Next-generation Sequencing and Bioinformatics for Plant Science
Caister Academic Press
Semiarid Prairie Agricultural Research Centre, Agriculture and Agri-Food Canada, Swift Current, Canada
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Next-generation sequencing coupled with high-performance computing methods have revolutionised the field of plant breeding and genetics.
In this timely overview of the field, expert scientists review current developments in next-generation sequencing and bioinformatics and discuss their application in understanding and improving agronomic traits such as yield, drought tolerance and disease resistance. The up-to-date reviews cover genome assembly and annotation, omics technologies, structural variations, abnormal chromosome number, chromosomal rearrangement, copy number variation, mobile elements, sequencing of small RNA nucleotides and transcription factor binding sites. Specific topics include the evolution analysis of rice, maize, sorghum and orchids, fruit development and ripening, plant disease resistance, fusarium head blight and stripe rust resistance in wheat and rice, host defence and pathogen virulence, crop design with improved resistance, and biotic and abiotic stress tolerance.
This is a useful review of current developments in next-generation sequencing and essential reading for plant geneticists and crop scientists.
Table of contents
Vijai Bhadauria and Lucia Popescu
With the advent of high-throughput sequencing platforms, such as Illumina's Genome Analyzer, HiSeq, MiSeq and NextSeq, Roche/454's Genome Sequencer FLX, Thermo-Fisher Scientific's SOLiD, Ion Torrent and Ion Proton, PacBio's Real-Time Sequencer and more recently Oxford Nanopore's MinION, it has become feasible to sequence entire genomes and transcriptomes at an exponential pace. This has huge implications in plant breeding and genetics. The reviews presented in this volume summarize recent developments in next-generation sequencing and bioinformatics tools and their application in understanding and improving agronomic traits.
1. Status and Prospects of Next Generation Sequencing Technologies in Crop Plants
T.R. Sharma, B.N. Devanna, Kanti Kiran, Pankaj K. Singh, Kirti Arora, Priyanka Jain, Ila M. Tiwari, Himanshu Dubey, Banita Saklani, Mandeep Kumari, Jyoti Singh, Rajdeep Jaswal, Ritu Kapoor, Deepak V. Pawar, Shruti Sinha, Deepak Singh Bisht, A.U. Solanke and T.K. Mondal
The history of DNA sequencing dates back to 1970s. During this period the two first generation nucleotide sequencing techniques were developed. Subsequently the Sanger's dideoxy method of sequencing gained popularity over Maxam and Gilbert's chemical method of sequencing. However, in the last decade, we have observed revolutionary changes in DNA sequencing technologies leading to the emergence of next-generation sequencing (NGS) techniques. NGS technologies have enhanced the throughput and speed of sequencing combined with bringing down the overall cost of the process over a time. The major applications of NGS technologies being genome sequencing and resequencing, transcriptomics, metagenomics in relation to plant-microbe interactions, exon and genome capturing, development of molecular markers and evolutionary studies. In this review, we present a broader picture of evolution of NGS tools, its various applications in crop plants, and future prospects of the technology for crop improvement.
2. Next-Generation Sequencing Promoted the Release of Reference Genomes and Discovered Genome Evolution in Cereal Crops
Yong Huang, Haiyang Liu and Yongzhong Xing
In recent decades, next-generation sequencing (NGS) was developed and brought biology into a new era. Rice, maize, wheat, sorghum and barley are the most important cereal crops and feed most of the world's population. Great progress in the study of cereal genomes has been made with the help of NGS. Reference genome sequence assembly and re-sequencing have grown exponentially. Thus, evolution and comparative genomics are renewed, including origin verification, evolution tracking and so on. In this review, we briefly record the development of sequencing technology, the comparison of next-generation sequencing methods and platforms and summarize the bioinformatics tools used for NGS data analysis. We describe how NGS accelerates reference genome assembly and new evolutionary findings. We finally discuss how to discover more valuable resources and improve cereal breeding in the future.
3. Advanced Applications of Next-Generation Sequencing Technologies to Orchid Biology
Chuan-Ming Yeh, Zhong-Jian Liu and Wen-Chieh Tsai
Next-generation sequencing technologies are revolutionizing biology by permitting, transcriptome sequencing, whole-genome sequencing and resequencing, and genome-wide single nucleotide polymorphism profiling. Orchid research has benefited from this breakthrough, and a few orchid genomes are now available; new biological questions can be approached and new breeding strategies can be designed. The first part of this review describes the unique features of orchid biology. The second part provides an overview of the current next-generation sequencing platforms, many of which are already used in plant laboratories. The third part summarizes the state of orchid transcriptome and genome sequencing and illustrates current achievements. The genetic sequences currently obtained will not only provide a broad scope for the study of orchid biology, but also serves as a starting point for uncovering the mystery of orchid evolution.
4. Bioinformatics Resources for Plant Genomics: Opportunities and Bottlenecks in The -omics Era
Luca Ambrosino, Chiara Colantuono, Francesco Monticolo and Maria Luisa Chiusano
The sudden exponential increase of biological data concerning genome structure and functionalities, also fostered by the advent of Next Generation Sequencing (NGS) technologies, while expanding the opportunity to highlight still uncovered molecular aspects, challenges bioinformatics in several repects. Data management, processing, updating, dissemination and integration are the major areas of concern. The rapid increase in various omics technologies causes two major issues, which may even appear contrasting: the dissemination of poorly curated datasets, still in the form of raw collections or preliminary draft results, and the fast updating of information that, as a consequence, affects the establishment of stable reliable resources. These issues are mainly caused by the lower rate of bioinformatics in extracting added value information from the large amount of data, when compared to the faster technologies involved in data production. This review describes main bioinformatics resources for plants genomics to underline the heterogeneity of the available collections, coherent with the multifaceted complexity of plant sciences. It aims to provide an in-depth report highlighting bottlenecks that may significantly affect a fluent progress in the field and attempts to suggest possible solutions to the various issues.
5. Applications of Bioinformatics to Plant Biotechnology
Diego F. Gomez-Casati, María V. Busi, Julieta Barchiesi, Diego A. Peralta, Nicolás Hedin and Vijai Bhadauria
Bioinformatics encompasses many tools and techniques that today are essential for all areas of research in the biological sciences. New databases with a wealth of information about genomes, proteins, metabolites, and metabolic pathways appear almost daily. Particularly, for scientists who carry out research in plant biology, the amount of information has multiplied exponentially due to the large number of databases available for many individual plant species. In this sense, bioinformatics together with next generation sequencing and 'omics' approaches, can provide tools for plant breeding and the genetic engineering of plants. In addition, these technologies enable a better understanding of the processes and mechanisms that can lead to plants with increased tolerance to different abiotic stress conditions and resistance to pathogen attack, as well as the development of crop varieties with improved nutritional quality of seeds and fruits.
6. Quantitative Genetics of Disease Resistance in Wheat
Vijai Bhadauria and Lucia Popescu
Wheat (Triticum aestivum L.) is one of the top three global food security crops. Fusarium head blight is one of the major constraints in sustainable wheat production and resistance to the disease is polygenic. This review provides an overview of recent efforts in mapping these genes/loci with the objective to aid marker-assisted selection breeding.
7. A Rice Genetic Improvement Boom by Next Generation Sequencing
Xiangchun Zhou, Xufeng Bai and Yongzhong Xing
Rice (Oryza sativa L.) is a staple food crop for people worldwide, and a key goal has been to increase its grain yield. An increasing population that relies on a decreasing level of farmland has rendered the traditional method for the isolation and use of genetic loci in rice breeding unsatisfactory. Recently, the rapid development in next generation sequencing (NGS) has boosted the number of genome sequences for hundreds to thousands of rice varieties. A MutMap strategy and bulk segregation analysis (BSA) has been developed to directly identify candidate genes based on NGS. The genome-wide association analysis (GWAS) has become a commonly used approach toward identifying the genetic loci and candidate genes for several traits that are closely associated with grain yield. The Multi-parent Advanced Generation Inter-Cross population (MAGIC) is introduced here to discuss potential applications for mapping QTLs for rice varietal development. These strategies broaden the capacity of functional gene identification and its application as a complementary method to insert mutants that comprise T-DNA and transposons. High-throughput SNP analysis platforms, such as the SNP array, provide novel strategies for genomic-assisted selections (GAS) for rice genetic improvements. Moreover, accurate genome sequence information enables genome editing for the utilization of key recessive genes that control important agronomic traits. This review summarizes how NGS accelerates rice genetic improvements through the identification and utilization of key functional genes that regulate agronomic traits.
8. Dual RNA-Sequencing to Elucidate the Plant-Pathogen Duel Free download
Sanushka Naidoo, Erik Andrei Visser, Lizahn Zwart, Yves du Toit, Vijai Bhadauria and Louise Simone Shuey
RNA-sequencing technology has been widely adopted to investigate host responses during infection with pathogens. Dual RNA-sequencing (RNA-seq) allows the simultaneous capture of pathogen specific transcripts during infection, providing a more complete view of the interaction. In this review, we focus on the design of dual RNA-seq experiments and the application of downstream data analysis to gain biological insight into both sides of the interaction. Recent literature in this area demonstrates the power of the dual RNA-seq approach and shows that it is not limited to model systems where genomic resources are available. A reduction in sequencing cost and single cell transcriptomics coupled with protein and metabolite level dual approaches are set to enhance our understanding of plant-pathogen interactions. Sequencing costs continue to decrease and single cell transcriptomics is becoming more feasible. In combination with proteomics and metabolomics studies, these technological advances are likely to contribute to our understanding of the temporal and spatial aspects of dynamic plant-pathogen interactions.
9. Next-Generation Sequencing Sheds New Light on Small RNAs in Plant Reproductive Development
Reproductive development is a key step of the plant life cycles and indicates the start of a new life cycle. The reproductive organs including flower, fruit and seed, have diverse and complex structures, which is a syndrome in the evolution of angiosperms. The development of plant reproductive organs depends on the correct spatial and temporal expression of numerous genes acting in concert to form regulatory networks. Small non-coding RNAs (sRNAs) play a key role in the reproductive development through different modes of sequence-specific interaction with their targets. The sRNAs guide transcriptional and post-transcriptional regulation to intensively integrate into the complex process. Next generation sequencing techniques (NGS) has greatly extended scientist's capabilities to identified and quantify sRNAs by supplying a massive of sequences. In turn this has led to a greater understanding of the many complex roles and interactions that sRNAs are involved with during reproductive development. In this review, we provide an overview of the biogenesis and classification of plant sRNAs, and summarize the recent progress in the understanding of plant sRNA in the flower, and fruit/seed development. Also, we discuss NGS approaches to profile global sRNA expression, as well as the application of sRNA-seq/degradome-seq approaches to identify novel sRNAs and verify their targets related to the above development processes.
10. ChIP-Seq: A Powerful Tool for Studying Protein-DNA Interactions in Plants
Xifeng Chen, Vijai Bhadauria and Bojun Ma
DNA-binding proteins, including transcription factors, epigenetic and chromatin modifiers, control gene expressions in plants. To pinpoint the binding sits of DNA-binding proteins in genome is crucial for decoding gene regulatory networks. Chromatin immunoprecipitation (ChIP) followed by high-throughput DNA sequencing (ChIP-Seq) is a widely used approach to identify the DNA regions bound by a specific protein in vivo. The information generated from ChIP-Seq has tremendously advanced our understanding on the mechanism of transcription factors, cofactors and histone modifications in regulating gene expression. In this review, we reviewed the recent research advance of ChIP-Seq in plants, including description of the ChIP-Seq workflow and its various applications in plants, and in addition, provided perspective of the potential advances of ChIP-Seq.
Xingtan Zhang, Xuequn Chen, Pingping Liang and Haibao Tang
Structural variation (SV) is a type of genetic variation identified through the comparison of genome structures which often have direct and significant associations with phenotypic variations. Building on the next generation sequencing (NGS) technologies, research on plant structural variations are gaining momentum and have revolutionized our view on the functional impact of the 'hidden' diversity that were largely understudied before. Herein, we first describe the current state of plant genomic SV research based on NGS and in particular focus on the biological insights gained from the large-scale identification of various types of plant SVs. Specific examples are chosen to demonstrate the genetic basis for phenotype diversity in model plant and major agricultural crops. Additionally, development of new genomic mapping technologies, including optical mapping and long read sequencing, as well as improved computational algorithms associated with these technologies have helped to pinpoint the exact nature and location of genomic SVs with much better resolution and precision. Future direction of plant research on SVs should focus on the population level to build a comprehensive catalog of SVs, leading to full assessment of their impact on biological diversity.
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(EAN: 9781910190654 9781910190661 Subjects: [bioinformatics] [molecular biology] [plant science] )