Chunguang Du

The Genomics Education Partnership: Successful Integration of Research into Laboratory Classes at a Diverse Group of Undergraduate Institutions

Genomics is not only essential for students to understand biology but also provides unprecedented opportunities for undergraduate research. The goal of the Genomics Education Partnership (GEP), a collaboration between a growing number of colleges and universities around the country and the Department of Biology and Genome Center of Washington University in St. Louis, is to provide such research opportunities. Using a versatile curriculum that has been adapted to many different class settings, GEP undergraduates undertake projects to bring draft-quality genomic sequence up to high quality and/or participate in the annotation of these sequences. GEP undergraduates have improved more than 2 million bases of draft genomic sequence from several species of Drosophila and have produced hundreds of gene models using evidence-based manual annotation. Students appreciate their ability to make a contribution to ongoing research, and report increased independence and a more active learning approach after participation in GEP projects. They show knowledge gains on pre- and postcourse quizzes about genes and genomes and in bioinformatic analysis. Participating faculty also report professional gains, increased access to genomics-related technology, and an overall positive experience. We have found that using a genomics research project as the core of a laboratory course is rewarding for both faculty and students.

Genomics Education Partnership

The Genomics Education Partnership offers an inclusive model for undergraduate research experiences, with students pooling their work to contribute to international databases.

The polychromatic Helitron landscape of the maize genome

Maize Helitron transposons are intriguing because of their notable ability to capture gene fragments and move them around the genome. To document more extensively their variability and their contribution to the remarkable genome structure variation of present-day maize, we have analyzed their composition, copy number, timing of insertion, and chromosomal distribution. First, we searched 2.4 Gb of sequences generated by the Maize Genome Sequencing Project with our HelitronFinder program. We identified 2,791 putative nonautonomous Helitrons and manually curated a subset of 272. The predicted Helitrons measure 11.9 kb on average and carry from zero to nine gene fragments, captured from 376 different genes. Although the diversity of Helitron gene fragments in maize is greater than in other species, more than one-third of annotated Helitrons carry fragments derived from just one of two genes. Most members in these two subfamilies inserted in the genome less than one million years ago. Second, we conducted a BLASTN search of the maize sequence database with queries from two previously described agenic Helitrons not detected by HelitronFinder. Two large subfamilies of Helitrons or Helitron-related transposons were identified. One subfamily, termed Cornucopious, consists of thousands of copies of an ≈1.0-kb agenic Helitron that may be the most abundant transposon in maize. The second subfamily consists of >150 copies of a transposon-like sequence, termed Heltir, that has terminal inverted repeats resembling Helitron 3′ termini. Nonautonomous Helitrons make up at least 2% of the maize genome and most of those tested show +/− polymorphisms among modern inbred lines.

Cloning, Characterization, and Evolution of the NBS-LRR-Encoding Resistance Gene Analogue Family in Polyploid Cotton (Gossypium hirsutum L.)

The nucleotide-binding site-leucine-rich repeat (NBS-LRR)-encoding gene family has attracted much research interest because approximately 75% of the plant disease resistance genes that have been cloned to date are from this gene family. We cloned the NBS-LRR-encoding genes from polyploid cotton by a polymerase chain reaction-based approach. A sample of 150 clones was selected from the NBS-LRR gene sequence library and was sequenced, and 61 resistance gene analogs (RGA) were identified. Sequence analysis revealed that RGA are abundant and highly diverged in the cotton genome and could be categorized into 10 distinct subfamilies based on the similarities of their nucleotide sequences. The numbers of members vary many fold among different subfamilies, and gene index analysis showed that each of the subfamilies is at a different stage of RGA family evolution. Genetic mapping of a selection of RGA indicates that the RGA reside on a limited number of the cotton chromosomes, with those from a single subfamily tending to cluster and two of the RGA loci being colocalized with the cotton bacterial blight resistance genes. The distribution of RGA between the two subgenomes A and D of cotton is uneven, with RGA being more abundant in the A subgenome than in the D subgenome. The data provide new insights into the organization and evolution of the NBS-LRR-encoding RGA family in polyploid plants.

A Course-Based Research Experience: How Benefits Change with Increased Investment in Instructional Time

While course-based research in genomics can generate both knowledge gains and a greater appreciation for how science is done, a significant investment of course time is required to enable students to show gains commensurate to a summer research experience. Nonetheless, this is a very cost-effective way to reach larger numbers of students.

HelitronScanner uncovers a large overlooked cache of Helitron transposons in many plant genomes

Significance Helitrons are unusual rolling-circle eukaryotic transposons with a remarkable ability to capture gene sequences, which makes them of considerable evolutionary importance. Because Helitrons lack typical transposon features, they are challenging to identify and are estimated to comprise at most 2% of sequenced genomes. Here, we describe HelitronScanner, a generalized tool for their identification based on a motif-extracting algorithm proposed initially in a study of natural languages. HelitronScanner overcomes the divergence of Helitron termini among species by using conserved nucleotides at potentially variable locations. Many new Helitrons were identified in all organisms examined, resulting in a major reassessment of their abundance in eukaryotic genomes. In maize, they make up >6% of the genome and are the most abundant DNA transposons identified. Transposons make up the bulk of eukaryotic genomes, but are difficult to annotate because they evolve rapidly. Most of the unannotated portion of sequenced genomes is probably made up of various divergent transposons that have yet to be categorized. Helitrons are unusual rolling circle eukaryotic transposons that often capture gene sequences, making them of considerable evolutionary importance. Unlike other DNA transposons, Helitrons do not end in inverted repeats or create target site duplications, so they are particularly challenging to identify. Here we present HelitronScanner, a two-layered local combinational variable (LCV) tool for generalized Helitron identification that represents a major improvement over previous identification programs based on DNA sequence or structure. HelitronScanner identified 64,654 Helitrons from a wide range of plant genomes in a highly automated way. We tested HelitronScanner’s predictive ability in maize, a species with highly heterogeneous Helitron elements. LCV scores for the 5′ and 3′ termini of the predicted Helitrons provide a primary confidence level and element copy number provides a secondary one. Newly identified Helitrons were validated by PCR assays or by in silico comparative analysis of insertion site polymorphism among multiple accessions. Many new Helitrons were identified in model species, such as maize, rice, and Arabidopsis, and in a variety of organisms where Helitrons had not been reported previously to our knowledge, leading to a major upward reassessment of their abundance in plant genomes. HelitronScanner promises to be a valuable tool in future comparative and evolutionary studies of this major transposon superfamily.

A Central Support System Can Facilitate Implementation and Sustainability of a Classroom-Based Undergraduate Research Experience (CURE) in Genomics

There have been numerous calls to engage students in science as science is done. A survey of 90-plus faculty members explores barriers and incentives when developing a research-based genomics course. The results indicate that a central core supporting a national experiment can help overcome local obstacles.

The complete Ac/Ds transposon family of maize

BackgroundThe nonautonomous maize Ds transposons can only move in the presence of the autonomous element Ac. They comprise a heterogeneous group that share 11-bp terminal inverted repeats (TIRs) and some subterminal repeats, but vary greatly in size and composition. Three classes of Ds elements can cause mutations: Ds-del, internal deletions of the 4.6-kb Ac element; Ds1, ~400-bp in size and sharing little homology with Ac, and Ds2, variably-sized elements containing about 0.5 kb from the Ac termini and unrelated internal sequences. Here, we analyze the entire complement of Ds-related sequences in the genome of the inbred B73 and ask whether additional classes of Ds-like (Ds-l) elements, not uncovered genetically, are mobilized by Ac. We also compare the makeup of Ds-related sequences in two maize inbreds of different origin.ResultsWe found 903 elements with 11-bp Ac/Ds TIRs flanked by 8-bp target site duplications. Three resemble Ac, but carry small rearrangements. The others are much shorter, once extraneous insertions are removed. There are 331 Ds1 and 39 Ds2 elements, many of which are likely mobilized by Ac, and two novel classes of Ds-l elements. Ds-l3 elements lack subterminal homology with Ac, but carry transposase gene fragments, and represent decaying Ac elements. There are 44 such elements in B73. Ds-l4 elements share little similarity with Ac outside of the 11-bp TIR, have a modal length of ~1 kb, and carry filler DNA which, in a few cases, could be matched to gene fragments. Most Ds-related elements in B73 (486/903) fall in this class. None of the Ds-l elements tested responded to Ac. Only half of Ds insertion sites examined are shared between the inbreds B73 and W22.ConclusionsThe majority of Ds-related sequences in maize correspond to Ds-l elements that do not transpose in the presence of Ac. Unlike actively transposing elements, many Ds-l elements are inserted in repetitive DNA, where they probably become methylated and begin to decay. The filler DNA present in most elements is occasionally captured from genes, a rare feature in transposons of the hAT superfamily to which Ds belongs. Maize inbreds of different origin are highly polymorphic in their DNA transposon makeup.

Dynamic Proteomic Characteristics and Network Integration Revealing Key Proteins for Two Kernel Tissue Developments in Popcorn

The formation and development of maize kernel is a complex dynamic physiological and biochemical process that involves the temporal and spatial expression of many proteins and the regulation of metabolic pathways. In this study, the protein profiles of the endosperm and pericarp at three important developmental stages were analyzed by isobaric tags for relative and absolute quantification (iTRAQ) labeling coupled with LC-MS/MS in popcorn inbred N04. Comparative quantitative proteomic analyses among developmental stages and between tissues were performed, and the protein networks were integrated. A total of 6,876 proteins were identified, of which 1,396 were nonredundant. Specific proteins and different expression patterns were observed across developmental stages and tissues. The functional annotation of the identified proteins revealed the importance of metabolic and cellular processes, and binding and catalytic activities for the development of the tissues. The whole, endosperm-specific and pericarp-specific protein networks integrated 125, 9 and 77 proteins, respectively, which were involved in 54 KEGG pathways and reflected their complex metabolic interactions. Confirmation for the iTRAQ endosperm proteins by two-dimensional gel electrophoresis showed that 44.44% proteins were commonly found. However, the concordance between mRNA level and the protein abundance varied across different proteins, stages, tissues and inbred lines, according to the gene cloning and expression analyses of four relevant proteins with important functions and different expression levels. But the result by western blot showed their same expression tendency for the four proteins as by iTRAQ. These results could provide new insights into the developmental mechanisms of endosperm and pericarp, and grain formation in maize.

Bioinformatics Tools for Plant Genomics

The articles in this special issue reflect a convergence of developments in the fields of bioinformatics and plant genomics. Bioinformatics has its roots vaguely seated in the early 1980s, a time when personal computers began appearing in research laboratories and researchers began recognizing that those computers could be used as tools to organize, analyze and visualize their data. In the ensuing years bioinformatics tools began appearing at various sites including the European Molecular Biology Laboratory, the Molecular Biology Research Resource at the Dana-Farber Cancer Institute in the mid 1980s, the National Center for Biotechnology Information (NCBI) in 1988, the Genome Database Project at Johns Hopkins University in early 1989, and in countless laboratories throughout the world. These last efforts resulted in the development of many of the tools described in this special issue. Progress and interest in plant genomics have been accelerating since the time in late 2000 when the genome of Arabidopsis thaliana was published. Since then many genome sequencing projects have been undertaken that include poplar (Populus), grape (Vitis), the moss Physcomitrella, the biflagellate algae Chlamydomonas and several globally crucial crop plants such as corn (Maize) and rice (Oryza). However, as we have witnessed on numerous occasions, determining the sequence of a genome is only the first step toward understanding genome organization, gene structure, gene expression patterns, disease pathogenesis and a host of other features of both scientific and commercial interests. Computational tools of genomic annotation and comparative genomics must be applied to gain a useful understanding of any genome. In this special issue we present a collection of papers that together describe a powerful and impactful toolbox of applications and resources for plant genomic analysis. Among those articles you will find a description of research performed by the Mexican headquartered Generation Challenge Programme (GCP) which led to the GCP Platform (Bruskiewich et al.). This research support tool supports a number of data formats and web services and provides access to high performance computing facilities and platform-specific middleware collectively designed to support crop science research. Probably one of the most promising empirical tools for investigating gene expression developed in the last 15 or so years is that of microarray technology. While the technology has become commonplace, with tools for generating and hybridizing arrays available to all, the analysis of microarray-derived data has been challenging. Many laboratories have struggled not only with this challenge but also with the task of sorting through the plethora of analytical tools available in an effort to find the ones that may be best suited to their own work. In this issue there are two reviews by Page and Coulibaly which examine and describe bioinformatics tools for inferring functional information from plant microarray data. Together these papers step the reader through a collection of tools, and their applications, for analyzing the expression of single and multiple gene expression profiles. This theme of microarray analysis is continued in the description of the cross chip probe matching tool (CCPMT) by Page et al. Indeed it expands the readers horizons beyond the analysis of individual microarrays with the ability to associate probes across species. And of course, microarray analysis is facilitated by careful experimental design from the start so Robert Tempelman provides a review of statistical methods used to design efficient two-color microarray experiments. Taken together, these microarray papers provide an overview of the design of microarray experiments and the interpretation of the complex results of those experiments that will be informative for new and experienced laboratorians alike. Several other novel tools are described herein. One, Blast2GO is a suite of tools for the analysis and functional annotation of plant genomes (Conesa and Goetz). It provides an intuitive interface for identifying functional regions within DNA sequences. Another sequence analysis tool described by da Maia et al. is the SSR locator. That tool enables researchers to identify suitable targets for binding PCR primers in order to ensure that those targets are unique within the genome. It also assists with primer design and has a PCR simulator which facilitates comparisons of hypothetical amplification products among different species. Another challenge facing scientists today is the need to stay abreast of advances in a field that is progressing rapidly as a consequence of newly available technologies. In order to address this challenge there are two review articles that together provide insights into the discovery of relationships among a varied array of plant species. The first article, by Abdurakhmonov and Abdukarimov, describes the application of association mapping to understanding traits in crop species. Their work is directed toward novices within the crop breeding community in order to expose them to potential problems that they may face and solutions they may employ to overcome those problems. The second article describes the tools available for phylogenetic analyses and the increased use of Bayesian methods in those tools (Aris-Brosou and Xia). Constructing phylogenies has traditionally been a challenge to even the most experienced researcher but modern bioinformatics tools are lowering the bar for those interested in detecting adaptive evolution and estimating divergence among species. The wealth of information available to researchers today can be overwhelming. In order to address this potential, two papers describe information resources which consolidate and organize related information. PPNEMA is a database resource for those interested in plant-parasitic nematode ribosomal genes (Rubino et al.). That resource allows the user to browse, search and generally explore phytoparasite ribosomal DNA. A second database described in these pages is the MaizeGDB (Lawrence et al.). This resource contains information about Zea mays which includes genomic sequences as well as functional information and the tools to explore both. The body of the papers in this special issue represents the leading edge of plant genomics research. Together they provide the reader with descriptions of the tools and resources necessary to understand and promote advances in this important field. Gary R. Skuse Chunguang Du