Demonstration of targeted crossovers in hybrid maize using CRISPR technology.

Naturally occurring chromosomal crossovers (CO) during meiosis are a key driver of genetic diversity. The ability to target CO at specific allelic loci in hybrid plants would provide an advantage to the plant breeding process by facilitating trait introgression, and potentially increasing the rate of genetic gain. We present the first demonstration of targeted CO in hybrid maize utilizing the CRISPR Cas12a system. Our experiments showed that stable and heritable targeted CO can be produced in F1 somatic cells using Cas12a at a significantly higher rate than the natural CO in the same interval. Molecular characterization of the recombinant plants demonstrated that the targeted CO were driven by the non-homologous end joining (NHEJ) or HDR repair pathways, presumably during the mitotic cell cycle. These results are a step towards the use of RNA-guided nuclease technology to simplify the creation of targeted genome combinations in progeny and accelerate breeding.

The Structural Biology Knowledgebase: a portal to protein structures, sequences, functions, and methods.

The Protein Structure Initiative's Structural Biology Knowledgebase (SBKB, URL: http://sbkb.org ) is an open web resource designed to turn the products of the structural genomics and structural biology efforts into knowledge that can be used by the biological community to understand living systems and disease. Here we will present examples on how to use the SBKB to enable biological research. For example, a protein sequence or Protein Data Bank (PDB) structure ID search will provide a list of related protein structures in the PDB, associated biological descriptions (annotations), homology models, structural genomics protein target status, experimental protocols, and the ability to order available DNA clones from the PSI:Biology-Materials Repository. A text search will find publication and technology reports resulting from the PSI's high-throughput research efforts. Web tools that aid in research, including a system that accepts protein structure requests from the community, will also be described. Created in collaboration with the Nature Publishing Group, the Structural Biology Knowledgebase monthly update also provides a research library, editorials about new research advances, news, and an events calendar to present a broader view of structural genomics and structural biology.

PSI-2: structural genomics to cover protein domain family space.

One major objective of structural genomics efforts, including the NIH-funded Protein Structure Initiative (PSI), has been to increase the structural coverage of protein sequence space. Here, we present the target selection strategy used during the second phase of PSI (PSI-2). This strategy, jointly devised by the bioinformatics groups associated with the PSI-2 large-scale production centers, targets representatives from large, structurally uncharacterized protein domain families, and from structurally uncharacterized subfamilies in very large and diverse families with incomplete structural coverage. These very large families are extremely diverse both structurally and functionally, and are highly overrepresented in known proteomes. On the basis of several metrics, we then discuss to what extent PSI-2, during its first 3 years, has increased the structural coverage of genomes, and contributed structural and functional novelty. Together, the results presented here suggest that PSI-2 is successfully meeting its objectives and provides useful insights into structural and functional space.

Structural genomics is the largest contributor of novel structural leverage.

The Protein Structural Initiative (PSI) at the US National Institutes of Health (NIH) is funding four large-scale centers for structural genomics (SG). These centers systematically target many large families without structural coverage, as well as very large families with inadequate structural coverage. Here, we report a few simple metrics that demonstrate how successfully these efforts optimize structural coverage: while the PSI-2 (2005-now) contributed more than 8% of all structures deposited into the PDB, it contributed over 20% of all novel structures (i.e. structures for protein sequences with no structural representative in the PDB on the date of deposition). The structural coverage of the protein universe represented by today's UniProt (v12.8) has increased linearly from 1992 to 2008; structural genomics has contributed significantly to the maintenance of this growth rate. Success in increasing novel leverage (defined in Liu et al. in Nat Biotechnol 25:849-851, 2007) has resulted from systematic targeting of large families. PSI's per structure contribution to novel leverage was over 4-fold higher than that for non-PSI structural biology efforts during the past 8 years. If the success of the PSI continues, it may just take another approximately15 years to cover most sequences in the current UniProt database.

The protein structure initiative structural genomics knowledgebase.

The Protein Structure Initiative Structural Genomics Knowledgebase (PSI SGKB, http://kb.psi-structuralgenomics.org) has been created to turn the products of the PSI structural genomics effort into knowledge that can be used by the biological research community to understand living systems and disease. This resource provides central access to structures in the Protein Data Bank (PDB), along with functional annotations, associated homology models, worldwide protein target tracking information, available protocols and the potential to obtain DNA materials for many of the targets. It also offers the ability to search all of the structural and methodological publications and the innovative technologies that were catalyzed by the PSI's high-throughput research efforts. In collaboration with the Nature Publishing Group, the PSI SGKB provides a research library, editorials about new research advances, news and an events calendar to present a broader view of structural biology and structural genomics. By making these resources freely available, the PSI SGKB serves as a bridge to connect the structural biology and the greater biomedical communities.

The RCSB PDB information portal for structural genomics.

The RCSB Protein Data Bank (PDB) offers online tools, summary reports and target information related to the worldwide structural genomics initiatives from its portal at http://sg.pdb.org. There are currently three components to this site: Structural Genomics Initiatives contains information and links on each structural genomics site, including progress reports, target lists, target status, targets in the PDB and level of sequence redundancy; Targets provides combined target information, protocols and other data associated with protein structure determination; and Structures offers an assessment of the progress of structural genomics based on the functional coverage of the human genome by PDB structures, structural genomics targets and homology models. Functional coverage can be examined according to enzyme classification, gene ontology (biological process, cell component and molecular function) and disease.

Genome-wide patterns of carbon and nitrogen regulation of gene expression validate the combined carbon and nitrogen (CN)-signaling hypothesis in plants.

BACKGROUND: Carbon and nitrogen are two signals that influence plant growth and development. It is known that carbon- and nitrogen-signaling pathways influence one another to affect gene expression, but little is known about which genes are regulated by interactions between carbon and nitrogen signaling or the mechanisms by which the different pathways interact. RESULTS: Microarray analysis was used to study global changes in mRNA levels due to carbon and nitrogen in Arabidopsis thaliana. An informatic analysis using InterAct Class enabled us to classify genes on the basis of their responses to carbon or nitrogen treatments. This analysis provides in vivo evidence supporting the hypothesis that plants have a carbon/nitrogen (CN)-sensing/regulatory mechanism, as we have identified over 300 genes whose response to combined CN treatment is different from that expected from expression values due to carbon and nitrogen treatments separately. Metabolism, energy and protein synthesis were found to be significantly affected by interactions between carbon and nitrogen signaling. Identified putative cis-acting regulatory elements involved in mediating CN-responsive gene expression suggest multiple mechanisms for CN responsiveness. One mechanism invokes the existence of a single CN-responsive cis element, while another invokes the existence of cis elements that promote nitrogen-responsive gene expression only when present in combination with a carbon-responsive cis element. CONCLUSION: This study has allowed us to identify genes and processes regulated by interactions between carbon and nitrogen signaling and take a first step in uncovering how carbon- and nitrogen-signaling pathways interact to regulate transcription.

A combined computational-experimental approach predicts human microRNA targets.

A new paradigm of gene expression regulation has emerged recently with the discovery of microRNAs (miRNAs). Most, if not all, miRNAs are thought to control gene expression, mostly by base pairing with miRNA-recognition elements (MREs) found in their messenger RNA (mRNA) targets. Although a large number of human miRNAs have been reported, many of their mRNA targets remain unknown. Here we used a combined bioinformatics and experimental approach to identify important rules governing miRNA-MRE recognition that allow prediction of human miRNA targets. We describe a computational program, "DIANA-microT", that identifies mRNA targets for animal miRNAs and predicts mRNA targets, bearing single MREs, for human and mouse miRNAs.

Genome-wide investigation of light and carbon signaling interactions in Arabidopsis.

BACKGROUND: Light and carbon are two essential signals influencing plant growth and development. Little is known about how carbon and light signaling pathways intersect or influence one another to affect gene expression. RESULTS: Microarrays are used to investigate carbon and light signaling interactions at a genome-wide level in Arabidopsis thaliana. A classification system, 'InterAct Class', is used to classify genes on the basis of their expression profiles. InterAct classes and the genes within them are placed into theoretical models describing interactions between carbon and light signaling. Within InterAct classes there are genes regulated by carbon (201 genes), light (77 genes) or through carbon and light interactions (1,247 genes). We determined whether genes involved in specific biological processes are over-represented in the population of genes regulated by carbon and/or light signaling. Of 29 primary functional categories identified by the Munich Information Center for Protein Sequences, five show over-representation of genes regulated by carbon and/or light. Metabolism has the highest representation of genes regulated by carbon and light interactions and includes the secondary functional categories of carbon-containing-compound/carbohydrate metabolism, amino-acid metabolism, lipid metabolism, fatty-acid metabolism and isoprenoid metabolism. Genes that share a similar InterAct class expression profile and are involved in the same biological process are used to identify putative cis elements possibly involved in responses to both carbon and light signals. CONCLUSIONS: The work presented here represents a method to organize and classify microarray datasets, enabling one to investigate signaling interactions and to identify putative cis elements in silico through the analysis of genes that share a similar expression profile and biological function.