Mapping the Neural Substrates of Behavior.

Assigning behavioral functions to neural structures has long been a central goal in neuroscience and is a necessary first step toward a circuit-level understanding of how the brain generates behavior. Here, we map the neural substrates of locomotion and social behaviors for Drosophila melanogaster using automated machine-vision and machine-learning techniques. From videos of 400,000 flies, we quantified the behavioral effects of activating 2,204 genetically targeted populations of neurons. We combined a novel quantification of anatomy with our behavioral analysis to create brain-behavior correlation maps, which are shared as browsable web pages and interactive software. Based on these maps, we generated hypotheses of regions of the brain causally related to sensory processing, locomotor control, courtship, aggression, and sleep. Our maps directly specify genetic tools to target these regions, which we used to identify a small population of neurons with a role in the control of walking.

Synaptic circuits and their variations within different columns in the visual system of Drosophila.

We reconstructed the synaptic circuits of seven columns in the second neuropil or medulla behind the fly's compound eye. These neurons embody some of the most stereotyped circuits in one of the most miniaturized of animal brains. The reconstructions allow us, for the first time to our knowledge, to study variations between circuits in the medulla's neighboring columns. This variation in the number of synapses and the types of their synaptic partners has previously been little addressed because methods that visualize multiple circuits have not resolved detailed connections, and existing connectomic studies, which can see such connections, have not so far examined multiple reconstructions of the same circuit. Here, we address the omission by comparing the circuits common to all seven columns to assess variation in their connection strengths and the resultant rates of several different and distinct types of connection error. Error rates reveal that, overall, <1% of contacts are not part of a consensus circuit, and we classify those contacts that supplement (E+) or are missing from it (E-). Autapses, in which the same cell is both presynaptic and postsynaptic at the same synapse, are occasionally seen; two cells in particular, Dm9 and Mi1, form ≥ 20-fold more autapses than do other neurons. These results delimit the accuracy of developmental events that establish and normally maintain synaptic circuits with such precision, and thereby address the operation of such circuits. They also establish a precedent for error rates that will be required in the new science of connectomics.

neuPrint: An open access tool for EM connectomics.

Due to advances in electron microscopy and deep learning, it is now practical to reconstruct a connectome, a description of neurons and the chemical synapses between them, for significant volumes of neural tissue. Smaller past reconstructions were primarily used by domain experts, could be handled by downloading data, and performance was not a serious problem. But new and much larger reconstructions upend these assumptions. These networks now contain tens of thousands of neurons and tens of millions of connections, with yet larger reconstructions pending, and are of interest to a large community of non-specialists. Allowing other scientists to make use of this data needs more than publication-it requires new tools that are publicly available, easy to use, and efficiently handle large data. We introduce neuPrint to address these data analysis challenges. Neuprint contains two major components-a web interface and programmer APIs. The web interface is designed to allow any scientist worldwide, using only a browser, to quickly ask and answer typical biological queries about a connectome. The neuPrint APIs allow more computer-savvy scientists to make more complex or higher volume queries. NeuPrint also provides features for assessing reconstruction quality. Internally, neuPrint organizes connectome data as a graph stored in a neo4j database. This gives high performance for typical queries, provides access though a public and well documented query language Cypher, and will extend well to future larger connectomics databases. Our experience is also an experiment in open science. We find a significant fraction of the readers of the article proceed to examine the data directly. In our case preprints worked exactly as intended, with data inquiries and PDF downloads starting immediately after pre-print publication, and little affected by formal publication later. From this we deduce that many readers are more interested in our data than in our analysis of our data, suggesting that data-only papers can be well appreciated and that public data release can speed up the propagation of scientific results by many months. We also find that providing, and keeping, the data available for online access imposes substantial additional costs to connectomics research.

A connectome and analysis of the adult Drosophila central brain.

The neural circuits responsible for animal behavior remain largely unknown. We summarize new methods and present the circuitry of a large fraction of the brain of the fruit fly Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, segment, find synapses in, and proofread such large data sets. We define cell types, refine computational compartments, and provide an exhaustive atlas of cell examples and types, many of them novel. We provide detailed circuits consisting of neurons and their chemical synapses for most of the central brain. We make the data public and simplify access, reducing the effort needed to answer circuit questions, and provide procedures linking the neurons defined by our analysis with genetic reagents. Biologically, we examine distributions of connection strengths, neural motifs on different scales, electrical consequences of compartmentalization, and evidence that maximizing packing density is an important criterion in the evolution of the fly's brain.

Animal brains of all sizes, from the smallest to the largest, work in broadly similar ways. Studying the brain of any one animal in depth can thus reveal the general principles behind the workings of all brains. The fruit fly Drosophila is a popular choice for such research. With about 100,000 neurons ­ compared to some 86 billion in humans ­ the fly brain is small enough to study at the level of individual cells. But it nevertheless supports a range of complex behaviors, including navigation, courtship and learning. Thanks to decades of research, scientists now have a good understanding of which parts of the fruit fly brain support particular behaviors. But exactly how they do this is often unclear. This is because previous studies showing the connections between cells only covered small areas of the brain. This is like trying to understand a novel when all you can see is a few isolated paragraphs. To solve this problem, Scheffer, Xu, Januszewski, Lu, Takemura, Hayworth, Huang, Shinomiya et al. prepared the first complete map of the entire central region of the fruit fly brain. The central brain consists of approximately 25,000 neurons and around 20 million connections. To prepare the map ­ or connectome ­ the brain was cut into very thin 8nm slices and photographed with an electron microscope. A three-dimensional map of the neurons and connections in the brain was then reconstructed from these images using machine learning algorithms. Finally, Scheffer et al. used the new connectome to obtain further insights into the circuits that support specific fruit fly behaviors. The central brain connectome is freely available online for anyone to access. When used in combination with existing methods, the map will make it easier to understand how the fly brain works, and how and why it can fail to work correctly. Many of these findings will likely apply to larger brains, including our own. In the long run, studying the fly connectome may therefore lead to a better understanding of the human brain and its disorders. Performing a similar analysis on the brain of a small mammal, by scaling up the methods here, will be a likely next step along this path.

Genome sequence of the dissimilatory metal ion-reducing bacterium Shewanella oneidensis.

Shewanella oneidensis is an important model organism for bioremediation studies because of its diverse respiratory capabilities, conferred in part by multicomponent, branched electron transport systems. Here we report the sequencing of the S. oneidensis genome, which consists of a 4,969,803-base pair circular chromosome with 4,758 predicted protein-encoding open reading frames (CDS) and a 161,613-base pair plasmid with 173 CDSs. We identified the first Shewanella lambda-like phage, providing a potential tool for further genome engineering. Genome analysis revealed 39 c-type cytochromes, including 32 previously unidentified in S. oneidensis, and a novel periplasmic [Fe] hydrogenase, which are integral members of the electron transport system. This genome sequence represents a critical step in the elucidation of the pathways for reduction (and bioremediation) of pollutants such as uranium (U) and chromium (Cr), and offers a starting point for defining this organism's complex electron transport systems and metal ion-reducing capabilities.

A connectome of a learning and memory center in the adult Drosophila brain.

Understanding memory formation, storage and retrieval requires knowledge of the underlying neuronal circuits. In Drosophila, the mushroom body (MB) is the major site of associative learning. We reconstructed the morphologies and synaptic connections of all 983 neurons within the three functional units, or compartments, that compose the adult MB's α lobe, using a dataset of isotropic 8 nm voxels collected by focused ion-beam milling scanning electron microscopy. We found that Kenyon cells (KCs), whose sparse activity encodes sensory information, each make multiple en passant synapses to MB output neurons (MBONs) in each compartment. Some MBONs have inputs from all KCs, while others differentially sample sensory modalities. Only 6% of KC>MBON synapses receive a direct synapse from a dopaminergic neuron (DAN). We identified two unanticipated classes of synapses, KC>DAN and DAN>MBON. DAN activation produces a slow depolarization of the MBON in these DAN>MBON synapses and can weaken memory recall.

The sequence and analysis of Trypanosoma brucei chromosome II.

We report here the sequence of chromosome II from Trypanosoma brucei, the causative agent of African sleeping sickness. The 1.2-Mb pairs encode about 470 predicted genes organised in 17 directional clusters on either strand, the largest cluster of which has 92 genes lined up over a 284-kb region. An analysis of the GC skew reveals strand compositional asymmetries that coincide with the distribution of protein-coding genes, suggesting these asymmetries may be the result of transcription-coupled repair on coding versus non-coding strand. A 5-cM genetic map of the chromosome reveals recombinational 'hot' and 'cold' regions, the latter of which is predicted to include the putative centromere. One end of the chromosome consists of a 250-kb region almost exclusively composed of RHS (pseudo)genes that belong to a newly characterised multigene family containing a hot spot of insertion for retroelements. Interspersed with the RHS genes are a few copies of truncated RNA polymerase pseudogenes as well as expression site associated (pseudo)genes (ESAGs) 3 and 4, and 76 bp repeats. These features are reminiscent of a vestigial variant surface glycoprotein (VSG) gene expression site. The other end of the chromosome contains a 30-kb array of VSG genes, the majority of which are pseudogenes, suggesting that this region may be a site for modular de novo construction of VSG gene diversity during transposition/gene conversion events.

GeneLink: a database to facilitate genetic studies of complex traits.

BACKGROUND: In contrast to gene-mapping studies of simple Mendelian disorders, genetic analyses of complex traits are far more challenging, and high quality data management systems are often critical to the success of these projects. To minimize the difficulties inherent in complex trait studies, we have developed GeneLink, a Web-accessible, password-protected Sybase database. RESULTS: GeneLink is a powerful tool for complex trait mapping, enabling genotypic data to be easily merged with pedigree and extensive phenotypic data. Specifically designed to facilitate large-scale (multi-center) genetic linkage or association studies, GeneLink securely and efficiently handles large amounts of data and provides additional features to facilitate data analysis by existing software packages and quality control. These include the ability to download chromosome-specific data files containing marker data in map order in various formats appropriate for downstream analyses (e.g., GAS and LINKAGE). Furthermore, an unlimited number of phenotypes (either qualitative or quantitative) can be stored and analyzed. Finally, GeneLink generates several quality assurance reports, including genotyping success rates of specified DNA samples or success and heterozygosity rates for specified markers. CONCLUSIONS: GeneLink has already proven an invaluable tool for complex trait mapping studies and is discussed primarily in the context of our large, multi-center study of hereditary prostate cancer (HPC). GeneLink is freely available at http://research.nhgri.nih.gov/genelink.

The ENCODEdb portal: simplified access to ENCODE Consortium data.

The Encyclopedia of DNA Elements (ENCODE) project aims to identify and characterize all functional elements in a representative chromosomal sample comprising 1% of the human genome. Data generated by members of The ENCODE Project Consortium are housed in a number of public databases, such as the UCSC Genome Browser, NCBI's Gene Expression Omnibus (GEO), and EBI's ArrayExpress. As such, it is often difficult for biologists to gather all of the ENCODE data from a particular genomic region of interest and integrate them with relevant information found in other public databases. The ENCODEdb portal was developed to address this problem. ENCODEdb provides a unified, single point-of-access to data generated by the ENCODE Consortium, as well as to data from other source databases that lie within ENCODE regions; this provides the user a complete view of all known data in a particular region of interest. ENCODEdb Genomic Context searches allow for the retrieval of information on functional elements annotated within ENCODE regions, including mRNA, EST, and STS sequences; single nucleotide polymorphisms, and UniGene clusters. Information is also retrieved from GEO, OMIM, and major genome sequence browsers. ENCODEdb Consortium Data searches allow users to perform compound queries on array-based ENCODE data available both from GEO and from the UCSC Genome Browser. Results are retrieved from a specific genomic area of interest and can be further manipulated in a variety of contexts, including the UCSC Genome Browser and the Galaxy large-scale genome analysis platform. The ENCODEdb portal is freely accessible at http://research.nhgri.nih.gov/ENCODEdb.

Informatic and genomic analysis of melanocyte cDNA libraries as a resource for the study of melanocyte development and function.

As part of the RIKEN mouse encyclopedia project, two cDNA libraries were prepared from melanocyte-derived cell lines, using techniques of full-length clone selection and subtraction/normalization to enrich for rare transcripts. End sequencing showed that these libraries display over 83% complete coding sequence at the 5' end and 96-97% complete coding sequence at the 3' end. Evaluation of the libraries, derived from B16F10Y tumor cells and melan-c cells, revealed that they contain clones for a majority of the genes previously demonstrated to function in melanocyte biology. Analysis of genomic locations for transcripts revealed that the distribution of melanocyte genes is non-random throughout the genome. Three genomic regions identified that showed significant clustering of melanocyte-expressed genes contain one or more genes previously shown to regulate melanocyte development or function. A catalog of genes expressed in these libraries is presented, providing a valuable resource of cDNA clones and sequence information that can be used for identification of new genes important for melanocyte development, function, and disease.

Comparative genome sequencing for discovery of novel polymorphisms in Bacillus anthracis.

Comparison of the whole-genome sequence of Bacillus anthracis isolated from a victim of a recent bioterrorist anthrax attack with a reference reveals 60 new markers that include single nucleotide polymorphisms (SNPs), inserted or deleted sequences, and tandem repeats. Genome comparison detected four high-quality SNPs between the two sequenced B. anthracis chromosomes and seven differences among different preparations of the reference genome. These markers have been tested on a collection of anthrax isolates and were found to divide these samples into distinct families. These results demonstrate that genome-based analysis of microbial pathogens will provide a powerful new tool for investigation of infectious disease outbreaks.

Short interfering RNAs can induce unexpected and divergent changes in the levels of untargeted proteins in mammalian cells.

RNA interference (RNAi) mediated by short interfering RNAs (siRNAs) is a widely used method to analyze gene function. To use RNAi knockdown accurately to infer gene function, it is essential to determine the specificity of siRNA-mediated RNAi. We have assessed the specificity of 10 different siRNAs corresponding to the MEN1 gene by examining the expression of two additional genes, TP53 (p53) and CDKN1A (p21), which are considered functionally unrelated to menin but are sensitive markers of cell state. MEN1 RNA and corresponding protein levels were all reduced after siRNA transfection of HeLa cells, although the degree of inhibition mediated by individual siRNAs varied. Unexpectedly, we observed dramatic and significant changes in protein levels of p53 and p21 that were unrelated to silencing of the target gene. The modulations in p53 and p21 levels were not abolished on titration of the siRNAs, and similar results were obtained in three other cell lines; in none of the cell lines tested did we see an effect on the protein levels of actin. These data suggest that siRNAs can induce nonspecific effects on protein levels that are siRNA sequence dependent but that these effects may be difficult to detect until genes central to a pivotal cellular response, such as p53 and p21, are studied. We find no evidence that activation of the double-stranded RNA-triggered IFN-associated antiviral pathways accounts for these effects, but we speculate that partial complementary sequence matches to off-target genes may result in a micro-RNA-like inhibition of translation.

The Brucella suis genome reveals fundamental similarities between animal and plant pathogens and symbionts.

The 3.31-Mb genome sequence of the intracellular pathogen and potential bioterrorism agent, Brucella suis, was determined. Comparison of B. suis with Brucella melitensis has defined a finite set of differences that could be responsible for the differences in virulence and host preference between these organisms, and indicates that phage have played a significant role in their divergence. Analysis of the B. suis genome reveals transport and metabolic capabilities akin to soil/plant-associated bacteria. Extensive gene synteny between B. suis chromosome 1 and the genome of the plant symbiont Mesorhizobium loti emphasizes the similarity between this animal pathogen and plant pathogens and symbionts. A limited repertoire of genes homologous to known bacterial virulence factors were identified.

The complete genome sequence of Chlorobium tepidum TLS, a photosynthetic, anaerobic, green-sulfur bacterium.

The complete genome of the green-sulfur eubacterium Chlorobium tepidum TLS was determined to be a single circular chromosome of 2,154,946 bp. This represents the first genome sequence from the phylum Chlorobia, whose members perform anoxygenic photosynthesis by the reductive tricarboxylic acid cycle. Genome comparisons have identified genes in C. tepidum that are highly conserved among photosynthetic species. Many of these have no assigned function and may play novel roles in photosynthesis or photobiology. Phylogenomic analysis reveals likely duplications of genes involved in biosynthetic pathways for photosynthesis and the metabolism of sulfur and nitrogen as well as strong similarities between metabolic processes in C. tepidum and many Archaeal species.

The genome of M. acetivorans reveals extensive metabolic and physiological diversity.

Methanogenesis, the biological production of methane, plays a pivotal role in the global carbon cycle and contributes significantly to global warming. The majority of methane in nature is derived from acetate. Here we report the complete genome sequence of an acetate-utilizing methanogen, Methanosarcina acetivorans C2A. Methanosarcineae are the most metabolically diverse methanogens, thrive in a broad range of environments, and are unique among the Archaea in forming complex multicellular structures. This diversity is reflected in the genome of M. acetivorans. At 5,751,492 base pairs it is by far the largest known archaeal genome. The 4524 open reading frames code for a strikingly wide and unanticipated variety of metabolic and cellular capabilities. The presence of novel methyltransferases indicates the likelihood of undiscovered natural energy sources for methanogenesis, whereas the presence of single-subunit carbon monoxide dehydrogenases raises the possibility of nonmethanogenic growth. Although motility has not been observed in any Methanosarcineae, a flagellin gene cluster and two complete chemotaxis gene clusters were identified. The availability of genetic methods, coupled with its physiological and metabolic diversity, makes M. acetivorans a powerful model organism for the study of archaeal biology. [Sequence, data, annotations and analyses are available at http://www-genome.wi.mit.edu/.]