Bioinformatics in Agriculture

Next Generation Sequencing Era

1st Edition - April 26, 2022
Imprint: Academic Press
Editors: Pradeep Sharma, Dinesh Yadav, R.K. Gaur
Language: English
Paperback ISBN:
9 7 8 - 0 - 3 2 3 - 8 9 7 7 8 - 5
eBook ISBN:
9 7 8 - 0 - 3 2 3 - 8 8 5 9 9 - 7

Bioinformatics in Agriculture: Next Generation Sequencing Era is a comprehensive volume presenting an integrated research and development approach to the practical applicati… Read more

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Bioinformatics in Agriculture: Next Generation Sequencing Era is a comprehensive volume presenting an integrated research and development approach to the practical application of genomics to improve agricultural crops. Exploring both the theoretical and applied aspects of computational biology, and focusing on the innovation processes, the book highlights the increased productivity of a translational approach. Presented in four sections and including insights from experts from around the world, the book includes: Section I: Bioinformatics and Next Generation Sequencing Technologies; Section II: Omics Application; Section III: Data mining and Markers Discovery; Section IV: Artificial Intelligence and Agribots.

Bioinformatics in Agriculture: Next Generation Sequencing Era explores deep sequencing, NGS, genomic, transcriptome analysis and multiplexing, highlighting practices forreducing time, cost, and effort for the analysis of gene as they are pooled, and sequenced. Readers will gain real-world information on computational biology, genomics, applied data mining, machine learning, and artificial intelligence.

This book serves as a complete package for advanced undergraduate students, researchers, and scientists with an interest in bioinformatics.

Cover image
Title page
Table of Contents
Copyright
List of contributors
About the editors
Foreword
Preface
Section I: Bioinformatics and next-generation sequencing technologies (Chapters 1–14)
Section II: Omics application (Chapters 15–26)
Section III: Data mining and markers discovery (Chapters 27–33)
Section IV: Artificial intelligence and agribots (Chapters 34–37)
Section I: Bioinformatics and next generation sequencing technologies
Chapter 1. Advances in agricultural bioinformatics: an outlook of multi “omics” approaches
Abstract
1.1 Introduction
1.2 Different types of “omics” approaches
1.3 Conclusions and future prospective
References
Chapter 2. Promises and benefits of omics approaches to data-driven science industries
Abstract
2.1 Sequencing technologies
2.2 Advances in genome assembly technology
2.3 Transcriptomics—where genome connects to gene function
2.4 Beyond genomics and transcriptomics toward proteomics and metabolomics
2.5 Integrating omics datasets
2.6 Challenges
2.7 Machine learning in omics
2.8 Big data storage and management
2.9 Future directions
References
Chapter 3. Bioinformatics intervention in functional genomics: current status and future perspective—an overview
Abstract
3.1 Introduction
3.2 Functional genomic approaches
3.3 Serial analysis of gene expression
3.4 DNA microarray
3.5 Next-generation sequencing technologies
3.6 Databases and genome annotation
3.7 Conclusion
References
Chapter 4. Genome informatics: present status and future prospects in agriculture
Abstract
4.1 Introduction
4.2 The evolution of DNA-seq
4.3 Genomics in agriculture
4.4 Conclusion, applications, and future prospects of next-generation sequencing in agriculture
References
Chapter 5. Genomics and its role in crop improvement
Abstract
5.1 Introduction
5.2 Development of genomic resources
5.3 Application of genomic resources for crop improvement
5.4 Genome analysis
5.5 Applications of genomics
5.6 Next-generation genomics for crop improvement
5.7 Genomic features for future breeding
References
Chapter 6. Genome-wide predictions, structural and functional annotations of plant transcription factor gene families: a bioinformatics approach
Abstract
6.1 Transcription factor: an introduction
6.2 Plant transcription factors and its multifarious applications
6.3 Transcription factors for biotic and abiotic tolerance
6.4 Transcription factor databases
6.5 Bioinformatics tools used for structural and functional analysis of transcription factor gene families
6.6 Conclusion
References
Chapter 7. Proteomics as a tool to understand the biology of agricultural crops
Abstract
7.1 Introduction
7.2 Gel-based proteomics
7.3 Gel-free proteomics
7.4 High-throughput posttranslational modification proteomics
7.5 Conclusion
References
Further reading
Chapter 8. Metabolomics and sustainable agriculture: concepts, applications, and perspectives
Abstract
8.1 Introduction
8.2 Sustainable agriculture and agro-production systems
8.3 Concepts of metabolomics and their applications to agriculture
8.4 Bridging metabolomics to sustainable agriculture
8.5 Conclusions and future perspectives
References
Chapter 9. Plant metabolomics: a new era in the advancement of agricultural research
Abstract
9.1 An introduction to metabolomics
9.2 Significance of metabolomics in plant biotechnology
9.3 Technologies involved in metabolomics improvement
9.4 Metabolomics databases
9.5 Metabolite profiling, identification, and quantification
9.6 Metabolic engineering in plants
9.7 Environmental and ecological metabolomics
9.8 Extraction methods in metabolomics
9.9 Metabolomics-assisted breeding techniques
9.10 Metabolites present in plant metabolome
9.11 Workflow of metabolomics analysis
9.12 Current and emerging methodologies of metabolomics in agriculture
9.13 Integration of metabolomics tools with other omics tools
9.14 Metabolomics under normal and stress conditions in plants
9.15 Applications and future perspective of metabolomics in plant biotechnology and agriculture
References
Chapter 10. Explore the RNA-sequencing and the next-generation sequencing in crops responding to abiotic stress
Abstract
10.1 Introduction
10.2 From the beginning to the crop sciences: transcriptome analysis, its evolution, and state of the art
10.3 The overview on plant sequencing of RNA studies
10.4 The RNA-sequencing analysis workflow
10.5 Functional genomics
10.6 Final considerations
Acknowledgments
References
Chapter 11. Identification of novel RNAs in plants with the help of next-generation sequencing technologies
Abstract
11.1 Introduction
11.2 Small RNA
11.3 Long noncoding RNA
11.4 Circular RNA
11.5 Chimeric RNA
References
Chapter 12. Molecular evolution, three-dimensional structural characteristics, mechanism of action, and functions of plant beta-galactosidases
Abstract
12.1 Introduction
12.2 Protein sequence features of plant beta-galactosidases
12.3 Molecular evolution of beta-galactosidases and their classification
12.4 Three-dimensional structural characteristics of plant beta-galactosidases
12.5 Structural comparison between MiBGAL and TBG4
12.6 Substrate specificity of plant beta-galactosidases
12.7 Mechanism of action of plant beta-galactosidases
12.8 Physiological function of plant beta-galactosidase
12.9 Conclusion
Conflict of interest
References
Chapter 13. Next generation genomics: toward decoding domestication history of crops
Abstract
13.1 Introduction
13.2 Whole genome sequencing
13.3 Alternative genome scale approaches
13.4 Emergence of pan-genomics
13.5 Methodologies in domestication genomics
13.6 Case studies on next-generation sequencing-assisted inference of domestication history
References
Chapter 14. In-silico identification of small RNAs: a tiny silent tool against agriculture pest
Abstract
14.1 Introduction
14.2 Small RNAs
14.3 Types of small noncoding RNAs
14.4 Next-generation sequencing in agronomic advancements
14.5 Small RNA world and their identification
14.6 Limitations
14.7 Conclusion
Acknowledgments
References
Section II: Omics application
Chapter 15. Bioinformatics-assisted multiomics approaches to improve the agronomic traits in cotton
Abstract
15.1 Introduction
15.2 Big data in biology and omics
15.3 Bioinformatics resources for cotton-omics
15.4 Integration of multiomics data to cope with cotton plant diseases
15.5 Challenges in the integration and analysis of multiomics data of cotton
15.6 Conclusion
Acknowledgments
References
Chapter 16. Omics-assisted understanding of BPH resistance in rice: current updates and future prospective
Abstract
16.1 Introduction
16.2 Rice genomics in brown planthopper resistance
16.3 Rice transcriptomics in brown planthopper resistance
16.4 Rice proteomics in brown planthopper resistance
16.5 Rice metabolomics in brown planthopper resistance
16.6 Bioinformatics in brown planthopper resistance in rice
16.7 Conclusion and future prospective
References
Chapter 17. Contemporary genomic approaches in modern agriculture for improving tomato varieties
Abstract
17.1 Importance and origin of tomatoes
17.2 Organization of tomato genome and genetic variation of tomato cultivars
17.3 Tomato breeding
17.4 Disease resistance
17.5 Insect resistance
17.6 Abiotic stress tolerance
17.7 Tomato genetic markers for selection
17.8 Genomic selection for abiotic stress in tomato
17.9 Tomato transcriptomics
17.10 Tomato proteomics
17.11 Tomato metabolomics
References
Chapter 18. Characterization of drought tolerance in maize: omics approaches
Abstract
18.1 Introduction
18.2 Drought timing
18.3 Plant response to drought
18.4 Progress with conventional breeding strategies for drought tolerance in maize
18.5 Omics for characterizing drought stress responses in maize
18.6 Conclusion
References
Chapter 19. Deciphering the genomic hotspots in wheat for key breeding traits using comparative and structural genomics
Abstract
19.1 Introduction
19.2 Genomic comparisons and gene discovery
19.3 Genomic hotspots in wheat
19.4 Genomic sequences to genomic hotspot
19.5 Conclusion
References
Chapter 20. Prospects of molecular markers for wheat improvement in postgenomic era
Abstract
20.1 Introduction
20.2 Overview of molecular marker systems in wheat
20.3 Genome-wide markers for gene mapping
20.4 Wheat genomics for development of marker and its utilization
20.5 Status of genotyping platform of bread wheat and its progenitors
20.6 Utility and achievement of high-throughput genotyping approaches in wheat
20.7 Conversion of trait-linked SNPs to user-friendly markers
20.8 Conclusions and future directions
References
Chapter 21. Omics approaches for biotic, abiotic, and quality traits improvement in potato (Solanum tuberosum L.)
Abstract
21.1 Introduction
21.2 Potato genomics
21.3 Potato transcriptomic
21.4 Potato proteomics
21.5 Potato metabolomics
21.6 Potato ionomics
21.7 Phenomics
21.8 Potato omics resources and integration of technologies
21.9 Conclusions
References
Chapter 22. Tea plant genome sequencing: prospect for crop improvement using genomics tools
Abstract
22.1 Introduction
22.2 Whole-genome sequencing of tea plant
22.3 Identification and characterization of gene families
22.4 Tea transcriptome sequencing
22.5 Discovery of single-nucleotide polymorphism
22.6 Conclusion
References
Chapter 23. Next-generation sequencing and viroid research
Abstract
23.1 Introduction
23.2 Next-generation sequencing technology
23.3 Impact of next-generation sequencing on viroid discovery
23.4 Role of next-generation sequencing in unraveling viroid RNA biology
23.5 Bioinformatic intervention in next-generation sequencing
23.6 Conclusion
References
Chapter 24. Computational analysis for plant virus analysis using next-generation sequencing
Abstract
24.1 Introduction
24.2 Development of next-generation sequencing technology
24.3 Next-generation sequencing data analysis by bioinformatics tools
24.4 Next-generation sequencing in plant virology
24.5 Challenges
24.6 Conclusion and future prospective
References
Chapter 25. Microbial degradation of herbicides in contaminated soils by following computational approaches
Abstract
25.1 Herbicides: use and impact on environment
25.2 Microbial degradation of herbicides
25.3 Strategies to improve biodegradation of herbicides
25.4 Integration of computational biology to improve biodegradation of herbicides
25.5 Bioremediation of atrazine by following metabolic modeling method
25.6 Conclusion
Acknowledgments
References
Chapter 26. Chloroplast genome and plant–virus interaction
Abstract
26.1 Introduction
26.2 Chloroplast genome
26.3 Viral infection symptoms in plants
26.4 Role of chloroplasts in plant–virus life cycle
26.5 Role of chloroplast in the defense against plant pathogenic viruses
26.6 Plant–virus metagenomics
26.7 Conclusion
References
Section III: Data mining, markers discovery
Chapter 27. Deciphering soil microbiota using metagenomic approach for sustainable agriculture: an overview
Abstract
27.1 Introduction
27.2 Sustainable agriculture
27.3 Soil microbiomes
27.4 Soil microbial diversity
27.5 Analysis of the rhizosphere microbial community
27.6 Metagenomics in agriculture
27.7 Metagenomics for sustainable agriculture
27.8 Concluding remarks
References
Chapter 28. Concepts and applications of bioinformatics for sustainable agriculture
Abstract
28.1 Introduction—a conceptual framework for sustainable agriculture
28.2 Database resources for agricultural bioinformatics
28.3 Genome mapping
28.4 DNA marker development and application to genotyping
28.5 Genome-wide association studies
28.6 Emerging strategies for breeding and genetics
28.7 Conclusion and future prospects
References
Chapter 29. Application of high-throughput structural and functional genomic technologies in crop nutrition research
Abstract
29.1 Introduction
29.2 Structural genomics
29.3 Application of structural genomics
29.4 Dynamic expression of functional genomics
29.5 Functional genomics approaches
29.6 Developing genomic technologies for enhancing food crops security
29.7 Application of high-throughput genomics technologies in nutrition research
References
Further reading
Chapter 30. Bioinformatics approach for whole transcriptomics-based marker prediction in agricultural crops
Abstract
30.1 Introduction to transcriptomics
30.2 Markers
30.3 Markers in plants
30.4 Expressed sequence tags and simple sequence repeats
30.5 Tools for generating transcriptomic data
30.6 Why transcriptomic markers?
30.7 How are markers developed/selected?
30.8 What has been done
30.9 Future prospects
References
Chapter 31. Computational approaches toward single-nucleotide polymorphism discovery and its applications in plant breeding
Abstract
31.1 Introduction
31.2 Single-nucleotide polymorphism discovery
31.3 Single-nucleotide polymorphism annotation
31.4 Single-nucleotide polymorphism database
31.5 Single-nucleotide polymorphism genotyping
31.6 Application of single-nucleotide polymorphisms in plants
31.7 Conclusion and prospects
Acknowledgment
References
Chapter 32. Bioinformatics intervention in identification and development of molecular markers: an overview
Abstract
32.1 Introduction
32.2 Genetic markers
32.3 Restriction fragment length polymorphism (RFLP)
32.4 Random amplified polymorphic DNA (RAPD)
32.5 Amplified fragment length polymorphism (AFLP)
32.6 Simple sequence repeats (SSR)
32.7 Intersimple sequence repeat (ISSR)
32.8 Single-nucleotide polymorphism (SNP)
32.9 Quantitative trait loci (QTL)
32.10 Association mapping
32.11 Marker-assisted selection (MAS)
32.12 Bioinformatics intervention in molecular markers
32.13 Software for simple sequence repeats discovery
32.14 Software for single-nucleotide polymorphism discovery
References
Chapter 33. Deciphering comparative and structural variation that regulates abiotic stress response
Abstract
33.1 Introduction
33.2 Expression quantitative trait loci and their functional significance
33.3 Regulatory small RNAs
33.4 Epigenomic regulation of gene expression in plant
33.5 Protein structure provides vital information of function during salt stress
33.6 High performance computing in comparative genomics
33.7 Conclusion
References
Section IV: Artificial intelligence and agribots
Chapter 34. Deep Learning applied to computational biology and agricultural sciences
Abstract
34.1 Introduction
34.2 Deep Learning and Convolutional Neural Network
34.3 Deep Learning applications in computational biology
34.4 Deep Learning applications in agricultural sciences
34.5 Conclusion
References
Chapter 35. Image processing–based artificial intelligence system for rapid detection of plant diseases
Abstract
35.1 Introduction
35.2 Visual symptoms of diseases in plant
35.3 Imaging
35.4 Database creation
35.5 Disease identification using feature extraction and classification
35.6 Disease identification using convolutional neural network
35.7 Determination of the accuracy of the system
35.8 Severity estimation
35.9 Conclusion
References
Chapter 36. Role of artificial intelligence, sensor technology, big data in agriculture: next-generation farming
Abstract
36.1 Introduction
36.2 Characteristics of big data
36.3 Big data and smart agriculture
36.4 Sources of big data
36.5 Techniques and tool use in big data analysis
36.6 Role of big data in agriculture ecosystem: for smart farming
Acknowledgments
Conflict of interest
Author contributions
References
Chapter 37. Artificial intelligence: a way forward for agricultural sciences
Abstract
37.1 Introduction of artificial intelligence
37.2 History of artificial intelligence
37.3 Methods and approaches in artificial intelligence
37.4 Technological advancements in artificial intelligence
37.5 Application of artificial intelligence
37.6 Future perspective and challenges
37.7 Conclusion
References
Index

Pradeep Sharma

Dr. Sharma’s research focuses on Agriculture Biotechnology, specifically on the characterization of genes and SSRs for abiotic stresses (drought and heat) and understating the role of epigenetics, Gene silencing and small RNAs in for wheat improvement. He has been associated with several networking projects funded as Agri-Bioinformatics Promotion Program, ACIAR-DST, and DBT-BBSRC, ICAR Networking projects on AMMAS, Cabin and AMAAS schemes etc. He has published 90 peer reviewed papers, editor of six books published in CRC, Elsevier and Academic Press, and 20 book chapters. Dr Sharma has been associated with a recently released bread wheat variety DBW71 and three trait specific genetic and has been awarded with ICAR-Lal Bahadur Shastri Outstanding Young Scientist Award, NAAS- Young Scientist 2007 and ISCA- Pran Vohra Awards. Dr Sharma is Chief Editor of Journal of Cereal Research and editorial of several journals.

Affiliations and expertise

Principal Scientist (Biotechnology), Division of Crop Improvement, ICAR-Indian Institute of Wheat and Barley Research (IIWBR), Haryana, India

Dinesh Yadav

Prof. Dinesh Yadav is Professor, Department of Biotechnology at D.D.U Gorakhpur University, Gorakhpur, INDIA. Presently he is a coordinator of newly established “Centre for Genomics and Bioinformatics “at D.D.U Gorakhpur University. He was Head, Department of Biotechnology, D.D.U. Gorakhpur University from August 2016 to August 2019. He is also serving as nodal officer IPR cell at DDU Gorakhpur University since Jan 2019. He has also served as Associate Professor in Department of Molecular Biology and Genetic Engineering at G.B Pant University of Agriculture and Technology, Pantnagar from 2006-2009. He has completed his Master Degree in Biotechnology from Devi Ahilya University, Indore in 1996 and Ph.D. from G.B. Pant University of Agriculture and Technology, Pantnagar in 2002. He has more than 19 years of teaching /research experiences. His areas of specialization are Molecular biology, Bioinformatics, Plant biotechnology and Enzyme technology. He has published more than 130 research papers including reviews, books, chapters in Books and proceedings in conferences and more than 230 GenBank accession numbers. He has guided 12 students for Ph.D. in Biotechnology and presently three students are pursuing PhD. He has been mentor for five post-doctoral fellowships namely UGC-Dr. D.S. Kothari (twice), DST-Women Scientist-A DST-Women Scientist-B and SERB-National PDF. He has also supervised 90 students for M.Sc. dissertation/short project work in Biotechnology. He has carried out projects from funding agencies like DBT, UGC, UP Council of Agricultural Research, Lucknow and DST. He has availed DST-BOYSCAST Fellowship at Australian Centre for Plant Functional Genomics (ACPFG), University of Adelaide, South Australia from 3rd May 2012-12th April 2013.He has been awarded Dr. Pushpendra Kumar Gupta Vishisht Krishi Vaigyanik Puraskar-2015 in the field of Agricultural Sciences by Uttar Pradesh Academy of Agricultural Sciences (UPAAS), Lucknow and Young Scientist Award-2008 by Uttarakhand Sate Council of Science & Technology in the discipline Biotechnology, Biochemistry and Microbiology. He is life member of scientific societies namely BRSI, Trivendrum, SBC(I), Bangalore, Indian Science Congress, Association, Calcutta, Society of Plant Biochemistry and Biotechnology, IARI, New Delhi, Association of Microbiologist of India (AMI), New Delhi and UPAAS, Lucknow. He has delivered more than 80 invited talks/ lectures in conference/symposium and also served as Mentor for DST-INSPIRE Science internship camp and Inspire-awards. Presently he is working on Plant specific transcription factor-DOF (DNA binding with One finger) and Nuclear Factor-Y (NF-Y) for developing biotic and abiotic stress tolerance crops and pectinases group of enzymes with potential applications in different industries. His research work has been published in National and International journals of repute like Journal of Experimental Botany, Planta, Theoretical and Applied Genetics, Process Biochemistry, Molecular Biology Reports, Plant Systematics and Evolution, Molecular Biotechnology, Applied Biochemistry and Biotechnology, Annals of Microbiology, Journal of Basic Microbiology, 3 Biotech, Biologia, Journal of Cereal Sciences, Physiology and Molecular Biology of Plants, Biochemistry (Moscow), Current Proteomics, Interdisciplinary Sciences: Computational Life Sciences, Biocatalysis and Agricultural Biotechnology, Cell Biochemistry and Biophysics, Online Journal of Bioinformatics, Chemistry and Ecology, African Journal of Biotechnology, Applied Biochemistry and Microbiology, SugarTech, Enzyme Research etc.

Affiliations and expertise

Professor and Ex-Head, Dept. of Biotechnology, D.D.U. Gorakhpur University, Gorakhpur, Uttar Pradesh, India

R.K. Gaur

Prof. (Dr.) R.K. Gaur earned his Ph.D. in 2005, and is now a Professor at the Department of Biotechnology, Deen Dayal Upadhyaya Gorakhpur University, Gorakhpur, Uttar Pradesh, India. His Ph.D. was on the molecular characterization of sugarcane viruses, i.e., mosaic, streak mosaic, and yellow luteovirus. He received a MASHAV fellowship of the Israeli government for his postdoctoral studies and joined The Volcani Center, Israel and Ben-Gurion University, Negev, Israel. In 2007 he received the Visiting Scientist Fellowship from the Swedish Institute, Sweden to work at Umea˚ University, Umea˚, Sweden. He received a postdoc fellowship from ICGEB, Italy in 2008. He has made significant contributions on sugarcane viruses and has pub lished 130 national/international papers, authored 17 edited books and presented about 50 papers at national and international conferences. He has been honored as a Fellow of Linnean Society, a Fellow of the Royal Society of Biology, a Fellow of the Society of Plant Research, a Fellow of the Society of Applied Biology (FSAB), and a Fellow of the International Society of Biotechnology (FISBT). He has received many other awards, including the Prof. B.M. Johri memorial Award, Society of Plant Research (SPR); Excellent Teaching Award by Astha Foundation, Meerut; UGC-Research Teacher Award; Young Scientist Award in 2012 in Biotechnology by the Society of Plant Research (SPR), Meerut; and Scientific and Applied Research Center Gold Medal Award in 2011 for outstanding contribution in the field of Biotechnology. He has visited several laborato ries in the United States, Canada, New Zealand, United Kingdom, Thailand, Sweden, and Italy. Currently, he is han dling many national and international grants and international collaborative projects on plant viruses and disease management

Affiliations and expertise

Department of Biotechnology, Deen Dayal Upadhyaya Gorakhpur University, Gorakhpur, Uttar Pradesh, India

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Bioinformatics in Agriculture

Next Generation Sequencing Era

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Pradeep Sharma

Dinesh Yadav

R.K. Gaur

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