abstract: # Background
  .
  Recent developments in high-throughput sequencing (HTS) technologies have made it feasible to sequence the complete transcriptomes of non-model organisms or metatranscriptomes from environmental samples. The challenge after generating hundreds of millions of sequences is to annotate these transcripts and classify the transcripts based on their putative functions. Because many biological scientists lack the knowledge to install Linux-based software packages or maintain databases used for transcript annotation, we developed an automatic annotation tool with an easy-to-use interface.
  .
  # Methods
  .
  To elucidate the potential functions of gene transcripts, we integrated well-established annotation tools: Blast2GO, PRIAM and RPS BLAST in a web-based service, FastAnnotator, which can assign Gene Ontology (GO) terms, Enzyme Commission numbers (EC numbers) and functional domains to query sequences.
  .
  # Results
  .
  Using six transcriptome sequence datasets as examples, we demonstrated the ability of FastAnnotator to assign functional annotations. FastAnnotator annotated 88.1% and 81.3% of the transcripts from the well-studied organisms *Caenorhabditis elegans* and *Streptococcus parasanguinis*, respectively. Furthermore, FastAnnotator annotated 62.9%, 20.4%, 53.1% and 42.0% of the sequences from the transcriptomes of sweet potato, clam, amoeba, and *Trichomonas vaginalis*, respectively, which lack reference genomes. We demonstrated that FastAnnotator can complete the annotation process in a reasonable amount of time and is suitable for the annotation of transcriptomes from model organisms or organisms for which annotated reference genomes are not avaiable.
  .
  # Conclusions
  .
  The sequencing process no longer represents the bottleneck in the study of genomics, and automatic annotation tools have become invaluable as the annotation procedure has become the limiting step. We present FastAnnotator, which was an automated annotation web tool designed to efficiently annotate sequences with their gene functions, enzyme functions or domains. FastAnnotator is useful in transcriptome studies and especially for those focusing on non-model organisms or metatranscriptomes. FastAnnotator does not require local installation and is freely available at <http://fastannotator.cgu.edu.tw>.
author: Ting-Wen Chen; Ruei-Chi Richie Gan; Timothy H Wu; Po-Jung Huang; Cheng-Yang Lee; Yi-Ywan M Chen; Che-Chun Chen; Petrus Tang
date: 2012
institute: 1Molecular Medicine Research Center, Chang Gung University, Taoyuan, Taiwan; 2Bioinformatics Center, Chang Gung University, Taoyuan, Taiwan; 3Department of Biological Science and Technology, National Chiao Tung University, Hsinchu, Taiwan; 4Institute of Biomedical Informatics, National Yang-Ming University, Taipei, Taiwan; 5Graduate Institute of Biomedical Sciences, Chang Gung University, Taoyuan, Taiwan; 6Department of Microbiology and Immunology, Chang Gung University, Taoyuan, Taiwan; 7Department of Aquatic Biosciences, National Chiayi University Chiayi, Taiwan
references:
title: FastAnnotator- an efficient transcript annotation web tool

# Background

As sequencing technologies have improved, transcriptome sequencing (RNA-Seq) or whole-genome sequencing have become faster and cheaper than ever before. In addition, sequencing projects addressing non-model organisms or environmental samples (metagenomics) have now become feasible and affordable. For example, the sequencing of relatively unexplored organisms, such as the human gut microbiome or the transcriptome of clams or butterflies, has been accomplished \[1-3\]. However, sequencing is only the first step in the process of understanding the biology underlying the obtained sequences. Bioinformatics analyses performed after sequencing, including assembly, functional annotation and classification, are becoming increasingly important. Several annotation pipelines have been developed, such as CycADS, PRIAM and Blast2GO \[4-6\], which can provide putative functions for a transcript based on sequence similarity to known genes. Although these tools are useful for understanding the newly explored sequences, they usually contain many manual steps and often are not easy to implement for biologists who are unfamiliar with the command line inputs. Web tools have been developed for the annotation of expressed sequence tags (EST), such as ESTAnnotator, ESTpass, and ESTExplorer \[7-10\]. These pipelines are specifically designed for EST analyses that include the cleaning, assembly and clustering and functional annotation of ESTs. However, we found that the online Uniform Resource Locators (URLs) for ESTpass and ESTAnnotator are no longer functional for ESTpass and ESTAnnotator, and ESTExplorer cannot simultaneously process more than ten thousand contigs. Thus the development of a web server that can provide an automatic annotation pipeline for contigs derived from RNA-Seq data with a user-friendly interface would be beneficial to the research community.

Functional annotation strategies are typically based on previously identified protein functions. Many protein function databases, such as BRENDA, Enzyme and Amigo, have been established as collections based on the functions of enzymes or genes \[11-13\]. These databases categorize protein functions into structured groups as either Enzyme Commission numbers (EC numbers) or Gene Ontology (GO) terms. EC numbers are assigned to enzymes according to the chemical reactions they catalyze \[14\], whereas GO terms include information on the molecular function, cellular component and biological processes of genes and can be used to describe the biological function of proteins \[15\]. These protein function or enzyme function databases document well-studied and well-annotated biological functions and provide resources for the annotation of newly sequenced genes. The majority of established annotation methods utilize these functional annotation systems and transfer functional annotations among sequences based on sequence similarity or pattern searches. For example, the CycADS pipeline integrates multiple annotation tools and databases \[4\]; PRIAM identifies enzyme functions based on profiles constructed from known enzymes \[6\]; and Blast2GO annotates gene functions based on a combinations of various annotation methods \[5\]. The strategy of annotation transfer has been shown to work well and is frequently employed.

Herein, we present an automatic, efficient and easy-to-use web-based annotation tool named FastAnnotator. Given that many tools have been proposed to annotate sequences based on previously established knowledge, we chose to integrate several well-established and popular tools to construct this service. FastAnnotator utilizes Blast2GO and PRIAM to identify GO terms and EC numbers for transcript sequences. Blast2GO has a high annotation accuracy (65-70%) \[16\], and PRIAM provides an enzyme profile database that was updated in October 2011 \[6\]. As certain assembled sequences identified using RNA-Seq may not cover full-length coding regions, we also included a domain search in FastAnnotator. In addition to the possibility of identifying domains based on partial transcript sequences, domain searching also enables FastAnnotator to identify possible functions for sequences that show a significant level of divergence. This feature was included because sequences may evolve to become dissimilar, although the functional domain regions are likely to be conserved through evolution under functional constraints. It has also been shown that proteins having the same domain composition are homologs and likely have the same function \[17-19\]. Therefore, domain annotation in FastAnnotator can not only provide an annotation for a partially sequenced transcript but also improve the annotation performance for sequences that are highly divergent from existing database sequences. This property is particularly useful for metatranscriptomic analyses or samples from organisms that are distantly related to model organisms.

In summary, we have developed the FastAnnotator pipeline to provide automatic annotation of nucleotide sequences via a web interface. Users can begin their annotation by uploading their sequences to the FastAnnotator website. FastAnnotator then assigns possible functions and identified domains in those input query sequences based on sequence similarity and pattern searches. The output of FastAnnotator includes the best hits in the NCBI non-redundant database, GO terms, EC numbers, and domain identities \[20,21\]. Users can explore the output on the website, access other external functional databases (BRENDA, Amigo or Pfam) for detailed functional descriptions and simply download the output for further analysis. As a web service specifically developed for ease-of-use annotations, the use of FastAnnotator does not demand any knowledge of the command line. Moreover, FastAnnotator is free, efficient and user-friendly. Relative to existing annotation pipelines, FastAnnotator is much more convenient because it does not require installation or tedious manual steps and allows the user to analyze a large number of sequences with a single click. FastAnnotator is now available at <http://fastannotator.cgu.edu.tw/>.

# Implementation

## Flowchart of the FastAnnotator pipeline

The annotation process in FastAnnotator consists of four main parts: finding the best hit in the NCBI non-redundant database, assignment of GO terms, identification of enzymes, and identification of domains. The assignment of the GO terms requires the result from LAST searching against the NCBI non-redundant database, and these four main steps can therefore be divided into three independent modules: GO term assignment, enzyme identification, and domain identification (Figure 1). FastAnnotator runs these three steps in parallel to accelerate the annotation procedure and also calculates the basic statistics of the input sequences and provides a statistical report in the results.

## The identification of GO terms

LAST \[22-24\] and Blast2GO (B2G4Pipe) \[5\] were used together to identify GO annotations for the query sequences. We downloaded the non-redundant protein sequences from the NCBI database \[21\] and constructed a local database for Blast2GO. In FastAnnotator, LAST is used to find the similar sequences within the non-redundant protein sequence database. The output of LAST is then transformed into the equivalent BLASTX XML output format, which is the required input file format for Blast2GO. We used the statistical parameters λ and κ provided by the LAST output result to derive the bit score based on the following definition \[25\]:

$$\textsf{S'~=~}\frac{\lambda\;\textsf{S}\;\textsf{~-~}\;\textsf{In}\;\textsf{κ}}{\textsf{In}\;\;\textsf{2}}$$

The alignment result generated by LAST is then used as an input to Blast2GO. The final assignments of GO terms are extracted and presented in a table on the website, which is made available for download.

## The identification of domains

We downloaded the standalone BLAST+ (v2.2.25) program from NCBI \[26\] and used as database the 13,672 domain models (Pfam v26) from the Conserved Domains Database (CDD) \[19,20\]. FastAnnotator applies the rpstblastn to identify domains in the query nucleotide sequences by searching against the preformatted domain database with mostly default parameters except the expectation value (e-value) which is set to be less than 0.01, and the hit aligned length which is longer than 50% of the domain PSSM \[27\]. After the domains of the query sequences are identified, FastAnnotator calculates the length coverage and presents the percentage of coverage for the domain in the report table.

## The identification of EC numbers

FastAnnotator utilizes PRIAM \[6\] to identify potential enzyme functions. PRIAM can detect specific enzymes patterns and annotate these enzymes with EC numbers. The latest version of the enzyme profiles (released on 19 Oct, 2011) was downloaded from the PRIAM website. The nucleotide sequence inputs were translated into protein sequences in six frames using Transeq, a tool a part of the European Molecular Biology Open Software Suite (EMBOSS) \[28\]. These translated protein sequences are then used as inputs to search against the enzyme profile database. FastAnnotator identifies transcripts that may act as enzymes and presents the transcripts together with EC numbers in the output table.

# Results and discussion

The FastAnnotator website allows users to upload *de novo* assembled sequences from RNA-Seq dataset through the upload page (shown in Figure 1). Only FASTA files of less than 100 megabytes are able to be uploaded to the server. After a successful upload, a unique job ID is provided as an identifier to start the annotation pipeline. All annotation results can be inspected over the Internet or downloaded in a compressed file for further analysis. The report consists of five sections. The first section is a histogram of the length distribution of the input sequences as well as a list of other statistics, including the average length, total number of bases, and the N50 value. The second section lists the best hits for all sequences against the NCBI non-redundant database. To avoid overloading the browser, only the top 100 entries are shown on the website results page as a demonstration, although users can download all of the best hits from the download link. The third section contains the results of the functional annotation (GO terms). GO term annotations are grouped according to biological processes, cellular components and molecular functions and are plotted in three separate horizontal bar charts; an example is shown in Figure 2. To better represent the overall distribution of functional annotations, additional spread-out or clustered views are provided based on different filtering level of GO terms. For example, when level 3 is chosen, all annotated GO terms are traced back to the root until reaching the nodes that were 2 edges away from the root (the 3^rd^ node) on the GO acyclic graph. Users can then choose among different level of GO terms to get a better biological interpretation. The fourth section presents the enzyme annotation, which lists all enzyme hits and their corresponding query sequences. The last section contains a list of domain identifications, and again, only 100 entries are shown to avoiding overloading the browser. All of these annotations can be downloaded as a compressed zip file. Annotation results for each job will be retained on the FastAnnotator server for two weeks after the job is finished, and users can retrieve the finished job using the job IDs provided by the server.

To demonstrate the performance and speed of FastAnnotator, we ran it on several transcriptome sequence datasets from different organisms. We were especially interested in how FastAnnotator could assist in the annotation of non-model organisms. The unpublished RNA-Seq dataset from a clam (*Meretrix meretrix*) was used as an example. This transcriptome included 22,129,105 cDNA sequence reads generated using an Illumina Genome Analyzer, and the average read length was 80 base pairs. A reference genome for the clam is currently not available, and thus, the reads were assembled *de novo* into 101,795 contigs using the software package CLC Genomics Workbench (CLC bio, Denmark). Using these contigs as the input, FastAnnotator required approximately 16 hours to finish the annotation. The statistical output showed that the N50 of these contigs was 390 nucleotides and the majority of these assembled contigs (73,878 contigs) ranged from 200-399 base pairs. This large number of short contigs may have resulted from a low level of coverage, and we believe that many of these contigs were actually partial transcript sequences. Of these contigs, 24,919 were found to be similar to sequences in the NCBI non-redundant protein database; 15,112 were assigned at least one Gene Ontology term; 13,015 were found to contain at least one domain; and 585 were assigned an enzyme annotation. Among all of the contigs, 20.4 % of contigs were annotated, and the annotation rate was even higher (26.4%) if we only considered contigs longer than 250 base pairs. These contig annotation rate was slightly higher than that reported in previous studies \[1,29\], the majority of which were based on domain identification. A further comparison of our annotation results with a recently published clam transcriptomic analysis by Huan et al. \[1\] showed that our annotation results for the clam transcriptome were similar.

We were interested in the performance of FastAnnotator for different organisms from different evolutionary lineages. We tested FastAnnotator using six transcriptome datasets, which includes data from plants, invertebrates, protists and prokaryotes (Table 1). All of these transcriptomes were derived from the *de novo* assembly from NGS reads with the exception of the amoeba transcriptome, which was derived from EST data. Reference genomes were available for *C. elegans* and *S. parasanguinis* \[30\], and the highest sequence annotation percentages were obtained for these organisms. Given the high accuracy obtained using Blast2GO, which was used in the FastAnnotator annotation, these annotation results can be considered highly reliable. For the non-model organisms, FastAnnotator was able to annotate approximately half of the input sequences in three out of the four cases. We found the annotation rate was much lower than half in clam transcriptome (20.4%). Meanwhile we found the percentage of annotated contigs in our clam transcriptome was similar to those reported in previous clam studies (12.2% and 20.7% for the clam *M. meretrix* transcriptome and an Agamaki clam EST study, respectively \[1,29\]) and the dataset used here was composed with numerous of partial transcripts. Thus we conclude that FastAnnotator is a suitable annotation tool for non-model organisms.

FastAnnotator results for five different organisms

Organism
# of entries (total base)
Processing time
% of sequences with best hit
% of annotated sequence*

C. elegans+
4,456

(1,339,253)
1.25 h
97.8%
88.1%

Bacteria example+
1,219

(423,067)
21 min
94.7%
81.3%

Plant example+
39,914

(24,168,315)
16 h
77.0%
62.9%

Clam+
101,795

(38,886,727)
15.5 h
24.5%
20.4%

Amoeba EST
13,814

(11,055,101)
3.5 h
68.4%
53.1%

Trichomonas vaginalis+
35,989

(26,716,478)
11 h
93.7%
42.0%

^+^RNA-Seq denovo assembly result

\*Percentages of sequences had been annotated with GO, enzyme or domains.

GO annotation is the most commonly used and well-established functional annotation scheme. To identify GO terms for the input sequences, FastAnnotator incorporates the Blast2GO pipeline, which is one of the most widely used annotation tools and claims to have an annotation accuracy of 65-70% \[16\]. However, we made a small modification to the Blast2GO pipeline by replacing BLASTX with LAST, as LAST is significantly faster and is capable of detecting evolutionarily conserved regions \[23\]. We also used the example file provided by the B2G4Pipe package to benchmark the computation time and comparing output results of BLASTX and LAST on the same machine (IBM X3850 with four Xeon E7540 2.0GHz CPUs and 128G RAM). We found that for this file of 10 nucleotide sequences, BLASTX took 5 times longer to search against the non-redundant database comparing to LAST. The resulting 30 annotations reported by each tool differed in only 2 cases. A closer inspection of the results revealed that the differences were minor and could be explained by the parent and child relationship within the GO acyclic graph. Therefore, we concluded that replacing BLASTX with LAST resulted in a minimal difference in the annotation while providing a substantial improvement in the computational speed.

Regarding the detection of enzymes, FastAnnotator annotates enzyme functions based on the database of 2,844 EC numbers included in the most recent PRIAM release. According to Integrated relational Enzyme database (IntEnz) release 76, there were 4,812 active EC numbers \[30\]. Furthermore, it is well-known that more than one-third of the enzyme activities with EC numbers are so-called orphan enzyme activities, which are not associated with a protein or gene sequences \[32-34\]. Approximately 50% of the orphan enzyme activities are limited to only one species or closely related organisms, which implies that orphan enzyme activities may be limited to certain organisms that remain to be fully explored \[35\]. Due to these limitations, current annotation tools that are based on sequence similarity searches are restricted to detecting only certain enzyme activities. Consequently, FastAnnotator may overlook certain enzyme functional annotations, especially if those functions are restricted to particular organisms. In our clam transcriptome, for example, only 585 contigs were identified as enzymes. Because it has been estimated that approximately 18-29% of genes encode enzymes in eukaryotes \[36\], it is very likely that this level of enzyme annotation was an underestimate, which may have occurred due to the fact that the majority of the contigs are only partial transcripts in our clam example and because the enzyme database used in FastAnnotator was imcomplete. FastAnnotator may provide improved annotations in the future after additional enzyme functions and associated sequences are identified and included in the enzyme databases.

# Conclusions

As sequencing technologies improve and decrease in cost, an increasing number of sequences can be generated. However, the annotation of these sequences, especially for those generated from unfamiliar biological samples, becomes an important issue. In this project, we developed FastAnnotator, an automatic annotation web tool, which integrates several well-developed annotation tools together to provide annotations for query sequences. FastAnnotator allows users to assign protein functions, cellular location, enzyme activity, and function domains to query sequences through an easy-to-use interface. By adopting a different sequence search program, LAST, and including domain identification, it is capable of efficiently annotating sequences and is suitable for annotation of sequences derived from less well-studied organisms or environmental samples. In summary, we present a web-based annotation tool, FastAnnotator, which should be helpful in transcriptome studies, particularly metatranscriptome or non-model organism studies.

# Availability and requirements

Project name: FastAnnotator

Project home page: <http://fastannotator.cgu.edu.tw>

Hardware specifications: IBM X3850 with four Xeon E7540 2.0GHz CPUs and 128G RAM

Operating system(s): CentOS Release 5.7 with Linux kernel 2.6.18

Programming language: Python and Perl for pipeline building, PHP for website interface.

Browser requirements: The website can be access by popular web browser with Javascript enabled include Mozilla Firefox, Google Chrome and Microsoft Internet Explorer.

# Competing interests

The authors declare that they have no competing interests.

# Authors' contributions

TWC and THW built the pipeline. RCRG designed and constructed the website. TWC and RCRG wrote the manuscript together. PJH and CYL maintain the system. YMC and CCC performed RNA-Seq of *Streptococcus parasanguinis* and clam. PT and CCC supervised and revised the manuscript.

## Acknowledgements

This work is supported by a grant (CMRPD190142) from the Chang Gung Memorial Hospital to PT. We thank Dr. Frith for his useful suggestion on parsing the output data from LAST.

This article has been published as part of *BMC Genomics* Volume 13 Supplement 7, 2012: Eleventh International Conference on Bioinformatics (InCoB2012): Computational Biology. The full contents of the supplement are available online at <http://www.biomedcentral.com/bmcgenomics/supplements/13/S7>.


abstract: A report on the symposium 'Genomic and Proteomic Approaches to Crustacean Biology' held as part of the Society for Integrative and Comparative Biology 2006 Annual Meeting, Orlando, USA, 4-8 January 2006.
author: Timothy S McClintock; Charles D Derby
date: 2006
institute: 1Department of Physiology, Cellular and Molecular Neuroscience of Sensory Systems Training Program, University of Kentucky, Lexington, KY 40536-0298, USA; 2Department of Biology, Brains and Behavior Program, and Center for Behavioral Neuroscience, Georgia State University, Atlanta, GA 30303, USA
title: Shelling out for genomics

Consistent with its goal of integrating diverse fields studying basic and applied problems in biology, the Society for Integrative and Comparative Biology showcased a symposium on the genomics and proteomics of crustaceans at its recent annual meeting. This symposium emphasized the future prospects for crustacean genomics by highlighting two themes - an explosion of sequencing efforts and the implementation of physiological genomics approaches in crustaceans.

# First crustacean genome sequence

Crustaceans comprise a major clade of arthropods, with thousands of extant species (see the Tree of Life web project <http://tolweb.org/tree?group=Arthropoda>). They have significant economic, ecological, and scientific importance, but have received little attention from molecular biologists beyond efforts to assess their phylogenetic relationships. Although the list of available crustacean DNA sequences is growing exponentially, it still numbers less than 100,000 (Figure 1), so there has been little grist for the genomics mill. But this is about to change - and change substantially. John Colbourne (Indiana University, Bloomington, USA), representing the Daphnia Genomics Consortium, reported on the sequencing of the genome of a cladoceran, the water flea *Daphnia pulex*. The selection of *D. pulex* was based on two considerations: genome size and ecology. The vast majority of crustaceans have genomes larger than that of *Homo sapiens* (see <http://www.genomesize.com> for a comparison of sizes), which is a significant source of inertia, but the *D. pulex* genome is only around 200 Mb. Ecologically, *D. pulex* populations show intriguing physiological and anatomical responses to changes in their physical environments such as shifts in pH or introduction of toxic metals, and to changes in predator abundance or type. The assembly and initial annotation of the *D. pulex* genome is expected to be completed by early 2007.

The impact of this genome will be felt far and wide as a lodestone for the comparative genomics of crustaceans and as an important outgroup for genomics studies of other arthropods. It will also invigorate ongoing cDNA sequencing efforts reported at the symposium, all of which are from the Decapoda (lobsters, crabs and shrimp). David Durica (University of Oklahoma, Norman, USA) reported the sequencing of cDNAs from blastema tissue of fiddler crab (*Celuca pugilator*) legs during limb regeneration, thereby identifying genes potentially regulated by ecdysteroids. Thomas Shafer (University of North Carolina, Wilmington, USA) has sequenced cDNAs from epidermis of the blue crab *Callinectes sapidus*. He identified at least 45 cuticular proteins, some predicted to form the flexible arthrodial cuticle in crustacean joints, others to form the calcified cuticle. David Towle (Mt Desert Island Biological Laboratory, Salisbury Cove, USA) reported cDNA sequences from the green shore crab *Carcinus maenas* and the lobster *Homarus americanus* that have helped identify enzymes, ion exchangers and pumps involved in osmoregulation, a significant challenge faced by euryhaline species (that is, species adapted to a wide range of salinity) such as *C. maenas*. cDNAs are also being sequenced from other crustaceans with the aim of producing cDNA microarrays to study gene expression, as discussed later.

A common finding in these projects was that about 50-60% of new crustacean sequences lack a significant match in the public sequence databases. A major contributing factor is certainly the sequencing of ends of cDNAs, such that untranslated regions are over-represented. Another contributing factor may be the dearth of crustacean sequences combined with the large evolutionary distance of crustaceans from species whose genomes have been sequenced (the closest being insects). Plans for additional whole-genome sequencing were discussed informally, with hopes centering on the decapod with the smallest genome, *C. maenas*, and on a second *Daphnia* species.

# Physiological genomics in crustaceans

Physiological ecology is the discipline currently driving crustacean genomics. *Daphnia* species are important indicators of the health of lakes and ponds, so their transcriptional responses to toxins and environmental stresses are of broad interest. Colbourne reported the analysis of cDNA libraries from populations exposed to aquatic stressors such as pH change and heavy-metal pollution as a clone-and-count method of mRNA expression profiling. The results imply that a majority of mRNAs change in abundance in response to most of these stresses - an amazing result given that expression profiling in laboratory model organisms typically detects statistically significant changes in less than 10% of the mRNAs tested. This surprising finding was supported by the report from Jonathon Stillman (San Francisco State University, California, USA) that porcelain crab (*Petrolisthes cinctipes*) cDNA microarrays reveal responses to thermal stress that are just as diverse. That two crustaceans show such broad responses raises questions as to whether environmental stresses have a greater impact in crustaceans than in other animals, whether genetic diversity is a contributing factor, and whether transcriptional regulation is especially sensitive to environmental conditions. Robert Chapman (Hollings Marine Laboratory, Charleston, USA) reported new bioinformatics approaches employing fractal mathematics to analyze microarray data on crustacean responses to environmental stress. This is an intriguing approach in which the global response and its component parts, such as clusters of related mRNAs, might both be apparent in a single integrated analysis.

Nuala O'Leary (Hollings Marine Laboratory, Charleston, USA) is using cDNA microarrays to investigate the effect of viral infections in the Pacific white shrimp (*Litopenaeus vannamei*) hepatopancreas. The transcriptional changes observed may help efforts to ameliorate the effects of infection on shrimp, which constitute 25% of all seafood consumed in the United States. O'Leary also revealed some success in using RNA interference, in the form of double-stranded RNAs to suppress individual mRNA expression, welcome evidence that this potent mechanism of viral defense is present in crustaceans. Even more sophisticated methods of studying gene expression, such as *in vivo* gene targeting and transgene insertion, need to be developed.

One of us (T.M.) reported the use of cDNA microarrays and differential amplification to investigate olfaction in *H. americanus* and the spiny lobster *Panulirus argus*. Specific markers were identified for the olfactory sensory neurons, their glial cells, reactive epithelial cells at sites of proliferation and regeneration, and secretory cells, the latter revealing a new exocrine gland in the olfactory organ, which has been named the aesthetasc tegumental gland. Nora Terwilliger (Oregon Institute of Marine Biology, Charleston, USA) reported analyses of the evolution of arthropod hemocyanins and related genes, including the prediction of hypoxia-response elements in their promoters. Many crustaceans experience fluctuations in oxygen tension, a problem that is exacerbated by human activity.

Don Mykles (Colorado State University, Fort Collins, USA) reported the first use of proteomics in a crustacean (the red land crab *Gecarcinus lateralis*). These experiments targeted the endocrinology of molting and identified numerous proteins, including proteins that bind molt-inhibiting hormone, that are candidates for regulating molting.

None of the crustacean cDNA microarrays described above is yet sufficiently broad in its coverage of the genome and sophisticated enough in its bioinformatics to provide a systems-level view of function - that is, where activated biological processes can be identified via statistically over-represented functional groups among the affected mRNAs. Coulborne reported that coverage of the genome by the *Daphnia* microarray should soon achieve this ideal, however.

Crustaceans are an ancient and highly successful clade whose members have evolved into niches that span vitally important marine and aquatic environments. Crustacean genomics is therefore poised to have a significant impact on our understanding of environmental and physiological ecology. Even though significant technological hurdles remain, this symposium was a justifiable celebration of significant achievement and the dawning of the age of crustacean genomics.

## Figures and Tables


abstract: A report on the Keystone symposium 'Non-coding RNAs' held at Snowbird, Utah, USA, 31 March to 5 April 2012.
author: Ezgi Hacisuleyman; Moran N Cabili; John L Rinn
date: 2012
institute: 1Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA; 2Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA; 3Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA; 4Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
title: A Keystone for ncRNA

Once upon a time RNA fit cleanly into the central dogma as a messenger between DNA and protein. Over the past 50 years, RNA molecules have continually emerged as dynamic and versatile regulators of the genome. Our modern understanding of non-coding RNAs (ncRNAs) may look like an intertwined mess of molecules, but collectively they exhibit architecture and coordination, leading to elegantly choreographed regulation of DNA and protein by RNA. The emerging role of RNA as an orchestrator resonated throughout the inaugural Keystone symposium on ncRNAs, with many examples of long ncRNAs (lncRNAs) having critical roles across numerous biological pathways. After the meeting, it was clear that more surprises would emerge from the 'dark matter' of the genome.

The keynote address by Nick Proudfoot (University of Oxford) set the stage by describing how the most classically studied regions of the genome, such as the β-globin locus, are now emerging as being exquisitely regulated by RNA. Specifically, Proudfoot summarized years of work showing how the act of transcription through non-coding regions, and importantly where transcriptional termination occurs, regulates the epigenetic dynamics of the locus. Intriguingly, convergent transcription by RNA polymerase II (RNA pol II) may serve as a substrate to recruit Dicer and other factors of the RNA interference (RNAi) machinery. Similarly, Robert Martienssen (Cold Spring Harbor Laboratory) presented an interplay between RNA/DNA polymerase activity and RNAi in establishing heterochromatic domains. The dependence on co-transcriptional RNAi allows the release of RNA polymerase and prevents collision with the centromeric DNA replication machinery. Together these studies demonstrate the need for not only identifying lncRNAs involved in epigenetic establishment but also for understanding many simultaneous intertwined layers of regulation.

# The human noncoding transcriptome reveals a map of 'noncodarnia'

Thomas Gingeras (Cold Spring Harbor Laboratory) provided an overview of the complexity of the human transcriptome resulting from the efforts of the ENCODE consortium. The transcriptomic map has gained an unprecedented resolution, revealing that 76% of our genome is transcribed. With an average of approximately eight transcripts per genic region, the wealth of ENCODE has redefined the 'one gene - one function' hypothesis into 'many transcripts - one function', or possibly many. Using complementary datasets and approaches, Piero Carninci and the Riken OMICs Center have provided new insights into lncRNA promoter regulation. By fine mapping of the 5' 7-methyl guanosine caps on RNA, the group have found that 6 to 30% of 5' start sites of mouse and human transcripts initiate within repetitive elements. Remarkably, over 250,000 retrotransposon-derived transcription start sites show tissue- and cell-compartment-specific expression.

Leonard Lipovich (Wayne State University) and colleagues added 6,000 lncRNAs to this catalog by examining unclassified human cDNA clones and their expression profiles to determine whether these lncRNAs contribute to neurological disease phenotypes. They found that certain primate-specific and non-conserved lncRNAs are differentially expressed in brain regions that show high levels of activity. Some of these lncRNAs, antisense to protein-coding genes, can regulate their neighbors' expression. Weaving the intricacy of the transcriptome with the complexity of the mammalian body development and cognition, John Mattick (Garvan Institute of Medical Research) presented examples that emphasized the need to further understand the diversity of lncRNAs. Digging into the depths of the 'dark matter in the genome' using capture enrichment methods revealed not only numerous novel lncRNAs and their isoforms but also isoforms of well-studied protein-coding mRNAs such as p53. Hundreds of lncRNAs were shown to change during stem cell differentiation and to have similar transcript stability to mRNAs, and many are associated with epigenetic complexes, suggesting that this complexity cannot be dismissed *en masse* as transcriptional noise.

# RNA-RNA interactions

An ever emerging theme is the importance of RNA-RNA interactions and gene regulation. Kevin Morris (The Scripps Research Institute) described new findings on lncRNA-directed epigenetic regulation through RNA-RNA interactions. Morris and colleagues observed an antisense transcript from the *PTEN* pseudogene (*PTENpg1* asRNA), which is transcribed in the opposite direction to the previously reported *PTENpg1* sense transcript (which can sequester microRNAs and affects *PTEN* translation rates). The *PTENpg1* asRNA seems to direct transcriptional gene silencing of *PTEN* by interacting with the DNA methyltransferase Dnmt3a and the histone-lysine N-methyltransferase Ezh2 and affecting their localization to the *PTEN* promoter. Moreover, the *PTENpg1* asRNA (containing a poly(A) tail) seems to facilitate the cellular localization of *PTENpg1* sense transcript (lacking a poly(A) tail). Thus, this pseudogene node seems to control *PTEN* at both the translational and the transcriptional level.

# ncRNAs in cellular and developmental biology

David Spector (Cold Spring Harbor Laboratory) and Shinichi Nakagawa (RIKEN Advanced Science Institute) presented a comprehensive investigation of the physiological roles of lncRNAs in mouse model systems. Using knockout mice, Spector and colleagues concluded that the lncRNA Malat1 was physiologically dispensable under laboratory conditions. This lack of phenotype may be attributed to genetic redundancy or stress conditions that were not examined. Indeed, Nakagawa examined the physiological role of the nuclear lncRNA *Neat1* (which is essential for the formation of nuclear structures involved in splicing termed paraspeckles) using knockout mice and observed a phenotype only in adult homozygote females, which became infertile at an earlier age. Seth Blackshaw (John Hopkins University School of Medicine) presented the *Six3OS* RNA as another example of a lncRNA required in developmental processes. Loss and gain of function of *Six3OS*, which is transcribed in the opposite direction from the Six3 transcription factor (TF) mRNA, showed that *Six3OS* regulates retinal cell specification. Several elegant follow-up experiments suggest that *Six3OS* regulates Six3-dependent transcription by recruiting the Polycomb repressive complex 2 (PRC2) to Six3 target genes.

Martin Walsh (Mount Sinai School of Medicine) presented his recent work on the complex interplay between RNA pol II and pol III, whereby RNA pol III can affect transcription by accentuating the function of RNA pol II. Ablation of the components of RNA pol III caused a significant depletion of an enhancer ncRNA in the *Sox2* locus followed by changes in chromatin

signatures. Further analysis of the three-dimensional spacing of RNA pol III sites suggest that RNA pol III-regulated transcription could have a role in chromatin architecture, especially in the context of embryonic stem cell differentiation.

Rachel Duffié (Institut Curie) demonstrated how lncRNAs could control differential methylation patterns and imprinting during germ layer specification. Duffié presented a biallelically expressed lncRNA that was sufficient to induce DNA methylation *in* *cis*. Carla Klattenhoff (Massachusetts Institute of Technology) presented *braveheart*, a lncRNA required for stem cell differentiation into cardiomyocytes. Loss of *braveheart* causes disorganization and lack of beating in myofibrils and shorter sarcomeres. Collectively, these studies demonstrate the importance of lncRNAs in establishing cellular identity.

# RNA and chromatin

The intersection of RNA with chromatin was introduced by the well-studied example of *Xist* by Neil Brockdorff (University of Oxford) and Jeannie Lee (Massachusetts General Hospital). Brockdorff showed that *Xist* RNA associates directly with additional proteins such as heterogeneous nuclear ribonucleoprotein U (hnRNPU) and PRC1. Brockdorff and colleagues have also identified a distinct form of PRC1, in which RING1 and YY1 binding protein (Rybp) replaces the catalytic Cbx subunit and associates with *Xist* RNA, suggesting that in addition to PRC2, hnRNPU and PRC1 are also involved in localizing *Xist* RNA to the inactive X. Lee further elucidated the mechanism by which the *Xist* lncRNA controls the silencing on the inactive X. Allele-specific localization profiles of PRC2 during × inactivation suggest a highly selective localization: first, PRC2 localizes to limited number of nucleation spots and, as *Xist* RNAs spreads *in cis*, PRC2 is recruited to additional sites in a gradient, unlike recruitment on autosomes.

As an attempt to generalize the observation that ncRNAs such as *Xist* bind the PRC2 and recruit it to its target loci, Richard Jenner (University College London) and colleagues observed short RNAs that are transcribed from CpG islands surrounding PRC2-bound promoters. Jenner's group showed that these short RNAs are required for efficient methylation of histone H3 on lysine 27 (H3K27me3) through interaction with a newly characterized amino-terminal domain of Suppressor of zeste 12 (Suz12). Collectively, these studies clearly demonstrate the interplay between DNA, lncRNAs, and proteins to establish proper epigenetic states and cellular physiology.

With the goal of identifying where RNA localizes on chromatin, Matthew Simon (Massachusetts General Hospital) and Jason West (Massachusetts General Hospital) introduced a new method (CHART) to purify regions directly bound by lncRNAs. CHART successfully identified the protein and chromatin targets of the paraspeckle-associated lncRNA *NEAT1* in human cells. Initial analysis of CHART coupled with sequencing revealed the chromosomal binding sites of *NEAT1* and suggested that *NEAT1* facilitates tertiary DNA interactions involved in nuclear architecture.

Deepening our understanding of recruitment of chromatin modifiers by lncRNAs, Howard Chang (Stanford University) and colleagues discovered the lncRNA *HOTTIP*, which activates the expression of its neighboring genes *in cis* by recruiting the activating modifier WDR5. Using crystallography and site-specific mutagenesis, the group identified the RNA-binding domain of WDR5. Moreover, binding to *HOTTIP* regulates the stability of WDR5, suggesting a model in which a RNA-based molecular clock regulates protein complex formation and stability. Similar to *HOTTIP*, Ramin Shiekhattar (Wistar Institute) presented a set of lncRNAs with enhancer-like functions. Shiekhattar described a specific example, in which an lncRNA enhances the expression of genes *in cis* through physical interactions with the Mediator complex. The lncRNA-Mediator interaction facilitates DNA looping to activate distal genes. Together, these suggest that lncRNAs emanating from enhancer regions may have RNA-based functions.

Using a detailed map of large intergenic ncRNAs (lincRNAs), one of us (JR) and colleagues used a computational 'guilt-by-association approach' to identify lincRNAs involved in specific pathways. One such example led to the discovery of a lncRNA, Required for adipogenesis 1 (*RAP1*). *RAP1* contains a striking feature: multiple repetitive exonic sequences that physically associate with hnRNPU. Single-molecule RNA localization methods showed that *RAP1* shows nuclear localization indicative of large chromosomal domains. Using a similar guilt-by-association approach, Keith Vance (University of Oxford) from Chris Ponting's group used computational and evolutionary genomics to identify mouse lincRNAs close to genes encoding developmental TFs. One such lincRNA is *Plinc*, which can act *in cis* to repress its bidirectionally promoted neighbor Pax6, as well as *in trans* to repress other targets involved in cell cycle and synaptic function. *Plinc* is enriched on chromatin and associates with the transcriptional cofactors Kap1 and Erh.

# Non-mammalian ncRNA

ncRNAs also have critical regulatory roles in prokaryotes. Gisela Storz (National Institute of Child Health and Human Development) gave several examples from bacteria, in which small RNAs act in parallel to TFs to fine-tune the TFs' target gene levels through a base-pairing mechanism. In parallel, Jennifer Doudna (University of California, Berkeley) gave new insights into the CRISPR adaptive immune system in bacteria, in which viral DNA segments are integrated within bacterial DNA repeat clusters and are later transcribed to short RNAs that act in a viral defense pathway. Doudna highlighted some similarities between eukaryotic RNAi and prokaryotic CRISPR target recognition mechanisms based on molecular structures of these machineries.

# RNA and disease

Andrew Feinberg (John Hopkins University School of Medicine) presented a comprehensive analysis of the epigenetic changes in cancer. Surveying differential DNA methylation in cancer revealed the loss of DNA methylation of the lncRNA termed *HOTS* (H19 opposite tumor suppressor) encoded antisense to the maternally imprinted *H19* gene, which encodes an untranslated RNA of unknown function. Feinberg described large lamin-associated DNA domains that are also lost in cancer. Similar to *HOTS*, almost all genes have naturally occurring antisense transcripts (NATs) that are ripe for RNA-RNA interactions and are often misregulated in disease states. Claes Wahlestedt (University of Miami) and colleagues have developed single-stranded oligonucleotides termed antagonists of NATs (antagoNATs) that upregulate specific endogenous genes *in vitro* and *in vivo* by interfering with the function of NATs. As NATs are widely expressed, the approach holds promise for potential RNA-based therapeutics. Together these studies highlight the need to understand the link between epigenetic regulation and lncRNAs in the etiology of disease.

# Trans-generational RNA for the future

Paramutation is a form of non-Mendelian heredity in which the phenotypic expression of an allele is mutated while its genotype is intact. The meeting concluded with exciting updates on the current understanding of this phenomenon from worms to mammals. Andrew Spence (University of Toronto) described how a maternal transcript of the sex-determining gene *fem-1* does not require any coding capacity to trigger *fem-1* expression, which it does by preventing RNA-dependent epigenetic silencing of this gene. Oded Rechavi (Columbia University Medical Center) demonstrated how virus-derived small interfering RNAs can be trans-generationally transmitted in a non-Mendelian manner. Finally, Minoo Rassoulzadegan (University of Nice) showed evidence for RNA-induced hereditary transmission of variation affecting the phenotype of three different genes in mouse animals. By electroporating an inducer small RNA homologous to the gene of interest to embryonic stem cells, Rassoulzadegan and colleagues were able to obtain a paramutable effect over many passages in cell culture. Collectively, these studies have provided exciting new evidence for the potential role of RNA in trans-generational inheritance in mammals.

This meeting was a resounding success and clearly demonstrated the versatility, diversity, and importance of ncRNAs in gene regulatory programs. John Mattick ended the meeting with inspiring words, highlighting the imminence of many groundbreaking discoveries to come from the dark matter of the genome. Kevin Morris reinforced the need for a collaborative spirit among the ncRNA community, which will rapidly drive the field to a greater success. One thing was clear: the transcriptome has revealed many mysterious creatures that comprise the mysterious world of 'Noncodarnia'.


date: 2019
title: ADOPTING A HEALTHY LIFESTYLE HELPS REDUCE THE RISK OF DEMENTIA

**14 May 2019** - People can reduce their risk of dementia by getting regular exercise, not smoking, avoiding harmful use of alcohol, controlling their weight, eating a healthy diet, and maintaining healthy blood pressure, cholesterol and blood sugar levels, according to new guidelines issued by the World Health Organization (WHO) today.

"In the next 30 years, the number of people with dementia is expected to triple," said WHO Director-General Dr Tedros Adhanom Ghebreyesus. "We need to do everything we can to reduce our risk of dementia. The scientific evidence gathered for these Guidelines confirm what we have suspected for some time, that what is good for our heart, is also good for our brain."

The Guidelines provide the knowledge base for health-care providers to advise patients on what they can do to help prevent cognitive decline and dementia. They will also be useful for governments, policy-makers and planning authorities to guide them in developing policy and designing programmes that encourage healthy lifestyles.

The reduction of risk factors for dementia is one of several areas of action included in WHO's Global action plan for the public health response to dementia. Other areas include: strengthening information systems for dementia; diagnosis, treatment and care; supporting carers of people with dementia; and research and innovation.

WHO's Global Dementia Observatory, launched in December 2017, is a compilation of information about country activities and resources for dementia, such as national plans, dementia-friendly initiatives, awareness campaigns and facilities for care. Data from 21 countries, including Bangladesh, Chile, France, Japan, Jordan and Togo, have already been included, with a total of 80 countries now engaged in providing data.

Creating national policies and plans for dementia are among WHO's key recommendations for countries in their efforts to manage this growing health challenge. During 2018, WHO provided support to countries such as Bosnia and Herzegovina, Croatia, Qatar, Slovenia and Sri Lanka to help them develop a comprehensive, multi-sectoral public health response to dementia.

An essential element of every national dementia plan is support for carers of people with dementia, said Dr Dévora Kestel, Director of the Department of Mental Health and Substance Abuse at WHO. "Dementia carers are very often family members who need to make considerable adjustments to their family and professional lives to care for their loved ones. This is why WHO created iSupport. iSupport is an online training programme providing carers of people with dementia with advice on overall management of care, dealing with behaviour changes and how to look after their own health."

iSupport is currently being used in eight countries, with more expected to follow.

Dementia: a rapidly growing public health problem

Dementia is an illness characterized by a deterioration in cognitive function beyond what might be expected from normal ageing. It affects memory, thinking, orientation, comprehension, calculation, learning capacity, language and judgement. Dementia results from a variety of diseases and injuries that affect the brain, such as Alzheimer disease or stroke.

Dementia is a rapidly growing public health problem affecting around 50 million people globally. There are nearly 10 million new cases every year. Dementia is a major cause of disability and dependency among older people. Additionally, the disease inflicts a heavy economic burden on societies as a whole, with the costs of caring for people with dementia estimated to rise to US\$ 2 trillion annually by 2030.

Available from: <https://www.who.int/news-room/detail/14-05-2019-adopting-a-healthy-lifestyle-helps-reduce-the-risk-of-dementia>


abstract: A report on the FASEB meeting 'Nuclear Structure and Cancer', Saxtons River, USA, 16-21 June 2007.
author: David M Gilbert; Daniele Zink
date: 2007
institute: 1Department of Biological Science, Florida State University, Tallahassee, FL 32306, USA; 2Ludwig-Maximilians-University Munich, Department of Biology II, Grosshaderner Str., 82152 Planegg-Martinsried, Germany
title: Intranuclear changes in cancer cells

This year's Federation of American Societies for Experimental Biology (FASEB) conference on nuclear structure and cancer opened with keynote speaker Donald Coffey (Johns Hopkins University, Baltimore, USA), who together with Ronald Berezney (University at Buffalo, Buffalo, USA) is credited with the discovery of the nuclear matrix. Coffey pointed out that changes in nuclear structure are diagnostic hallmarks of many cancers that are frequently utilized by the pathologist but are poorly understood from a molecular standpoint. This set the tone for a stimulating meeting, where talks on the fundamental organization of the nucleus were intermingled with reports of direct links to cancer and perspectives from pathologists. There were many interesting talks and here we report a few of the highlights.

# Chromosomal organization and aberrations

How universal are the 'rules' of chromosome organization within the nucleus that are so frequently abrogated in cancer cells? Thomas Cremer (Ludwig-Maximilians-University, Munich, Germany) reported that in rod cells of the retina of nocturnal animals, the heterochromatin is in the center of the nucleus and euchromatin at the periphery, which is the inverse of nearly all other cell types examined to date. He speculates that this arrangement may be less diffractive to light and might, therefore, provide an advantage for nocturnal animals.

Live-cell imaging is now a standard tool in the analysis of nuclear structure and function. Andrew Belmont (University of Illinois, Urbana, USA) addressed the large-scale chromatin organization of actively transcribing genes in somatic diploid nuclei of living cells. In contrast to models proposing the transition from loops of 30-nm chromatin fibers to 10-nm fibers during transcriptional activation, Belmont finds that transcribed chromatin remains several-fold more compact than even the 30-nm fiber. How do transcription factors find their cognate sites in these thick fibers? Gordon Hager (National Cancer Institute, Bethesda, USA) emphasized the highly dynamic nature of transcription factor binding as illustrated by the implication of chromatin remodeling as a key mechanism in nuclear receptor 'hit-and-run'. He described recent work addressing the question of whether chromatin remodeling is always required for interactions of the glucocorticoid receptor (GR) with its binding sites and whether these are always dependent on Brg1, a component of the chromatin-remodeling SWI/SNF complex. Genome-wide analyses revealed that chromatin remodeling takes place at all GR-binding sites, but is not always dependent on Brg1. The results suggest that GR searches chromatin randomly, but that chromatin remodeling distinguishes functional and non-functional interactions. Hager also pointed out that mapping of DNase I hypersensitive sites is an important tool in the identification of functional regulatory sites where chromatin remodeling takes place.

A common characteristic of tumor cells is genomic instability leading to chromosomal aberrations. For example, aggregates of telomeres are frequently observed in the nuclei of tumor cells but not in those of normal cells. Sabine Mai (University of Manitoba, Winnipeg, Canada) reported that expression of the proto-oncogene *c-Myc* leads to the formation of telomeric aggregates and telomeric fusions. She has found that the normal intranuclear positioning of centromeres and chromosomes was disturbed in cells over-expressing c-Myc, and that this was associated with the formation of chromosomal aberrations. These nuclear changes required the Myc box II domain of c-Myc, which associates with the histone acetyltransferase (HAT) Tip60; c-Myc overexpression in combination with Tip60 heterozygosity led to enhanced lymphoma formation in mice. These findings suggest that c-Myc-induced changes in nuclear organization play an important role in the genomic instability associated with tumorigenesis.

Jeffrey Salisbury (Mayo Clinic, Rochester, USA) presented an elegant study on the regulation of centrosome duplication. Centrosome amplification is often observed in tumor cells and can lead to aberrant spindle formation and chromosomal instability. Normally, centrosome duplication is coordinated with the cell cycle. During the cell-cycle arrest that follows DNA damage the protein xeroderma pigmentosum C (XPC) becomes upregulated. XPC binds to centrin 2, which is essential for centrosome duplication, and the complex moves into the nucleus - a movement dependent on the presence of the tumor suppressor protein p53. This depletes the cytoplasmic pool of centrin 2, and the resulting low levels are not sufficient to support centrosome duplication. Salisbury has found that in cells, such as tumor cells, that are defective in p53 function, or following post-transcriptional silencing of XPC, the cytoplasmic pool of centrin 2 remains high enough to support aberrant duplication, resulting in spindle abnormalities and chromosome instability.

The relation between cell-cycle stage and vulnerability to carcinogens was addressed by David Kaufman (University of North Carolina, Chapel Hill, USA), who has shown previously that cells are most susceptible to transformation by chemical carcinogens when treated at the beginning of S phase. He now reported that in two different human cell types (normal fibroblasts and lymphoblastoid cells), genes replicated at the beginning of S phase include the majority of apoptosis genes and Wnt genes, both of which are frequently associated with cancer. This suggests the existence of a class of important cancer-related genes, located on several different chromosomes, which are replicated simultaneously during the cell cycle and are most vulnerable to cancer-causing mutations during replication.

The organization of the sites at which DNA replication and transcription take place within the nucleus and their potential roles in the generation of chromosomal aberrations associated with cancer were addressed in several presentations. James Davie (University of Manitoba, Winnipeg, Canada) outlined work showing that transcription factors Sp1 and Sp3, which are ubiquitously expressed in mammalian cells, form distinct unrelated nuclear foci and associate with histone deacetylase (HDAC) 1 and phosphorylated HDAC2. Using chromatin immunoprecipitation (ChIP), he studied the binding of the estrogen receptor alpha, Sp1 and Sp3 to the estrogen-responsive trefoil factor 1 promoter in MCF-7 breast cancer cells. The findings suggested that Sp1 and Sp3 aid in recruitment of HDACs and HATs. Spectral karyotype analyses revealed high chromosomal instability in MCF-7 cells and Davie pointed out that the question of cell-to-cell variation in the karyotype of cancer cell lines must be carefully addressed when performing ChIP analyses.

The importance of the organization of the transcriptional regulatory machinery in nuclear microenvironments in cancer was underlined by work presented by Gary Stein (University of Massachusetts, Worcester, USA). He reported that the NMTS domain of the Runx transcription factors is necessary and sufficient for subnuclear targeting and trafficking. Perturbations in subnuclear targeting of Runx1 (also known as AML1) are associated with altered competence for myeloid differentiation and with expression of the transformed/leukemia phenotype in myeloid progenitors. Impaired intranuclear trafficking of Runx2 (also known as AML3) in metastatic breast cancer cells interferes with the formation of osteolytic lesions *in vivo*.

Cameron Osborne (Babraham Institute, Cambridge, UK) reported that immediate early genes, including *c-Myc*, are recruited within minutes into transcription factories - complexes of transcribing genes - upon B-cell stimulation. He has found that 25% of transcribing *c-Myc* alleles colocalize with the *IgH* locus. Other active loci did not show a correspondingly high degree of association. Intriguingly, *c-Myc* and *IgH* are the most frequent translocation partners in mouse plasmacytoma and Burkitt's lymphoma, suggesting that intermingling of chromatin from the *c-Myc* and *IgH* loci during co-transcription makes it more likely that these loci will undergo translocations.

# Epigenetic changes in cancer cells

In addition to genetic lesions, cancer cells display characteristic epigenetic changes associated with altered gene-expression patterns, which include CpG island hyper- and hypo-methylation. CpG island hypermethylation leads to epigenetic silencing by recruiting methyl-CpG-binding domain (MBD) family proteins. William Nelson (Sidney Kimmel Comprehensive Cancer Center, Baltimore, USA) reported that hypermethylation leads to epigenetic silencing of the *GSTP1* locus (encoding the π-class glutathione S-transferase) in nearly all prostate cancers, and most breast and liver cancers. High-throughput chemical screening has yielded a number of compounds capable of activating transcription from hypermethylated *GSTP1* promoters, and several of these compounds antagonized the binding of MBDs to methyl-CpG-containing DNA. Nelson described a strategy for characterizing methyl-CpG patterns based on the binding of DNA to the DNA-binding domain of MBD2 and subsequent hybridization to whole-genome tiled arrays. This approach has potential applications in cancer screening, detection, diagnosis and prognosis.

A direct link between oncogene activation and diagnostic nuclear changes in human papillary thyroid carcinoma cells was reported by Andrew Fischer (University of Massachusetts, Worcester, USA). Changes diagnostic of this type of cancer are the dispersal of heterochromatin and irregularity of the nuclear lamina. Activation of either of the tyrosine kinases Ret or Trk is sufficient to induce the diagnostic changes *in vitro*. Fischer reported that dispersal of heterochromatin is associated with a decrease in monomethylation of lysine 4 of histone H3, and that Trk is sufficient to induce this decrease.

Previous work from the laboratory of Donald Tindall (Mayo Clinic, Rochester, USA) showed that the transcriptional co-activator p300 is involved in the progression of prostate cancer. At the meeting, Tindall reported that transfection of p300 into prostate cancer cells induces quantifiable nuclear alterations associated with prostate cancer. Furthermore, he proposed the provocative idea that androgen ablation, a routine treatment for prostate cancer, might initiate an androgen-independent cycle of activity. This suggestion is based on the findings that p300 mediates androgen-independent activation of the androgen receptor and that androgens downregulate p300 in cancer cell lines. Thus, androgen ablation might increase p300 expression in prostate cancer cells, which might initiate aberrant androgen-independent activation of the androgen receptor. Androgen-independent activation of the androgen receptor is usually observed in refractory prostate cancer after androgen-deprivation therapy.

The molecular basis by which alterations in nuclear structure and function lead to cancer is unquestionably an exciting new area for young researchers. Exchange between clinicians and basic researchers in this field is still limited, but is an inevitable prerequisite for investigating and understanding nuclear changes in cancer. This biennial meeting will continue to provide an exceptional forum for such discussions between clinicians, pathologists and basic researchers. The conference also provided a forum for investigators from academia and the biotech and pharmaceutical industries to explore cancer-related changes in the organization and localization of regulatory machinery within the cell nucleus as a platform for new diagnostic and therapeutic strategies.


abstract: The American focus on the sexual purpose of breasts, rather than the physiological function of breasts, has serious public health consequences. Discomfort with breastfeeding in public lowers breastfeeding rates, which in turn negatively affects women's and children's short- and long-term health.
author: Jacqueline H Wolf
date: 2008
institute: 1Department of Social Medicine, College of Osteopathic Medicine, Ohio University, Athens, Ohio, USA
references:
title: Got milk? Not in public!

# Debate

When I was growing up in the 1960s my best friend's father was an obstetrician. This was the heyday of formula feeding and my friend's father, even with his vast experience in women's reproductive health, had virtually no experience with breastfeeding. His expertise continued to be so negligible, in fact, that when my friend nursed her newborn son in front of him in the early 1980s – this is his first grandchild being nursed – he watched for a minute and then he said to his daughter, "That will ruin your breasts, you know." When my friend called to report this comment to me sometime later, she was still bewildered. She asked me: "What does he think breasts are *for*?"

Her story captures the essence of why breastfeeding in public is such a controversial topic in American culture. Americans think breasts are primarily for enhancing sexual activity, which results in widespread discomfort when they are reminded that breasts go into babies' mouths. While *our* culture defines breasts primarily as enhancing sexual appeal, other cultures emphasize the "sexiness," if you will, of *other* body parts: buttocks, hips, shoulders, feet. It varies according to culture, since sexual attractiveness is always culturally defined.

Yet the American obsession with breasts is so unique that it is often puzzling to people from other cultures. One of my graduate students who conducted field work in Samoa reported to me that when she told a Samoan woman that American men like to suck on women's breasts, the Samoan was amazed. She asked my student, apparently with genuine interest and concern, "Do American men like to pretend they're babies?" That is how strictly Samoans define the purpose of women's breasts. In many countries, breastfeeding in public is as mundane an activity as public conversation; no one is concerned when women use their breasts in public for their primary biological function: to feed babies.

My purpose today is not to argue that we should think more like Samoans, but to point out that the American obsession with breasts has consequences most Americans fail to consider: ready access to human milk is vital to babies' short- and long-term health. We are all affected by our culture's sexual emphasis on breasts and our consequent discomfort with breastfeeding in public. While people from other cultures often find this controversy inexplicable, the reasons for the controversy are obvious to Americans – even those of us who fully support breastfeeding in public. We understand that many equate public breastfeeding with lewd behavior. However, equating breastfeeding with vulgarity has dire consequences; this attitude lowers the country's breastfeeding rates which in turn affects women's and children's short and long-term health. If women are made to feel uncomfortable with public breastfeeding, breastfeeding becomes difficult, if not impossible, to sustain. Women who have successfully breastfed for long periods of time know that unless women can feed their babies anytime, anywhere, they're going to end up housebound. And it's the rare American woman who is willing to be housebound for months on end. So, many women give up breastfeeding early on and opt for the bottle.

Here are the statistics: 70% of new mothers initiate breastfeeding. But all initiation means is breastfeeding once before hospital discharge. Of far greater meaning is the breastfeeding exclusivity rate, which is terrible. By the time American babies are six weeks old, 53% of breastfeeding mothers have introduced at least some infant formula to their babies' diet and by six months, 90% \[1\]. Fewer than 18% of mothers who initiate breastfeeding are giving their babies *any breast milk at all* at the end of the minimal year recommended by the American Academy of Pediatrics.

One reason that rates are so high *initially* and then plummet almost immediately when it comes to exclusivity and duration is because most women are *not c*omfortable breastfeeding in public because the public is not comfortable seeing them breastfeed. That is a fundamental problem because human milk is low in fat and it is especially low in protein, much lower, for example, than cows' milk. That means human babies are almost constant feeders by design – which is why women in so many cultures literally wear their babies on their bodies, for easy access so they can feed often. In the U.S., people who oppose breastfeeding in public often argue, "What's the problem? Feed the baby before you leave the house. There's no reason, with a little planning, to breastfeed in a restaurant or at the mall." This insistence that babies should only be breastfed behind closed doors demonstrates a fundamental lack of understanding of both the composition of human milk and babies' needs. Babies have to nurse while they are out and about due to the nature of human milk.

This insistence that babies should only be breastfed behind closed doors exposes our split personality on breastfeeding. We insist breastfeeding is a good thing to do. And, we insist it is an offensive thing to do.

Our squeamishness with breastfeeding in public has consequences we refuse to acknowledge. Hurricane Katrina is a prime example of an unacknowledged consequence of our culture's revulsion at breastfeeding in public. We all watched with horror as New Orleans drowned two years ago. For days, Katrina and its aftermath were the only items in the news. And, whenever there is a news story of that magnitude there are always a lot of sidebars to the story. Remember? Katrina exposed America's class and racial divisions. We heard stories about inefficient government agencies, abandoned pets, lethal mold.

But do you know what story I kept looking for and never found? What happens to formula fed babies during a disaster when mothers cannot buy infant formula and they do not even have access to water? And there was ample opportunity to have a sidebar that pondered those awful questions. Some of the most memorable film clips coming out of New Orleans in 2005 pictured frantic mothers clutching their barely conscious, dehydrated babies.

Discussing our culture's attitude toward breastfeeding in relation to the Katrina disaster would have been a tremendous public service. Think about how much our discomfort with breastfeeding would have been mitigated if one of the Katrina reports contrasted the convenience and dependability of breastfeeding with the difficulty and unreliability of formula feeding. Imagine: images of mothers' breasts saving babies' lives. That would have been a national revelation. We talk about the importance of breastfeeding, yet we're a formula feeding culture. It seemed perfectly natural to all the reporters and much of the viewing audience during Katrina that mothers were hysterical and babies were dehydrated because there was not enough infant formula available. The entire nation seemed to be saying, "Of course that's a consequence of a hurricane." No reporter thought to ask, "Why aren't these women breastfeeding?" No reporter thought to ask, "What roadblocks have we constructed as a nation that would dissuade women from breastfeeding and put their babies through this completely avoidable horror?"

To those of us who work on breastfeeding, the "issue" of breastfeeding in public is a periodic amusing and frustrating annoyance. However, we have to start treating it as more than that. The negative attitude toward public breastfeeding is a cornerstone of low breastfeeding rates and a basis of our persistently formula feeding culture. Aside from all the mothers who quickly learn to use infant formula because they are embarrassed by their hungry babies when there is no private space to breastfeed, women in the U.S. often fail at breastfeeding because they do not have adequate opportunity to observe other women breastfeeding. Breastfeeding is not intuitive, it is a learned behavior. In other words: Breastfeeding in our culture is deemed a private bodily function when – for many reasons, all having to do with infant and maternal health – it *should* be a public one.

# Competing interests

The author declares that they have no competing interests.

### Acknowledgements

"Got milk?" is an American advertising campaign marketing cow's milk.


date: 2009-01
title: Journals under Threat: A Joint Response from History of Science, Technology and Medicine Editors

We live in an age of metrics. All around us, things are being standardized, quantified, measured. Scholars concerned with the work of science and technology must regard this as a fascinating and crucial practical, cultural and intellectual phenomenon. Analysis of the roots and meaning of metrics and metrology has been a preoccupation of much of the best work in our field for the past quarter century at least. As practitioners of the interconnected disciplines that make up the field of science studies we understand how significant, contingent and uncertain can be the process of rendering nature and society in grades, classes and numbers.

We now confront a situation in which our own research work is being subjected to putatively precise accountancy by arbitrary and unaccountable agencies. Some may already be aware of the proposed European Reference Index for the Humanities (ERIH), an initiative originating with the European Science Foundation. The ERIH is an attempt to grade journals in the humanities—including "history and philosophy of science". The initiative proposes a league table of academic journals, with premier, second and third divisions. According to the European Science Foundation, ERIH "aims initially to identify, and gain more visibility for, top-quality European Humanities research published in academic journals in, potentially, all European languages". It is hoped "that ERIH will form the backbone of a fully-fledged research information system for the Humanities". What is meant, however, is that ERIH will provide funding bodies and other agencies in Europe and elsewhere with an allegedly exact measure of research quality. In short, if research is published in a premier league journal it will be recognized as first rate; if it appears somewhere in the lower divisions, it will be rated (and not funded) accordingly.

This initiative is entirely defective in conception and execution. Consider the major issues of accountability and transparency. The process of producing the graded list of journals in science studies was overseen by a committee of four (the membership is currently listed at http://www.esf.org/research-areas/humanities/research-infrastructures-including-erih/erih-governance-and-panels/erih-expert-panels.html). This committee cannot be considered representative. It was not selected in consultation with any of the various disciplinary organizations that currently represent our field such as the European Association for the History of Medicine and Health, the Society for the Social History of Medicine, the British Society for the History of Science, the History of Science Society, the Philosophy of Science Association, the Society for the History of Technology or the Society for Social Studies of Science. Journal editors were only belatedly informed of the process and its relevant criteria or asked to provide any information regarding their publications. No indication has been given of the means through which the list was compiled; nor how it might be maintained in the future.

The ERIH depends on a fundamental misunderstanding of conduct and publication of research in our field, and in the humanities in general. Journals' quality cannot be separated from their contents and their review processes. Great research may be published anywhere and in any language. Truly ground-breaking work may be more likely to appear from marginal, dissident or unexpected sources, rather than from a well-established and entrenched mainstream. Our journals are various, heterogeneous and distinct. Some are aimed at a broad, general and international readership, others are more specialized in their content and implied audience. Their scope and readership say nothing about the quality of their intellectual content. The ERIH, on the other hand, confuses internationality with quality in a way that is particularly prejudicial to specialist and non-English language journals. In a recent report, the British Academy, with judicious understatement, concludes that "the European Reference Index for the Humanities as presently conceived does not represent a reliable way in which metrics of peer-reviewed publications can be constructed" (*Peer Review: the Challenges for the Humanities and Social Sciences*, September 2007: http://www.britac.ac.uk/reports/peer-review). Such exercises as ERIH can become self-fulfilling prophecies. If such measures as ERIH are adopted as metrics by funding and other agencies, then many in our field will conclude that they have little choice other than to limit their publications to journals in the premier division. We will sustain fewer journals, much less diversity and impoverish our discipline.

Along with many others in our field, this Journal has concluded that we want no part of this dangerous and misguided exercise. This joint Editorial is being published in journals across the fields of history of science and science studies as an expression of our collective dissent and our refusal to allow our field to be managed and appraised in this fashion. We, among others, have asked the compilers of the ERIH to remove our journals' titles from their lists.

Hal Cook and Anne Hardy (*Medical History*)

Hanne Andersen (*Centaurus*)

Roger Ariew and Moti Feingold (*Perspectives on Science*)

A K Bag (*Indian Journal of History of Science*)

June Barrow-Green and Benno van Dalen (*Historia Mathematica*)

Keith Benson (*History and Philosophy of the Life Sciences*)

Marco Beretta (*Nuncius*)

Michel Blay (*Revue d'Histoire des Sciences*)

Johanna Bleker (*Medizinhistorisches Journal*)

Cornelius Borck (*Berichte zur Wissenschaftsgeschichte*)

Geof Bowker and Susan Leigh Star (*Science, Technology and Human Values*)

Massimo Bucciantini and Michele Camerota (*Galilaeana: Journal of Galilean Studies*)

Jed Buchwald and Jeremy Gray (*Archive for History of Exact Sciences*)

Vincenzo Cappelletti and Guido Cimino (*Physis*)

Cathryn Carson (*Historical Studies in the Natural Sciences*)

Mark Clark and Alex Keller (*ICON*)

Roger Cline (*International Journal for the History of Engineering & Technology*)

Stephen Clucas and Stephen Gaukroger (*Intellectual History Review*)

Leo Corry, Alexandre Métraux and Jürgen Renn (*Science in Context*)

Brian Dolan and Bill Luckin (*Social History of Medicine*)

Hilmar Duerbeck and Wayne Orchiston (*Journal of Astronomical History and Heritage*)

Moritz Epple, Mikael Hård, Hans-Jörg Rheinberger and Volker Roelcke (*NTM: Zeitschrift für Geschichte der Wissenschaften, Technik und Medizin)*

Paul Farber (*Journal of the History of Biology*)

Mary Fissell and Randall Packard (*Bulletin of the History of Medicine*)

Robert Fox (*Notes & Records of the Royal Society*)

Marina Frasca-Spada (*Studies in History and Philosophy of Science*)

Steven French (*Metascience*)

Jim Good (*History of the Human Sciences*)

Willem Hackmann (*Bulletin of the Scientific Instrument Society*)

Robert Halleux (*Archives Internationales d'Histoire des Sciences*)

Bosse Holmqvist (*Lychnos*)

Rod Home (*Historical Records of Australian Science*)

Michael Hoskin (*Journal for the History of Astronomy*)

Ian Inkster (*History of Technology*)

Nick Jardine (*Studies in History and Philosophy of Biological and Biomedical Sciences*)

Trevor Levere (*Annals of Science*)

Bernard Lightman (*Isis*)

Christoph Lüthy (*Early Science and Medicine*)

Michael Lynch (*Social Studies of Science*)

Stephen McCluskey and Clive Ruggles (*Archaeastronomy: The Journal of Astronomy in Culture*)

Peter Morris (*Ambix*)

Iwan Rhys Morus (*History of Science*)

E Charles Nelson (*Archives of Natural History*)

Ian Nicholson (*Journal of the History of the Behavioral Sciences*)

Kathy Olesko (*Osiris*)

Liliane Pérez (*Documents pour l'Histoire des Techniques*)

John Rigden and Roger H Stuewer (*Physics in Perspective*)

Julio Samsó (*Suhayl: Journal for the History of the Exact and Natural Sciences in Islamic Civilisation*)

Simon Schaffer (*British Journal for the History of Science*)

Norbert Schappacher (*Revue d'Histoire des Mathématiques*)

John Staudenmaier SJ (*Technology and Culture*)

Claire Strom (*Agricultural History*)

Paul Unschuld (*Sudhoffs Archiv*)

Peter Weingart (*Minerva*)

Stefan Zamecki (*Kwartalnik Historii Nauki i Techniki*)

Huib Zuidervaart (*Studium: Tijdschrift voor Wetenschaps- en Universiteitgeschiedenis* /*Revue de l'Histoire des Sciences et des Universités*)


abstract: A report on the 10th annual Research in Computational Molecular Biology (RECOMB) Conference, Venice, Italy, 2-5 April 2006.
author: Balaji S Srinivasan; Chuong B Do; Serafim Batzoglou
date: 2006
institute: 1Department of Electrical Engineering, Stanford University, Stanford CA 94305, USA; 2Department of Developmental Biology, Stanford University, Stanford CA 94305, USA; 3Department of Computer Science, Stanford University, Stanford CA 94305, USA
title: Evidence for intelligent (algorithm) design

More than 700 computational biologists convened in beautiful Venice in early April for RECOMB 2006, the 10th annual Conference on Research in Computational Molecular Biology. After 40 talks, 6 keynote lectures, 180 posters, and at least two cameos by the Riemann zeta function, several emerging trends in computational biology are apparent.

First, there has been a strong shift towards empirical studies of molecular evolution and variation, with approximately 25% of the papers in this broad area. We expect that this number can only increase in the near future, given the ENCODE project <http://www.genome.gov/10005107> and the forthcoming release of several new eukaryotic genomes.

Second, there is a resurgence of interest in two of the oldest problems in computational biology: RNA folding and protein sequence alignment. The interest in noncoding RNAs (ncRNAs) is driven by experiment: recent work on RNA interference (RNAi), microRNAs, ribozymes, and the rest of the 'modern RNA world' has once again stimulated interest in the classical problems of ncRNA identification and fold prediction. Advances in protein sequence alignment draw on the development of new algorithmic and machine-learning techniques for principled estimation of gap penalties (the penalty for inserting a gap in the alignment to improve it) and the rigorous incorporation of non-local similarity measures that move beyond residue-residue similarity.

Interest in classic areas such as protein structure and folding remains strong, with several papers tacitly or explicitly motivated by the coming flood of data promised by structural genomics. Many of the other mainstays of computational biology were also represented at the conference, including old favorites such as expression analysis and genome evolution, as well as the newer areas of data integration and network alignment. Notable by their absence were papers on genome assembly and human single-nucleotide polymorphism (SNP) variation; this is likely to be a fluke rather than a trend, however, given the impending deluge of data from high-throughput sequencing and resequencing projects. We have selected a few of the talks that particularly caught our eye out of the many excellent ones given at the conference.

# Focus on ncRNA folding

One of the highlights of the conference was the demonstration by Ydo Wexler (Technion-Israel Institute of Technology, Haifa, Israel) of a quadratic time algorithm for RNA folding, a result that deservedly won a special mention award. For several decades, RNA folding algorithms had running times that scaled with at least the cube of the length of the RNA sequence. This O(L^3^) time complexity worsens further if pseudoknots are involved in the folding model. By combining a simple 'triangle inequality' heuristic with empirical validation of the 'polymer zeta' behavior of RNA folding, Wexler and colleagues developed an O(L^2^) average time algorithm for RNA folding, a result which makes high-throughput ncRNA prediction far more feasible.

The pseudoknot, a fold comprising two or more helical segments connected by single-stranded loops, was the subject of a talk by Banu Dost (University of California, San Diego, USA), who presented a new algorithm for aligning a subset of ncRNAs with computationally tractable pseudoknots to a database of known ncRNA sequences. Sequences that interact to serve a structural or biochemical function often show coevolution. In this regard, Jeremy Darot (University of Cambridge, UK) presented a general probabilistic graphical model for detecting interdependent evolution between sites in nucleic acid and protein sequences, which he applied to the problem of identifying secondary and tertiary structure interactions in tRNA.

# Interaction networks and microarray analysis

The broad area of functional genomics encompasses methods for the prediction of gene function and interaction. Talks covered the inference and comparison of protein-interaction networks, and the statistical issues associated with the detection of functional enrichment in microarray data. One of us (B.S.S) described an algorithm for integrating a number of different predictors of protein interaction without making assumptions about statistical dependence. He showed that this approach revealed hidden interactions that would not have been found without data integration, and used the method to produce probabilistic protein-interaction networks for 11 microbes. Benny Chor (Tel-Aviv University, Tel-Aviv, Israel) presented work on graphs of metabolic reactions from different species, showing that a taxonomy inferred from network-based characters corresponded fairly well to the known consensus phylogeny.

The problem of comparing large collections of networks from different species motivates work on network alignment, whose goal is to detect conserved modules between networks. By analogy with the existing theory for sequence alignment, Mehmet Koyutürk (Purdue University, West Lafayette, USA) presented an asymptotic theory for estimating the statistical significance of network alignments, with respect to certain classes of large random networks. Developing a version of this theory applicable to alignments of few proteins, which are more common in practice, is an open problem.

Steffen Grossmann (Max Planck Institute for Molecular Genetics, Berlin, Germany) presented an improved statistic for estimating the functional enrichment of gene sets based on Gene Ontology (GO) that takes account of the complex parent-child dependencies in the GO hierarchy (this statistic is implemented in the Ontologizer package available at <http://www.charite.de/ch/medgen/ontologizer>). Stefanie Scheid (Max Planck Institute for Molecular Genetics) presented a novel permutation-filtering technique for the detection of differentially expressed genes in microarray analysis. Her method filters the results of a naive data permutation to estimate a more accurate null distribution, and her work is implemented in the Twilight package available online <http://www.bioconductor.org>.

# Parameter estimation in protein sequence alignment

Two speakers addressed the issue of estimating parameters such as substitution scores and gap penalties for protein sequence alignment. John Kececioglu (University of Arizona, Tucson, USA) provided a solution to the 'inverse sequence alignment' problem, where one estimates parameter values from a training set of alignments. He described a linear programming algorithm for determining a set of alignment parameters under which every example alignment in a given training set is guaranteed to be nearly optimal with respect to that parameter set. The algorithm can learn both residue substitution and gap scores simultaneously, and it will be interesting to see how the resulting parameters perform when used to make new alignments.

One of us (C.B.D) introduced pair-conditional random fields for incorporating non-local sequence similarities (such as hydropathy) into the alignment scoring framework. As such similarities are functions of peptide windows of variable length rather than of individual residues, they cannot easily be incorporated into standard methods based on hidden Markov models (HMMs) for sequence alignment without heuristics. The resulting algorithm, CONTRAlign (source code available online <http://contra.stanford.edu/contralign>), achieves the highest cross-validated pairwise protein alignment accuracies to date.

# Protein structure, dynamics and identification

Perhaps the biggest obstacle to deriving insights from protein structure is the sheer size and complexity of a typical polypeptide. Addressing the problem of protein structure alignment, Wei Xie (University of Illinois at Urbana-Champaign, USA) and Jinbo Xu (Massachusetts Institute of Technology, Cambridge, USA) manage this complexity by focusing on maps of intra-protein contacts. Xie presented work on aligning structures by overlapping their contact maps, by developing a brand-and-reduce algorithm that allows rapid superposition of structurally homologous proteins. By analogy with sequence alignment, Xu presented a polynomial time-parametric algorithm for aligning a protein represented by a contact map to another protein represented by a contact map or an interatomic distance matrix.

Many scientists are interested not just in alignments of stable protein structures, but also in the dynamics of the folding process. Chakra Chennubhotla (University of Pittsburgh, Pittsburgh, USA) reduced the complexity of an all-atom protein simulation by calculating a low-rank, eigenmode-based approximation to the molecular dynamics that is designed to preserve certain stochastic properties of the original protein. Shawna Thomas (Texas A&M University, College Station, USA) took a technically different but conceptually similar approach by approximating a protein as a chain of rigid bodies and then sampling its conformation space with a probabilistic roadmap method imported from motion planning for robotics (for further details, see the parasol website <http://parasol.tamu.edu/foldingserver>). The 'roadmap' in the protein context contains thousands of feasible folding pathways.

The ultimate purpose of protein-folding simulation (as distinct from protein-structure prediction) is to use the observed dynamics to yield insight into aspects of protein biochemistry, such as cooperativity or macromolecular assembly. To this end, Tsung-Han Chiang (National University of Singapore, Singapore) showed that the probabilistic roadmap framework can be used to calculate the probability of proper folding from any given protein conformation, and then to estimate protein-folding rates.

Two speakers addressed problems of fast protein identification by clever hashing methods. Brian Chen in collaboration with Viacheslav Fofanov (both from Rice University, Houston, Texas, USA) showed that one can use geometric hashing techniques to speed up the identification of three-dimensional structural motifs in functionally uncharacterized proteins of known structure. In a different problem domain, Nuno Bandeira (University of California, San Diego, USA) demonstrated a rapid hashing algorithm for identifying proteins from tandem mass spectrometry (MS/MS) spectra. The input protein sample is split into two groups, chemical modifications are applied to one group, and spectra are obtained for both groups. Bandeira showed how using correlations between the two spectra greatly reduces the noise of protein identification.

# Reconstructing the past

Talks on evolution and phylogenetics included richer models of sequence evolution, new methods for tree building, and applications of molecular evolution to questions in functional genomics. On the topic of richer models for deducing phylogeny from sequences, Yun Song (University of California, Davis, USA) described a method for including gene conversion in reconstructions of SNP phylogenies (software available online <http://www.cs.ucdavis.edu/~gusfield>); existing methods typically incorporate only point mutation and recombination as possible events. Sagi Snir (University of California, Berkeley, USA) presented work on the inference of micro-indel events (insertions and/or deletions) from multiple sequence alignments; the method has a time-complexity that is exponential in the number of species, but is linear in terms of sequence length. Miklós Csürös (Université de Montréal, Montreal, Canada) dealt with gene evolution. He described a parametric model for gene family evolution that models gene duplication, gene loss, and (most significantly) horizontal gene transfer.

With respect to the general problem of building trees from data, Constantinos Daskalakis (University of California, Berkeley, USA) described an algorithm for calculating phylogenies from distance matrices (compiled from the differences between sequences), which compares favorably to neighbor-joining on specific examples, without requiring strong assumptions about possible model tree topologies. Adam Siepel (University of California, Santa Cruz, USA) addressed the problem of using molecular evolution to detect functional elements in genomic sequences. He has extended the phastCons program, a phylogenetic HMM model for segmenting a genomic sequence into conserved and nonconserved regions, by introducing lineage-specific models which allow for simple gains or losses of constraint along specific branches of the evolutionary tree relating the sequences. The output of the program, called DLESS, is available as a track on the University of California Santa Cruz genome browser <http://genome.ucsc.edu/encode>.

Evolution also figured prominently in the only talk at the conference given by a non-scientist. In his keynote address, author and journalist Carl Zimmer warned of the perils of 'genomic myopia' and challenged computational molecular biologists to create a model of life's evolution that was consistent with the wealth of knowledge from paleontology and the fossil record. Given the rapid advance of bioinformatics apparent at RECOMB 2006, we have no doubt that our community is up to the challenge.