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Rasheed A, Hao Y, Xia X, Khan A, Xu Y, Varshney RK, He Z. Crop Breeding Chips and Genotyping Platforms: Progress, Challenges, and Perspectives. MOLECULAR PLANT 2017; 10:1047-1064. [PMID: 28669791 DOI: 10.1016/j.molp.2017.06.008] [Citation(s) in RCA: 219] [Impact Index Per Article: 31.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/25/2017] [Revised: 05/29/2017] [Accepted: 06/19/2017] [Indexed: 05/18/2023]
Abstract
There is a rapidly rising trend in the development and application of molecular marker assays for gene mapping and discovery in field crops and trees. Thus far, more than 50 SNP arrays and 15 different types of genotyping-by-sequencing (GBS) platforms have been developed in over 25 crop species and perennial trees. However, much less effort has been made on developing ultra-high-throughput and cost-effective genotyping platforms for applied breeding programs. In this review, we discuss the scientific bottlenecks in existing SNP arrays and GBS technologies and the strategies to develop targeted platforms for crop molecular breeding. We propose that future practical breeding platforms should adopt automated genotyping technologies, either array or sequencing based, target functional polymorphisms underpinning economic traits, and provide desirable prediction accuracy for quantitative traits, with universal applications under wide genetic backgrounds in crops. The development of such platforms faces serious challenges at both the technological level due to cost ineffectiveness, and the knowledge level due to large genotype-phenotype gaps in crop plants. It is expected that such genotyping platforms will be achieved in the next ten years in major crops in consideration of (a) rapid development in gene discovery of important traits, (b) deepened understanding of quantitative traits through new analytical models and population designs, (c) integration of multi-layer -omics data leading to identification of genes and pathways responsible for important breeding traits, and (d) improvement in cost effectiveness of large-scale genotyping. Crop breeding chips and genotyping platforms will provide unprecedented opportunities to accelerate the development of cultivars with desired yield potential, quality, and enhanced adaptation to mitigate the effects of climate change.
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Affiliation(s)
- Awais Rasheed
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100081, China; International Maize and Wheat Improvement Center (CIMMYT), c/o CAAS, Beijing 100081, China
| | - Yuanfeng Hao
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100081, China
| | - Xianchun Xia
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100081, China
| | - Awais Khan
- Department of Plant Pathology and Plant-Microbe Biology, Cornell University, Geneva, NY, USA
| | - Yunbi Xu
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100081, China; International Maize and Wheat Improvement Center (CIMMYT), c/o CAAS, Beijing 100081, China
| | - Rajeev K Varshney
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru 502324, India
| | - Zhonghu He
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100081, China; International Maize and Wheat Improvement Center (CIMMYT), c/o CAAS, Beijing 100081, China.
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102
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Shakoor N, Lee S, Mockler TC. High throughput phenotyping to accelerate crop breeding and monitoring of diseases in the field. CURRENT OPINION IN PLANT BIOLOGY 2017; 38:184-192. [PMID: 28738313 DOI: 10.1016/j.pbi.2017.05.006] [Citation(s) in RCA: 130] [Impact Index Per Article: 18.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/06/2017] [Accepted: 05/17/2017] [Indexed: 05/18/2023]
Abstract
Effective implementation of technology that facilitates accurate and high-throughput screening of thousands of field-grown lines is critical for accelerating crop improvement and breeding strategies for higher yield and disease tolerance. Progress in the development of field-based high throughput phenotyping methods has advanced considerably in the last 10 years through technological progress in sensor development and high-performance computing. Here, we review recent advances in high throughput field phenotyping technologies designed to inform the genetics of quantitative traits, including crop yield and disease tolerance. Successful application of phenotyping platforms to advance crop breeding and identify and monitor disease requires: (1) high resolution of imaging and environmental sensors; (2) quality data products that facilitate computer vision, machine learning and GIS; (3) capacity infrastructure for data management and analysis; and (4) automated environmental data collection. Accelerated breeding for agriculturally relevant crop traits is key to the development of improved varieties and is critically dependent on high-resolution, high-throughput field-scale phenotyping technologies that can efficiently discriminate better performing lines within a larger population and across multiple environments.
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Affiliation(s)
| | - Scott Lee
- Donald Danforth Plant Science Center, United States
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103
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Xu Y, Li P, Zou C, Lu Y, Xie C, Zhang X, Prasanna BM, Olsen MS. Enhancing genetic gain in the era of molecular breeding. JOURNAL OF EXPERIMENTAL BOTANY 2017; 68:2641-2666. [PMID: 28830098 DOI: 10.1093/jxb/erx135] [Citation(s) in RCA: 92] [Impact Index Per Article: 13.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2016] [Accepted: 04/03/2017] [Indexed: 05/20/2023]
Abstract
As one of the important concepts in conventional quantitative genetics and breeding, genetic gain can be defined as the amount of increase in performance that is achieved annually through artificial selection. To develop pro ducts that meet the increasing demand of mankind, especially for food and feed, in addition to various industrial uses, breeders are challenged to enhance the potential of genetic gain continuously, at ever higher rates, while they close the gaps that remain between the yield potential in breeders' demonstration trials and the actual yield in farmers' fields. Factors affecting genetic gain include genetic variation available in breeding materials, heritability for traits of interest, selection intensity, and the time required to complete a breeding cycle. Genetic gain can be improved through enhancing the potential and closing the gaps, which has been evolving and complemented with modern breeding techniques and platforms, mainly driven by molecular and genomic tools, combined with improved agronomic practice. Several key strategies are reviewed in this article. Favorable genetic variation can be unlocked and created through molecular and genomic approaches including mutation, gene mapping and discovery, and transgene and genome editing. Estimation of heritability can be improved by refining field experiments through well-controlled and precisely assayed environmental factors or envirotyping, particularly for understanding and controlling spatial heterogeneity at the field level. Selection intensity can be significantly heightened through improvements in the scale and precision of genotyping and phenotyping. The breeding cycle time can be shortened by accelerating breeding procedures through integrated breeding approaches such as marker-assisted selection and doubled haploid development. All the strategies can be integrated with other widely used conventional approaches in breeding programs to enhance genetic gain. More transdisciplinary approaches, team breeding, will be required to address the challenge of maintaining a plentiful and safe food supply for future generations. New opportunities for enhancing genetic gain, a high efficiency breeding pipeline, and broad-sense genetic gain are also discussed prospectively.
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Affiliation(s)
- Yunbi Xu
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China
- International Maize and Wheat Improvement Center (CIMMYT), El Batan, Texcoco, CP 56130, México
| | - Ping Li
- Nantong Xinhe Bio-Technology, Nantong 226019, PR China
| | - Cheng Zou
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Yanli Lu
- Maize Research Institute, Sichuan Agricultural University, Wenjiang 611130, Sichuan, China
| | - Chuanxiao Xie
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Xuecai Zhang
- International Maize and Wheat Improvement Center (CIMMYT), El Batan, Texcoco, CP 56130, México
| | - Boddupalli M Prasanna
- CIMMYT (International Maize and Wheat Improvement Center), ICRAF campus, United Nations Avenue, Nairobi, Kenya
| | - Michael S Olsen
- CIMMYT (International Maize and Wheat Improvement Center), ICRAF campus, United Nations Avenue, Nairobi, Kenya
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104
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Ma J, Li R, Wang H, Li D, Wang X, Zhang Y, Zhen W, Duan H, Yan G, Li Y. Transcriptomics Analyses Reveal Wheat Responses to Drought Stress during Reproductive Stages under Field Conditions. FRONTIERS IN PLANT SCIENCE 2017; 8:592. [PMID: 28484474 PMCID: PMC5399029 DOI: 10.3389/fpls.2017.00592] [Citation(s) in RCA: 60] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/30/2016] [Accepted: 03/31/2017] [Indexed: 05/04/2023]
Abstract
Drought is a major abiotic stress that limits wheat production worldwide. To ensure food security for the rapidly increasing world population, improving wheat yield under drought stress is urgent and relevant. In this study, an RNA-seq analysis was conducted to study the effect of drought on wheat transcriptome changes during reproductive stages under field conditions. Our results indicated that drought stress during early reproductive periods had a more severe impact on wheat development, gene expression and yield than drought stress during flowering. In total, 115,656 wheat genes were detected, including 309 differentially expressed genes (DEGs) which responded to drought at various developmental stages. These DEGs were involved in many critical processes including floral development, photosynthetic activity and stomatal movement. At early developmental stages, the proteins of drought-responsive DEGs were mainly located in the nucleus, peroxisome, mitochondria, plasma membrane and chloroplast, indicating that these organelles play critical roles in drought tolerance in wheat. Furthermore, the validation of five DEGs confirmed their responsiveness to drought under different genetic backgrounds. Functional verification of DEGs of interest will occur in our subsequent research. Collectively, the results of this study not only advanced our understanding of wheat transcriptome changes under drought stress during early reproductive stages but also provided useful targets to manipulate drought tolerance in wheat at different development stages.
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Affiliation(s)
- Jun Ma
- Faculty of Science, School of Plant Biology, The UWA Institute of Agriculture, The University of Western AustraliaPerth, WA, Australia
| | - Ruiqi Li
- North China Key Laboratory for Crop Germplasm Resources of Education Ministry, College of Agronomy, Hebei Agricultural UniversityBaoding, China
| | - Hongguang Wang
- North China Key Laboratory for Crop Germplasm Resources of Education Ministry, College of Agronomy, Hebei Agricultural UniversityBaoding, China
| | - Dongxiao Li
- North China Key Laboratory for Crop Germplasm Resources of Education Ministry, College of Agronomy, Hebei Agricultural UniversityBaoding, China
| | - Xingyi Wang
- Faculty of Science, School of Plant Biology, The UWA Institute of Agriculture, The University of Western AustraliaPerth, WA, Australia
| | - Yuechen Zhang
- North China Key Laboratory for Crop Germplasm Resources of Education Ministry, College of Agronomy, Hebei Agricultural UniversityBaoding, China
| | - Wenchao Zhen
- North China Key Laboratory for Crop Germplasm Resources of Education Ministry, College of Agronomy, Hebei Agricultural UniversityBaoding, China
| | - Huijun Duan
- North China Key Laboratory for Crop Germplasm Resources of Education Ministry, College of Agronomy, Hebei Agricultural UniversityBaoding, China
| | - Guijun Yan
- Faculty of Science, School of Plant Biology, The UWA Institute of Agriculture, The University of Western AustraliaPerth, WA, Australia
| | - Yanming Li
- North China Key Laboratory for Crop Germplasm Resources of Education Ministry, College of Agronomy, Hebei Agricultural UniversityBaoding, China
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105
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Naylor D, Coleman-Derr D. Drought Stress and Root-Associated Bacterial Communities. FRONTIERS IN PLANT SCIENCE 2017; 8:2223. [PMID: 29375600 PMCID: PMC5767233 DOI: 10.3389/fpls.2017.02223] [Citation(s) in RCA: 222] [Impact Index Per Article: 31.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/17/2017] [Accepted: 12/18/2017] [Indexed: 05/20/2023]
Abstract
Root-associated bacterial communities play a vital role in maintaining health of the plant host. These communities exist in complex relationships, where composition and abundance of community members is dependent on a number of factors such as local soil chemistry, plant genotype and phenotype, and perturbations in the surrounding abiotic environment. One common perturbation, drought, has been shown to have drastic effects on bacterial communities, yet little is understood about the underlying causes behind observed shifts in microbial abundance. As drought may affect root bacterial communities both directly by modulating moisture availability, as well as indirectly by altering soil chemistry and plant phenotypes, we provide a synthesis of observed trends in recent studies and discuss possible directions for future research that we hope will provide for more knowledgeable predictions about community responses to future drought events.
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Affiliation(s)
- Dan Naylor
- Department of Plant and Microbial Biology, University of California, Berkeley, Berkeley, CA, United States
- Plant Gene Expression Center, United States Department of Agriculture-Agricultural Research Service, Albany, CA, United States
| | - Devin Coleman-Derr
- Department of Plant and Microbial Biology, University of California, Berkeley, Berkeley, CA, United States
- Plant Gene Expression Center, United States Department of Agriculture-Agricultural Research Service, Albany, CA, United States
- *Correspondence: Devin Coleman-Derr,
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106
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Lyu JIL, Baek SH, Jung S, Chu H, Nam HG, Kim J, Lim PO. High-Throughput and Computational Study of Leaf Senescence through a Phenomic Approach. FRONTIERS IN PLANT SCIENCE 2017; 8:250. [PMID: 28280501 PMCID: PMC5322180 DOI: 10.3389/fpls.2017.00250] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2016] [Accepted: 02/09/2017] [Indexed: 05/19/2023]
Abstract
Leaf senescence is influenced by its life history, comprising a series of developmental and physiological experiences. Exploration of the biological principles underlying leaf lifespan and senescence requires a schema to trace leaf phenotypes, based on the interaction of genetic and environmental factors. We developed a new approach and concept that will facilitate systemic biological understanding of leaf lifespan and senescence, utilizing the phenome high-throughput investigator (PHI) with a single-leaf-basis phenotyping platform. Our pilot tests showed empirical evidence for the feasibility of PHI for quantitative measurement of leaf senescence responses and improved performance in order to dissect the progression of senescence triggered by different senescence-inducing factors as well as genetic mutations. Such an establishment enables new perspectives to be proposed, which will be challenged for enhancing our fundamental understanding on the complex process of leaf senescence. We further envision that integration of phenomic data with other multi-omics data obtained from transcriptomic, proteomic, and metabolic studies will enable us to address the underlying principles of senescence, passing through different layers of information from molecule to organism.
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Affiliation(s)
- Jae IL Lyu
- Center for Plant Aging Research, Institute for Basic ScienceDaegu, South Korea
| | - Seung Hee Baek
- Department of New Biology, Daegu Gyeongbuk Institute of Science and TechnologyDaegu, South Korea
| | - Sukjoon Jung
- Department of New Biology, Daegu Gyeongbuk Institute of Science and TechnologyDaegu, South Korea
| | - Hyosub Chu
- Center for Plant Aging Research, Institute for Basic ScienceDaegu, South Korea
| | - Hong Gil Nam
- Center for Plant Aging Research, Institute for Basic ScienceDaegu, South Korea
- Department of New Biology, Daegu Gyeongbuk Institute of Science and TechnologyDaegu, South Korea
| | - Jeongsik Kim
- Center for Plant Aging Research, Institute for Basic ScienceDaegu, South Korea
- *Correspondence: Jeongsik Kim, Pyung Ok Lim,
| | - Pyung Ok Lim
- Department of New Biology, Daegu Gyeongbuk Institute of Science and TechnologyDaegu, South Korea
- *Correspondence: Jeongsik Kim, Pyung Ok Lim,
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107
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Bernardo R. Bandwagons I, too, have known. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2016; 129:2323-2332. [PMID: 27681088 DOI: 10.1007/s00122-016-2772-5] [Citation(s) in RCA: 100] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2016] [Accepted: 08/12/2016] [Indexed: 05/19/2023]
Abstract
Bandwagons come in waves. A plant breeder, just like a surfer, needs to carefully choose which waves to be on. A bandwagon is an idea, activity, or cause that becomes increasingly fashionable as more and more people adopt it. In a 1991 article entitled Bandwagons I Have Known, Professor N. W. Simmonds described several bandwagons that he encountered in his career, beginning with induced polyploidy and mutation breeding and ending with the then-new field of biotechnology. This article reviews and speculates about post-1990 bandwagons in plant improvement, including transgenic cultivars, quantitative trait locus (QTL) mapping, association mapping, genomewide (or genomic) selection, phenomics, envirotyping, and genome editing. The life cycle of a bandwagon includes an excitement phase of hype and funding; a realization phase when the initial hype is either tempered or the initial expectations are found to have been too low; and a reality phase when the useful aspects of a bandwagon become part of mainstream thinking and practice, or when an unsuccessful bandwagon is largely abandoned. During the realization phase, a new bandwagon that draws our attention and gives us renewed optimism typically arises. The most popular bandwagons, such as QTL mapping, are those for which the needed experimental resources are accessible, the required technical knowledge and skills can be easily learned, and the outputs can almost always be reported. The favorite bandwagon of any plant breeder has, in one way or another, resulted from Mendel's seminal discoveries 150 years ago. Our community of plant breeders needs to be continually diligent in welcoming new bandwagons, but also in hopping off from those that do not prove useful.
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Affiliation(s)
- Rex Bernardo
- Department of Agronomy and Plant Genetics, University of Minnesota, 411 Borlaug Hall, 1991 Upper Buford Circle, Saint Paul, MN, 55108, USA.
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108
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Zou C, Wang P, Xu Y. Bulked sample analysis in genetics, genomics and crop improvement. PLANT BIOTECHNOLOGY JOURNAL 2016; 14:1941-55. [PMID: 26990124 PMCID: PMC5043468 DOI: 10.1111/pbi.12559] [Citation(s) in RCA: 158] [Impact Index Per Article: 19.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/04/2016] [Revised: 03/09/2016] [Accepted: 03/12/2016] [Indexed: 05/18/2023]
Abstract
Biological assay has been based on analysis of all individuals collected from sample populations. Bulked sample analysis (BSA), which works with selected and pooled individuals, has been extensively used in gene mapping through bulked segregant analysis with biparental populations, mapping by sequencing with major gene mutants and pooled genomewide association study using extreme variants. Compared to conventional entire population analysis, BSA significantly reduces the scale and cost by simplifying the procedure. The bulks can be built by selection of extremes or representative samples from any populations and all types of segregants and variants that represent wide ranges of phenotypic variation for the target trait. Methods and procedures for sampling, bulking and multiplexing are described. The samples can be analysed using individual markers, microarrays and high-throughput sequencing at all levels of DNA, RNA and protein. The power of BSA is affected by population size, selection of extreme individuals, sequencing strategies, genetic architecture of the trait and marker density. BSA will facilitate plant breeding through development of diagnostic and constitutive markers, agronomic genomics, marker-assisted selection and selective phenotyping. Applications of BSA in genetics, genomics and crop improvement are discussed with their future perspectives.
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Affiliation(s)
- Cheng Zou
- Institute of Crop Science, National Key Facility of Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Pingxi Wang
- Institute of Crop Science, National Key Facility of Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yunbi Xu
- Institute of Crop Science, National Key Facility of Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences, Beijing, China.
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico.
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