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Kapoor C, Anamika, Mukesh Sankar S, Singh SP, Singh N, Kumar S. Omics-driven utilization of wild relatives for empowering pre-breeding in pearl millet. PLANTA 2024; 259:155. [PMID: 38750378 DOI: 10.1007/s00425-024-04423-0] [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: 12/17/2023] [Accepted: 04/25/2024] [Indexed: 05/23/2024]
Abstract
MAIN CONCLUSION Pearl millet wild relatives harbour novel alleles which could be utilized to broaden genetic base of cultivated species. Genomics-informed pre-breeding is needed to speed up introgression from wild to cultivated gene pool in pearl millet. Rising episodes of intense biotic and abiotic stresses challenge pearl millet production globally. Wild relatives provide a wide spectrum of novel alleles which could address challenges posed by climate change. Pre-breeding holds potential to introgress novel diversity in genetically narrow cultivated Pennisetum glaucum from diverse gene pool. Practical utilization of gene pool diversity remained elusive due to genetic intricacies. Harnessing promising traits from wild pennisetum is limited by lack of information on underlying candidate genes/QTLs. Next-Generation Omics provide vast scope to speed up pre-breeding in pearl millet. Genomic resources generated out of draft genome sequence and improved genome assemblies can be employed to utilize gene bank accessions effectively. The article highlights genetic richness in pearl millet and its utilization with a focus on harnessing next-generation Omics to empower pre-breeding.
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Affiliation(s)
- Chandan Kapoor
- ICAR-Indian Agricultural Research Institute, New Delhi, 110012, India.
| | - Anamika
- ICAR-Indian Agricultural Research Institute, New Delhi, 110012, India
| | - S Mukesh Sankar
- ICAR-Indian Institute of Spices Research, Kozhikode, Kerala, 673012, India
| | - S P Singh
- ICAR-Indian Agricultural Research Institute, New Delhi, 110012, India
| | - Nirupma Singh
- ICAR-Indian Agricultural Research Institute, New Delhi, 110012, India
| | - Sudhir Kumar
- ICAR-Indian Agricultural Research Institute, New Delhi, 110012, India
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2
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Chang-Brahim I, Koppensteiner LJ, Beltrame L, Bodner G, Saranti A, Salzinger J, Fanta-Jende P, Sulzbachner C, Bruckmüller F, Trognitz F, Samad-Zamini M, Zechner E, Holzinger A, Molin EM. Reviewing the essential roles of remote phenotyping, GWAS and explainable AI in practical marker-assisted selection for drought-tolerant winter wheat breeding. FRONTIERS IN PLANT SCIENCE 2024; 15:1319938. [PMID: 38699541 PMCID: PMC11064034 DOI: 10.3389/fpls.2024.1319938] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Accepted: 03/13/2024] [Indexed: 05/05/2024]
Abstract
Marker-assisted selection (MAS) plays a crucial role in crop breeding improving the speed and precision of conventional breeding programmes by quickly and reliably identifying and selecting plants with desired traits. However, the efficacy of MAS depends on several prerequisites, with precise phenotyping being a key aspect of any plant breeding programme. Recent advancements in high-throughput remote phenotyping, facilitated by unmanned aerial vehicles coupled to machine learning, offer a non-destructive and efficient alternative to traditional, time-consuming, and labour-intensive methods. Furthermore, MAS relies on knowledge of marker-trait associations, commonly obtained through genome-wide association studies (GWAS), to understand complex traits such as drought tolerance, including yield components and phenology. However, GWAS has limitations that artificial intelligence (AI) has been shown to partially overcome. Additionally, AI and its explainable variants, which ensure transparency and interpretability, are increasingly being used as recognised problem-solving tools throughout the breeding process. Given these rapid technological advancements, this review provides an overview of state-of-the-art methods and processes underlying each MAS, from phenotyping, genotyping and association analyses to the integration of explainable AI along the entire workflow. In this context, we specifically address the challenges and importance of breeding winter wheat for greater drought tolerance with stable yields, as regional droughts during critical developmental stages pose a threat to winter wheat production. Finally, we explore the transition from scientific progress to practical implementation and discuss ways to bridge the gap between cutting-edge developments and breeders, expediting MAS-based winter wheat breeding for drought tolerance.
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Affiliation(s)
- Ignacio Chang-Brahim
- Unit Bioresources, Center for Health & Bioresources, AIT Austrian Institute of Technology, Tulln, Austria
| | | | - Lorenzo Beltrame
- Unit Assistive and Autonomous Systems, Center for Vision, Automation & Control, AIT Austrian Institute of Technology, Vienna, Austria
| | - Gernot Bodner
- Department of Crop Sciences, Institute of Agronomy, University of Natural Resources and Life Sciences Vienna, Tulln, Austria
| | - Anna Saranti
- Human-Centered AI Lab, Department of Forest- and Soil Sciences, Institute of Forest Engineering, University of Natural Resources and Life Sciences Vienna, Vienna, Austria
| | - Jules Salzinger
- Unit Assistive and Autonomous Systems, Center for Vision, Automation & Control, AIT Austrian Institute of Technology, Vienna, Austria
| | - Phillipp Fanta-Jende
- Unit Assistive and Autonomous Systems, Center for Vision, Automation & Control, AIT Austrian Institute of Technology, Vienna, Austria
| | - Christoph Sulzbachner
- Unit Assistive and Autonomous Systems, Center for Vision, Automation & Control, AIT Austrian Institute of Technology, Vienna, Austria
| | - Felix Bruckmüller
- Unit Assistive and Autonomous Systems, Center for Vision, Automation & Control, AIT Austrian Institute of Technology, Vienna, Austria
| | - Friederike Trognitz
- Unit Bioresources, Center for Health & Bioresources, AIT Austrian Institute of Technology, Tulln, Austria
| | | | - Elisabeth Zechner
- Verein zur Förderung einer nachhaltigen und regionalen Pflanzenzüchtung, Zwettl, Austria
| | - Andreas Holzinger
- Human-Centered AI Lab, Department of Forest- and Soil Sciences, Institute of Forest Engineering, University of Natural Resources and Life Sciences Vienna, Vienna, Austria
| | - Eva M. Molin
- Unit Bioresources, Center for Health & Bioresources, AIT Austrian Institute of Technology, Tulln, Austria
- Human-Centered AI Lab, Department of Forest- and Soil Sciences, Institute of Forest Engineering, University of Natural Resources and Life Sciences Vienna, Vienna, Austria
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3
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Guo M, Deng L, Gu J, Miao J, Yin J, Li Y, Fang Y, Huang B, Sun Z, Qi F, Dong W, Lu Z, Li S, Hu J, Zhang X, Ren L. Genome-wide association study and development of molecular markers for yield and quality traits in peanut (Arachis hypogaea L.). BMC PLANT BIOLOGY 2024; 24:244. [PMID: 38575936 PMCID: PMC10996145 DOI: 10.1186/s12870-024-04937-5] [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: 05/06/2023] [Accepted: 03/20/2024] [Indexed: 04/06/2024]
Abstract
BACKGROUND This study aims to decipher the genetic basis governing yield components and quality attributes of peanuts, a critical aspect for advancing molecular breeding techniques. Integrating genotype re-sequencing and phenotypic evaluations of seven yield components and two grain quality traits across four distinct environments allowed for the execution of a genome-wide association study (GWAS). RESULTS The nine phenotypic traits were all continuous and followed a normal distribution. The broad heritability ranged from 88.09 to 98.08%, and the genotype-environment interaction effects were all significant. There was a highly significant negative correlation between protein content (PC) and oil content (OC). The 10× genome re-sequencing of 199 peanut accessions yielded a total of 631,988 high-quality single nucleotide polymorphisms (SNPs), with 374 significant SNP loci identified in association with the nine traits of interest. Notably, 66 of these pertinent SNPs were detected in multiple environments, and 48 of them were linked to multiple traits of interest. Five loci situated on chromosome 16 (Chr16) exhibited pleiotropic effects on yield traits, accounting for 17.64-32.61% of the observed phenotypic variation. Two loci on Chr08 were found to be strongly associated with protein and oil contents, accounting for 12.86% and 14.06% of their respective phenotypic variations, respectively. Linkage disequilibrium (LD) block analysis of these seven loci unraveled five nonsynonymous variants, leading to the identification of one yield-related candidate gene and two quality-related candidate genes. The correlation between phenotypic variation and SNP loci in these candidate genes was validated by Kompetitive allele-specific PCR (KASP) marker analysis. CONCLUSIONS Overall, molecular markers were developed for genetic loci associated with yield and quality traits through a GWAS investigation of 199 peanut accessions across four distinct environments. These molecular tools can aid in the development of desirable peanut germplasm with an equilibrium of yield and quality through marker-assisted breeding.
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Affiliation(s)
- Minjie Guo
- Peanut Institute, Kaifeng Academy of Agricultural and Forestry Sciences, Kaifeng, 475004, China
| | - Li Deng
- Peanut Institute, Kaifeng Academy of Agricultural and Forestry Sciences, Kaifeng, 475004, China
| | - Jianzhong Gu
- Peanut Institute, Kaifeng Academy of Agricultural and Forestry Sciences, Kaifeng, 475004, China
| | - Jianli Miao
- Peanut Institute, Kaifeng Academy of Agricultural and Forestry Sciences, Kaifeng, 475004, China
| | - Junhua Yin
- Peanut Institute, Kaifeng Academy of Agricultural and Forestry Sciences, Kaifeng, 475004, China
| | - Yang Li
- Peanut Institute, Kaifeng Academy of Agricultural and Forestry Sciences, Kaifeng, 475004, China
| | - Yuanjin Fang
- Shennong Laboratory, Henan Provincial Key Laboratory for Oil Crops Improvement, Henan Academy of Crop Molecular Breeding, Henan Academy of Agricultural Sciences, Zhengzhou, 450002, China
| | - Bingyan Huang
- Shennong Laboratory, Henan Provincial Key Laboratory for Oil Crops Improvement, Henan Academy of Crop Molecular Breeding, Henan Academy of Agricultural Sciences, Zhengzhou, 450002, China
| | - Ziqi Sun
- Shennong Laboratory, Henan Provincial Key Laboratory for Oil Crops Improvement, Henan Academy of Crop Molecular Breeding, Henan Academy of Agricultural Sciences, Zhengzhou, 450002, China
| | - Feiyan Qi
- Shennong Laboratory, Henan Provincial Key Laboratory for Oil Crops Improvement, Henan Academy of Crop Molecular Breeding, Henan Academy of Agricultural Sciences, Zhengzhou, 450002, China
| | - Wenzhao Dong
- Shennong Laboratory, Henan Provincial Key Laboratory for Oil Crops Improvement, Henan Academy of Crop Molecular Breeding, Henan Academy of Agricultural Sciences, Zhengzhou, 450002, China
| | - Zhenhua Lu
- Peanut Institute, Kaifeng Academy of Agricultural and Forestry Sciences, Kaifeng, 475004, China
| | - Shaowei Li
- Peanut Institute, Kaifeng Academy of Agricultural and Forestry Sciences, Kaifeng, 475004, China
| | - Junping Hu
- Peanut Institute, Kaifeng Academy of Agricultural and Forestry Sciences, Kaifeng, 475004, China
| | - Xinyou Zhang
- Shennong Laboratory, Henan Provincial Key Laboratory for Oil Crops Improvement, Henan Academy of Crop Molecular Breeding, Henan Academy of Agricultural Sciences, Zhengzhou, 450002, China.
| | - Li Ren
- Peanut Institute, Kaifeng Academy of Agricultural and Forestry Sciences, Kaifeng, 475004, China.
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Ding Y, Fang H, Gao Y, Fan G, Shi X, Yu S, Ding S, Huang T, Wang W, Song J. Genome-wide association analysis of time to heading and maturity in bread wheat using 55K microarrays. FRONTIERS IN PLANT SCIENCE 2023; 14:1296197. [PMID: 38107003 PMCID: PMC10722194 DOI: 10.3389/fpls.2023.1296197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Accepted: 11/14/2023] [Indexed: 12/19/2023]
Abstract
To investigate the genetic mechanisms underlying the reproductive traits (time to flowering and maturity) in wheat and identify candidate genes associated, a phenotypic analysis was conducted on 239 wheat accessions (lines) from around the world. A genome-wide association study (GWAS) of wheat heading and maturity phases was performed using the MLM (Q+K) model in the TASSLE software, combined with the Wheat 55K SNP array. The results revealed significant phenotypic variation in heading and maturity among the wheat accessions across different years, with coefficients of variation ranging from 0.96% to 1.97%. The phenotypic data from different years exhibited excellent correlation, with a genome-wide linkage disequilibrium (LD) attenuation distance of 3 Mb. Population structure analysis, evolutionary tree analysis, and principal component analysis indicated that the 239 wheat accessions formed a relatively homogeneous natural population, which could be divided into three subgroups. The GWAS results identified a total of 293 SNP marker loci that were significantly associated with wheat heading and maturity stages (P ≤ 0.001) in different environments. Among them, nine stable SNP marker loci were consistently detected in multiple environments. These marker loci were distributed on wheat chromosomes 1A、1B、2D、3A、5B、6D and 7A. Each individual locus explained 4.03%-16.06% of the phenotypic variation. Furthermore, through careful analysis of the associated loci with large phenotypic effect values and stable inheritance, a total of nine candidate genes related to wheat heading and maturity stages were identified. These findings have implications for molecular marker-assisted selection breeding programs targeting specific wheat traits at the heading and maturity stages. In summary, this study conducted a comprehensive GWAS of wheat heading and maturity phases, revealing significant associations between genetic markers and key developmental stages in wheat. The identification of candidate genes and marker loci provides valuable information for further studies on wheat breeding and genetic improvement targeted at enhancing heading and maturity traits.
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Affiliation(s)
- Yindeng Ding
- Institute of Grain Crops, Xinjiang Academy of Agricultural Sciences, Urumqi, Xinjiang, China
| | - Hui Fang
- Institute of Grain Crops, Xinjiang Academy of Agricultural Sciences, Urumqi, Xinjiang, China
| | - Yonghong Gao
- Institute of Grain Crops, Xinjiang Academy of Agricultural Sciences, Urumqi, Xinjiang, China
| | - Guiqiang Fan
- Institute of Grain Crops, Xinjiang Academy of Agricultural Sciences, Urumqi, Xinjiang, China
| | - Xiaolei Shi
- Institute of Crop Variety Resources, Xinjiang Academy of Agricultural Sciences, Urumqi, Xinjiang, China
| | - Shan Yu
- College of Agriculture, Xinjiang Agricultural University, Urumqi, Xinjiang, China
| | - Sunlei Ding
- Institute of Crop Variety Resources, Xinjiang Academy of Agricultural Sciences, Urumqi, Xinjiang, China
| | - Tianrong Huang
- Institute of Grain Crops, Xinjiang Academy of Agricultural Sciences, Urumqi, Xinjiang, China
| | - Wei Wang
- Department of Computer Science and Information Engineering, Anyang Institute of Technology, Anyang, China
| | - Jikun Song
- Cotton Research Institute, Chinese Academy of Agricultural Sciences, Anyang, China
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5
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Minow MAA, Marand AP, Schmitz RJ. Leveraging Single-Cell Populations to Uncover the Genetic Basis of Complex Traits. Annu Rev Genet 2023; 57:297-319. [PMID: 37562412 PMCID: PMC10775913 DOI: 10.1146/annurev-genet-022123-110824] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/12/2023]
Abstract
The ease and throughput of single-cell genomics have steadily improved, and its current trajectory suggests that surveying single-cell populations will become routine. We discuss the merger of quantitative genetics with single-cell genomics and emphasize how this synergizes with advantages intrinsic to plants. Single-cell population genomics provides increased detection resolution when mapping variants that control molecular traits, including gene expression or chromatin accessibility. Additionally, single-cell population genomics reveals the cell types in which variants act and, when combined with organism-level phenotype measurements, unveils which cellular contexts impact higher-order traits. Emerging technologies, notably multiomics, can facilitate the measurement of both genetic changes and genomic traits in single cells, enabling single-cell genetic experiments. The implementation of single-cell genetics will advance the investigation of the genetic architecture of complex molecular traits and provide new experimental paradigms to study eukaryotic genetics.
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Affiliation(s)
- Mark A A Minow
- Department of Genetics, University of Georgia, Athens, Georgia, USA;
| | | | - Robert J Schmitz
- Department of Genetics, University of Georgia, Athens, Georgia, USA;
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6
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Zhang H, Hansson B. RecView: an interactive R application for locating recombination positions using pedigree data. BMC Genomics 2023; 24:712. [PMID: 38007417 PMCID: PMC10676570 DOI: 10.1186/s12864-023-09807-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Accepted: 11/14/2023] [Indexed: 11/27/2023] Open
Abstract
BACKGROUND Recombination reshuffles alleles at linked loci, allowing genes to evolve independently and consequently enhancing the efficiency of selection. This makes quantifying recombination along chromosomes an important goal for understanding how selection and drift are acting on genes and chromosomes. RESULTS We present RecView, an interactive R application and its homonymous R package, to facilitate locating recombination positions along chromosomes or scaffolds using whole-genome genotype data of a three-generation pedigree. RecView analyses and plots the grandparent-of-origin of all informative alleles along each chromosome of the offspring in the pedigree, and infers recombination positions with either of two built-in algorithms: one based on change in the proportion of the alleles with specific grandparent-of-origin, and one on the degree of continuity of alleles with the same grandparent-of-origin. RecView handles multiple offspring and chromosomes simultaneously, and all putative recombination positions are reported in base pairs together with an estimated precision based on the local density of informative alleles. We demonstrate RecView using genotype data of a passerine bird with an available reference genome, the great reed warbler (Acrocephalus arundinaceus), and show that recombination events can be located to specific positions. CONCLUSIONS RecView is an easy-to-use and highly effective application for locating recombination positions with high precision. RecView is available on GitHub ( https://github.com/HKyleZhang/RecView.git ).
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Affiliation(s)
- Hongkai Zhang
- Department of Biology, Lund University, Lund, 22362, Sweden.
| | - Bengt Hansson
- Department of Biology, Lund University, Lund, 22362, Sweden.
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7
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Ellis N, Hofer J, Sizer-Coverdale E, Lloyd D, Aubert G, Kreplak J, Burstin J, Cheema J, Bal M, Chen Y, Deng S, Wouters RHM, Steuernagel B, Chayut N, Domoney C. Recombinant inbred lines derived from wide crosses in Pisum. Sci Rep 2023; 13:20408. [PMID: 37990072 PMCID: PMC10663473 DOI: 10.1038/s41598-023-47329-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Accepted: 11/12/2023] [Indexed: 11/23/2023] Open
Abstract
Genomic resources are becoming available for Pisum but to link these to phenotypic diversity requires well marked populations segregating for relevant traits. Here we describe two such resources. Two recombinant inbred populations, derived from wide crosses in Pisum are described. One high resolution mapping population involves cv Caméor, for which the first pea whole genome assembly was obtained, crossed to JI0281, a basally divergent P. sativum sativum landrace from Ethiopia. The other is an inter sub-specific cross between P. s. sativum and the independently domesticated P. s. abyssinicum. The corresponding genetic maps provide information on chromosome level sequence assemblies and identify structural differences between the genomes of these two Pisum subspecies. In order to visualise chromosomal translocations that distinguish the mapping parents, we created a simplified version of Threadmapper to optimise it for interactive 3-dimensional display of multiple linkage groups. The genetic mapping of traits affecting seed coat roughness and colour, plant height, axil ring pigmentation, leaflet number and leaflet indentation enabled the definition of their corresponding genomic regions. The consequence of structural rearrangement for trait analysis is illustrated by leaf serration. These analyses pave the way for identification of the underlying genes and illustrate the utility of these publicly available resources. Segregating inbred populations derived from wide crosses in Pisum, together with the associated marker data, are made publicly available for trait dissection. Genetic analysis of these populations is informative about chromosome scale assemblies, structural diversity in the pea genome and has been useful for the fine mapping of several discrete and quantitative traits.
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Affiliation(s)
- N Ellis
- John Innes Centre, Norwich Research Park, Colney Lane, Norwich, NR4 7UH, UK.
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Plas Gogerddan, Aberystwyth, SY23 3EB, UK.
| | - J Hofer
- John Innes Centre, Norwich Research Park, Colney Lane, Norwich, NR4 7UH, UK
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Plas Gogerddan, Aberystwyth, SY23 3EB, UK
| | - E Sizer-Coverdale
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Plas Gogerddan, Aberystwyth, SY23 3EB, UK
- Germinal Horizon, Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Plas Gogerddan, Aberystwyth, SY23 3EB, UK
| | - D Lloyd
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Plas Gogerddan, Aberystwyth, SY23 3EB, UK
- Germinal Horizon, Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Plas Gogerddan, Aberystwyth, SY23 3EB, UK
| | - G Aubert
- Agroécologie, INRAE, Institut Agro, Univ. Bourgogne, Univ. Bourgogne Franche-Comté, 21000, Dijon, France
| | - J Kreplak
- Agroécologie, INRAE, Institut Agro, Univ. Bourgogne, Univ. Bourgogne Franche-Comté, 21000, Dijon, France
| | - J Burstin
- Agroécologie, INRAE, Institut Agro, Univ. Bourgogne, Univ. Bourgogne Franche-Comté, 21000, Dijon, France
| | - J Cheema
- John Innes Centre, Norwich Research Park, Colney Lane, Norwich, NR4 7UH, UK
| | - M Bal
- John Innes Centre, Norwich Research Park, Colney Lane, Norwich, NR4 7UH, UK
| | - Y Chen
- John Innes Centre, Norwich Research Park, Colney Lane, Norwich, NR4 7UH, UK
| | - S Deng
- John Innes Centre, Norwich Research Park, Colney Lane, Norwich, NR4 7UH, UK
| | - R H M Wouters
- John Innes Centre, Norwich Research Park, Colney Lane, Norwich, NR4 7UH, UK
| | - B Steuernagel
- John Innes Centre, Norwich Research Park, Colney Lane, Norwich, NR4 7UH, UK
| | - N Chayut
- John Innes Centre, Norwich Research Park, Colney Lane, Norwich, NR4 7UH, UK
| | - C Domoney
- John Innes Centre, Norwich Research Park, Colney Lane, Norwich, NR4 7UH, UK
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8
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Zemach I, Alseekh S, Tadmor-Levi R, Fisher J, Torgeman S, Trigerman S, Nauen J, Hayut SF, Mann V, Rochsar E, Finkers R, Wendenburg R, Osorio S, Bergmann S, Lunn JE, Semel Y, Hirschberg J, Fernie AR, Zamir D. Multi-year field trials provide a massive repository of trait data on a highly diverse population of tomato and uncover novel determinants of tomato productivity. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2023; 116:1136-1151. [PMID: 37150955 DOI: 10.1111/tpj.16268] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 04/21/2023] [Accepted: 04/29/2023] [Indexed: 05/09/2023]
Abstract
Tomato (Solanum lycopersicum) is a prominent fruit with rich genetic resources for crop improvement. By using a phenotype-guided screen of over 7900 tomato accessions from around the world, we identified new associations for complex traits such as fruit weight and total soluble solids (Brix). Here, we present the phenotypic data from several years of trials. To illustrate the power of this dataset we use two case studies. First, evaluation of color revealed allelic variation in phytoene synthase 1 that resulted in differently colored or even bicolored fruit. Secondly, in view of the negative relationship between fruit weight and Brix, we pre-selected a subset of the collection that includes high and low Brix values in each category of fruit size. Genome-wide association analysis allowed us to detect novel loci associated with total soluble solid content and fruit weight. In addition, we developed eight F2 biparental intraspecific populations. Furthermore, by taking a phenotype-guided approach we were able to isolate individuals with high Brix values that were not compromised in terms of yield. In addition, the demonstration of novel results despite the high number of previous genome-wide association studies of these traits in tomato suggests that adoption of a phenotype-guided pre-selection of germplasm may represent a useful strategy for finding target genes for breeding.
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Affiliation(s)
- Itay Zemach
- The Robert H Smith Faculty of Agriculture, Food and Environment, Hebrew University of Jerusalem, Rehovot, Israel
| | - Saleh Alseekh
- Max-Planck-Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476, Potsdam-Golm, Germany
- Center of Plant Systems Biology and Biotechnology, 4000, Plovdiv, Bulgaria
| | - Roni Tadmor-Levi
- The Robert H Smith Faculty of Agriculture, Food and Environment, Hebrew University of Jerusalem, Rehovot, Israel
| | - Josef Fisher
- The Robert H Smith Faculty of Agriculture, Food and Environment, Hebrew University of Jerusalem, Rehovot, Israel
| | - Shai Torgeman
- The Robert H Smith Faculty of Agriculture, Food and Environment, Hebrew University of Jerusalem, Rehovot, Israel
| | - Shay Trigerman
- The Robert H Smith Faculty of Agriculture, Food and Environment, Hebrew University of Jerusalem, Rehovot, Israel
| | - Julia Nauen
- Max-Planck-Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476, Potsdam-Golm, Germany
| | - Shdema Filler Hayut
- Department of Genetics, Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, 9190401, Israel
| | - Varda Mann
- Department of Genetics, Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, 9190401, Israel
| | - Edan Rochsar
- The Robert H Smith Faculty of Agriculture, Food and Environment, Hebrew University of Jerusalem, Rehovot, Israel
| | - Richard Finkers
- Plant Breeding, Wageningen Plant Research, Droevendaalsesteeg 1, 6708PB, Wageningen, The Netherlands
| | - Regina Wendenburg
- Max-Planck-Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476, Potsdam-Golm, Germany
| | - Sonia Osorio
- Max-Planck-Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476, Potsdam-Golm, Germany
- Department of Molecular Biology and Biochemistry, Instituto de Hortofruticultura Subtropical y Mediterranea "La Mayora", University of Malaga-Consejo Superior de Investigaciones Cientıficas, Malaga, Spain
| | - Susan Bergmann
- Max-Planck-Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476, Potsdam-Golm, Germany
| | - John E Lunn
- Max-Planck-Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476, Potsdam-Golm, Germany
| | - Yaniv Semel
- Phenome Networks, 10 Plaut Street, Science Park, 76706, Rehovot, Israel
| | - Joseph Hirschberg
- Department of Genetics, Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, 9190401, Israel
| | - Alisdair R Fernie
- Max-Planck-Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476, Potsdam-Golm, Germany
- Center of Plant Systems Biology and Biotechnology, 4000, Plovdiv, Bulgaria
| | - Dani Zamir
- The Robert H Smith Faculty of Agriculture, Food and Environment, Hebrew University of Jerusalem, Rehovot, Israel
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9
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James ME, Allsopp RN, Groh JS, Kaur A, Wilkinson MJ, Ortiz-Barrientos D. Uncovering the genetic architecture of parallel evolution. Mol Ecol 2023; 32:5575-5589. [PMID: 37740681 DOI: 10.1111/mec.17134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 07/31/2023] [Accepted: 08/07/2023] [Indexed: 09/25/2023]
Abstract
Identifying the genetic architecture underlying adaptive traits is exceptionally challenging in natural populations. This is because associations between traits not only mask the targets of selection but also create correlated patterns of genomic divergence that hinder our ability to isolate causal genetic effects. Here, we examine the repeated evolution of components of the auxin pathway that have contributed to the replicated loss of gravitropism (i.e. the ability of a plant to bend in response to gravity) in multiple populations of the Senecio lautus species complex in Australia. We use a powerful approach which combines parallel population genomics with association mapping in a Multiparent Advanced Generation Inter-Cross (MAGIC) population to break down genetic and trait correlations to reveal how adaptive traits evolve during replicated evolution. We sequenced auxin and shoot gravitropism-related gene regions in 80 individuals from six natural populations (three parallel divergence events) and 133 individuals from a MAGIC population derived from two of the recently diverged natural populations. We show that artificial tail selection on gravitropism in the MAGIC population recreates patterns of parallel divergence in the auxin pathway in the natural populations. We reveal a set of 55 auxin gene regions that have evolved repeatedly during the evolution of the species, of which 50 are directly associated with gravitropism divergence in the MAGIC population. Our work creates a strong link between patterns of genomic divergence and trait variation contributing to replicated evolution by natural selection, paving the way to understand the origin and maintenance of adaptations in natural populations.
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Affiliation(s)
- Maddie E James
- School of Biological Sciences, The University of Queensland, St Lucia, Queensland, Australia
- Australian Research Council Centre of Excellence for Plant Success in Nature and Agriculture, The University of Queensland, St Lucia, Queensland, Australia
| | - Robin N Allsopp
- School of Biological Sciences, The University of Queensland, St Lucia, Queensland, Australia
| | - Jeffrey S Groh
- School of Biological Sciences, The University of Queensland, St Lucia, Queensland, Australia
| | - Avneet Kaur
- School of Biological Sciences, The University of Queensland, St Lucia, Queensland, Australia
- Australian Research Council Centre of Excellence for Plant Success in Nature and Agriculture, The University of Queensland, St Lucia, Queensland, Australia
| | - Melanie J Wilkinson
- School of Biological Sciences, The University of Queensland, St Lucia, Queensland, Australia
- Australian Research Council Centre of Excellence for Plant Success in Nature and Agriculture, The University of Queensland, St Lucia, Queensland, Australia
| | - Daniel Ortiz-Barrientos
- School of Biological Sciences, The University of Queensland, St Lucia, Queensland, Australia
- Australian Research Council Centre of Excellence for Plant Success in Nature and Agriculture, The University of Queensland, St Lucia, Queensland, Australia
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10
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Sun Z, Zheng Z, Qi F, Wang J, Wang M, Zhao R, Liu H, Xu J, Qin L, Dong W, Huang B, Han S, Zhang X. Development and evaluation of the utility of GenoBaits Peanut 40K for a peanut MAGIC population. MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2023; 43:72. [PMID: 37786866 PMCID: PMC10542084 DOI: 10.1007/s11032-023-01417-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 09/07/2023] [Indexed: 10/04/2023]
Abstract
Population and genotype data are essential for genetic mapping. The multi-parent advanced generation intercross (MAGIC) population is a permanent mapping population used for precisely mapping quantitative trait loci. Moreover, genotyping-by-target sequencing (GBTS) is a robust high-throughput genotyping technology characterized by its low cost, flexibility, and limited requirements for information management and support. In this study, an 8-way MAGIC population was constructed using eight elite founder lines. In addition, GenoBaits Peanut 40K was developed and utilized for the constructed MAGIC population. A subset (297 lines) of the MAGIC population at the S2 stage was genotyped using GenoBaits Peanut 40K. Furthermore, these lines and the eight parents were analyzed in terms of pod length, width, area, and perimeter. A total of 27 single nucleotide polymorphisms (SNPs) were revealed to be significantly associated with peanut pod size-related traits according to a genome-wide association study. The GenoBaits Peanut 40K provided herein and the constructed MAGIC population will be applicable for future research to identify the key genes responsible for important peanut traits. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-023-01417-w.
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Affiliation(s)
- Ziqi Sun
- Institute of Crop Molecular Breeding, Henan Academy of Agricultural Sciences/The Shennong Laboratory/State Industrial Innovation Center of Biological Breeding/Key Laboratory of Oil Crops in Huang-Huai-Hai Plains, Ministry of Agriculture/Henan Provincial Key Laboratory for Oil Crops Improvement, Zhengzhou, Henan China
| | - Zheng Zheng
- Institute of Crop Molecular Breeding, Henan Academy of Agricultural Sciences/The Shennong Laboratory/State Industrial Innovation Center of Biological Breeding/Key Laboratory of Oil Crops in Huang-Huai-Hai Plains, Ministry of Agriculture/Henan Provincial Key Laboratory for Oil Crops Improvement, Zhengzhou, Henan China
| | - Feiyan Qi
- Institute of Crop Molecular Breeding, Henan Academy of Agricultural Sciences/The Shennong Laboratory/State Industrial Innovation Center of Biological Breeding/Key Laboratory of Oil Crops in Huang-Huai-Hai Plains, Ministry of Agriculture/Henan Provincial Key Laboratory for Oil Crops Improvement, Zhengzhou, Henan China
| | - Juan Wang
- Institute of Crop Molecular Breeding, Henan Academy of Agricultural Sciences/The Shennong Laboratory/State Industrial Innovation Center of Biological Breeding/Key Laboratory of Oil Crops in Huang-Huai-Hai Plains, Ministry of Agriculture/Henan Provincial Key Laboratory for Oil Crops Improvement, Zhengzhou, Henan China
| | - Mengmeng Wang
- Institute of Crop Molecular Breeding, Henan Academy of Agricultural Sciences/The Shennong Laboratory/State Industrial Innovation Center of Biological Breeding/Key Laboratory of Oil Crops in Huang-Huai-Hai Plains, Ministry of Agriculture/Henan Provincial Key Laboratory for Oil Crops Improvement, Zhengzhou, Henan China
| | - Ruifang Zhao
- Institute of Crop Molecular Breeding, Henan Academy of Agricultural Sciences/The Shennong Laboratory/State Industrial Innovation Center of Biological Breeding/Key Laboratory of Oil Crops in Huang-Huai-Hai Plains, Ministry of Agriculture/Henan Provincial Key Laboratory for Oil Crops Improvement, Zhengzhou, Henan China
| | - Hua Liu
- Institute of Crop Molecular Breeding, Henan Academy of Agricultural Sciences/The Shennong Laboratory/State Industrial Innovation Center of Biological Breeding/Key Laboratory of Oil Crops in Huang-Huai-Hai Plains, Ministry of Agriculture/Henan Provincial Key Laboratory for Oil Crops Improvement, Zhengzhou, Henan China
| | - Jing Xu
- Institute of Crop Molecular Breeding, Henan Academy of Agricultural Sciences/The Shennong Laboratory/State Industrial Innovation Center of Biological Breeding/Key Laboratory of Oil Crops in Huang-Huai-Hai Plains, Ministry of Agriculture/Henan Provincial Key Laboratory for Oil Crops Improvement, Zhengzhou, Henan China
| | - Li Qin
- Institute of Crop Molecular Breeding, Henan Academy of Agricultural Sciences/The Shennong Laboratory/State Industrial Innovation Center of Biological Breeding/Key Laboratory of Oil Crops in Huang-Huai-Hai Plains, Ministry of Agriculture/Henan Provincial Key Laboratory for Oil Crops Improvement, Zhengzhou, Henan China
| | - Wenzhao Dong
- Institute of Crop Molecular Breeding, Henan Academy of Agricultural Sciences/The Shennong Laboratory/State Industrial Innovation Center of Biological Breeding/Key Laboratory of Oil Crops in Huang-Huai-Hai Plains, Ministry of Agriculture/Henan Provincial Key Laboratory for Oil Crops Improvement, Zhengzhou, Henan China
| | - Bingyan Huang
- Institute of Crop Molecular Breeding, Henan Academy of Agricultural Sciences/The Shennong Laboratory/State Industrial Innovation Center of Biological Breeding/Key Laboratory of Oil Crops in Huang-Huai-Hai Plains, Ministry of Agriculture/Henan Provincial Key Laboratory for Oil Crops Improvement, Zhengzhou, Henan China
| | - Suoyi Han
- Institute of Crop Molecular Breeding, Henan Academy of Agricultural Sciences/The Shennong Laboratory/State Industrial Innovation Center of Biological Breeding/Key Laboratory of Oil Crops in Huang-Huai-Hai Plains, Ministry of Agriculture/Henan Provincial Key Laboratory for Oil Crops Improvement, Zhengzhou, Henan China
| | - Xinyou Zhang
- Institute of Crop Molecular Breeding, Henan Academy of Agricultural Sciences/The Shennong Laboratory/State Industrial Innovation Center of Biological Breeding/Key Laboratory of Oil Crops in Huang-Huai-Hai Plains, Ministry of Agriculture/Henan Provincial Key Laboratory for Oil Crops Improvement, Zhengzhou, Henan China
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11
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Kumar N, Boatwright JL, Sapkota S, Brenton ZW, Ballén-Taborda C, Myers MT, Cox WA, Jordan KE, Kresovich S, Boyles RE. Discovering useful genetic variation in the seed parent gene pool for sorghum improvement. Front Genet 2023; 14:1221148. [PMID: 37790706 PMCID: PMC10544336 DOI: 10.3389/fgene.2023.1221148] [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: 05/11/2023] [Accepted: 09/04/2023] [Indexed: 10/05/2023] Open
Abstract
Multi-parent populations contain valuable genetic material for dissecting complex, quantitative traits and provide a unique opportunity to capture multi-allelic variation compared to the biparental populations. A multi-parent advanced generation inter-cross (MAGIC) B-line (MBL) population composed of 708 F6 recombinant inbred lines (RILs), was recently developed from four diverse founders. These selected founders strategically represented the four most prevalent botanical races (kafir, guinea, durra, and caudatum) to capture a significant source of genetic variation to study the quantitative traits in grain sorghum [Sorghum bicolor (L.) Moench]. MBL was phenotyped at two field locations for seven yield-influencing traits: panicle type (PT), days to anthesis (DTA), plant height (PH), grain yield (GY), 1000-grain weight (TGW), tiller number per meter (TN) and yield per panicle (YPP). High phenotypic variation was observed for all the quantitative traits, with broad-sense heritabilities ranging from 0.34 (TN) to 0.84 (PH). The entire population was genotyped using Diversity Arrays Technology (DArTseq), and 8,800 single nucleotide polymorphisms (SNPs) were generated. A set of polymorphic, quality-filtered markers (3,751 SNPs) and phenotypic data were used for genome-wide association studies (GWAS). We identified 52 marker-trait associations (MTAs) for the seven traits using BLUPs generated from replicated plots in two locations. We also identified desirable allelic combinations based on the plant height loci (Dw1, Dw2, and Dw3), which influences yield related traits. Additionally, two novel MTAs were identified each on Chr1 and Chr7 for yield traits independent of dwarfing genes. We further performed a multi-variate adaptive shrinkage analysis and 15 MTAs with pleiotropic effect were identified. The five best performing MBL progenies were selected carrying desirable allelic combinations. Since the MBL population was designed to capture significant diversity for maintainer line (B-line) accessions, these progenies can serve as valuable resources to develop superior sorghum hybrids after validation of their general combining abilities via crossing with elite pollinators. Further, newly identified desirable allelic combinations can be used to enrich the maintainer germplasm lines through marker-assisted backcross breeding.
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Affiliation(s)
- Neeraj Kumar
- Advanced Plant Technology, Clemson University, Clemson, SC, United States
- Department of Plant and Environmental Sciences, Clemson University, Clemson, SC, United States
| | - J. Lucas Boatwright
- Advanced Plant Technology, Clemson University, Clemson, SC, United States
- Department of Plant and Environmental Sciences, Clemson University, Clemson, SC, United States
| | - Sirjan Sapkota
- Advanced Plant Technology, Clemson University, Clemson, SC, United States
| | - Zachary W. Brenton
- Advanced Plant Technology, Clemson University, Clemson, SC, United States
- Carolina Seed Systems, Darlington, SC, United States
| | - Carolina Ballén-Taborda
- Department of Plant and Environmental Sciences, Clemson University, Clemson, SC, United States
- Pee Dee Research and Education Center, Clemson University, Florence, SC, United States
| | - Matthew T. Myers
- Advanced Plant Technology, Clemson University, Clemson, SC, United States
- Department of Plant and Environmental Sciences, Clemson University, Clemson, SC, United States
| | - William A. Cox
- Advanced Plant Technology, Clemson University, Clemson, SC, United States
- Department of Plant and Environmental Sciences, Clemson University, Clemson, SC, United States
| | - Kathleen E. Jordan
- Advanced Plant Technology, Clemson University, Clemson, SC, United States
- Department of Plant and Environmental Sciences, Clemson University, Clemson, SC, United States
| | - Stephen Kresovich
- Advanced Plant Technology, Clemson University, Clemson, SC, United States
- Department of Plant and Environmental Sciences, Clemson University, Clemson, SC, United States
- Feed the Future Innovation Lab for Crop Improvement, Cornell University, Ithaca, NY, United States
| | - Richard E. Boyles
- Department of Plant and Environmental Sciences, Clemson University, Clemson, SC, United States
- Pee Dee Research and Education Center, Clemson University, Florence, SC, United States
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12
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Peng Y, Yuan Y, Chang W, Zheng L, Ma W, Ren H, Liu P, Zhu L, Su J, Ma F, Li M, Ma B. Transcriptional repression of MdMa1 by MdMYB21 in Ma locus decreases malic acid content in apple fruit. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2023; 115:1231-1242. [PMID: 37219375 DOI: 10.1111/tpj.16314] [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: 10/27/2022] [Revised: 05/08/2023] [Accepted: 05/18/2023] [Indexed: 05/24/2023]
Abstract
Malic acid is a major organic acid component of apples and a crucial determinant of fruit organoleptic quality. A candidate gene for malic acid content, designated MdMa1, was previously identified in the Ma locus, which is a major quantitative trait locus (QTL) for apple fruit acidity located on the linkage group 16. Region-based association mapping to detect candidate genes in the Ma locus identified MdMa1 and an additional MdMYB21 gene putatively associated with malic acid. MdMYB21 was significantly associated with fruit malic acid content, accounting for ~7.48% of the observed phenotypic variation in the apple germplasm collection. Analyses of transgenic apple calli, fruits and tomatoes demonstrated that MdMYB21 negatively regulated malic acid accumulation. The apple fruit acidity-related MdMa1 and its tomato ortholog, SlALMT9, exhibited lower expression profiles in apple calli, mature fruits and tomatoes in which MdMYB21 was overexpressed, compared with their corresponding wild-type variety. MdMYB21 directly binds to the MdMa1 promoter and represses its expression. Interestingly, a 2-bp variation in the MdMYB21 promoter region altered its expression and regulation of its target gene, MdMa1, expression. Our findings not only demonstrate the efficiency of integrating QTL and association mapping in the identification of candidate genes controlling complex traits in apples, but also provide insights into the complex regulatory mechanism of fruit malic acid accumulation.
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Affiliation(s)
- Yunjing Peng
- State Key Laboratory of Crop Stress Biology for Arid Areas/Shaanxi Key Laboratory of Apple, College of Horticulture, Northwest A&F University, Yangling, 712100, Shaanxi, China
| | - Yangyang Yuan
- State Key Laboratory of Crop Stress Biology for Arid Areas/Shaanxi Key Laboratory of Apple, College of Horticulture, Northwest A&F University, Yangling, 712100, Shaanxi, China
| | - Wenjing Chang
- State Key Laboratory of Crop Stress Biology for Arid Areas/Shaanxi Key Laboratory of Apple, College of Horticulture, Northwest A&F University, Yangling, 712100, Shaanxi, China
| | - Litong Zheng
- State Key Laboratory of Crop Stress Biology for Arid Areas/Shaanxi Key Laboratory of Apple, College of Horticulture, Northwest A&F University, Yangling, 712100, Shaanxi, China
| | - Wenfang Ma
- State Key Laboratory of Crop Stress Biology for Arid Areas/Shaanxi Key Laboratory of Apple, College of Horticulture, Northwest A&F University, Yangling, 712100, Shaanxi, China
| | - Hang Ren
- State Key Laboratory of Crop Stress Biology for Arid Areas/Shaanxi Key Laboratory of Apple, College of Horticulture, Northwest A&F University, Yangling, 712100, Shaanxi, China
| | - Peipei Liu
- State Key Laboratory of Crop Stress Biology for Arid Areas/Shaanxi Key Laboratory of Apple, College of Horticulture, Northwest A&F University, Yangling, 712100, Shaanxi, China
| | - Lingcheng Zhu
- State Key Laboratory of Crop Stress Biology for Arid Areas/Shaanxi Key Laboratory of Apple, College of Horticulture, Northwest A&F University, Yangling, 712100, Shaanxi, China
| | - Jing Su
- State Key Laboratory of Crop Stress Biology for Arid Areas/Shaanxi Key Laboratory of Apple, College of Horticulture, Northwest A&F University, Yangling, 712100, Shaanxi, China
| | - Fengwang Ma
- State Key Laboratory of Crop Stress Biology for Arid Areas/Shaanxi Key Laboratory of Apple, College of Horticulture, Northwest A&F University, Yangling, 712100, Shaanxi, China
| | - Mingjun Li
- State Key Laboratory of Crop Stress Biology for Arid Areas/Shaanxi Key Laboratory of Apple, College of Horticulture, Northwest A&F University, Yangling, 712100, Shaanxi, China
| | - Baiquan Ma
- State Key Laboratory of Crop Stress Biology for Arid Areas/Shaanxi Key Laboratory of Apple, College of Horticulture, Northwest A&F University, Yangling, 712100, Shaanxi, China
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13
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Zhao M, Zhang J, Yang C, Cui Z, Chen L. Identification of QTLs and Putative Candidate Genes for Plant Architecture of Lotus Revealed by Regional Association Mapping. PLANTS (BASEL, SWITZERLAND) 2023; 12:1221. [PMID: 36986910 PMCID: PMC10051333 DOI: 10.3390/plants12061221] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 02/26/2023] [Accepted: 03/02/2023] [Indexed: 06/18/2023]
Abstract
The lotus (Nelumbo Adans.) is one of the most economically relevant ornamental aquatic plants. Plant architecture (PA) is an important trait for lotus classification, cultivation, breeding, and applications. However, the underlying genetic and molecular basis controlling PA remains poorly understood. In this study, an association study for PA-related traits was performed with 93 genome-wide microsatellite markers (simple sequence repeat, SSR) and 51 insertion-deletion (InDel) markers derived from the candidate regions using a panel of 293 lotus accessions. Phenotypic data analysis of the five PA-related traits revealed a wide normal distribution and high heritability from 2013 to 2016, which indicated that lotus PA-related traits are highly polygenic traits. The population structure (Q-matrix) and the relative kinships (K-matrix) of the association panels were analyzed using 93 SSR markers. The mixed linear model (MLM) taking Q-matrix and K-matrix into account was used to estimate the association between markers and the traits. A total of 26 markers and 65 marker-trait associations were identified by considering associations with p < 0.001 and Q < 0.05. Based on the significant markers, two QTLs on Chromosome 1 were identified, and two candidate genes were preliminarily determined. The results of our study provided useful information for the lotus breeding aiming at different PA phenotypes using a molecular-assisted selection (MAS) method and also laid the foundation for the illustration of the molecular mechanism underlying the major QTL and key markers associated with lotus PA.
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Affiliation(s)
- Mei Zhao
- College of Landscape and Forestry, Qingdao Agricultural University, Qingdao 266109, China
| | - Jibin Zhang
- College of Landscape and Forestry, Qingdao Agricultural University, Qingdao 266109, China
| | - Chuxuan Yang
- College of Horticulture, Qingdao Agricultural University, Qingdao 266109, China
| | - Zhenhua Cui
- College of Horticulture, Qingdao Agricultural University, Qingdao 266109, China
| | - Longqing Chen
- Southwest Landscape Architecture Engineering Research Center (National Forestry and Grassland Administration), Southwest Forestry University, Kunming 650224, China
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Xiong H, Chen Y, Pan YB, Shi A. A Genome-Wide Association Study and Genomic Prediction for Fiber and Sucrose Contents in a Mapping Population of LCP 85-384 Sugarcane. PLANTS (BASEL, SWITZERLAND) 2023; 12:1041. [PMID: 36903902 PMCID: PMC10005238 DOI: 10.3390/plants12051041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 02/11/2023] [Accepted: 02/21/2023] [Indexed: 06/18/2023]
Abstract
Sugarcane (Saccharum spp. hybrids) is an economically important crop for both sugar and biofuel industries. Fiber and sucrose contents are the two most critical quantitative traits in sugarcane breeding that require multiple-year and multiple-location evaluations. Marker-assisted selection (MAS) could significantly reduce the time and cost of developing new sugarcane varieties. The objectives of this study were to conduct a genome-wide association study (GWAS) to identify DNA markers associated with fiber and sucrose contents and to perform genomic prediction (GP) for the two traits. Fiber and sucrose data were collected from 237 self-pollinated progenies of LCP 85-384, the most popular Louisiana sugarcane cultivar from 1999 to 2007. The GWAS was performed using 1310 polymorphic DNA marker alleles with three models of TASSEL 5, single marker regression (SMR), general linear model (GLM) and mixed linear model (MLM), and the fixed and random model circulating probability unification (FarmCPU) of R package. The results showed that 13 and 9 markers were associated with fiber and sucrose contents, respectively. The GP was performed by cross-prediction with five models, ridge regression best linear unbiased prediction (rrBLUP), Bayesian ridge regression (BRR), Bayesian A (BA), Bayesian B (BB) and Bayesian least absolute shrinkage and selection operator (BL). The accuracy of GP varied from 55.8% to 58.9% for fiber content and 54.6% to 57.2% for sucrose content. Upon validation, these markers can be applied in MAS and genomic selection (GS) to select superior sugarcane with good fiber and high sucrose contents.
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Affiliation(s)
- Haizheng Xiong
- Department of Horticulture, University of Arkansas, Fayetteville, AR 72701, USA
| | - Yilin Chen
- Department of Horticulture, University of Arkansas, Fayetteville, AR 72701, USA
| | - Yong-Bao Pan
- USDA-ARS, Sugarcane Research Unit, Houma, LA 70360, USA
| | - Ainong Shi
- Department of Horticulture, University of Arkansas, Fayetteville, AR 72701, USA
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Odesola KA, Olawuyi OJ, Paliwal R, Oyatomi OA, Abberton MT. Genome-Wide association analysis of phenotypic traits in Bambara groundnut under drought-stressed and non-stressed conditions based on DArTseq SNP. FRONTIERS IN PLANT SCIENCE 2023; 14:1104417. [PMID: 36866383 PMCID: PMC9972976 DOI: 10.3389/fpls.2023.1104417] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Accepted: 01/05/2023] [Indexed: 06/18/2023]
Abstract
INTRODUCTION Bambara groundnut (BG) (Vigna subterranea [L.] Verdc) is an indigenous, resilient, but underutilized leguminous crop that occurs mostly as genetically heterogeneous landraces with limited information on the drought tolerant attributes. This study elucidates the associations between sequencing-based diversity array technology (DArTseq) and phenotypic character as well as differing indices related to drought tolerance in one hundred accessions of Bambara groundnut. METHODS The field experiments were conducted at IITA research stations in Kano and Ibadan between 2016 and 2018 planting seasons. The experiments were arranged in randomised complete block design with three replications, under the different water regimes. The phenotypic traits evaluated was further to construct the dendrogram. Genome-wide association mapping was conducted based on 5927 DArTs loci with < 20% missing data. RESULTS AND DISCUSSIONS The genome wide association study predicted drought tolerance in Bambara accessions for geometric mean productivity (GMP) and stress tolerance index (STI). TVSu-423 had the highest GMP and STI values (28.50, 2.40), while TVSu-2017 had the lowest at GMP (1.74) and STI (0.01) respectively. The relative water content (%) was significantly higher for accessions; TVSu-266 (60.35, 61.49), TVSu-2 (58.29, 53.94), and TVSu-411 (55.17, 58.92) in 2016/2017 and 2017/2018, respectively. The phenotypic characters studied delineated the accessions into two major clusters and five distinct sub-clusters, indicating variations across all the geographical locations. The 5,927 DArTseq genomic markers in association with STI further grouped the 100 accessions into two main clusters. TVSu-1897 from Botswana (Southern Africa) was in the first cluster, while the remaining 99 accessions from Western, Central, and Eastern Africa made up the second cluster. The eight significant Quantitative Trait Loci (QTLs) (24346377|F|0-22:A>G-22:A>G, 24384105|F|0-56:A>G33 :A> G, 24385643|F|0-53:G>C-53:G>C, 24385696|F|0-43:A>G-43:A>G, 4177257|F|0-44:A>T-44:A>T, 4182070|F|0-66:G>A-66:G>A, 4183483|F|0-24:G>A-24:G>A, 4183904|F|0-11:C>T-11:C>T) identified with Bonferroni threshold was in association with STI, indicative of variations under the drought-stressed condition. The observation of consistent SNPs in the 2016 and 2017 planting seasons, as well as in combination with the 2016 and 2017 planting seasons, led to the designation of these QTLs as significant. The drought selected accessions could form basis for hybridization breeding. The identified quantitative trait loci could be useful in marker-assisted selection in drought molecular breeding programs.
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Affiliation(s)
- Kafilat Abiodun Odesola
- Department of Biological Sciences, Bells University of Technology, Sango Otta, Ogun State, Nigeria
- Genetic Resources Centre, International Institute of Tropical Agriculture, Ibadan, Oyo State, Nigeria
- Department of Botany, University of Ibadan, Ibadan, Oyo State, Nigeria
| | | | - Rajneesh Paliwal
- Genetic Resources Centre, International Institute of Tropical Agriculture, Ibadan, Oyo State, Nigeria
| | - Olaniyi Ajewole Oyatomi
- Genetic Resources Centre, International Institute of Tropical Agriculture, Ibadan, Oyo State, Nigeria
| | - Michael T. Abberton
- Genetic Resources Centre, International Institute of Tropical Agriculture, Ibadan, Oyo State, Nigeria
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16
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Roy A, Sahu PK, Das C, Bhattacharyya S, Raina A, Mondal S. Conventional and new-breeding technologies for improving disease resistance in lentil ( Lens culinaris Medik). FRONTIERS IN PLANT SCIENCE 2023; 13:1001682. [PMID: 36743558 PMCID: PMC9896981 DOI: 10.3389/fpls.2022.1001682] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Accepted: 12/02/2022] [Indexed: 06/02/2023]
Abstract
Lentil, an important cool season food legume, is a rich source of easily digestible protein, folic acid, bio-available iron, and zinc nutrients. Lentil grows mainly as a sole crop in the winter after harvesting rice in South Asia. However, the annual productivity is low due to its slow growth during the early phase, competitive weed infestation, and disease outbreaks during the crop growth period. Disease resistance breeding has been practiced for a long time to enhance resistance to various diseases. Often the sources of resistance are available in wild crop relatives. Thus, wide hybridization and the ovule rescue technique have helped to introgress the resistance trait into cultivated lentils. Besides hybridization, induced mutagenesis contributed immensely in creating variability for disease tolerance, and several disease-resistant mutant lines have been developed. However, to overcome the limitations of traditional breeding approaches, advancement in molecular marker technologies, and genomics has helped to develop disease-resistant and climate-resilient lentil varieties with more precision and efficiency. This review describes types of diseases, disease screening methods, the role of conventional and new breeding technologies in alleviating disease-incurred damage and progress toward making lentil varieties more resilient to disease outbreaks under the shadow of climate change.
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Affiliation(s)
- Anirban Roy
- Department of Genetics and Plant Breeding, Bidhan Chandra Krishi Viswavidyalaya, Mohanpur West Bengal, India
- Department of Genetics and Plant Breeding, Ramakrishna Mission Vivekananda Educational & Research Institute (RKMVERI), Ramkrishna Mission Ashrama, Kolkata, India
| | - Parmeshwar K. Sahu
- Department of Genetics and Plant Breeding, College of Agriculture, Indira Gandhi Krishi Viswavidyalaya, Raipur, Chhattisgarh, India
| | - Camellia Das
- Department of Genetics and Plant Breeding, Bidhan Chandra Krishi Viswavidyalaya, Mohanpur West Bengal, India
| | - Somnath Bhattacharyya
- Department of Genetics and Plant Breeding, Bidhan Chandra Krishi Viswavidyalaya, Mohanpur West Bengal, India
| | - Aamir Raina
- Mutation Breeding Laboratory, Department of Botany, Aligarh Muslim University, Aligarh, Uttar Pradesh, India
- Botany Section, Women’s College, Aligarh Muslim University, Aligarh, Uttar Pradesh, India
| | - Suvendu Mondal
- Nuclear Agriculture and Biotechnology Division, Bhabha Atomic Research Centre, Mumbai, India
- Homi Bhabha National Institute, Training School Complex, Anushaktinagar, Mumbai, India
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17
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Yuan G, Sun K, Yu W, Jiang Z, Jiang C, Liu D, Wen L, Si H, Wu F, Meng H, Cheng L, Yang A, Wang Y. Development of a MAGIC population and high-resolution quantitative trait mapping for nicotine content in tobacco. FRONTIERS IN PLANT SCIENCE 2023; 13:1086950. [PMID: 36704165 PMCID: PMC9871594 DOI: 10.3389/fpls.2022.1086950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 12/02/2022] [Indexed: 06/18/2023]
Abstract
Multiparent Advanced Generation Inter-Cross (MAGIC) population is an ideal genetic and breeding material for quantitative trait locus (QTL) mapping and molecular breeding. In this study, a MAGIC population derived from eight tobacco parents was developed. Eight parents and 560 homozygous lines were genotyped by a 430K single-nucleotide polymorphism (SNP) chip assay and phenotyped for nicotine content under different conditions. Four QTLs associated with nicotine content were detected by genome-wide association mapping (GWAS), and one major QTL, named qNIC7-1, was mapped repeatedly under different conditions. Furthermore, by combining forward mapping, bioinformatics analysis and gene editing, we identified an ethylene response factor (ERF) transcription factor as a candidate gene underlying the major QTL qNIC7-1 for nicotine content in tobacco. A presence/absence variation (PAV) at qNIC7-1 confers changes in nicotine content. Overall, the large size of this MAGIC population, diverse genetic composition, balanced parental contributions and high levels of recombination all contribute to its value as a genetic and breeding resource. The application of the tobacco MAGIC population for QTL mapping and detecting rare allelic variation was demonstrated using nicotine content as a proof of principle.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | - Lirui Cheng
- *Correspondence: Lirui Cheng, ; Aiguo Yang, ; Yuanying Wang,
| | - Aiguo Yang
- *Correspondence: Lirui Cheng, ; Aiguo Yang, ; Yuanying Wang,
| | - Yuanying Wang
- *Correspondence: Lirui Cheng, ; Aiguo Yang, ; Yuanying Wang,
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18
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Capo-chichi LJA, Elakhdar A, Kubo T, Nyachiro J, Juskiw P, Capettini F, Slaski JJ, Ramirez GH, Beattie AD. Genetic diversity and population structure assessment of Western Canadian barley cooperative trials. FRONTIERS IN PLANT SCIENCE 2023; 13:1006719. [PMID: 36699829 PMCID: PMC9868428 DOI: 10.3389/fpls.2022.1006719] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Accepted: 11/25/2022] [Indexed: 06/17/2023]
Abstract
Studying the population structure and genetic diversity of historical datasets is a proposed use for association analysis. This is particularly important when the dataset contains traits that are time-consuming or costly to measure. A set of 96 elite barley genotypes, developed from eight breeding programs of the Western Canadian Cooperative Trials were used in the current study. Genetic diversity, allelic variation, and linkage disequilibrium (LD) were investigated using 5063 high-quality SNP markers via the Illumina 9K Barley Infinium iSelect SNP assay. The distribution of SNPs markers across the barley genome ranged from 449 markers on chromosome 1H to 1111 markers on chromosome 5H. The average polymorphism information content (PIC) per locus was 0.275 and ranged from 0.094 to 0.375. Bayesian clustering in STRUCTURE and principal coordinate analysis revealed that the populations are differentiated primarily due to the different breeding program origins and ear-row type into five subpopulations. Analysis of molecular variance based on PhiPT values suggested that high values of genetic diversity were observed within populations and accounted for 90% of the total variance. Subpopulation 5 exhibited the most diversity with the highest values of the diversity indices, which represent the breeding program gene pool of AFC, AAFRD, AU, and BARI. With increasing genetic distance, the LD values, expressed as r2, declined to below the critical r2 = 0.18 after 3.91 cM, and the same pattern was observed on each chromosome. Our results identified an important pattern of genetic diversity among the Canadian barley panel that was proposed to be representative of target breeding programs and may have important implications for association mapping in the future. This highlight, that efforts to identify novel variability underlying this diversity may present practical breeding opportunities to develop new barley genotypes.
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Affiliation(s)
- Ludovic J. A. Capo-chichi
- Department of Renewable Resources, Faculty of Agriculture, Life and Environmental Sciences, University of Alberta, Edmonton, AB, Canada
| | - Ammar Elakhdar
- Institute of Genetic Resources, Faculty of Agriculture, Kyushu University, Fukuoka, Japan
- Field Crops Research Institute, Agricultural Research Center, Giza, Egypt
| | - Takahiko Kubo
- Institute of Genetic Resources, Faculty of Agriculture, Kyushu University, Fukuoka, Japan
| | - Joseph Nyachiro
- Field Crop Development Centre, Alberta Agriculture and Forestry, Lacombe, AB, Canada
| | - Patricia Juskiw
- Field Crop Development Centre, Alberta Agriculture and Forestry, Lacombe, AB, Canada
| | - Flavio Capettini
- Field Crop Development Centre, Alberta Agriculture and Forestry, Lacombe, AB, Canada
| | - Jan J. Slaski
- Ecosystems and Plant Sciences, InnoTech Alberta Inc., Vegreville, AB, Canada
| | - Guillermo Hernandez Ramirez
- Department of Renewable Resources, Faculty of Agriculture, Life and Environmental Sciences, University of Alberta, Edmonton, AB, Canada
| | - Aaron D. Beattie
- Department of Plant Sciences, College of Agriculture and Bioresources, University of Saskatchewan, Saskatoon, SK, Canada
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19
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Rani R, Raza G, Ashfaq H, Rizwan M, Shimelis H, Tung MH, Arif M. Analysis of genotype × environment interactions for agronomic traits of soybean ( Glycine max [L.] Merr.) using association mapping. Front Genet 2023; 13:1090994. [PMID: 36685981 PMCID: PMC9851276 DOI: 10.3389/fgene.2022.1090994] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Accepted: 12/12/2022] [Indexed: 01/06/2023] Open
Abstract
The soybean yield is a complex quantitative trait that is significantly influenced by environmental factors. G × E interaction (GEI), which derives the performance of soybean genotypes differentially in various environmental conditions, is one of the main obstacles to increasing the net production. The primary goal of this study is to identify the outperforming genotypes in different latitudes, which can then be used in future breeding programs. A total of 96 soybean genotypes were examined in two different ecological regions: Faisalabad and Tando Jam in Pakistan. The evaluation of genotypes in different environmental conditions showed a substantial amount of genetic diversity for grain yield. We identified 13 environment-specific genotypes showing their maximum grain yield in each environment. Genotype G69 was found to be an ideal genotype with higher grain yield than other genotypes tested in this study and is broadly adapted for environments E1 and E2 and also included in top-yielding genotypes in E3, E4, and E5. G92 is another genotype that is broadly adapted in E1, E3, and E4. In the case of environments, E3 is suggested to be a more ideal environment as it is plotted near the concentric circle and is very informative for the selection of genotypes with high yield. Despite the presence of GEI, advances in DNA technology provided very useful tools to investigate the insight of advanced genotypes. Association mapping is a useful method for swiftly and efficiently investigating the genetic basis of significant plant traits. A total of 26 marker-trait associations were found for six agronomic traits in five environments, with the highest significance (p-value = 2.48 × 10-08) for plant height and the lowest significance (1.03 × 10-03) for hundred-grain weight. Soybean genotypes identified in the present study could be a valuable source for future breeding programs as they are adaptable to a wide range of environments. Genetic selection of genotypes with the best yields can be used for gross grain production in a wide range of climatic conditions, and it would give an essential reference in terms of soybean variety selection.
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Affiliation(s)
- Reena Rani
- DNA Markers and Applied Genomics Lab, Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE), Constituent College Pakistan Institute of Engineering and Applied Sciences (PIEAS), Faisalabad, Pakistan
| | - Ghulam Raza
- DNA Markers and Applied Genomics Lab, Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE), Constituent College Pakistan Institute of Engineering and Applied Sciences (PIEAS), Faisalabad, Pakistan
| | - Hamza Ashfaq
- DNA Markers and Applied Genomics Lab, Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE), Constituent College Pakistan Institute of Engineering and Applied Sciences (PIEAS), Faisalabad, Pakistan
| | - Muhammad Rizwan
- Plant Breeding and Genetics Division, Nuclear Institute of Agriculture (NIA), Tando Jam, Pakistan
| | - Hussein Shimelis
- School of Agricultural, Earth and Environmental Sciences, African Centre for Crop Improvement, University of KwaZulu-Natal, Pietermaritzburg, South Africa,*Correspondence: Hussein Shimelis, ; Muhammad Arif,
| | - Muhammad Haseeb Tung
- DNA Markers and Applied Genomics Lab, Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE), Constituent College Pakistan Institute of Engineering and Applied Sciences (PIEAS), Faisalabad, Pakistan
| | - Muhammad Arif
- DNA Markers and Applied Genomics Lab, Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE), Constituent College Pakistan Institute of Engineering and Applied Sciences (PIEAS), Faisalabad, Pakistan,*Correspondence: Hussein Shimelis, ; Muhammad Arif,
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20
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Hasing T, Bombarely A. Genomic Approaches for the Study of Flower Development in Floriculture Crops. Methods Mol Biol 2023; 2686:453-494. [PMID: 37540373 DOI: 10.1007/978-1-0716-3299-4_22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/05/2023]
Abstract
The advances in genomics and bioinformatics have made possible the study in non-model plants of phenotypes associated to flower development. Floriculture crops are an interesting source of traits associated to flower development such as the transition between zygomorphic and actinomorphic flowers or the production of flowers with double and triple corollas. In this chapter, we summarize the material and methods for the use of floriculture crops to study flower development using genomic tools, from the sequencing and assembly of a reference genome to QTL and RNA-Seq analysis to search candidate genes associated to specific traits.
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Affiliation(s)
| | - Aureliano Bombarely
- Instituto de Biología Molecular y Celular de Plantas (IBMCP) (UPV-CSIC), Valencia, Spain.
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21
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Kumari G, Shanmugavadivel PS, Lavanya GR, Tiwari P, Singh D, Gore PG, Tripathi K, Madhavan Nair R, Gupta S, Pratap A. Association mapping for important agronomic traits in wild and cultivated Vigna species using cross-species and cross-genera simple sequence repeat markers. Front Genet 2022; 13:1000440. [PMID: 36406138 PMCID: PMC9669911 DOI: 10.3389/fgene.2022.1000440] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Accepted: 10/06/2022] [Indexed: 10/10/2023] Open
Abstract
The genus Vigna is an agronomically important taxon, with many of its species inhabiting a wide range of environments and offering numerous useful genes for the improvement of the cultivated types. The present study aimed to detect the genomic regions associated with yield-attributing traits by genome-wide association mapping. A diverse panel of 98 wild and cultivated Vigna accessions (acc.) belonging to 13 different species was evaluated for yield and related traits during the kharif season of 2017 and 2018. The panel was also genotyped using 92 cross-genera and cross-species simple sequence repeat markers to study the population genetic structure and useful market-trait associations. The PCA and trait correlation established relationships amongst the traits during both seasons while 100-seed weight (HSW) had a positive correlation with pod length (PL), and days to first flowering (DFF) with days to maturity (DM). The population genetic structure analysis grouped different acc. into three genetically distinct sub-populations with SP-1 comprising 34 acc., SP-2 (24 acc.), and SP-3 (33 acc.) and one admixture group (7 acc.). Mixed linear model analysis revealed an association of 13 markers, namely, VR018, VR039, VR022, CEDG033, GMES0337, MBSSR008, CEDG220, VM27, CP1225, CP08695, CEDG100, CEDG008, and CEDG096A with nine traits. Seven of the aforementioned markers, namely, VR018 for plant height (PH) and terminal leaflet length (TLL), VR022 for HSW and pod length (PL), CEDG033 for DFF and DM, MBSSR008 for DFF and DM, CP1225 for CC at 30 days (CC30), DFF and DM, CEDG100 for PH and terminal leaflet length (TLL), and CEDG096A for CC30 and chlorophyll content at 45 days were associated with multiple traits. The marker CEDG100, associated with HSW, PH, and TLL, is co-localized in gene-encoding histone-lysine N-methyltransferase ATX5. Similarly, VR22, associated with PL and HSW, is co-located in gene-encoding SHOOT GRAVITROPISM 5 in mungbean. These associations may be highly useful for marker-assisted genetic improvement of mungbean and other related Vigna species.
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Affiliation(s)
- Gita Kumari
- ICAR-Indian Institute of Pulses Research, Kanpur, India
| | | | - G. Roopa Lavanya
- Sam Higginbottom University of Agricultural Technology and Sciences, Prayagraj, India
| | - Pravin Tiwari
- ICAR-Indian Institute of Pulses Research, Kanpur, India
| | | | - P. G. Gore
- ICAR-National Bureau of Plant Genetic Resources, New Delhi, India
| | - Kuldeep Tripathi
- ICAR-National Bureau of Plant Genetic Resources, New Delhi, India
| | | | - Sanjeev Gupta
- ICAR-Indian Institute of Pulses Research, Kanpur, India
| | - Aditya Pratap
- ICAR-Indian Institute of Pulses Research, Kanpur, India
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22
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Seyum EG, Bille NH, Abtew WG, Munyengwa N, Bell JM, Cros D. Genomic selection in tropical perennial crops and plantation trees: a review. MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2022; 42:58. [PMID: 37313015 PMCID: PMC10248687 DOI: 10.1007/s11032-022-01326-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Accepted: 09/06/2022] [Indexed: 06/15/2023]
Abstract
To overcome the multiple challenges currently faced by agriculture, such as climate change and soil deterioration, more efficient plant breeding strategies are required. Genomic selection (GS) is crucial for the genetic improvement of quantitative traits, as it can increase selection intensity, shorten the generation interval, and improve selection accuracy for traits that are difficult to phenotype. Tropical perennial crops and plantation trees are of major economic importance and have consequently been the subject of many GS articles. In this review, we discuss the factors that affect GS accuracy (statistical models, linkage disequilibrium, information concerning markers, relatedness between training and target populations, the size of the training population, and trait heritability) and the genetic gain expected in these species. The impact of GS will be particularly strong in tropical perennial crops and plantation trees as they have long breeding cycles and constrained selection intensity. Future GS prospects are also discussed. High-throughput phenotyping will allow constructing of large training populations and implementing of phenomic selection. Optimized modeling is needed for longitudinal traits and multi-environment trials. The use of multi-omics, haploblocks, and structural variants will enable going beyond single-locus genotype data. Innovative statistical approaches, like artificial neural networks, are expected to efficiently handle the increasing amounts of heterogeneous multi-scale data. Targeted recombinations on sites identified from profiles of marker effects have the potential to further increase genetic gain. GS can also aid re-domestication and introgression breeding. Finally, GS consortia will play an important role in making the best of these opportunities. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-022-01326-4.
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Affiliation(s)
- Essubalew Getachew Seyum
- Department of Plant Biology and Physiology, Faculty of Sciences, University of Yaoundé I, Yaoundé, Cameroon
- Department of Horticulture and Plant Sciences, College of Agriculture and Veterinary Medicine, Jimma University, P.O. Box 307, Jimma, Ethiopia
| | - Ngalle Hermine Bille
- Department of Plant Biology and Physiology, Faculty of Sciences, University of Yaoundé I, Yaoundé, Cameroon
| | - Wosene Gebreselassie Abtew
- Department of Horticulture and Plant Sciences, College of Agriculture and Veterinary Medicine, Jimma University, P.O. Box 307, Jimma, Ethiopia
| | - Norman Munyengwa
- Queensland Alliance for Agriculture and Food Innovation, University of Queensland, Brisbane, QLD 4072 Australia
| | - Joseph Martin Bell
- Department of Plant Biology and Physiology, Faculty of Sciences, University of Yaoundé I, Yaoundé, Cameroon
| | - David Cros
- CIRAD, UMR AGAP Institut, 34398 Montpellier, France
- UMR AGAP Institut, CIRAD, INRAE, Univ. Montpellier, Institut Agro, 34398 Montpellier, France
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23
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Wang J, Ye H, Zhou H, Chen P, Liu H, Xi R, Wang G, Hou N, Zhao P. Genome-wide association analysis of 101 accessions dissects the genetic basis of shell thickness for genetic improvement in Persian walnut (Juglans regia L.). BMC PLANT BIOLOGY 2022; 22:436. [PMID: 36096735 PMCID: PMC9469530 DOI: 10.1186/s12870-022-03824-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Accepted: 09/02/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Understanding the underlying genetic mechanisms that drive phenotypic variations is essential for enhancing the efficacy of crop improvement. Persian walnut (Juglans regia L.), which is grown extensively worldwide, is an important economic tree fruit due to its horticultural, medicinal, and material value. The quality of the walnut fruit is related to the selection of traits such as thinner shells, larger filling rates, and better taste, which is very important for breeding in China. The complex quantitative fruit-related traits are influenced by a variety of physiological and environmental factors, which can vary widely between walnut genotypes. RESULTS For this study, a set of 101 Persian walnut accessions were re-sequenced, which generated a total of 906.2 Gb of Illumina sequence data with an average read depth of 13.8× for each accession. We performed the genome-wide association study (GWAS) using 10.9 Mb of high-quality single-nucleotide polymorphisms (SNPs) and 10 agronomic traits to explore the underlying genetic basis of the walnut fruit. Several candidate genes are proposed to be involved in walnut characteristics, including JrPXC1, JrWAKL8, JrGAMYB, and JrFRK1. Specifically, the JrPXC1 gene was confirmed to participate in the regulation of secondary wall cellulose thickening in the walnut shell. CONCLUSION In addition to providing considerable available genetic resources for walnut trees, this study revealed the underlying genetic basis involved in important walnut agronomic traits, particularly shell thickness, as well as providing clues for the improvement of genetic breeding and domestication in other perennial economic crops.
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Affiliation(s)
- Jiangtao Wang
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, College of Life Sciences, Northwest University, Xi'an, 710069, Shaanxi, China
| | - Hang Ye
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, College of Life Sciences, Northwest University, Xi'an, 710069, Shaanxi, China
| | - Huijuan Zhou
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, College of Life Sciences, Northwest University, Xi'an, 710069, Shaanxi, China
- College of Forestry, Northwest A&F University, Yangling, 712100, China
| | - Pengpeng Chen
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, College of Life Sciences, Northwest University, Xi'an, 710069, Shaanxi, China
| | - Hengzhao Liu
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, College of Life Sciences, Northwest University, Xi'an, 710069, Shaanxi, China
| | - Ruimin Xi
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, College of Life Sciences, Northwest University, Xi'an, 710069, Shaanxi, China
| | - Gang Wang
- Guizhou Academy of Forestry, Guiyang, 550005, Guizhou, China
| | - Na Hou
- Guizhou Academy of Forestry, Guiyang, 550005, Guizhou, China.
| | - Peng Zhao
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, College of Life Sciences, Northwest University, Xi'an, 710069, Shaanxi, China.
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Yang CJ, Ladejobi O, Mott R, Powell W, Mackay I. Analysis of historical selection in winter wheat. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2022; 135:3005-3023. [PMID: 35864201 PMCID: PMC9482581 DOI: 10.1007/s00122-022-04163-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/23/2022] [Accepted: 06/22/2022] [Indexed: 06/15/2023]
Abstract
KEY MESSAGE Modeling of the distribution of allele frequency over year of variety release identifies major loci involved in historical breeding of winter wheat. Winter wheat is a major crop with a rich selection history in the modern era of crop breeding. Genetic gains across economically important traits like yield have been well characterized and are the major force driving its production. Winter wheat is also an excellent model for analyzing historical genetic selection. As a proof of concept, we analyze two major collections of winter wheat varieties that were bred in Western Europe from 1916 to 2010, namely the Triticeae Genome (TG) and WAGTAIL panels, which include 333 and 403 varieties, respectively. We develop and apply a selection mapping approach, Regression of Alleles on Years (RALLY), in these panels, as well as in simulated populations. RALLY maps loci under sustained historical selection by using a simple logistic model to regress allele counts on years of variety release. To control for drift-induced allele frequency change, we develop a hybrid approach of genomic control and delta control. Within the TG panel, we identify 22 significant RALLY quantitative selection loci (QSLs) and estimate the local heritabilities for 12 traits across these QSLs. By correlating predicted marker effects with RALLY regression estimates, we show that alleles whose frequencies have increased over time are heavily biased toward conferring positive yield effect, but negative effects in flowering time, lodging, plant height and grain protein content. Altogether, our results (1) demonstrate the use of RALLY to identify selected genomic regions while controlling for drift, and (2) reveal key patterns in the historical selection in winter wheat and guide its future breeding.
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Affiliation(s)
- Chin Jian Yang
- Scotland's Rural College (SRUC), Kings Buildings, West Mains Road, Edinburgh, EH9 3JG, UK
| | - Olufunmilayo Ladejobi
- Department of Genetics, Evolution and Environment, University College London, London, WC1E 6BT, UK
| | - Richard Mott
- Department of Genetics, Evolution and Environment, University College London, London, WC1E 6BT, UK
| | - Wayne Powell
- Scotland's Rural College (SRUC), Kings Buildings, West Mains Road, Edinburgh, EH9 3JG, UK
| | - Ian Mackay
- Scotland's Rural College (SRUC), Kings Buildings, West Mains Road, Edinburgh, EH9 3JG, UK.
- IMplant Consultancy Ltd, Chelmsford, UK.
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25
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Singh RK, Singh C, Chandana BS, Mahto RK, Patial R, Gupta A, Gahlaut V, Hamwieh A, Upadhyaya HD, Kumar R. Exploring Chickpea Germplasm Diversity for Broadening the Genetic Base Utilizing Genomic Resourses. Front Genet 2022; 13:905771. [PMID: 36035111 PMCID: PMC9416867 DOI: 10.3389/fgene.2022.905771] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2022] [Accepted: 06/24/2022] [Indexed: 12/01/2022] Open
Abstract
Legume crops provide significant nutrition to humans as a source of protein, omega-3 fatty acids as well as specific macro and micronutrients. Additionally, legumes improve the cropping environment by replenishing the soil nitrogen content. Chickpeas are the second most significant staple legume food crop worldwide behind dry bean which contains 17%–24% protein, 41%–51% carbohydrate, and other important essential minerals, vitamins, dietary fiber, folate, β-carotene, anti-oxidants, micronutrients (phosphorus, calcium, magnesium, iron, and zinc) as well as linoleic and oleic unsaturated fatty acids. Despite these advantages, legumes are far behind cereals in terms of genetic improvement mainly due to far less effort, the bottlenecks of the narrow genetic base, and several biotic and abiotic factors in the scenario of changing climatic conditions. Measures are now called for beyond conventional breeding practices to strategically broadening of narrow genetic base utilizing chickpea wild relatives and improvement of cultivars through advanced breeding approaches with a focus on high yield productivity, biotic and abiotic stresses including climate resilience, and enhanced nutritional values. Desirable donors having such multiple traits have been identified using core and mini core collections from the cultivated gene pool and wild relatives of Chickpea. Several methods have been developed to address cross-species fertilization obstacles and to aid in inter-specific hybridization and introgression of the target gene sequences from wild Cicer species. Additionally, recent advances in “Omics” sciences along with high-throughput and precise phenotyping tools have made it easier to identify genes that regulate traits of interest. Next-generation sequencing technologies, whole-genome sequencing, transcriptomics, and differential genes expression profiling along with a plethora of novel techniques like single nucleotide polymorphism exploiting high-density genotyping by sequencing assays, simple sequence repeat markers, diversity array technology platform, and whole-genome re-sequencing technique led to the identification and development of QTLs and high-density trait mapping of the global chickpea germplasm. These altogether have helped in broadening the narrow genetic base of chickpeas.
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Affiliation(s)
| | - Charul Singh
- University School of Biotechnology, Guru Gobind Singh Indraprastha University, New Delhi, India
| | - B S Chandana
- Indian Agricultural Research Institute (ICAR), New Delhi, India
| | - Rohit K Mahto
- Indian Agricultural Research Institute (ICAR), New Delhi, India
| | - Ranjana Patial
- Department of Agricultural Sciences, Chandigarh University, Mohali, India
| | - Astha Gupta
- School of Agricultural Sciences, Sharda University, Greater Noida, India
| | - Vijay Gahlaut
- Institute of Himalayan Bioresource Technology (CSIR), Pālampur, India
| | - Aladdin Hamwieh
- International Center for Agriculture Research in the Dry Areas (ICARDA), Giza, Egypt
| | - H D Upadhyaya
- Department of Entomology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India
- Plant Genome Mapping Laboratory, University of Georgia, Athens, GA, United States
| | - Rajendra Kumar
- Indian Agricultural Research Institute (ICAR), New Delhi, India
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26
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Seyum EG, Bille NH, Abtew WG, Rastas P, Arifianto D, Domonhédo H, Cochard B, Jacob F, Riou V, Pomiès V, Lopez D, Bell JM, Cros D. Genome properties of key oil palm (Elaeis guineensis Jacq.) breeding populations. J Appl Genet 2022; 63:633-650. [PMID: 35691996 DOI: 10.1007/s13353-022-00708-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 05/26/2022] [Accepted: 06/04/2022] [Indexed: 11/29/2022]
Abstract
A good knowledge of the genome properties of the populations makes it possible to optimize breeding methods, in particular genomic selection (GS). In oil palm (Elaeis guineensis Jacq), the world's main source of vegetable oil, this would provide insight into the promising GS results obtained so far. The present study considered two complex breeding populations, Deli and La Mé, with 943 individuals and 7324 single-nucleotide polymorphisms (SNPs) from genotyping-by-sequencing. Linkage disequilibrium (LD), haplotype sharing, effective size (Ne), and fixation index (Fst) were investigated. A genetic linkage map spanning 1778.52 cM and with a recombination rate of 2.85 cM/Mbp was constructed. The LD at r2=0.3, considered the minimum to get reliable GS results, spanned over 1.05 cM/0.22 Mbp in Deli and 0.9 cM/0.21 Mbp in La Mé. The significant degree of differentiation existing between Deli and La Mé was confirmed by the high Fst value (0.53), the pattern of correlation of SNP heterozygosity and allele frequency among populations, and the decrease of persistence of LD and of haplotype sharing among populations with increasing SNP distance. However, the level of resemblance between the two populations over short genomic distances (correlation of r values between populations >0.6 for SNPs separated by <0.5 cM/1 kbp and percentage of common haplotypes >40% for haplotypes <3600 bp/0.20 cM) likely explains the superiority of GS models ignoring the parental origin of marker alleles over models taking this information into account. The two populations had low Ne (<5). Population-specific genetic maps and reference genomes are recommended for future studies.
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Affiliation(s)
- Essubalew Getachew Seyum
- Department of Plant Biology and Physiology, Faculty of Sciences, University of Yaoundé I, Yaoundé, Cameroon
- CETIC (African Center of Excellence in Information and Communication Technologies), University of Yaoundé I, Yaoundé, Cameroon
- Department of Horticulture and Plant Sciences, Jimma University College of Agriculture and Veterinary Medicine, P.O. Box 307, Jimma, Ethiopia
| | - Ngalle Hermine Bille
- Department of Plant Biology and Physiology, Faculty of Sciences, University of Yaoundé I, Yaoundé, Cameroon
| | - Wosene Gebreselassie Abtew
- Department of Horticulture and Plant Sciences, Jimma University College of Agriculture and Veterinary Medicine, P.O. Box 307, Jimma, Ethiopia
| | - Pasi Rastas
- Institute of Biotechnology, Helsinki Institute of Life Science (HiLIFE), University of Helsinki, 00014, Helsinki, Finland
| | | | | | | | | | - Virginie Riou
- CIRAD (Centre de coopération Internationale en Recherche Agronomique pour le Développement), UMR AGAP Institut, F-34398, Montpellier, France
- UMR AGAP Institut, University of Montpellier, CIRAD, INRAE, Institut Agro, F-34398, Montpellier, France
| | - Virginie Pomiès
- CIRAD (Centre de coopération Internationale en Recherche Agronomique pour le Développement), UMR AGAP Institut, F-34398, Montpellier, France
- UMR AGAP Institut, University of Montpellier, CIRAD, INRAE, Institut Agro, F-34398, Montpellier, France
| | - David Lopez
- CIRAD (Centre de coopération Internationale en Recherche Agronomique pour le Développement), UMR AGAP Institut, F-34398, Montpellier, France
- UMR AGAP Institut, University of Montpellier, CIRAD, INRAE, Institut Agro, F-34398, Montpellier, France
| | - Joseph Martin Bell
- Department of Plant Biology and Physiology, Faculty of Sciences, University of Yaoundé I, Yaoundé, Cameroon
| | - David Cros
- CIRAD (Centre de coopération Internationale en Recherche Agronomique pour le Développement), UMR AGAP Institut, F-34398, Montpellier, France.
- UMR AGAP Institut, University of Montpellier, CIRAD, INRAE, Institut Agro, F-34398, Montpellier, France.
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Simpson CJC, Reeves G, Tripathi A, Singh P, Hibberd JM. Using breeding and quantitative genetics to understand the C4 pathway. JOURNAL OF EXPERIMENTAL BOTANY 2022; 73:3072-3084. [PMID: 34747993 PMCID: PMC9126733 DOI: 10.1093/jxb/erab486] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Accepted: 11/03/2021] [Indexed: 05/09/2023]
Abstract
Reducing photorespiration in C3 crops could significantly increase rates of photosynthesis and yield. One method to achieve this would be to integrate C4 photosynthesis into C3 species. This objective is challenging as it involves engineering incompletely understood traits into C3 leaves, including complex changes to their biochemistry, cell biology, and anatomy. Quantitative genetics and selective breeding offer underexplored routes to identify regulators of these processes. We first review examples of natural intraspecific variation in C4 photosynthesis as well as the potential for hybridization between C3 and C4 species. We then discuss how quantitative genetic approaches including artificial selection and genome-wide association could be used to better understand the C4 syndrome and in so doing guide the engineering of the C4 pathway into C3 crops.
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Affiliation(s)
- Conor J C Simpson
- Department of Plant Sciences, University of Cambridge, Cambridge, UK
| | - Gregory Reeves
- Department of Plant Sciences, University of Cambridge, Cambridge, UK
| | - Anoop Tripathi
- Department of Plant Sciences, University of Cambridge, Cambridge, UK
| | - Pallavi Singh
- Department of Plant Sciences, University of Cambridge, Cambridge, UK
| | - Julian M Hibberd
- Department of Plant Sciences, University of Cambridge, Cambridge, UK
- Correspondence:
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28
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Pan Y, Zhu J, Hong Y, Zhang M, Lv C, Guo B, Shen H, Xu X, Xu R. Screening of stable resistant accessions and identification of resistance loci to Barley yellow mosaic virus disease. PeerJ 2022; 10:e13128. [PMID: 35317071 PMCID: PMC8934529 DOI: 10.7717/peerj.13128] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Accepted: 02/25/2022] [Indexed: 01/12/2023] Open
Abstract
Background The disease caused by Barley yellow mosaic virus (BaYMV) infection is a serious threat to autumn-sown barley (Hordeum vulgare L.) production in Europe, East Asia and Iran. Due to the rapid diversification of BaYMV strains, it is urgent to discover novel germplasm and genes to assist breeding new varieties with resistance to different BaYMV strains, thus minimizing the effect of BaYMV disease on barley cropping. Methods A natural population consisting of 181 barley accessions with different levels of resistance to BaYMV disease was selected for field resistance identification in two separate locations (Yangzhou and Yancheng, Jiangsu Province, China). Additive main effects and multiplicative interaction (AMMI) analysis was used to identify accessions with stable resistance. Genome-wide association study (GWAS) of BaYMV disease resistance was broadly performed by combining both single nucleotide polymorphisms (SNPs) and specific molecular markers associated with the reported BaYMV disease resistance genes. Furthermore, the viral protein genome linked (VPg) sequences of the virus were amplified and analyzed to assess the differences between the BaYMV strains sourced from the different experimental sites. Results Seven barley accessions with lower standardized Area Under the Disease Progress Steps (sAUDPS) index in every environment were identified and shown to have stable resistance to BaYMV disease in each assessed location. Apart from the reported BaYMV disease resistance genes rym4 and rym5, one novel resistance locus explaining 24.21% of the phenotypic variation was identified at the Yangzhou testing site, while two other novel resistance loci that contributed 19.23% and 19.79% of the phenotypic variation were identified at the Yancheng testing site, respectively. Further analysis regarding the difference in the VPg sequence of the predominant strain of BaYMV collected from these two testing sites may explain the difference of resistance loci differentially identified under geographically distinct regions. Our research provides novel genetic resources and resistance loci for breeding barley varieties for BaMYV disease resistance.
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Affiliation(s)
- Yuhan Pan
- Yangzhou University, Key Laboratory of Plant Functional Genomics of the Ministry of Education/Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops/Institutes of Agricultural Science, Yangzhou, Jiangsu, China
| | - Juan Zhu
- Yangzhou University, Key Laboratory of Plant Functional Genomics of the Ministry of Education/Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops/Institutes of Agricultural Science, Yangzhou, Jiangsu, China
| | - Yi Hong
- Yangzhou University, Key Laboratory of Plant Functional Genomics of the Ministry of Education/Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops/Institutes of Agricultural Science, Yangzhou, Jiangsu, China
| | - Mengna Zhang
- Yangzhou University, Key Laboratory of Plant Functional Genomics of the Ministry of Education/Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops/Institutes of Agricultural Science, Yangzhou, Jiangsu, China
| | - Chao Lv
- Yangzhou University, Key Laboratory of Plant Functional Genomics of the Ministry of Education/Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops/Institutes of Agricultural Science, Yangzhou, Jiangsu, China
| | - Baojian Guo
- Yangzhou University, Key Laboratory of Plant Functional Genomics of the Ministry of Education/Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops/Institutes of Agricultural Science, Yangzhou, Jiangsu, China
| | - Huiquan Shen
- Jiangsu Institute for Seaside Agricultural Sciences and Yancheng Academy of Agricultural Science, Yancheng, Jiangsu, China
| | - Xiao Xu
- Jiangsu Institute for Seaside Agricultural Sciences and Yancheng Academy of Agricultural Science, Yancheng, Jiangsu, China
| | - Rugen Xu
- Yangzhou University, Key Laboratory of Plant Functional Genomics of the Ministry of Education/Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops/Institutes of Agricultural Science, Yangzhou, Jiangsu, China
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29
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Gong H, Rehman F, Ma Y, A B, Zeng S, Yang T, Huang J, Li Z, Wu D, Wang Y. Germplasm Resources and Strategy for Genetic Breeding of Lycium Species: A Review. FRONTIERS IN PLANT SCIENCE 2022; 13:802936. [PMID: 35222468 PMCID: PMC8874141 DOI: 10.3389/fpls.2022.802936] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Accepted: 01/07/2022] [Indexed: 06/01/2023]
Abstract
Lycium species (goji), belonging to Solanaceae, are widely spread in the arid to semiarid environments of Eurasia, Africa, North and South America, among which most species have affinal drug and diet functions, resulting in their potential to be a superior healthy food. However, compared with other crop species, scientific research on breeding Lycium species lags behind. This review systematically introduces the present germplasm resources, cytological examination and molecular-assisted breeding progress in Lycium species. Introduction of the distribution of Lycium species around the world could facilitate germplasm collection for breeding. Karyotypes of different species could provide a feasibility analysis of fertility between species. The introduction of mapping technology has discussed strategies for quantitative trait locus (QTL) mapping in Lycium species according to different kinds of traits. Moreover, to extend the number of traits and standardize the protocols of trait detection, we also provide 1,145 potential traits (275 agronomic and 870 metabolic) in different organs based on different reference studies on Lycium, tomato and other Solanaceae species. Finally, perspectives on goji breeding research are discussed and concluded. This review will provide breeders with new insights into breeding Lycium species.
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Affiliation(s)
- Haiguang Gong
- Key Laboratory of South China Agricultural Plant Molecular Analysis and Genetic Improvement, Provincial Key Laboratory of Digital Botanical Garden and Public Science, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China
- School of Life Science, University of Chinese Academy of Sciences, Beijing, China
| | - Fazal Rehman
- Key Laboratory of South China Agricultural Plant Molecular Analysis and Genetic Improvement, Provincial Key Laboratory of Digital Botanical Garden and Public Science, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China
- School of Life Science, University of Chinese Academy of Sciences, Beijing, China
| | - Yun Ma
- Key Laboratory of South China Agricultural Plant Molecular Analysis and Genetic Improvement, Provincial Key Laboratory of Digital Botanical Garden and Public Science, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China
- School of Life Science, University of Chinese Academy of Sciences, Beijing, China
| | - Biao A
- Key Laboratory of South China Agricultural Plant Molecular Analysis and Genetic Improvement, Provincial Key Laboratory of Digital Botanical Garden and Public Science, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China
- School of Life Science, University of Chinese Academy of Sciences, Beijing, China
| | - Shaohua Zeng
- Key Laboratory of South China Agricultural Plant Molecular Analysis and Genetic Improvement, Provincial Key Laboratory of Digital Botanical Garden and Public Science, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China
- School of Life Science, University of Chinese Academy of Sciences, Beijing, China
| | - Tianshun Yang
- Key Laboratory of South China Agricultural Plant Molecular Analysis and Genetic Improvement, Provincial Key Laboratory of Digital Botanical Garden and Public Science, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China
| | - Jianguo Huang
- Key Laboratory of South China Agricultural Plant Molecular Analysis and Genetic Improvement, Provincial Key Laboratory of Digital Botanical Garden and Public Science, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China
- School of Life Science, University of Chinese Academy of Sciences, Beijing, China
| | - Zhong Li
- Agricultural Comprehensive Development Center in Ningxia Hui Autonomous Region, Yinchuan, China
| | | | - Ying Wang
- Key Laboratory of South China Agricultural Plant Molecular Analysis and Genetic Improvement, Provincial Key Laboratory of Digital Botanical Garden and Public Science, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China
- School of Life Science, Gannan Normal University, Ganzhou, China
- School of Life Science, University of Chinese Academy of Sciences, Beijing, China
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30
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Rohilla V, Yadav RK, Poonia A, Sheoran R, Kumari G, Shanmugavadivel PS, Pratap A. Association Mapping for Yield Attributing Traits and Yellow Mosaic Disease Resistance in Mung Bean [ Vigna radiata (L.) Wilczek]. FRONTIERS IN PLANT SCIENCE 2022; 12:749439. [PMID: 35111171 PMCID: PMC8801447 DOI: 10.3389/fpls.2021.749439] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 12/17/2021] [Indexed: 06/14/2023]
Abstract
Mung bean [Vigna radiata (L.) Wilczek] is an important short-duration grain legume widely known for its nutritional, soil ameliorative, and cropping system intensification properties. This study aims at evaluating genetic diversity among mung bean genotypes and detecting genomic regions associated with various yield attributing traits and yellow mosaic disease (YMD) resistance by association mapping. A panel of 80 cultivars and advanced breeding lines was evaluated for 10 yield-related and YMD resistance traits during kharif (monsoon) and summer seasons of 2018-2019 and 2019-2020. A total of 164 genome-wide simple sequence repeat (SSR) markers were initially screened, out of which 89 were found polymorphic which generated 317 polymorphic alleles with an average of 3.56 alleles per SSR locus. The number of alleles at each locus varied from 2 to 7. The population genetic structure analysis grouped different genotypes in three major clusters and three genetically distinct subpopulations (SPs) (i.e., SP-1, SP-2, and SP-3) with one admixture subpopulation (SP-4). Both cluster and population genetic structure analysis categorized the advanced mung bean genotypes in a single group/SP and the released varieties in other groups/SPs, suggesting that the studied genotypes may have common ancestral history at some level. The population genetic structure was also in agreement with the genetic diversity analysis. The estimate of the average degree of linkage disequilibrium (LD) present at the genome level in 80 mung bean genotypes unveiled significant LD blocks. Over the four seasons, 10 marker-trait associations were observed significant for YMD and four seed yield (SY)-related traits viz., days to flowering, days to maturity, plant height, and number of pods per plant using the mixed linear model (MLM) method. These associations may be useful for marker-assisted mung bean yield improvement programs and YMD resistance.
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Affiliation(s)
- Versha Rohilla
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh Haryana Agricultural University, Hisar, India
| | - Rajesh Kumar Yadav
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh Haryana Agricultural University, Hisar, India
| | - Atman Poonia
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh Haryana Agricultural University, Hisar, India
| | - Ravika Sheoran
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh Haryana Agricultural University, Hisar, India
| | - Gita Kumari
- ICAR-Indian Institute of Pulses Research, Kanpur, India
| | | | - Aditya Pratap
- ICAR-Indian Institute of Pulses Research, Kanpur, India
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31
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Gesteiro N, Cao A, Santiago R, Malvar RA, Butrón A. Genomics of maize resistance to kernel contamination with fumonisins using a multiparental advanced generation InterCross maize population (MAGIC). BMC PLANT BIOLOGY 2021; 21:596. [PMID: 34915847 PMCID: PMC8675497 DOI: 10.1186/s12870-021-03380-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Accepted: 11/17/2021] [Indexed: 06/01/2023]
Abstract
Maize kernel is exposed to several fungal species, most notably Fusarium verticillioides, which can contaminate maize kernels with fumonisins. In an effort to increase genetic gains and avoid the laborious tasks of conventional breeding, the use of marker-assisted selection or genomic selection programs was proposed. To this end, in the present study a Genome Wide Association Study (GWAS) was performed on 339 RILs of a Multiparental Advanced Generation InterCross (MAGIC) population that had previously been used to locate Quantitative Trait Locus (QTL) for resistance to Fusarium Ear Rot (FER). Six QTLs for fumonisin content were detected in the bins 3.08, 4.07, 4.10, 7.03-7.04, 9.04-9.05 and 10.04-10.5. Five of the six QTLs collocate in regions where QTLs for FER were also found. However, the genetic variation for fumonisin content in kernel is conditioned by many other QTLs of small effect that could show QTL x environment interaction effects. Although a genomic selection approach to directly reduce fumonisin content in the kernel could be suitable, improving resistance to fumonisin content by genomic selection for FER would be more advisable.
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Affiliation(s)
- Noemi Gesteiro
- Misión Biológica de Galicia (CSIC), Box 28, 36080, Pontevedra, Spain
| | - Ana Cao
- Misión Biológica de Galicia (CSIC), Box 28, 36080, Pontevedra, Spain
| | - Rogelio Santiago
- Departamento Biología Vegetal y Ciencias del Suelo, Facultad de Biología, Universidad de Vigo, Unidad Asociada Agrobiología Ambiental, Calidad de Suelos y Plantas, As Lagoas Marcosende, 36310 Vigo, Spain
| | - Rosa Ana Malvar
- Misión Biológica de Galicia (CSIC), Box 28, 36080, Pontevedra, Spain
| | - Ana Butrón
- Misión Biológica de Galicia (CSIC), Box 28, 36080, Pontevedra, Spain
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32
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Zuo Z, Lu Y, Zhu M, Chen R, Zhang E, Hao D, Huang Q, Wang H, Su Y, Wang Z, Xu Y, Li P, Xu C, Yang Z. Nucleotide Diversity of the Maize ZmCNR13 Gene and Association With Ear Traits. Front Genet 2021; 12:773597. [PMID: 34764988 PMCID: PMC8576287 DOI: 10.3389/fgene.2021.773597] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Accepted: 10/14/2021] [Indexed: 11/16/2022] Open
Abstract
The maize (Zea mays L.) ZmCNR13 gene, encoding a protein of fw2.2-like (FWL) family, has been demonstrated to be involved in cell division, expansion, and differentiation. In the present study, the genomic sequences of the ZmCNR13 locus were re-sequenced in 224 inbred lines, 56 landraces and 30 teosintes, and the nucleotide polymorphism and selection signature were estimated. A total of 501 variants, including 415 SNPs and 86 Indels, were detected. Among them, 51 SNPs and 4 Indels were located in the coding regions. Although neutrality tests revealed that this locus had escaped from artificial selection during the process of maize domestication, the population of inbred lines possesses lower nucleotide diversity and decay of linkage disequilibrium. To estimate the association between sequence variants of ZmCNR13 and maize ear characteristics, a total of ten ear-related traits were obtained from the selected inbred lines. Four variants were found to be significantly associated with six ear-related traits. Among them, SNP2305, a non-synonymous mutation in exon 2, was found to be associated with ear weight, ear grain weight, ear diameter and ear row number, and explained 4.59, 4.61, 4.31, and 8.42% of the phenotypic variations, respectively. These results revealed that natural variations of ZmCNR13 might be involved in ear development and can be used in genetic improvement of maize ear-related traits.
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Affiliation(s)
- Zhihao Zuo
- Jiangsu Key Laboratory of Crop Genetics and Physiology Key Laboratory of Plant Functional Genomics of the Ministry of Education Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding, Agricultural College of Yangzhou University, Yangzhou, China.,Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou, China.,Joint International Research Laboratory of Agriculture and Agri-Product Safety of Ministry of Education of China, Yangzhou University, Yangzhou, China
| | - Yue Lu
- Jiangsu Key Laboratory of Crop Genetics and Physiology Key Laboratory of Plant Functional Genomics of the Ministry of Education Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding, Agricultural College of Yangzhou University, Yangzhou, China.,Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou, China.,Joint International Research Laboratory of Agriculture and Agri-Product Safety of Ministry of Education of China, Yangzhou University, Yangzhou, China
| | - Minyan Zhu
- Jiangsu Key Laboratory of Crop Genetics and Physiology Key Laboratory of Plant Functional Genomics of the Ministry of Education Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding, Agricultural College of Yangzhou University, Yangzhou, China.,Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou, China.,Joint International Research Laboratory of Agriculture and Agri-Product Safety of Ministry of Education of China, Yangzhou University, Yangzhou, China
| | - Rujia Chen
- Jiangsu Key Laboratory of Crop Genetics and Physiology Key Laboratory of Plant Functional Genomics of the Ministry of Education Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding, Agricultural College of Yangzhou University, Yangzhou, China.,Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou, China.,Joint International Research Laboratory of Agriculture and Agri-Product Safety of Ministry of Education of China, Yangzhou University, Yangzhou, China
| | - Enying Zhang
- College of Agronomy, Qingdao Agricultural University, Qingdao, China
| | - Derong Hao
- Jiangsu Yanjiang Institute of Agricultural Sciences, Nantong, China
| | - Qianfeng Huang
- Jiangsu Key Laboratory of Crop Genetics and Physiology Key Laboratory of Plant Functional Genomics of the Ministry of Education Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding, Agricultural College of Yangzhou University, Yangzhou, China.,Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou, China
| | - Hanyao Wang
- Jiangsu Key Laboratory of Crop Genetics and Physiology Key Laboratory of Plant Functional Genomics of the Ministry of Education Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding, Agricultural College of Yangzhou University, Yangzhou, China
| | - Yanze Su
- Jiangsu Key Laboratory of Crop Genetics and Physiology Key Laboratory of Plant Functional Genomics of the Ministry of Education Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding, Agricultural College of Yangzhou University, Yangzhou, China
| | - Zhichao Wang
- Jiangsu Key Laboratory of Crop Genetics and Physiology Key Laboratory of Plant Functional Genomics of the Ministry of Education Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding, Agricultural College of Yangzhou University, Yangzhou, China
| | - Yang Xu
- Jiangsu Key Laboratory of Crop Genetics and Physiology Key Laboratory of Plant Functional Genomics of the Ministry of Education Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding, Agricultural College of Yangzhou University, Yangzhou, China.,Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou, China.,Joint International Research Laboratory of Agriculture and Agri-Product Safety of Ministry of Education of China, Yangzhou University, Yangzhou, China
| | - Pengcheng Li
- Jiangsu Key Laboratory of Crop Genetics and Physiology Key Laboratory of Plant Functional Genomics of the Ministry of Education Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding, Agricultural College of Yangzhou University, Yangzhou, China.,Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou, China.,Joint International Research Laboratory of Agriculture and Agri-Product Safety of Ministry of Education of China, Yangzhou University, Yangzhou, China
| | - Chenwu Xu
- Jiangsu Key Laboratory of Crop Genetics and Physiology Key Laboratory of Plant Functional Genomics of the Ministry of Education Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding, Agricultural College of Yangzhou University, Yangzhou, China.,Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou, China.,Joint International Research Laboratory of Agriculture and Agri-Product Safety of Ministry of Education of China, Yangzhou University, Yangzhou, China
| | - Zefeng Yang
- Jiangsu Key Laboratory of Crop Genetics and Physiology Key Laboratory of Plant Functional Genomics of the Ministry of Education Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding, Agricultural College of Yangzhou University, Yangzhou, China.,Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou, China.,Joint International Research Laboratory of Agriculture and Agri-Product Safety of Ministry of Education of China, Yangzhou University, Yangzhou, China
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Zhang-Biehn S, Fritz AK, Zhang G, Evers B, Regan R, Poland J. Accelerating wheat breeding for end-use quality through association mapping and multivariate genomic prediction. THE PLANT GENOME 2021; 14:e20164. [PMID: 34817128 DOI: 10.1002/tpg2.20164] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Accepted: 08/23/2021] [Indexed: 06/13/2023]
Abstract
In hard-winter wheat (Triticum aestivum L.) breeding, the evaluation of end-use quality is expensive and time-consuming, being relegated to the final stages of the breeding program after selection for many traits including disease resistance, agronomic performance, and grain yield. In this study, our objectives were to identify genetic variants underlying baking quality traits through genome-wide association study (GWAS) and develop improved genomic selection (GS) models for the quality traits in hard-winter wheat. Advanced breeding lines (n = 462) from 2015-2017 were genotyped using genotyping-by-sequencing (GBS) and evaluated for baking quality. Significant associations were detected for mixograph mixing time and bake mixing time, most of which were within or in tight linkage to glutenin and gliadin loci and could be suitable for marker-assisted breeding. Candidate genes for newly associated loci are phosphate-dependent decarboxylase and lipid transfer protein genes, which are believed to affect nitrogen metabolism and dough development, respectively. The use of GS can both shorten the breeding cycle time and significantly increase the number of lines that could be selected for quality traits, thus we evaluated various GS models for end-use quality traits. As a baseline, univariate GS models had 0.25-0.55 prediction accuracy in cross-validation and from 0 to 0.41 in forward prediction. By including secondary traits as additional predictor variables (univariate GS with covariates) or correlated response variables (multivariate GS), the prediction accuracies were increased relative to the univariate model using only genomic information. The improved genomic prediction models have great potential to further accelerate wheat breeding for end-use quality.
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Affiliation(s)
- Shichen Zhang-Biehn
- Dep. of Plant Pathology, Kansas State Univ., 4024 Throckmorton Plant Sciences Center, 1712 Claflin Rd., Manhattan, KS, 66506, USA
- current address: Syngenta, 317 330th St., Stanton, MN, 55018, USA
| | - Allan K Fritz
- Dep. of Agronomy, Kansas State Univ., 4012 Throckmorton Plant Sciences Center, 1712 Claflin Rd., Manhattan, KS, 66506, USA
| | - Guorong Zhang
- Agricultural Research Center-Hays, Kansas State Univ., 1232 240th Ave., Hays, KS, 67601, USA
| | - Byron Evers
- Dep. of Plant Pathology, Kansas State Univ., 4024 Throckmorton Plant Sciences Center, 1712 Claflin Rd., Manhattan, KS, 66506, USA
| | - Rebecca Regan
- Dep. of Grain Science and Industry, Kansas State Univ., Shellenberger 108, Manhattan, KS, 66506, USA
| | - Jesse Poland
- Dep. of Plant Pathology, Kansas State Univ., 4024 Throckmorton Plant Sciences Center, 1712 Claflin Rd., Manhattan, KS, 66506, USA
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34
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Lai R, Ikram M, Li R, Xia Y, Yuan Q, Zhao W, Zhang Z, Siddique KHM, Guo P. Identification of Novel Quantitative Trait Nucleotides and Candidate Genes for Bacterial Wilt Resistance in Tobacco ( Nicotiana tabacum L.) Using Genotyping-by-Sequencing and Multi-Locus Genome-Wide Association Studies. FRONTIERS IN PLANT SCIENCE 2021; 12:744175. [PMID: 34745174 PMCID: PMC8566715 DOI: 10.3389/fpls.2021.744175] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Accepted: 09/22/2021] [Indexed: 05/17/2023]
Abstract
Tobacco bacterial wilt (TBW) is a devastating soil-borne disease threatening the yield and quality of tobacco. However, its genetic foundations are not fully understood. In this study, we identified 126,602 high-quality single-nucleotide polymorphisms (SNPs) in 94 tobacco accessions using genotyping-by-sequencing (GBS) and a 94.56 KB linkage disequilibrium (LD) decay rate for candidate gene selection. The population structure analysis revealed two subpopulations with 37 and 57 tobacco accessions. Four multi-locus genome-wide association study (ML-GWAS) approaches identified 142 quantitative trait nucleotides (QTNs) in E1-E4 and the best linear unbiased prediction (BLUP), explaining 0.49-22.52% phenotypic variance. Of these, 38 novel stable QTNs were identified across at least two environments/methods, and their alleles showed significant TBW-DI differences. The number of superior alleles associated with TBW resistance for each accession ranged from 4 to 24; eight accessions had more than 18 superior alleles. Based on TBW-resistant alleles, the five best cross combinations were predicted, including MC133 × Ruyuan No. 1 and CO258 × ROX28. We identified 52 candidate genes around 38 QTNs related to TBW resistance based on homologous functional annotation and KEGG enrichment analysis, e.g., CYCD3;2, BSK1, Nitab4.5_0000641g0050, Nitab4.5_0000929g0030. To the best of our knowledge, this is the first comprehensive study to identify QTNs, superior alleles, and their candidate genes for breeding TBW-resistant tobacco varieties. The results provide further insight into the genetic architecture, marker-assisted selection, and functional genomics of TBW resistance, improving future breeding efforts to increase crop productivity.
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Affiliation(s)
- Ruiqiang Lai
- International Crop Research Center for Stress Resistance, School of Life Sciences, Guangzhou University, Guangzhou, China
| | - Muhammad Ikram
- International Crop Research Center for Stress Resistance, School of Life Sciences, Guangzhou University, Guangzhou, China
| | - Ronghua Li
- International Crop Research Center for Stress Resistance, School of Life Sciences, Guangzhou University, Guangzhou, China
| | - Yanshi Xia
- International Crop Research Center for Stress Resistance, School of Life Sciences, Guangzhou University, Guangzhou, China
| | - Qinghua Yuan
- Crop Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou, China
| | - Weicai Zhao
- Nanxiong Research Institute of Guangdong Tobacco Co., Ltd., Nanxiong, China
| | - Zhenchen Zhang
- Crop Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou, China
| | - Kadambot H. M. Siddique
- The UWA Institute of Agriculture, UWA School of Agriculture and Environment, The University of Western Australia, Perth, WA, Australia
| | - Peiguo Guo
- International Crop Research Center for Stress Resistance, School of Life Sciences, Guangzhou University, Guangzhou, China
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Yang CJ, Edmondson RN, Piepho HP, Powell W, Mackay I. Crafting for a better MAGIC: systematic design and test for Multiparental Advanced Generation Inter-Cross population. G3 GENES|GENOMES|GENETICS 2021; 11:6354367. [PMID: 34849794 PMCID: PMC8527519 DOI: 10.1093/g3journal/jkab295] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Accepted: 08/15/2021] [Indexed: 12/04/2022]
Abstract
Multiparental Advanced Generation Inter-Cross (MAGIC) populations are valuable crop resources with a wide array of research uses including genetic mapping of complex traits, management of genetic resources and breeding of new varieties. Multiple founders are crossed to create a rich mosaic of highly recombined founder genomes in the MAGIC recombinant inbred lines (RILs). Many variations of MAGIC population designs exist; however, a large proportion of the currently available populations have been created empirically and based on similar designs. In our evaluations of five MAGIC populations, we found that the choice of designs has a large impact on the recombination landscape in the RILs. The most popular design used in many MAGIC populations has been shown to have a bias in recombinant haplotypes and low level of unique recombinant haplotypes, and therefore is not recommended. To address this problem and provide a remedy for the future, we have developed the “magicdesign” R package for creating and testing any MAGIC population design via simulation. A Shiny app version of the package is available as well. Our “magicdesign” package provides a unifying tool and a framework for creativity and innovation in MAGIC population designs. For example, using this package, we demonstrate that MAGIC population designs can be found which are very effective in creating haplotype diversity without the requirement for very large crossing programs. Furthermore, we show that interspersing cycles of crossing with cycles of selfing is effective in increasing haplotype diversity. These approaches are applicable in species that are hard to cross or in which resources are limited.
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Affiliation(s)
| | | | - Hans-Peter Piepho
- Biostatistics Unit, Institute of Crop Science, University of Hohenheim, Stuttgart 70593, Germany
| | - Wayne Powell
- Scotland’s Rural College (SRUC), Edinburgh EH9 3JG, UK
| | - Ian Mackay
- Scotland’s Rural College (SRUC), Edinburgh EH9 3JG, UK
- IMplant Consultancy Ltd., Chelmsford, UK
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Gupta PK. GWAS for genetics of complex quantitative traits: Genome to pangenome and SNPs to SVs and k-mers. Bioessays 2021; 43:e2100109. [PMID: 34486143 DOI: 10.1002/bies.202100109] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Revised: 08/21/2021] [Accepted: 08/23/2021] [Indexed: 12/22/2022]
Abstract
The development of improved methods for genome-wide association studies (GWAS) for genetics of quantitative traits has been an active area of research during the last 25 years. This activity initially started with the use of mixed linear model (MLM), which was variously modified. During the last decade, however, with the availability of high throughput next generation sequencing (NGS) technology, development and use of pangenomes and novel markers including structural variations (SVs) and k-mers for GWAS has taken over as a new thrust area of research. Pangenomes and SVs are now available in humans, livestock, and a number of plant species, so that these resources along with k-mers are being used in GWAS for exploring additional genetic variation that was hitherto not available for analysis. These developments have resulted in significant improvement in GWAS methodology for detection of marker-trait associations (MTAs) that are relevant to human healthcare and crop improvement.
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Affiliation(s)
- Pushpendra K Gupta
- Department of Genetics and Plant Breeding, Ch. Charan Singh University Meerut, Meerut, Uttar Pradesh, India
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Huang C, Shen C, Wen T, Gao B, Zhu D, Li D, Lin Z. Genome-wide association mapping for agronomic traits in an 8-way Upland cotton MAGIC population by SLAF-seq. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2021; 134:2459-2468. [PMID: 33912997 DOI: 10.1007/s00122-021-03835-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Accepted: 04/12/2021] [Indexed: 06/12/2023]
Abstract
One sub-MAGIC population was genotyped using SLAF-seq, and QTLs and candidate genes for agronomic traits were identified in Upland cotton. The agronomic traits of Upland cotton have serious impacts on cotton production, as well as economic benefits. To discover the genetic basis of important agronomic traits in Upland cotton, a subset MAGIC (multi-parent advanced generation inter-cross) population containing 372 lines (SMLs) was selected from an 8-way MAGIC population with 960 lines. The 372 lines and 8 parents were phenotyped in six environments and deeply genotyped by SLAF-seq with 60,495 polymorphic SNPs. The genetic diversity indexes of all SNPs were 0.324 and 0.362 for the parents and MAGIC lines, respectively. The LD decay distance of the SMLs was 600 kb (r2 = 0.1). Genome-wide association mapping was performed using 60,495 SNPs and the phenotypic data of the SMLs, and 177 SNPs were identified to be significantly associated with 9 stable agronomic traits in multiple environments. The identified SNPs were divided into 117 QTLs (quantitative trait loci) by LD decay distance, explaining 5.44% to 31.64% of the phenotypic variation. Among the 117 QTLs, 3 QTLs were stable in multiple environments, and 11 QTL regions were proven to have pleiotropism associated with multiple traits. Within QTL regions, 154 genes were preferentially expressed in correlated tissues, and 8 genes with known functions were identified as priori candidate genes. Two genes, GhACT1 and GhGASL3, reported to have clear functions, were, respectively, located in qFE-A05-4 and qFE-D04-3, two stable QTLs for FE. This study revealed the genetic basis of important agronomic traits of Upland cotton, and the results will facilitate molecular breeding in cotton.
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Affiliation(s)
- Cong Huang
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Chao Shen
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Tianwang Wen
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Bin Gao
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - De Zhu
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Dingguo Li
- Institute of Crop Genetic and Breeding, Yangtze University, Jingzhou, 434025, Hubei, China.
| | - Zhongxu Lin
- National Key Laboratory of Crop Genetic Improvement, College of Plant Sciences & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
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Mohammadi Alaghuz R, Darvishzadeh R, Alijanpour A, Razi M. Toward the identification of molecular markers associated with phytochemical traits in the Iranian sumac ( Rhus coriaria L.) population. Food Sci Nutr 2021; 9:3142-3154. [PMID: 34136179 PMCID: PMC8194943 DOI: 10.1002/fsn3.2273] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Revised: 03/09/2021] [Accepted: 03/14/2021] [Indexed: 02/04/2023] Open
Abstract
Sumac (Rhus coriaria L.) is one of the important forest species dispersed in the northwest of Iran. It is one of the important spice in Iran and the Middle East because of active components containing organic acids, phenolic acids, flavonoids, anthocyanins, tannins and terpenoids. This study aimed to investigate population structure and linkage disequilibrium (LD) extent within Rhus coriaria L. genotypes using ISSR markers and identify molecular markers associated with phytochemical traits using association analysis. In the molecular part of the experiment, the genetic diversity of 75 sumac genotypes from five different areas of northwest Iran was assessed by 18 ISSR primers. In the phenotypic assessment, the fruits of the sumac genotypes were analyzed using HPLC-LC/MSMS for determining phytochemical components including maleic acid, ellagic acid, maleic acid hexoside, gallic acid, coumaric acid, quercetin, caftaric acid, and linoleic acid. The phenotypic data analysis revealed the great phenotypic diversity among and within Iranian sumac populations for the studied phytochemical traits. The studied sumac genotypes were divided into two subpopulations based on molecular marker-based structure analysis. A significant level of LD was observed in 11.64% of the ISSR marker pairs (p < .05). The mixed linear model procedure showed that 12 loci had a significant association with investigated traits. The ISSR loci identified in this study can be potentially used in marker-assisted selection in sumac breeding programs.
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Affiliation(s)
- Rasoul Mohammadi Alaghuz
- Agricultural BiotechnologyDepartment of Plant Production and GeneticsFaculty of Agriculture and Natural ResourcesUrmia UniversityUrmiaIran
| | - Reza Darvishzadeh
- Department of Plant Production and GeneticsFaculty of Agriculture and Natural ResourcesUrmia UniversityUrmiaIran
| | - Ahmad Alijanpour
- Department of ForestryFaculty of Agriculture and Natural ResourcesUrmia UniversityUrmiaIran
| | - Mitra Razi
- Department of Plant Production and GeneticsFaculty of Agriculture and Natural ResourcesUrmia UniversityUrmiaIran
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Quan X, Liu J, Zhang N, Xie C, Li H, Xia X, He W, Qin Y. Genome-Wide Association Study Uncover the Genetic Architecture of Salt Tolerance-Related Traits in Common Wheat ( Triticum aestivum L.). Front Genet 2021; 12:663941. [PMID: 34093656 PMCID: PMC8172982 DOI: 10.3389/fgene.2021.663941] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Accepted: 03/24/2021] [Indexed: 01/13/2023] Open
Abstract
Soil salinity is a serious threat to wheat yield affecting sustainable agriculture. Although salt tolerance is important for plant establishment at seedling stage, its genetic architecture remains unclear. In the present study, we have evaluated eight salt tolerance-related traits at seedling stage and identified the loci for salt tolerance by genome-wide association study (GWAS). This GWAS panel comprised 317 accessions and was genotyped with the wheat 90 K single-nucleotide polymorphism (SNP) chip. In total, 37 SNPs located at 16 unique loci were identified, and each explained 6.3 to 18.6% of the phenotypic variations. Among these, six loci were overlapped with previously reported genes or quantitative trait loci, whereas the other 10 were novel. Besides, nine loci were detected for two or more traits, indicating that the salt-tolerance genetic architecture is complex. Furthermore, five candidate genes were identified for salt tolerance-related traits, including kinase family protein, E3 ubiquitin-protein ligase-like protein, and transmembrane protein. SNPs identified in this study and the accessions with more favorable alleles could further enhance salt tolerance in wheat breeding. Our results are useful for uncovering the genetic mechanism of salt tolerance in wheat at seeding stage.
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Affiliation(s)
- Xiaoyan Quan
- Department of Biological Science, School of Biological Science and Technology, University of Jinan, Jinan, China
| | - Jindong Liu
- Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China.,Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Ning Zhang
- Department of Biological Science, School of Biological Science and Technology, University of Jinan, Jinan, China
| | - Chunjuan Xie
- Department of Biological Science, School of Biological Science and Technology, University of Jinan, Jinan, China
| | - Hongmei Li
- Department of Biological Science, School of Biological Science and Technology, University of Jinan, Jinan, China
| | - Xianchun Xia
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Wenxing He
- Department of Biological Science, School of Biological Science and Technology, University of Jinan, Jinan, China
| | - Yuxiang Qin
- Department of Biological Science, School of Biological Science and Technology, University of Jinan, Jinan, China
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Ullah S, Randhawa IAS, Trethowan R. Genome-wide association study of multiple traits linked to heat tolerance in emmer-derived hexaploid wheat genotypes. MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2021; 41:29. [PMID: 37309354 PMCID: PMC10236052 DOI: 10.1007/s11032-021-01222-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Accepted: 03/17/2021] [Indexed: 06/13/2023]
Abstract
Heat stress tolerance in plants is a complex trait controlled by multiple genes of minor effect which are influenced by the environment and this makes breeding and selection complicated. Emmer wheat (Triticum dicoccon Schrank) carries valuable diversity that can be used to improve the heat tolerance of modern bread wheat. A diverse set of emmer-based genotypes was developed by crossing emmer wheat with hexaploid wheat. These materials, along with their hexaploid recurrent parents and commercial cultivars, were evaluated at optimum (E1) and heat stressed (E2) sowing times in the field for three consecutive years (2014-2016). The material was genotyped using the Infinium iSelect SNP 90K SNP Assay. The phenotypic data were combined across years within each sowing time and best linear unbiased estimators calculated for each genotype in each environment. These estimates were used for GWAS analysis. Significant phenotypic and genotypic variation was observed for all traits. A total of 125 and 142 marker-trait associations (MTAs) were identified in E1 and E2, respectively. The highest number of MTAs were observed on the A genome (106), followed by the B (105) and D (56) genomes. MTAs with pleiotropic effects within and across the environments were observed. Many of the MTAs found were reported previously for various traits, and a few significant MTAs under heat stress were new and linked to emmer genome. Genomic regions identified on chromosomes 2B and 3A had a significant positive impact on grain yield under stress with a 7% allelic effect. Genomic regions on chromosomes 1A and 4B contributed 11% and 9% of the variation for thousand kernel weight (TKW) under heat stress respectively. Following fine mapping, these regions could be used for marker-assisted selection to improve heat tolerance in wheat. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-021-01222-3.
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Affiliation(s)
- Smi Ullah
- School of Life and Environmental Sciences, Plant Breeding Institute and Sydney Institute of Agriculture, The University of Sydney, Narrabri, New South Wales 2390 Australia
| | - Imtiaz A. S. Randhawa
- School of Veterinary Science, The University of Queensland, Gatton, Queensland 4343 Australia
| | - Richard Trethowan
- School of Life and Environmental Sciences, Plant Breeding Institute and Sydney Institute of Agriculture, The University of Sydney, Narrabri, New South Wales 2390 Australia
- School of Life and Environmental Sciences, Plant Breeding Institute and Sydney Institute of Agriculture, The University of Sydney, Cobbitty, New South Wales 2570 Australia
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Lucek K, Willi Y. Drivers of linkage disequilibrium across a species' geographic range. PLoS Genet 2021; 17:e1009477. [PMID: 33770075 PMCID: PMC8026057 DOI: 10.1371/journal.pgen.1009477] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2020] [Revised: 04/07/2021] [Accepted: 03/09/2021] [Indexed: 11/25/2022] Open
Abstract
While linkage disequilibrium (LD) is an important parameter in genetics and evolutionary biology, the drivers of LD remain elusive. Using whole-genome sequences from across a species’ range, we assessed the impact of demographic history and mating system on LD. Both range expansion and a shift from outcrossing to selfing in North American Arabidopsis lyrata were associated with increased average genome-wide LD. Our results indicate that range expansion increases short-distance LD at the farthest range edges by about the same amount as a shift to selfing. However, the extent over which LD in genic regions unfolds was shorter for range expansion compared to selfing. Linkage among putatively neutral variants and between neutral and deleterious variants increased to a similar degree with range expansion, providing support that genome-wide LD was positively associated with mutational load. As a consequence, LD combined with mutational load may decelerate range expansions and set range limits. Finally, a small number of genes were identified as LD outliers, suggesting that they experience selection by either of the two demographic processes. These included genes involved in flowering and photoperiod for range expansion, and the self-incompatibility locus for mating system. Nearby genomic variants are often co-inherited because of limited recombination. The extent of non-random association of alleles at different loci is called linkage disequilibrium (LD) and is commonly used in genomic analyses, for example to detect regions under selection or to determine effective population size. Here we reversed testing and addressed how demographic history may affect LD within a species. Using genomic data from more than a thousand individuals of North American Arabidopsis lyrata from across the entire species’ range, we quantified the effect of postglacial range expansion and a shift in mating system from outcrossing to selfing on LD. We show that both factors lead to increased LD, and that the maximal effect of range expansion is comparable with a shift in mating system to selfing. Heightened LD involves deleterious mutations, and therefore, LD can also serve as an indicator of mutation accumulation. Furthermore, we provide evidence that some genes experienced stronger increases in LD possibly due to selection associated with the two demographic changes. Our results provide a novel and broad view on the evolutionary factors shaping LD that may also apply to the very many species that underwent postglacial range expansion.
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Affiliation(s)
- Kay Lucek
- Department of Environmental Sciences, University of Basel, Basel, Switzerland
- * E-mail:
| | - Yvonne Willi
- Department of Environmental Sciences, University of Basel, Basel, Switzerland
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Miller CN, Busch W. Using natural variation to understand plant responses to iron availability. JOURNAL OF EXPERIMENTAL BOTANY 2021; 72:2154-2164. [PMID: 33458759 PMCID: PMC7966951 DOI: 10.1093/jxb/erab012] [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: 01/14/2021] [Accepted: 01/15/2021] [Indexed: 05/08/2023]
Abstract
Iron bioavailability varies dramatically between soil types across the globe. This has given rise to high levels of natural variation in plant iron responses, allowing members of even a single species to thrive across a wide range of soil types. In recent years we have seen the use of genome-wide association analysis to identify natural variants underlying plant responses to changes in iron availability in both Arabidopsis and important crop species. These studies have provided insights into which genes have been important in shaping local adaptation to iron availability in different plant species and have allowed the discovery of novel regulators and mechanisms, not previously identified using mutagenesis approaches. Furthermore, these studies have allowed the identification of markers that can be used to accelerate breeding of future elite varieties with increased resilience to iron stress and improved nutritional quality. The studies highlighted here show that, in addition to studying plant responses to iron alone, it is important to consider these responses within the context of plant nutrition more broadly and to also consider iron regulation in relation to additional traits of agronomic importance such as yield and disease resistance.
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Affiliation(s)
- Charlotte N Miller
- Salk Institute For Biological Studies, Plant Molecular and Cellular Biology Laboratory, 10010 N Torrey Pines Rd, La Jolla, CA 92037, USA
| | - Wolfgang Busch
- Salk Institute For Biological Studies, Plant Molecular and Cellular Biology Laboratory, 10010 N Torrey Pines Rd, La Jolla, CA 92037, USA
- Correspondence:
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Yadav AK, Kumar A, Grover N, Ellur RK, Bollinedi H, Krishnan SG, Bhowmick PK, Vinod KK, Nagarajan M, Singh AK. Genome-Wide Association Study Reveals Marker-Trait Associations for Early Vegetative Stage Salinity Tolerance in Rice. PLANTS (BASEL, SWITZERLAND) 2021; 10:559. [PMID: 33809618 PMCID: PMC8000697 DOI: 10.3390/plants10030559] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Revised: 03/04/2021] [Accepted: 03/10/2021] [Indexed: 11/16/2022]
Abstract
Rice germplasm is a rich resource for discovering genes associated with salt tolerance. In the current study, a set of 96 accessions were evaluated for seedling stage salinity tolerance and its component traits. Significant phenotypic variation was observed among the genotypes for all the measured traits and eleven accessions with high level of salt tolerance at seedling stage were identified. The germplasm set comprised of three sub-populations and genome-wide association study (GWAS) identified a total of 23 marker-trait associations (MTAs) for traits studied. These MTAs were located on rice chromosomes 1, 2, 5, 6, 7, 9, and 12 and explained the trait phenotypic variances ranging from 13.98 to 29.88 %. Twenty-one MTAs identified in this study were located either in or near the previously reported quantitative trait loci (QTLs), while two MTAs namely, qSDW2.1 and qSNC5 were novel. A total of 18 and 13 putative annotated candidate genes were identified in a genomic region spanning ~200 kb around the MTAs qSDW2.1 and qSNC5, respectively. Some of the important genes underlying the novel MTAs were OsFBA1,OsFBL7, and mTERF which are known to be associated with salinity tolerance in crops. These MTAs pave way for combining salinity tolerance with high yield in rice genotypes through molecular breeding.
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Affiliation(s)
- Ashutosh Kumar Yadav
- Division of Genetics, ICAR—Indian Agricultural Research Institute, New Delhi 110012, India; (A.K.Y.); (N.G.); (R.K.E.); (H.B.); (S.G.K.); (P.K.B.); (K.K.V.)
- Amity Institute of Biotechnology, Amity University, Noida 201303, India;
| | - Aruna Kumar
- Amity Institute of Biotechnology, Amity University, Noida 201303, India;
| | - Nitasha Grover
- Division of Genetics, ICAR—Indian Agricultural Research Institute, New Delhi 110012, India; (A.K.Y.); (N.G.); (R.K.E.); (H.B.); (S.G.K.); (P.K.B.); (K.K.V.)
| | - Ranjith Kumar Ellur
- Division of Genetics, ICAR—Indian Agricultural Research Institute, New Delhi 110012, India; (A.K.Y.); (N.G.); (R.K.E.); (H.B.); (S.G.K.); (P.K.B.); (K.K.V.)
| | - Haritha Bollinedi
- Division of Genetics, ICAR—Indian Agricultural Research Institute, New Delhi 110012, India; (A.K.Y.); (N.G.); (R.K.E.); (H.B.); (S.G.K.); (P.K.B.); (K.K.V.)
| | - Subbaiyan Gopala Krishnan
- Division of Genetics, ICAR—Indian Agricultural Research Institute, New Delhi 110012, India; (A.K.Y.); (N.G.); (R.K.E.); (H.B.); (S.G.K.); (P.K.B.); (K.K.V.)
| | - Prolay Kumar Bhowmick
- Division of Genetics, ICAR—Indian Agricultural Research Institute, New Delhi 110012, India; (A.K.Y.); (N.G.); (R.K.E.); (H.B.); (S.G.K.); (P.K.B.); (K.K.V.)
| | - Kunnummal Kurungara Vinod
- Division of Genetics, ICAR—Indian Agricultural Research Institute, New Delhi 110012, India; (A.K.Y.); (N.G.); (R.K.E.); (H.B.); (S.G.K.); (P.K.B.); (K.K.V.)
| | - Mariappan Nagarajan
- Rice Breeding and Genetics Research Centre, ICAR—Indian Agricultural Research Institute, Aduthurai 612101, Tamil Nadu, India;
| | - Ashok Kumar Singh
- Division of Genetics, ICAR—Indian Agricultural Research Institute, New Delhi 110012, India; (A.K.Y.); (N.G.); (R.K.E.); (H.B.); (S.G.K.); (P.K.B.); (K.K.V.)
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Hosseini MS, Ebrahimi M, Samsampour D, Abadía J, Khanahmadi M, Amirian R, Ghafoori IN, Ghaderi-Zefrehei M, Gogorcena Y. Association analysis and molecular tagging of phytochemicals in the endangered medicinal plant licorice (Glycyrrhiza glabra L.). PHYTOCHEMISTRY 2021; 183:112629. [PMID: 33516043 DOI: 10.1016/j.phytochem.2020.112629] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Revised: 12/15/2020] [Accepted: 12/16/2020] [Indexed: 05/12/2023]
Abstract
Licorice (Glycyrrhiza glabra L.) is a medicinal plant species valued in many countries in Asia and Europe for its phytochemical characteristics. Licorice biodiversity is becoming threatened nowadays in Iran due to increasing demand and a drastic decline of its natural habitats. Therefore, licorice domestication would be necessary in the near future, and molecular breeding would help to introduce genotypes suitable for cultivation. The present study was carried out with 170 individual licorice plants sampled in the wild in 59 localizations in 21 provinces of Iran. The association of 436 polymorphic AFLP markers, produced by 15 primer combinations (EcoRI/MseI), with six phenotypic phytochemical traits was studied. The AMOVA analysis show gene diversity among and within localizations. The population structure analysis identified two main sub-populations with significant genetic variation. Significant associations were identified between three markers (E3/M40-4, E34/M4-12 and E12/M31-15) and glycyrrhizin concentration, and between four markers (E11/M34-12, E11/M34-15, E9/M7-29, and E9/M7-30) and phenolic compounds contents. Markers detected can be useful in the domestication of licorice as well as in breeding programs. Licorice sampled in four localizations (KBA1, KBA2, SKh2 and Fa1) were found to be superior in terms of glycyrrhizin and antioxidants content, and therefore they can be considered as elite genotypes which could be included in the domestication process.
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Affiliation(s)
- Marjan Sadat Hosseini
- Agricultural Biotechnology Research Institute of Iran - Isfahan Branch, Agricultural Research, Education and Extension Organization (AREEO), P.O. Box 85135-487, Isfahan, Iran; Department of Horticultural Science, Faculty of Agriculture, University of Hormozgan, P.O.Box, 3995, Bandar Abbas, Iran.
| | - Morteza Ebrahimi
- Agricultural Biotechnology Research Institute of Iran - Isfahan Branch, Agricultural Research, Education and Extension Organization (AREEO), P.O. Box 85135-487, Isfahan, Iran.
| | - Davood Samsampour
- Department of Horticultural Science, Faculty of Agriculture, University of Hormozgan, P.O.Box, 3995, Bandar Abbas, Iran.
| | - Javier Abadía
- Department of Plant Nutrition, Aula Dei Experimental Station (CSIC), P.O. Box 13034, 50059, Zaragoza, Spain.
| | - Morteza Khanahmadi
- Agricultural Biotechnology Research Institute of Iran - Isfahan Branch, Agricultural Research, Education and Extension Organization (AREEO), P.O. Box 85135-487, Isfahan, Iran.
| | - Rasool Amirian
- Agricultural Biotechnology Research Institute of Iran - Isfahan Branch, Agricultural Research, Education and Extension Organization (AREEO), P.O. Box 85135-487, Isfahan, Iran.
| | - Iman Naseh Ghafoori
- Agricultural Biotechnology Research Institute of Iran - Isfahan Branch, Agricultural Research, Education and Extension Organization (AREEO), P.O. Box 85135-487, Isfahan, Iran.
| | - Mostafa Ghaderi-Zefrehei
- Department of Genetic and Animal Breeding, Faculty of Agriculture, Yasouj University, P.O. Box 75918-74831, Yasouj, Iran.
| | - Yolanda Gogorcena
- Department of Pomology, Aula Dei Experimental Station (CSIC), P.O. Box 13034, 50059, Zaragoza, Spain.
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Gerard D. Pairwise linkage disequilibrium estimation for polyploids. Mol Ecol Resour 2021; 21:1230-1242. [PMID: 33559321 DOI: 10.1111/1755-0998.13349] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Revised: 01/18/2021] [Accepted: 02/01/2021] [Indexed: 12/31/2022]
Abstract
Many tasks in statistical genetics involve pairwise estimation of linkage disequilibrium (LD). The study of LD in diploids is mature. However, in polyploids, the field lacks a comprehensive characterization of LD. Polyploids also exhibit greater levels of genotype uncertainty than diploids, yet no methods currently exist to estimate LD in polyploids in the presence of such genotype uncertainty. Furthermore, most LD estimation methods do not quantify the level of uncertainty in their LD estimates. Our study contains three major contributions. (i) We characterize haplotypic and composite measures of LD in polyploids. These composite measures of LD turn out to be functions of common statistical measures of association. (ii) We derive procedures to estimate haplotypic and composite LD in polyploids in the presence of genotype uncertainty. We do this by estimating LD directly from genotype likelihoods, which may be obtained from many genotyping platforms. (iii) We derive standard errors of all LD estimators that we discuss. We validate our methods on both real and simulated data. Our methods are implemented in the R package ldsep, available on the Comprehensive R Archive Network https://cran.r-project.org/package=ldsep.
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Affiliation(s)
- David Gerard
- Department of Mathematics and Statistics, American University, Washington, DC, USA
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Jabbari M, Fakheri BA, Aghnoum R, Darvishzadeh R, Mahdi Nezhad N, Ataei R, Koochakpour Z, Razi M. Association analysis of physiological traits in spring barley ( Hordeum vulgare L.) under water-deficit conditions. Food Sci Nutr 2021; 9:1761-1779. [PMID: 33747487 PMCID: PMC7958556 DOI: 10.1002/fsn3.2161] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Revised: 01/13/2021] [Accepted: 01/15/2021] [Indexed: 01/18/2023] Open
Abstract
In the present study, 148 commercial barley cultivars were assessed by 14 AFLP primer combinations and 32 SSRs primer pairs. Population structure, linkage disequilibrium, and genomic regions associated with physiological traits under drought stress were investigated. The phenotypic results showed a high level of diversity between studied cultivars. The studied barley cultivars were divided into two subgroups. Linkage disequilibrium analysis revealed that r 2 values among all possible marker pairs have an average value of 0.0178. The mixed linear model procedure showed that totally, 207 loci had a significant association with investigated traits. 120 QTLs out of 207 were detected for traits under normal conditions, and 90 QTLs were detected for traits under drought stress conditions. Identified QTLs after validation and transferring to SCAR markers in the case of AFLPs can be used to develop MAS strategies for barley breeding programs. Some common markers were identified for a particular trait or some traits across normal and drought stress conditions. These markers show low interaction with environmental conditions (stable markers); therefore, selection by them for a trait under normal conditions will improve the trait value under stress conditions, too.
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Affiliation(s)
- Mitra Jabbari
- Faculty of AgricultureHigher Education Complex of SaravanSaravanSistan and BaluchestanIran
| | - Barat Ali Fakheri
- Department of Plant Breeding and BiotechnologyFaculty of AgricultureUniversity of ZabolZabolSistan and BaluchestanIran
| | - Reza Aghnoum
- Seed and Plant Improvement Research DepartmentKhorasan Razavi Agricultural and Natural Resources Research and Education CenterAREEOMashhadKhorasan RazaviIran
| | - Reza Darvishzadeh
- Department of Plant Production and GeneticsFaculty of Agriculture and Natural ResourcesUrmia UniversityUrmiaIran
| | - Nafiseh Mahdi Nezhad
- Department of Plant Breeding and BiotechnologyFaculty of AgricultureUniversity of ZabolZabolSistan and BaluchestanIran
| | - Reza Ataei
- Seed and Plant Improvement InstituteAgricultural Research, Education and Extension Organization (AREEO)KarajIran
| | - Zahra Koochakpour
- Department of Plant Breeding and BiotechnologyFaculty of AgricultureUniversity of ZabolZabolSistan and BaluchestanIran
| | - Mitra Razi
- Department of Plant Production and GeneticsFaculty of Agriculture and Natural ResourcesUrmia UniversityUrmiaIran
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Lou XY, Hou TT, Liu SY, Xu HM, Lin F, Tang X, MacLeod SL, Cleves MA, Hobbs CA. Innovative approach to identify multigenomic and environmental interactions associated with birth defects in family-based hybrid designs. Genet Epidemiol 2021; 45:171-189. [PMID: 32996630 PMCID: PMC8495752 DOI: 10.1002/gepi.22363] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Revised: 09/08/2020] [Accepted: 09/11/2020] [Indexed: 11/09/2022]
Abstract
Genes, including those with transgenerational effects, work in concert with behavioral, environmental, and social factors via complex biological networks to determine human health. Understanding complex relationships between causal factors underlying human health is an essential step towards deciphering biological mechanisms. We propose a new analytical framework to investigate the interactions between maternal and offspring genetic variants or their surrogate single nucleotide polymorphisms (SNPs) and environmental factors using family-based hybrid study design. The proposed approach can analyze diverse genetic and environmental factors and accommodate samples from a variety of family units, including case/control-parental triads, and case/control-parental dyads, while minimizing potential bias introduced by population admixture. Comprehensive simulations demonstrated that our innovative approach outperformed the log-linear approach, the best available method for case-control family data. The proposed approach had greater statistical power and was capable to unbiasedly estimate the maternal and child genetic effects and the effects of environmental factors, while controlling the Type I error rate against population stratification. Using our newly developed approach, we analyzed the associations between maternal and fetal SNPs and obstructive and conotruncal heart defects, with adjustment for demographic and lifestyle factors and dietary supplements. Fourteen and 11 fetal SNPs were associated with obstructive and conotruncal heart defects, respectively. Twenty-seven and 17 maternal SNPs were associated with obstructive and conotruncal heart defects, respectively. In addition, maternal body mass index was a significant risk factor for obstructive defects. The proposed approach is a powerful tool for interrogating the etiological mechanism underlying complex traits.
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Affiliation(s)
- Xiang-Yang Lou
- Department of Biostatistics, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, Florida, USA
| | - Ting-Ting Hou
- Department of Biostatistics, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, Florida, USA
- Institute of Bioinformatics and Institute of Crop Science, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, China
| | - Shou-Ye Liu
- Institute of Bioinformatics and Institute of Crop Science, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, China
| | - Hai-Ming Xu
- Institute of Bioinformatics and Institute of Crop Science, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, China
| | - Feng Lin
- Institute of Bioinformatics and Institute of Crop Science, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, China
| | - Xinyu Tang
- The US Food and Drug Administration, Silver Spring, Maryland, USA
| | | | - Mario A. Cleves
- Department of Pediatrics, Morsani College of Medicine, Health Informatics Institute, University of South Florida, Tampa, Florida, USA
| | - Charlotte A. Hobbs
- Rady Children’s Institute for Genomic Medicine, San Diego, California, USA
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48
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Di Guardo M, Farneti B, Khomenko I, Modica G, Mosca A, Distefano G, Bianco L, Troggio M, Sottile F, La Malfa S, Biasioli F, Gentile A. Genetic characterization of an almond germplasm collection and volatilome profiling of raw and roasted kernels. HORTICULTURE RESEARCH 2021; 8:27. [PMID: 33518710 PMCID: PMC7848010 DOI: 10.1038/s41438-021-00465-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Revised: 12/11/2020] [Accepted: 12/17/2020] [Indexed: 05/16/2023]
Abstract
Almond is appreciated for its nutraceutical value and for the aromatic profile of the kernels. In this work, an almond collection composed of 96 Sicilian accessions complemented with 10 widely cultivated cultivars was phenotyped for the production of volatile organic compounds using a proton-transfer time-of-flight mass spectrometer and genotyped using the Illumina Infinium®18 K Peach SNP array. The profiling of the aroma was carried out on fresh and roasted kernels enabling the detection of 150 mass peaks. Sixty eight, for the most related with sulfur compounds, furan containing compounds, and aldehydes formed by Strecker degradation, significantly increased during roasting, while the concentration of fifty-four mass peaks, for the most belonging to alcohols and terpenes, significantly decreased. Four hundred and seventy-one robust SNPs were selected and employed for population genetic studies. Structure analysis detected three subpopulations with the Sicilian accessions characterized by a different genetic stratification compared to those collected in Apulia (South Italy) and the International cultivars. The linkage-disequilibrium (LD) decay across the genome was equal to r2 = 0.083. Furthermore, a high level of collinearity (r2 = 0.96) between almond and peach was registered confirming the high synteny between the two genomes. A preliminary application of a genome-wide association analysis allowed the detection of significant marker-trait associations for 31 fresh and 33 roasted almond mass peaks respectively. An accurate genetic and phenotypic characterization of novel germplasm can represent a valuable tool for the set-up of marker-assisted selection of novel cultivars with an enhanced aromatic profile.
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Affiliation(s)
- M Di Guardo
- Department of Agriculture, Food and Environment (Di3A), University of Catania, via Valdisavoia 5, 95123, Catania, Italy
| | - B Farneti
- Research and Innovation Centre, Fondazione Edmund Mach, San Michele all' Adige, Trento, Italy
| | - I Khomenko
- Research and Innovation Centre, Fondazione Edmund Mach, San Michele all' Adige, Trento, Italy
| | - G Modica
- Department of Agriculture, Food and Environment (Di3A), University of Catania, via Valdisavoia 5, 95123, Catania, Italy
| | - A Mosca
- Department of Agriculture, Food and Environment (Di3A), University of Catania, via Valdisavoia 5, 95123, Catania, Italy
| | - G Distefano
- Department of Agriculture, Food and Environment (Di3A), University of Catania, via Valdisavoia 5, 95123, Catania, Italy.
| | - L Bianco
- Research and Innovation Centre, Fondazione Edmund Mach, San Michele all' Adige, Trento, Italy
| | - M Troggio
- Research and Innovation Centre, Fondazione Edmund Mach, San Michele all' Adige, Trento, Italy
| | - F Sottile
- Dipartimento di Architettura, University of Palermo, Viale delle Scienze, Ed. 14 90128, Palermo, Italy
| | - S La Malfa
- Department of Agriculture, Food and Environment (Di3A), University of Catania, via Valdisavoia 5, 95123, Catania, Italy
| | - F Biasioli
- Research and Innovation Centre, Fondazione Edmund Mach, San Michele all' Adige, Trento, Italy
| | - A Gentile
- Department of Agriculture, Food and Environment (Di3A), University of Catania, via Valdisavoia 5, 95123, Catania, Italy
- National Center for Citrus Improvement, College of Horticulture and Landscape, Hunan Agricultural University, Changsha, China
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Diouf I, Pascual L. Multiparental Population in Crops: Methods of Development and Dissection of Genetic Traits. Methods Mol Biol 2021; 2264:13-32. [PMID: 33263900 DOI: 10.1007/978-1-0716-1201-9_2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Multiparental populations are located midway between association mapping that relies on germplasm collections and classic linkage analysis, based upon biparental populations. They provide several key advantages such as the possibility to include a higher number of alleles and increased level of recombination with respect to biparental populations, and more equilibrated allelic frequencies than association mapping panels. Moreover, in these populations new allele's combinations arise from recombination that may reveal transgressive phenotypes and make them a useful pre-breeding material. Here we describe the strategies for working with multiparental populations, focusing on nested association mapping populations (NAM) and multiparent advanced generation intercross populations (MAGIC). We provide details from the selection of founders, population development, and characterization to the statistical methods for genetic mapping and quantitative trait detection.
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Affiliation(s)
- Isidore Diouf
- INRAE, UR1052, Génétique et Amélioration des Fruits et Légumes, Centre de Recherche PACA, Montfavet, France
| | - Laura Pascual
- Department of Biotechnology-Plant Biology, School of Agricultural, Food and Biosystems Engineering, Universidad Politécnica de Madrid, Madrid, Spain.
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Mackay IJ, Cockram J, Howell P, Powell W. Understanding the classics: the unifying concepts of transgressive segregation, inbreeding depression and heterosis and their central relevance for crop breeding. PLANT BIOTECHNOLOGY JOURNAL 2021; 19:26-34. [PMID: 32996672 PMCID: PMC7769232 DOI: 10.1111/pbi.13481] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Revised: 09/07/2020] [Accepted: 09/12/2020] [Indexed: 05/12/2023]
Abstract
Transgressive segregation and heterosis are the reasons that plant breeding works. Molecular explanations for both phenomena have been suggested and play a contributing role. However, it is often overlooked by molecular genetic researchers that transgressive segregation and heterosis are most simply explained by dispersion of favorable alleles. Therefore, advances in molecular biology will deliver the most impact on plant breeding when integrated with sources of heritable trait variation - and this will be best achieved within a quantitative genetics framework. An example of the power of quantitative approaches is the implementation of genomic selection, which has recently revolutionized animal breeding. Genomic selection is now being applied to both hybrid and inbred crops and is likely to be the major source of improvement in plant breeding practice over the next decade. Breeders' ability to efficiently apply genomic selection methodologies is due to recent technology advances in genotyping and sequencing. Furthermore, targeted integration of additional molecular data (such as gene expression, gene copy number and methylation status) into genomic prediction models may increase their performance. In this review, we discuss and contextualize a suite of established quantitative genetics themes relating to hybrid vigour, transgressive segregation and their central relevance to plant breeding, with the aim of informing crop researchers outside of the quantitative genetics discipline of their relevance and importance to crop improvement. Better understanding between molecular and quantitative disciplines will increase the potential for further improvements in plant breeding methodologies and so help underpin future food security.
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Affiliation(s)
- Ian J. Mackay
- SRUC (Scotland’s Rural College)EdinburghUK
- IMplant ConsultancyChelmsfordUK
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