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Genome-wide association studies (GWAS) have been widely used in the genetic dissection of complex traits. However, there are still limits in current GWAS statistics. For example, (1) almost all the existing methods do not estimate additive and dominance effects in quantitative trait nucleotide (QTN) detection; (2) the methods for detecting QTN-by-environment interaction (QEI) are not straightforward and do not estimate additive and dominance effects as well as additive-by-environment and dominance-by-environment interaction effects, leading to unreliable results; and (3) no or too simple polygenic background controls have been employed in QTN-by-QTN interaction (QQI) detection. As a result, few studies of QEI and QQI for complex traits have been reported based on multiple-environment experiments. Recently, new statistical tools, including 3VmrMLM, have been developed to address these needs in GWAS. In 3VmrMLM, all the trait-associated effects, including QTN, QEI and QQI related effects, are compressed into a single effect-related vector, while all the polygenic backgrounds are compressed into a single polygenic effect matrix. These compressed parameters can be accurately and efficiently estimated through a unified mixed model analysis. To further validate these new GWAS methods, particularly 3VmrMLM, they should be rigorously tested in real data of various plants and a wide range of other species.
This book illustrates the importance and significance of bioinformatics in the field of agriculture. It first introduces the basic concepts of bioinformatics, such as homologous sequence and gene function analyses, determination of protein structures, and discusses machine learning applications for an in-depth understanding of the desired genes and proteins based on commonly used bioinformatics software and tools, e.g. BLAST, molecular modelling, molecular-docking and simulations, protein-protein and domain-domain interactions. The book also describes recent advances in the high-throughput analysis of whole genome and transcriptome using next-generation sequencing platforms, and functional proteome studies. It also examines the role of computational biology in understanding and improving the nutrient quality and yield of crops. Lastly, the book explores a comprehensive list of applications of bioinformatics to improve plant yield, biomass, and health, and the challenges involved.
Technologies collectively called omics enable simultaneous measurement of an enormous number of biomolecules; for example, genomics investigates thousands of DNA sequences, and proteomics examines large numbers of proteins. Scientists are using these technologies to develop innovative tests to detect disease and to predict a patient's likelihood of responding to specific drugs. Following a recent case involving premature use of omics-based tests in cancer clinical trials at Duke University, the NCI requested that the IOM establish a committee to recommend ways to strengthen omics-based test development and evaluation. This report identifies best practices to enhance development, evaluation, and translation of omics-based tests while simultaneously reinforcing steps to ensure that these tests are appropriately assessed for scientific validity before they are used to guide patient treatment in clinical trials.
This Research Topic addresses research in genomics and biotechnology to improve the growth and quality of forest trees for wood, pulp, biorefineries and carbon capture. Forests are the world’s greatest repository of terrestrial biomass and biodiversity. Forests serve critical ecological services, supporting the preservation of fauna and flora, and water resources. Planted forests also offer a renewable source of timber, for pulp and paper production, and the biorefinery. Despite their fundamental role for society, thousands of hectares of forests are lost annually due to deforestation, pests, pathogens and urban development. As a consequence, there is an increasing need to develop trees that are more productive under lower inputs, while understanding how they adapt to the environment and respond to biotic and abiotic stress. Forest genomics and biotechnology, disciplines that study the genetic composition of trees and the methods required to modify them, began over a quarter of a century ago with the development of the first genetic maps and establishment of early methods of genetic transformation. Since then, genomics and biotechnology have impacted all research areas of forestry. Genome analyses of tree populations have uncovered genes involved in adaptation and response to biotic and abiotic stress. Genes that regulate growth and development have been identified, and in many cases their mechanisms of action have been described. Genetic transformation is now widely used to understand the roles of genes and to develop germplasm that is more suitable for commercial tree plantations. However, in contrast to many annual crops that have benefited from centuries of domestication and extensive genomic and biotechnology research, in forestry the field is still in its infancy. Thus, tremendous opportunities remain unexplored. This Research Topic aims to briefly summarize recent findings, to discuss long-term goals and to think ahead about future developments and how this can be applied to improve growth and quality of forest trees.
Computational and high-throughput methods, such as genomics, proteomics, and transcriptomics, known collectively as “-omics,” have been used to study plant biology for well over a decade now. As these technologies mature, plant and crop scientists have started using these methods to improve crop varieties. Omics in Plant Breeding provides a timely introduction to key omicsbased methods and their application in plant breeding. Omics in Plant Breeding is a practical and accessible overview of specific omics-based methods ranging from metabolomics to phenomics. Covering a single methodology within each chapter, this book provides thorough coverage that ensures a strong understanding of each methodology both in its application to, and improvement of, plant breeding. Accessible to advanced students, researchers, and professionals, Omics in Plant Breeding will be an essential entry point into this innovative and exciting field. • A valuable overview of high-throughput, genomics-based technologies and their applications to plant breeding • Each chapter explores a single methodology, allowing for detailed and thorough coverage • Coverage ranges from well-established methodologies, such as genomics and proteomics, to emerging technologies, including phenomics and physionomics Aluízio Borém is a Professor of Plant Breeding at the University of Viçosa in Brazil. Roberto Fritsche-Neto is a Professor of Genetics and Plant Breeding at the University of São Paulo in Brazil.
Plants have been exposed to multiple environmental stressors on long-term (seasonal) and short-term (daily) basis since their appearance on land. However, the frequency and the intensity of stress events have increased much during the last three decades because of climate change. Plants have developed, however, a multiplicity of modular and highly integrated strategies to cope with challenges imposed by novel, usually harsher environments. These strategies include migration, acclimation and adaptation. Twelve articles in this research topic exactly focus on the relative significance of these response mechanisms for the successful acclimation of plants to a wide range of novel environmental pressures. Four articles , additionally, explore how plants respond to severe stress conditions resulting from the concurrent action of multiple stressors. Ten articles mostly examine how morpho-anatomical, physiological and biochemical-related traits integrate when plants suffer from ‘novel’ threats, such as solid, gaseous, and electromagnetic pollutants. Suitable physiological indicators for developing conservation strategies are described in the last two works. This research topic highlights that bottom-up, as well as, top-down approaches will be necessary to develop in near future in the study of plants´ responses to environmental pressures.