Next-generation education in crop genetics

Today, plant breeders are being met with new opportunities to develop superior varieties. Fruitful genetic research into populations with novel diversity using genotyping by sequencing combined with genotype-to-phenotype bioinformatics has generated much knowledge that is directly relevant to crop improvement. These advances can assist the breeders in associating genetic makeup with traits of commercial value. The greatest challenge now is to find ways to attract the best young people to work in plant breeding for its innovation, open field experience and ability to support food security. We discuss the need, opportunities and conflicts associated with revamping plant breeding teaching programs to bridge the art and science of this profession with a rapidly expanding job market.     

In Silico Analysis of Crop Science： Report on the First China-UK Workshop on Chips, Computers and Crops

A workshop on ＂Chips, Computers and Crops＂ was held in Hangzhou, China during September 26-27, 2008. The main objective of the workshop was to bring together China and UK scientists from mathematics, bioinformatics and plant molecular biology communities to exchange ideas, enhance awareness of each others＇ fields, explore synergisms and make recommendations on fruitful future directions in crop science. Here we describe the contributions to the workshop, and examine some conceptual issues that lie at the foundations and future of crop systems biology.     

Integrating genetic information into plant breeding programmes: how will we produce varieties from molecular variation,using bioinformatics?

The development of new varieties of crop plants is ongoing for plant breeders and progress since the Green Revolution has been steady, if not dramatic. With the recent sequencing of Arabidopsis thaliana and of rice the development of both physical and informational resources has entered a new phase. This paper examines the state of plant bioinformatics as it is now and as it is likely to develop in the future. It also looks rather further forward to what crop scientists might want from bioinformatics, before examining the likely physiological targets for sustainability traits and the prospects for their improvement in wheat. Wheat is taken as the focus crop because it is potentially one of the most dif. Cult to work with in molecular terms, both because of its large hexaploid genome size and because of its considerable genetic distance from the most information rich plant species, Arabidopsis. Finally, we examine how these tools might be used to track down the underlying genes controlling sustainability traits and how these may then be exploited in plant breeding programmes using marker‐ assisted selection.     

BioManager: the use of a bioinformatics web application as a teaching tool in undergraduate bioinformatics training

The completion of the human genome project, and other genome sequencing projects, has spearheaded the emergence of the field of bioinformatics. Using computer programs to analyse DNA and protein information has become an important area of life science research and development. While it is not necessary for most life science researchers to develop specialist bioinformatic skills (including software development), basic skills in the application of common bioinformatics software and the effective interpretation of results are increasingly required by all life science researchers. Training in bioinformatics is increasingly occurring within the university system as part of existing undergraduate science and specialist degrees. One difficulty in bioinformatics education is the sheer number of software programs required in order to provide a thorough grounding in the subject to the student. Teaching requires either a well-maintained internal server with all the required software, properly interfacing with student terminals, and with sufficient capacity to handle multiple simultaneous requests, or it requires the individual installation and maintenance of every piece of software on each computer. In both cases, there are difficult issues regarding site maintenance and accessibility. In this article, we discuss the use of BioManager, a web-based bioinformatics application integrating a variety of common bioinformatics tools, for teaching, including its role as the main bioinformatics training tool in some Australian and international universities. We discuss some of the issues with using a bioinformatics resource primarily created for research in an undergraduate teaching environment.     

Cross-fertilizing weed science and plant invasion science to improve efficient management: A European challenge

Both weed science and plant invasion science deal with noxious plants. Yet, they have historically developed as two distinct research areas in Europe, with different target species, approaches and management aims, as well as with diverging institutions and researchers involved. We argue that the strengths of these two disciplines can be highly complementary in implementing management strategies and outline how synergies were created in an international, multidisciplinary project to develop efficient and sustainable management of common ragweed, Ambrosia artemisiifolia. Because this species has severe impacts on human health and is also a crop weed in large parts of Europe, common ragweed is one of the economically most important plant invaders in Europe. Our multidisciplinary approach combining expertise from weed science and plant invasion science allowed us (i) to develop a comprehensive plant demographic model to evaluate and compare management tools, such as optimal cutting regimes and biological control for different regions and habitat types, and (ii) to assess benefits and risks of biological control. It further (iii) showed ways to reconcile different stakeholder interests and management objectives (health versus crop yield), and (iv) led to an economic model to assess invader impact across actors and domains, and effectiveness of control measures. (v) It also led to design and implement management strategies in collaboration with the various stakeholder groups affected by noxious weeds, created training opportunities for early stage researchers in the sustainable management of noxious plants, and actively promoted improved decision making regarding the use of exotic biocontrol agents at the national and European level. We critically discuss our achievements and limitations, and list and discuss other potential Old World (Afro-Eurasian) target species that could benefit from applying such an integrative approach, as typical invasive alien plants are increasingly reported from crop fields and native crop weeds are invading adjacent non-crop land, thereby forming new source populations for further spread.     

Plant metabolomics: large-scale phytochemistry in the functional genomics era

Metabolomics or the large-scale phytochemical analysis of plants is reviewed in relation to functional genomics and systems biology. A historical account of the introduction and evolution of metabolite profiling into today's modern comprehensive metabolomics approach is provided. Many of the technologies used in metabolomics, including optical spectroscopy, nuclear magnetic resonance, and mass spectrometry are surveyed. The critical role of bioinformatics and various methods of data visualization are summarized and the future role of metabolomics in plant science assessed.     

An integrated,modular approach to data science education in microbiology

We live in an increasingly data-driven world, where high-throughput sequencing and mass spectrometry platforms are transforming biology into an information science. This has shifted major challenges in biological research from data generation and processing to interpretation and knowledge translation. However, postsecondary training in bioinformatics, or more generally data science for life scientists, lags behind current demand. In particular, development of accessible, undergraduate data science curricula has the potential to improve research and learning outcomes as well as better prepare students in the life sciences to thrive in public and private sector careers. Here, we describe the Experiential Data science for Undergraduate Cross-Disciplinary Education (EDUCE) initiative, which aims to progressively build data science competency across several years of integrated practice. Through EDUCE, students complete data science modules integrated into required and elective courses augmented with coordinated cocurricular activities. The EDUCE initiative draws on a community of practice consisting of teaching assistants (TAs), postdocs, instructors, and research faculty from multiple disciplines to overcome several reported barriers to data science for life scientists, including instructor capacity, student prior knowledge, and relevance to discipline-specific problems. Preliminary survey results indicate that even a single module improves student self-reported interest and/or experience in bioinformatics and computer science. Thus, EDUCE provides a flexible and extensible active learning framework for integration of data science curriculum into undergraduate courses and programs across the life sciences.     

GERMINATE. a generic database for integrating genotypic and phenotypic information for plant genetic resource collections

The extensive germplasm resource collections that are now available for major crop plants and their wild relatives will increasingly provide valuable biological and bioinformatics resources for plant physiologists and geneticists to dissect the molecular basis of key traits and to develop highly adapted plant material to sustain future breeding programs. A key to the efficient deployment of these resources is the development of information systems that will enable the collection and storage of biological information for these plant lines to be integrated with the molecular information that is now becoming available through the use of high-throughput genomics and post-genomics technologies. The GERMINATE database has been designed to hold a diverse variety of data types, ranging from molecular to phenotypic, and to allow querying between such data for any plant species. Data are stored in GERMINATE in a technology-independent manner, such that new technologies can be accommodated in the database as they emerge, without modification of the underlying schema. Users can access data in GERMINATE databases either via a lightweight Perl-CGI Web interface or by the more complex Genomic Diversity and Phenotype Connection software. GERMINATE is released under the GNU General Public License and is available at http://germinate.scri.sari.ac.uk/germinate/.     

From crop domestication to super-domestication

Research related to crop domestication has been transformed by technologies and discoveries in the genome sciences as well as information-related sciences that are providing new tools for bioinformatics and systems' biology. Rapid progress in archaeobotany and ethnobotany are also contributing new knowledge to understanding crop domestication. This sense of rapid progress is encapsulated in this Special Issue, which contains 18 papers by scientists in botanical, crop sciences and related disciplines on the topic of crop domestication. One paper focuses on current themes in the genetics of crop domestication across crops, whereas other papers have a crop or geographic focus. One feature of progress in the sciences related to crop domestication is the availability of well-characterized germplasm resources in the global network of genetic resources centres (genebanks). Germplasm in genebanks is providing research materials for understanding domestication as well as for plant breeding. In this review, we highlight current genetic themes related to crop domestication. Impressive progress in this field in recent years is transforming plant breeding into crop engineering to meet the human need for increased crop yield with the minimum environmental impact - we consider this to be 'super-domestication'. While the time scale of domestication of 10 000 years or less is a very short evolutionary time span, the details emerging of what has happened and what is happening provide a window to see where domestication might - and can - advance in the future.     

Plant genomics in Africa: present and prospects

Plants are the world’s most consumed goods. They are of high economic value and bring many health benefits. In most countries in Africa, the supply and quality of food will rise to meet the growing population’s increasing demand. Genomics and other biotechnology tools offer the opportunity to improve subsistence crops and medicinal herbs in the continent. Significant advances have been made in plant genomics, which have enhanced our knowledge of the molecular processes underlying both plant quality and yield. The sequencing of complex genomes of African plant species, facilitated by the continuously evolving next-generation sequencing technologies and advanced bioinformatics approaches, has provided new opportunities for crop improvement. This review summarizes the achievements of genome sequencing projects of endemic African plants in the last two decades. We also present perspectives and challenges for future plant genomic studies that will accelerate important plant breeding programs for African communities. These challenges include a lack of basic facilities, a lack of sequencing and bioinformatics facilities, and a lack of skills to design genomics studies. However, it is imperative to state that African countries have become key players in the plant genome revolution and genome derived-biotechnology. Therefore, African governments should invest in public plant genomics research and applications, establish bioinformatics platforms and training programs, and stimulate university and industry partnerships to fully deploy plant genomics, particularly in the fields of agriculture and medicine.     

生物信息学在昆虫学研究中的应用

随着深度测序和基因芯片技术的不断发展,基因组、转录组、表达谱数据大量积累。目前,至少有10多个昆虫的基因组已被测序,30多个昆虫的转录组数据被报道。显然,传统的生物统计学方法无法处理如此海量的生物数据。量变引发质变,生物数据的大量积累催生了一门新兴学科,生物信息学。生物信息学融合了统计学、信息科学和生物学等各学科的理论和研究内容,在医学、基础生物学、农业科学以及昆虫学等方面获得了广泛的应用。生物信息学的目标是存储数据、管理数据和数据挖掘。因此,建立维护生物学数据库、设计开发基于模式识别、机器学习、数据挖掘等方法的生物软件,以及运用上述工具进行深度的数据挖掘,是生物信息学的重要研究内容。本文首先简要介绍了生物信息学的历史、研究现状及其在昆虫学科中的应用,然后综述了昆虫基因组学和转录组学的研究进展,最后对生物信息学在昆虫学研究中的应用前景进行了展望。     

生物信息学对计算机科学发展的机遇与挑战

生物信息学是一个发展很快的新兴学科,是计算机应用的最重要的领域之一,同时生物信息学的发展又给计算机学科提出了许多新的课题,从而促进计算机学科自身的发展。从数据库技术、海量存储技术、数据挖掘、计算几何、DNA计算、网格计算、机器学习、人工心智、web service等方面,就生物信息学对计算机科学发展的促进作用进行了论述。     

ELIXIR‐EXCELERATE: establishing Europe's data infrastructure for the life science research of the future

A new inter‐governmental research infrastructure, ELIXIR, aims to unify bioinformatics resources and life science data across Europe, thereby facilitating their mining and (re‐)use. Subject Categories: Computational Biology, Methods & Resources, S&S: Ethics

Creating knowledge by connecting and analysing large amounts of life science data is transforming our society, allowing us to start addressing major scientific and societal challenges, such as adaptation to climate change or pathogen outbreaks in an interconnected world. Modern biology is dependent on the generation, sharing and integrated analysis of digital data at scale. A deeper understanding of biological systems is now becoming possible thanks to breakthroughs in technologies that study life systematically at different scales, from molecules and single‐cell pathogens to complex animal or plant models and ecosystems as well as across temporal ranges spanning split‐second reactions to multi‐year clinical or agronomic trials, and beyond. The key to analyse and leverage this complex, fragmented and geographically dispersed life science data landscape is to ensure it is easy to find and reuse by researchers. This article comments on ELIXIR, an international organisation that brings together bioinformatics researchers and life science resources across Europe and integrates them into a single federated infrastructure.     

What is the subject of science "bioinformatics"?

The paper is concerned with some problems of terminology, in particular the term "bioinformatics". In the last few years, the term "bioinformatics" has been intensively used among molecular biologists to indicate a subject that is only a constituent of genomics and is considered to involve a computer-assisted analysis of all data on nucleotide sequences of DNA. However, a wide circle of scientists, including biologists, physicists, mathematicians, and specialists in the field of cybernetics, informatics, and other disciplines have accepted and accept, as a rule, the "bioinformatics" as a synonym of science cybernetics and as a successor of this science. In this case, the subject of science "bioinformatics" should embrace not only genomics but practically all sections of the biological science. It should involve a study of information processes (storage, transfer, and processing of information, etc.) participating in the regulation and control at all levels of living systems, from macromolecules to the brain of higher animals and human.     

The SOL Genomics Network: a comparative resource for Solanaceae biology and beyond

The SOL Genomics Network (SGN; http://sgn.cornell.edu) is a rapidly evolving comparative resource for the plants of the Solanaceae family, which includes important crop and model plants such as potato (Solanum tuberosum), eggplant (Solanum melongena), pepper (Capsicum annuum), and tomato (Solanum lycopersicum). The aim of SGN is to relate these species to one another using a comparative genomics approach and to tie them to the other dicots through the fully sequenced genome of Arabidopsis (Arabidopsis thaliana). SGN currently houses map and marker data for Solanaceae species, a large expressed sequence tag collection with computationally derived unigene sets, an extensive database of phenotypic information for a mutagenized tomato population, and associated tools such as real-time quantitative trait loci. Recently, the International Solanaceae Project (SOL) was formed as an umbrella organization for Solanaceae research in over 30 countries to address important questions in plant biology. The first cornerstone of the SOL project is the sequencing of the entire euchromatic portion of the tomato genome. SGN is collaborating with other bioinformatics centers in building the bioinformatics infrastructure for the tomato sequencing project and implementing the bioinformatics strategy of the larger SOL project. The overarching goal of SGN is to make information available in an intuitive comparative format, thereby facilitating a systems approach to investigations into the basis of adaptation and phenotypic diversity in the Solanaceae family, other species in the Asterid clade such as coffee (Coffea arabica), Rubiaciae, and beyond.     

Genotyping‐by‐sequencing approaches to characterize crop genomes: choosing the right tool for the right application

In the last decade, the revolution in sequencing technologies has deeply impacted crop genotyping practice. New methods allowing rapid, high‐throughput genotyping of entire crop populations have proliferated and opened the door to wider use of molecular tools in plant breeding. These new genotyping‐by‐sequencing (GBS) methods include over a dozen reduced‐representation sequencing (RRS) approaches and at least four whole‐genome resequencing (WGR) approaches. The diversity of methods available, each often producing different types of data at different cost, can make selection of the best‐suited method seem a daunting task. We review the most common genotyping methods used today and compare their suitability for linkage mapping, genomewide association studies (GWAS), marker‐assisted and genomic selection and genome assembly and improvement in crops with various genome sizes and complexity. Furthermore, we give an outline of bioinformatics tools for analysis of genotyping data. WGR is well suited to genotyping biparental cross populations with complex, small‐ to moderate‐sized genomes and provides the lowest cost per marker data point. RRS approaches differ in their suitability for various tasks, but demonstrate similar costs per marker data point. These approaches are generally better suited for de novo applications and more cost‐effective when genotyping populations with large genomes or high heterozygosity. We expect that although RRS approaches will remain the most cost‐effective for some time, WGR will become more widespread for crop genotyping as sequencing costs continue to decrease.     

Forensic DNA and bioinformatics

The field of forensic science is increasingly based on biomolecular data and many European countries are establishing forensic databases to store DNA profiles of crime scenes of known offenders and apply DNA testing. The field is boosted by statistical and technological advances such as DNA microarray sequencing, TFT biosensors, machine learning algorithms, in particular Bayesian networks, which provide an effective way of evidence organization and inference. The aim of this article is to discuss the state of art potentialities of bioinformatics in forensic DNA science. We also discuss how bioinformatics will address issues related to privacy rights such as those raised from large scale integration of crime, public health and population genetic susceptibility-to-diseases databases.     

FT-ICR/MS and GC-EI/MS Metabolomics Networking Unravels Global Potato Sprout's Responses to Rhizoctonia solani Infection

The complexity of plant-pathogen interactions makes their dissection a challenging task for metabolomics studies. Here we are reporting on an integrated metabolomics networking approach combining gas chromatography/mass spectrometry (GC/MS) with Fourier transform ion cyclotron resonance/mass spectrometry (FT-ICR/MS) and bioinformatics analyses for the study of interactions in the potato sprout-Rhizoctonia solani pathosystem and the fluctuations in the global metabolome of sprouts. The developed bioanalytical and bioinformatics protocols provided a snapshot of the sprout's global metabolic network and its perturbations as a result of pathogen invasion. Mevalonic acid and deoxy-xylulose pathways were substantially up-regulated leading to the biosynthesis of sesquiterpene alkaloids such as the phytoalexins phytuberin, rishitin, and solavetivone, and steroidal alkaloids having solasodine and solanidine as their common aglycons. Additionally, the perturbation of the sprout's metabolism was depicted in fluctuations of the content of their amino acids pool and that of carboxylic and fatty acids. Components of the systemic acquired resistance (SAR) and hypersensitive reaction (HR) such as azelaic and oxalic acids were detected in increased levels in infected sprouts and strategies of the pathogen to overcome plant defense were proposed. Our metabolic approach has not only greatly expanded the multitude of metabolites previously reported in potato in response to pathogen invasion, but also enabled the identification of bioactive plant-derived metabolites providing valuable information that could be exploited in biotechnology, biomarker-assisted plant breeding, and crop protection for the development of new crop protection agents.