusca and C. partellus in sorghum. 243 F9:10 sorghum RILs derived from ICSV 745 (S) and PB 15520-1 (R) were selected for the study with 4,955 SNP markers. The RILs were evaluated in three sites. Data was collected on leaf feeding, deadheart, exit holes, stem tunnels, leaf toughness, seedling vigour, bloom waxiness, and leaf glossiness. ANOVA for all the traits was done using Genstat statistical software. Insect damage traits and morphological traits were correlated using Pearson's correlation coefficients. Genetic mapping was done using JoinMap 4 software, while QTL analysis was done using PLABQTL software. A likelihood odds ratio (LOD) score of 3.0 was used to declare linkage. Joint analyses across borer species and sites revealed 4 QTLs controlling deadheart formation; 6 controlling leaf feeding damage; 5 controlling exit holes and stem tunneling damages; 2 controlling bloom waxiness, leaf glossiness, and seedling vigour; 4 conditioning trichome density; and 6 conditioning leaf toughness. Joint analyses for B. fusca and C. partellus further revealed that marker CS132-2 colocalised for leaf toughness and stem tunneling traits on QTLs 1 and 2, respectively; thus, the two traits can be improved using the same linked marker. This study recommended further studies to identify gene(s) underlying the mapped QTLs.
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Affiliation(s)
- Phyllis W. Muturi
- Department of Agricultural Resource Management, University of Embu, P.O. Box 60100, Embu, Kenya
| | - Mary Mgonja
- Alliance for a Green Revolution in Africa, P.O. Box 34441, Dar es Salaam, Tanzania
| | - Patrick Rubaihayo
- Department of Agricultural Production, Makerere University, P.O. Box 7062, Kampala, Uganda
| | - James K. Mwololo
- East and South African Research Program, International Crops Research Institute of the Semi-Arid Tropics (ICRISAT), P.O. Box 1096 Lilongwe, Malawi
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Identification of genomic regions associated with shoot fly resistance in maize and their syntenic relationships in the sorghum genome. PLoS One 2020; 15:e0234335. [PMID: 32516348 PMCID: PMC7282634 DOI: 10.1371/journal.pone.0234335] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Accepted: 05/22/2020] [Indexed: 11/19/2022] Open
Abstract
Shoot fly (Atherigona naqvii) is one of the major insects affecting spring maize in North India and can cause yield loss up to 60 per cent. The genetics of insect resistance is complex as influenced by genotypic background, insect population and climatic conditions. Therefore, quantitative trait loci (QTL) mapping is a highly effective approach for studying genetically complex forms of insect resistance. The objective of the present study was to dissect the genetic basis of resistance and identification of genomic regions associated with shoot fly resistance. A total of 107 F2 population derived from the cross CM143 (resistant) x CM144 (susceptible) was genotyped with 120 SSR markers. Phenotypic data were recorded on replicated F2:3 progenies for various component traits imparting resistance to shoot fly at different time intervals. Resistance to shoot fly was observed to be under polygenic control as evidenced by the identification of 19 putative QTLs governed by overdominance to partial dominance and additive gene actions. The major QTLs conditioning shoot fly resistance viz., qDH9.1 (deadheart) and qEC9.1 (oviposition) explaining 15.03 and 18.89 per cent phenotypic variance, respectively were colocalized on chromosome 9. These QTLs are syntenic to regions of chromosome 10 of sorghum which were also accounted for deadheart and oviposition suggesting that the same gene block may be responsible for shoot fly resistance. The candidate genes such as cysteine protease, subtilisin-chymotrypsin inhibitor, cytochrome P450 involved in synthesis of alleochemicals, receptor kinases, glossy15 and ubiquitin-proteasome degradation pathway were identified within the predicted QTL regions. This is the first reported mapping of QTLs conferring resistance to shoot fly in maize, and the markers identified here will be a valuable resource for developing elite maize cultivars with resistance to shoot fly.
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Zhao Y, Su C. Mapping quantitative trait loci for yield-related traits and predicting candidate genes for grain weight in maize. Sci Rep 2019; 9:16112. [PMID: 31695075 PMCID: PMC6834572 DOI: 10.1038/s41598-019-52222-5] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2019] [Accepted: 10/15/2019] [Indexed: 01/26/2023] Open
Abstract
Quantitative trait loci (QTLs) mapped in different genetic populations are of great significance for marker-assisted breeding. In this study, an F2:3 population were developed from the crossing of two maize inbred lines SG-5 and SG-7 and applied to QTL mapping for seven yield-related traits. The seven traits included 100-kernel weight, ear length, ear diameter, cob diameter, kernel row number, ear weight, and grain weight per plant. Based on an ultra-high density linkage map, a total of thirty-three QTLs were detected for the seven studied traits with composite interval mapping (CIM) method, and fifty-four QTLs were indentified with genome-wide composite interval mapping (GCIM) methods. For these QTLs, Fourteen were both detected by CIM and GCIM methods. Besides, eight of the thirty QTLs detected by CIM were identical to those previously mapped using a F2 population (generating from the same cross as the mapping population in this study), and fifteen were identical to the reported QTLs in other recent studies. For the fifty-four QTLs detected by GCIM, five of them were consistent with the QTLs mapped in the F2 population of SG-5 × SG-7, and twenty one had been reported in other recent studies. The stable QTLs associated with grain weight were located on maize chromosomes 2, 5, 7, and 9. In addition, differentially expressed genes (DEGs) between SG-5 and SG-7 were obtained from the transcriptomic profiling of grain at different developmental stages and overlaid onto the stable QTLs intervals to predict candidate genes for grain weight in maize. In the physical intervals of confirmed QTLs qKW-7, qEW-9, qEW-10, qGWP-6, qGWP-8, qGWP-10, qGWP-11 and qGWP-12, there were 213 DEGs in total. Finally, eight genes were predicted as candidate genes for grain size/weight. In summary, the stable QTLs would be reliable and the candidate genes predicted would be benefit for maker assisted breeding or cloning.
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Affiliation(s)
- Yanming Zhao
- College of Agronomy, Qingdao Agricultural University, Qingdao, 266109, P.R. China
| | - Chengfu Su
- College of Agronomy, Qingdao Agricultural University, Qingdao, 266109, P.R. China.
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Jiménez-Galindo JC, Malvar RA, Butrón A, Santiago R, Samayoa LF, Caicedo M, Ordás B. Mapping of resistance to corn borers in a MAGIC population of maize. BMC PLANT BIOLOGY 2019; 19:431. [PMID: 31623579 PMCID: PMC6796440 DOI: 10.1186/s12870-019-2052-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2018] [Accepted: 09/24/2019] [Indexed: 05/05/2023]
Abstract
BACKGROUND Corn borers constitute an important pest of maize around the world; in particular Sesamia nonagrioides Lefèbvre, named Mediterranean corn borer (MCB), causes important losses in Southern Europe. Methods of selection can be combined with transgenic approaches to increase the efficiency and durability of the resistance to corn borers. Previous studies of the genetic factors involved in resistance to MCB have been carried out using bi-parental populations that have low resolution or using association inbred panels that have a low power to detect rare alleles. We developed a Multi-parent Advanced Generation InterCrosses (MAGIC) population to map with high resolution the genetic determinants of resistance to MCB. RESULTS We detected multiple single nucleotide polymorphisms (SNPs) of low effect associated with resistance to stalk tunneling by MCB. We dissected a wide region related to stalk tunneling in multiple studies into three smaller regions (at ~ 150, ~ 155, and ~ 165 Mb in chromosome 6) that closely overlap with regions associated with cell wall composition. We also detected regions associated with kernel resistance and agronomic traits, although the co-localization of significant regions between traits was very low. This indicates that it is possible the concurrent improvement of resistance and agronomic traits. CONCLUSIONS We developed a mapping population which allowed a finer dissection of the genetics of maize resistance to corn borers and a solid nomination of candidate genes based on functional information. The population, given its large variability, was also adequate to map multiple traits and study the relationship between them.
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Affiliation(s)
- José Cruz Jiménez-Galindo
- Misión Biológica de Galicia, Spanish National Research Council (CSIC), Apartado 28, 36080 Pontevedra, Spain
- National Institute of Forestry, Agriculture and Livestock Research (INIFAP), Ave. Hidalgo 1213, Cd. Cuauhtémoc, 31500 Chihuahua, Mexico
| | - Rosa Ana Malvar
- Misión Biológica de Galicia, Spanish National Research Council (CSIC), Apartado 28, 36080 Pontevedra, Spain
| | - Ana Butrón
- Misión Biológica de Galicia, Spanish National Research Council (CSIC), Apartado 28, 36080 Pontevedra, Spain
| | - Rogelio Santiago
- Departamento Biología Vegetal y Ciencias del Suelo, Unidad Asociada BVE1-UVIGO y MBG (CSIC), Facultad de Biología, Universidad de Vigo, Campus As Lagoas Marcosende, 36310 Vigo, Spain
| | - Luis Fernando Samayoa
- North Carolina State University, 4210 Williams Hall 101, Derieux Place, Raleigh, NC 27695 USA
- Department of Crop and Soil Sciences, North Carolina State University, Raleigh, NC 27695-7620 USA
| | - Marlon Caicedo
- Instituto Nacional de Investigaciones Agropecuarias (INIAP), 170315 Quito, Ecuador
| | - Bernardo Ordás
- Misión Biológica de Galicia, Spanish National Research Council (CSIC), Apartado 28, 36080 Pontevedra, Spain
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Badji A, Otim M, Machida L, Odong T, Kwemoi DB, Okii D, Agbahoungba S, Mwila N, Kumi F, Ibanda A, Mugo S, Kyamanywa S, Rubaihayo P. Maize Combined Insect Resistance Genomic Regions and Their Co-localization With Cell Wall Constituents Revealed by Tissue-Specific QTL Meta-Analyses. FRONTIERS IN PLANT SCIENCE 2018; 9:895. [PMID: 30026746 PMCID: PMC6041972 DOI: 10.3389/fpls.2018.00895] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/01/2017] [Accepted: 06/07/2018] [Indexed: 05/09/2023]
Abstract
Combinatorial insect attacks on maize leaves, stems, and kernels cause significant yield losses and mycotoxin contaminations. Several small effect quantitative trait loci (QTL) control maize resistance to stem borers and storage pests and are correlated with secondary metabolites. However, efficient use of QTL in molecular breeding requires a synthesis of the available resistance information. In this study, separate meta-analyses of QTL of maize response to stem borers and storage pests feeding on leaves, stems, and kernels along with maize cell wall constituents discovered in these tissues generated 24 leaf (LIR), 42 stem (SIR), and 20 kernel (KIR) insect resistance meta-QTL (MQTL) of a diverse genetic and geographical background. Most of these MQTL involved resistance to several insect species, therefore, generating a significant interest for multiple-insect resistance breeding. Some of the LIR MQTL such as LIR4, 17, and 22 involve resistance to European corn borer, sugarcane borer, and southwestern corn borer. Eleven out of the 42 SIR MQTL related to resistance to European corn borer and Mediterranean corn borer. There KIR MQTL, KIR3, 15, and 16 combined resistance to kernel damage by the maize weevil and the Mediterranean corn borer and could be used in breeding to reduce insect-related post-harvest grain yield loss and field to storage mycotoxin contamination. This meta-analysis corroborates the significant role played by cell wall constituents in maize resistance to insect since the majority of the MQTL contain QTL for members of the hydroxycinnamates group such as p-coumaric acid, ferulic acid, and other diferulates and derivates, and fiber components such as acid detergent fiber, neutral detergent fiber, and lignin. Stem insect resistance MQTL display several co-localization between fiber and hydroxycinnamate components corroborating the hypothesis of cross-linking between these components that provide mechanical resistance to insect attacks. Our results highlight the existence of combined-insect resistance genomic regions in maize and set the basis of multiple-pests resistance breeding.
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Affiliation(s)
- Arfang Badji
- Department of Agricultural Production, Makerere University, Kampala, Uganda
- *Correspondence: Arfang Badji
| | - Michael Otim
- Cereals Program, National Crop Resource Research Institute, Kampala, Uganda
| | - Lewis Machida
- International Maize and Wheat Improvement Center, Nairobi, Kenya
| | - Thomas Odong
- Department of Agricultural Production, Makerere University, Kampala, Uganda
| | | | - Dennis Okii
- Department of Agricultural Production, Makerere University, Kampala, Uganda
| | | | - Natasha Mwila
- Department of Agricultural Production, Makerere University, Kampala, Uganda
| | - Frank Kumi
- Department of Agricultural Production, Makerere University, Kampala, Uganda
| | - Angele Ibanda
- Department of Agricultural Production, Makerere University, Kampala, Uganda
| | - Stephen Mugo
- International Maize and Wheat Improvement Center, Nairobi, Kenya
| | - Samuel Kyamanywa
- Department of Agricultural Production, Makerere University, Kampala, Uganda
| | - Patrick Rubaihayo
- Department of Agricultural Production, Makerere University, Kampala, Uganda
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