This book addresses complex problems associated with crop improvement programs, using a wide range of programming solutions, for genomics data handling and sustainable agriculture. It describes important concepts in genomics data analysis and sequence-based mapping approaches along with references. The book contains 16 chapters on recent developments in several methods of genomic data analysis for crop improvements and sustainable agriculture, all authored by eminent researchers who are experts in their fields. These chapters focus on applications of a wide range of key bioinformatics topics, including assembly, annotation, and visualization of next-generation sequencing (NGS) data; expression profiles of coding and noncoding RNA; statistical and quantitative genetics; trait-based association analysis, quantitative trait loci (QTL) mapping, and artificial intelligence in genomic studies. Real examples and case studies in the book will come in handy when applying the techniques. The relative scarcity of reference materials covering bioinformatics applications as compared with the readily available books also enhances the utility of this book. The targeted readers of the book are scientists, researchers, and bioinformaticians from genomics and advanced breeding in different areas. The book will appeal to the applied researchers engaged in crop improvements and sustainable agriculture by using bioinformatics tools, students, research project leaders, and practitioners from the various marginal disciplines and interdisciplinary research.

This book fills the gap between textbooks of quantitative genetic theory, and software manuals that provide details on analytical methods but little context or perspective on which methods may be most appropriate for a particular application. Accordingly this book is composed of two sections. The first section (Chapters 1 to 8) covers topics of classical phenotypic data analysis for prediction of breeding values in animal and plant breeding programs. In the second section (Chapters 9 to 13) we provide the concept and overall review of available tools for using DNA markers for predictions of genetic merits in breeding populations. With advances in DNA sequencing technologies, genomic data, especially single nucleotide polymorphism (SNP) markers, have become available for animal and plant breeding programs in recent years. Analysis of DNA markers for prediction of genetic merit is a relatively new and active research area. The algorithms and software to implement these algorithms are changing rapidly. This section represents state-of-the-art knowledge on the tools and technologies available for genetic analysis of plants and animals. However, readers should be aware that the methods or statistical packages covered here may not be available or they might be out of date in a few years. Ultimately the book is intended for professional breeders interested in utilizing these tools and approaches in their breeding programs. Lastly, we anticipate the usage of this volume for advanced level graduate courses in agricultural and breeding courses.

This book addresses complex problems associated with crop improvement programs, using a wide range of programming solutions, for genomics data handling and sustainable agriculture. It describes important concepts in genomics data analysis and sequence-based mapping approaches along with references. The book contains 16 chapters on recent developments in several methods of genomic data analysis for crop improvements and sustainable agriculture, all authored by eminent researchers who are experts in their fields. These chapters focus on applications of a wide range of key bioinformatics topics, including assembly, annotation, and visualization of next-generation sequencing (NGS) data; expression profiles of coding and noncoding RNA; statistical and quantitative genetics; trait-based association analysis, quantitative trait loci (QTL) mapping, and artificial intelligence in genomic studies. Real examples and case studies in the book will come in handy when applying the techniques. The relative scarcity of reference materials covering bioinformatics applications as compared with the readily available books also enhances the utility of this book. The targeted readers of the book are scientists, researchers, and bioinformaticians from genomics and advanced breeding in different areas. The book will appeal to the applied researchers engaged in crop improvements and sustainable agriculture by using bioinformatics tools, students, research project leaders, and practitioners from the various marginal disciplines and interdisciplinary research.

This book aims to help plant breeders by reviewing past achievements, currently successful practices, and emerging methods and techniques. Theoretical considerations are also presented to strike the right balance between being as simple as possible but as complex as necessary. The United Nations predicts that the global human population will continue rising to 9.0 billion by 2050. World food production will need to increase between 70-100 per cent in just 40 years. First generation bio-fuels are also using crops and cropland to produce energy rather than food. In addition, land area used for agriculture may remain static or even decrease as a result of degradation and climate change, despite more land being theoretically available, unless crops can be bred which tolerate associated abiotic stresses. Lastly, it is unlikely that steps can be taken to mitigate all of the climate change predicted to occur by 2050, and beyond, and hence adaptation of farming systems and crop production will be required to reduce predicted negative effects on yields that will occur without crop adaptation. Substantial progress will therefore be required in bridging the yield gap between what is currently achieved per unit of land and what should be possible in future, with the best farming methods and best storage and transportation of food, given the availability of suitably adapted cultivars, including adaptation to climate change. My book is divided into four parts: Part I is an historical introduction; Part II deals with the origin of genetic variation by mutation and recombination of DNA; Part III explains how the mating system of a crop species determines the genetic structure of its landraces; Part IV considers the three complementary options for future progress: use of sexual reproduction in further conventional breeding, base broadening and introgression; mutation breeding; and genetically modified crops.

This superb volume provides a critical assessment of genomics tools and approaches for crop breeding. Volume 1 presents the status and availability of genomic resources and platforms, and also devises strategies and approaches for effectively exploiting genomics research. Volume 2 goes into detail on a number of case studies of several important crop and plant species that summarize both the achievements and limitations of genomics research for crop improvement.

OGENOTYPING BY SEQUENCING FOR CROP IMPROVEMENT A thoroughly up-to-date exploration of genotyping-by-sequencing technologies and related methods in plant science In Genotyping by Sequencing for Crop Improvement, a team of distinguished researchers delivers an in-depth and current exploration of the latest advances in genotyping-by-sequencing (GBS) methods, the statistical approaches used to analyze GBS data, and its applications, including quantitative trait loci (QTL) mapping, genome-wide association studies (GWAS), and genomic selection (GS) in crop improvement. This edited volume includes insightful contributions on a variety of relevant topics, like advanced molecular markers, high-throughput genotyping platforms, whole genome resequencing, QTL mapping with advanced mapping populations, analytical pipelines for GBS analysis, and more. The distinguished contributors explore traditional and advanced markers used in plant genotyping in extensive detail, and advanced genotyping platforms that cater to unique research purposes are discussed, as is the whole-genome resequencing (WGR) methodology. The included chapters also examine the applications of these technologies in several different crop categories, including cereals, pulses, oilseeds, and commercial crops. Genotyping by Sequencing for Crop Improvement also offers: A thorough introduction to molecular marker techniques and recent advancements in the technology Comprehensive explorations of the genotyping of seeds while preserving their viability, as well as advances in genomic selection Practical discussions of opportunities and challenges relating to high throughput genotyping in polyploid crops In-depth examinations of recent advances and applications of GBS, GWAS, and GS in cereals, pulses, oilseeds, millets, and commercial crops Perfect for practicing plant scientists with an interest in genotyping-by-sequencing technology, Genotyping by Sequencing for Crop Improvement will also earn a place in the libraries of researchers and students seeking a one-stop reference on the foundational aspects of – and recent advances in – genotyping-by-sequencing, genome-wide association studies, and genomic selection.

A timely update of a highly popular handbook on statistical genomics This new, two-volume edition of a classic text provides a thorough introduction to statistical genomics, a vital resource for advanced graduate students, early-career researchers and new entrants to the field. It introduces new and updated information on developments that have occurred since the 3rd edition. Widely regarded as the reference work in the field, it features new chapters focusing on statistical aspects of data generated by new sequencing technologies, including sequence-based functional assays. It expands on previous coverage of the many processes between genotype and phenotype, including gene expression and epigenetics, as well as metabolomics. It also examines population genetics and evolutionary models and inference, with new chapters on the multi-species coalescent, admixture and ancient DNA, as well as genetic association studies including causal analyses and variant interpretation. The Handbook of Statistical Genomics focuses on explaining the main ideas, analysis methods and algorithms, citing key recent and historic literature for further details and references. It also includes a glossary of terms, acronyms and abbreviations, and features extensive cross-referencing between chapters, tying the different areas together. With heavy use of up-to-date examples and references to web-based resources, this continues to be a must-have reference in a vital area of research. Provides much-needed, timely coverage of new developments in this expanding area of study Numerous, brand new chapters, for example covering bacterial genomics, microbiome and metagenomics Detailed coverage of application areas, with chapters on plant breeding, conservation and forensic genetics Extensive coverage of human genetic epidemiology, including ethical aspects Edited by one of the leading experts in the field along with rising stars as his co-editors Chapter authors are world-renowned experts in the field, and newly emerging leaders. The Handbook of Statistical Genomics is an excellent introductory text for advanced graduate students and early-career researchers involved in statistical genetics.

Genomic selection (GS) is a promising tool in the field of breeding especially in the era where genomic data is becoming cheaper. The potential of this tool has not been realized due to its limited adaptation in various crops. Marker Assisted Selection (MAS) has been the method of choice for plant breeders while using the genomic information in the breeding pipeline. MAS, however, fails to capture vital minor gene effects while focusing only on the major genes, which is not ideal for breeding advancement especially for quantitative traits such as yield. The main aim of statistical methodologies coming under the umbrella of GS on using the whole genome information is to predict potential candidates for breeding advancement while optimizing the use of resources such as land, manpower, and most importantly time. Lack of proper understanding of the methods and their applications is one of the reasons why breeders shy away from this tool. The book is meant for biologists, especially breeders, and provides a comprehensive idea of the statistical methodologies used in GS, guidance on the choice of models, and design of datasets. The book also encourages the readers to adopt GS by demonstrating the current scenarios of these models in some of the important crops among oilseeds, vegetables, legumes, tuber crops, and cereals. For ease of implementation of GS, the book also provides hands-on scripts on GS data design and modeling in a popular open-source statistical program. Additionally, prospective in GS model development and thereby enhancement in crop improvement programs is discussed.

This book emphasizes on cutting-edge next-generation smart plant breeding approaches for maximizing the use of genomic resources generated by high-throughput genomics in the post-genomic era. Through this book the readers would learn about the recent development in the genomic approaches such as genotype by sequencing (GBS) for genomic analysis (SNPs, Single Nucleotide Polymorphism), whole-genome re-sequencing (WGRS) and RNAseq for transcriptomic analysis (DEGs, Differentially Expressed Genes). To maximize the genetic gains in the cereal/food crops, the book covers topics on transgenic breeding, genome editing, high-throughput phenotyping, reliable/precision phenotyping and genomic information-based analysis. In the era of climate change and the ever-increasing population, food security and nutritional security are the primary concern of plant breeders, growers, and policymakers to address the UN’s sustainable development goals. Chapters of this book cohere around these goals and covers techniques such as (QTL mapping, association studies, candidate gene identification), omics, RNAi [through micro RNA (miRNA), small interfering RNA (siRNA) and artificial micro RNA (amiRNA)]. It also covers other genomic techniques like antisense technology, genome editing (CRISPR/cas9, base editing) and epigenomics that assist the crop improvement programmes to fulfil the UNs sustainable development goals. It explores the influence of rapidly available sequencing data assisting in the next generation breeding programmes. This volume is a productive resource for the students, researchers, scientists, teachers, public and private sector stakeholders involved in the genetic enhancement of cereal crops.

This superb volume provides a critical assessment of genomics tools and approaches for crop breeding. Volume 1 presents the status and availability of genomic resources and platforms, and also devises strategies and approaches for effectively exploiting genomics research. Volume 2 goes into detail on a number of case studies of several important crop and plant species that summarize both the achievements and limitations of genomics research for crop improvement.