A cell-type-specific protein-protein interaction modulates transcriptional activity of a master regulator in Caulobacter crescentus.

Progression through the Caulobacter cell cycle is driven by the master regulator CtrA, an essential two-component signaling protein that regulates the expression of nearly 100 genes. CtrA is abundant throughout the cell cycle except immediately prior to DNA replication. However, the expression of CtrA-activated genes is generally restricted to S phase. We identify the conserved protein SciP (small CtrA inhibitory protein) and show that it accumulates during G1, where it inhibits CtrA from activating target genes. The depletion of SciP from G1 cells leads to the inappropriate induction of CtrA-activated genes and, consequently, a disruption of the cell cycle. Conversely, the ectopic synthesis of SciP is sufficient to inhibit CtrA-dependent transcription, also disrupting the cell cycle. SciP binds directly to CtrA without affecting stability or phosphorylation; instead, SciP likely prevents CtrA from recruiting RNA polymerase. CtrA is thus tightly regulated by a protein-protein interaction which is critical to cell-cycle progression.

An empirical estimate of carrier frequencies for 400+ causal Mendelian variants: results from an ethnically diverse clinical sample of 23,453 individuals.

PURPOSE: Recent developments in genomics have led to expanded carrier screening panels capable of assessing hundreds of causal mutations for genetic disease. This new technology enables simultaneous measurement of carrier frequencies for many diseases. As the resultant rank-ordering of carrier frequencies impacts the design and prioritization of screening programs, the accuracy of this ranking is a public health concern. METHODS: A total of 23,453 individuals from many obstetric, genetics, and infertility clinics were referred for routine recessive disease carrier screening. Multiplex carrier screening was performed and results were aggregated for this study. RESULTS: Twenty-four percent of individuals were identified as carriers for at least one of 108 disorders, and 5.2% were carriers for multiple disorders. We report tabulations of carrier frequency by self-identified ethnicity and disease. CONCLUSION: To our knowledge, this study of a large, ethnically diverse clinical sample provides the most accurate measurements to date of carrier frequencies for hundreds of recessive alleles. The study also yields information on the clinical considerations associated with routine use of expanded panels and provides support for a pan-ethnic screening paradigm that minimizes the use of "racial" categories by the physician, as recommended by recent guidelines.

Genetic and computational identification of a conserved bacterial metabolic module.

We have experimentally and computationally defined a set of genes that form a conserved metabolic module in the alpha-proteobacterium Caulobacter crescentus and used this module to illustrate a schema for the propagation of pathway-level annotation across bacterial genera. Applying comprehensive forward and reverse genetic methods and genome-wide transcriptional analysis, we (1) confirmed the presence of genes involved in catabolism of the abundant environmental sugar myo-inositol, (2) defined an operon encoding an ABC-family myo-inositol transmembrane transporter, and (3) identified a novel myo-inositol regulator protein and cis-acting regulatory motif that control expression of genes in this metabolic module. Despite being encoded from non-contiguous loci on the C. crescentus chromosome, these myo-inositol catabolic enzymes and transporter proteins form a tightly linked functional group in a computationally inferred network of protein associations. Primary sequence comparison was not sufficient to confidently extend annotation of all components of this novel metabolic module to related bacterial genera. Consequently, we implemented the Graemlin multiple-network alignment algorithm to generate cross-species predictions of genes involved in myo-inositol transport and catabolism in other alpha-proteobacteria. Although the chromosomal organization of genes in this functional module varied between species, the upstream regions of genes in this aligned network were enriched for the same palindromic cis-regulatory motif identified experimentally in C. crescentus. Transposon disruption of the operon encoding the computationally predicted ABC myo-inositol transporter of Sinorhizobium meliloti abolished growth on myo-inositol as the sole carbon source, confirming our cross-genera functional prediction. Thus, we have defined regulatory, transport, and catabolic genes and a cis-acting regulatory sequence that form a conserved module required for myo-inositol metabolism in select alpha-proteobacteria. Moreover, this study describes a forward validation of gene-network alignment, and illustrates a strategy for reliably transferring pathway-level annotation across bacterial species.

A universal carrier test for the long tail of Mendelian disease.

Mendelian disorders are individually rare but collectively common, forming a 'long tail' of genetic disease. A single highly accurate assay for this long tail would allow the scaling up of the Jewish community's successful campaign of population screening for Tay-Sachs disease to the general population, thereby improving millions of lives, greatly benefiting minority health and saving billions of dollars. This need has been addressed by designing a universal carrier test: a non-invasive, saliva-based assay for more than 100 Mendelian diseases across all major population groups. The test has been exhaustively validated with a median of 147 positive and 525 negative samples per variant, demonstrating a multiplex assay whose performance compares favourably with the previous standard of care, namely blood-based single-gene carrier tests. Because the test represents a dramatic reduction in the cost and complexity of large-scale population screening, an end to many preventable genetic diseases is now in sight. Moreover, given that the assay is inexpensive and requires only a saliva sample, it is now increasingly feasible to make carrier testing a routine part of preconception care.

Whole genome survey of coding SNPs reveals a reproducible pathway determinant of Parkinson disease.

It is quickly becoming apparent that situating human variation in a pathway context is crucial to understanding its phenotypic significance. Toward this end, we have developed a general method for finding pathways associated with traits that control for pathway size. We have applied this method to a new whole genome survey of coding SNP variation in 187 patients afflicted with Parkinson disease (PD) and 187 controls. We show that our dataset provides an independent replication of the axon guidance association recently reported by Lesnick et al. [PLoS Genet 2007;3:e98], and also indicates that variation in the ubiquitin-mediated proteolysis and T-cell receptor signaling pathways may predict PD susceptibility. Given this result, it is reasonable to hypothesize that pathway associations are more replicable than individual SNP associations in whole genome association studies. However, this hypothesis is complicated by a detailed comparison of our dataset to the second recent PD association study by Fung et al. [Lancet Neurol 2006;5:911-916]. Surprisingly, we find that the axon guidance pathway does not rank at the very top of the Fung dataset after controlling for pathway size. More generally, in comparing the studies, we find that SNP frequencies replicate well despite technologically different assays, but that both SNP and pathway associations are globally uncorrelated across studies. We thus have a situation in which an association between axon guidance pathway variation and PD has been found in 2 out of 3 studies. We conclude by relating this seeming inconsistency to the molecular heterogeneity of PD, and suggest future analyses that may resolve such discrepancies.

Current progress in network research: toward reference networks for key model organisms.

The collection of multiple genome-scale datasets is now routine, and the frontier of research in systems biology has shifted accordingly. Rather than clustering a single dataset to produce a static map of functional modules, the focus today is on data integration, network alignment, interactive visualization and ontological markup. Because of the intrinsic noisiness of high-throughput measurements, statistical methods have been central to this effort. In this review, we briefly survey available datasets in functional genomics, review methods for data integration and network alignment, and describe recent work on using network models to guide experimental validation. We explain how the integration and validation steps spring from a Bayesian description of network uncertainty, and conclude by describing an important near-term milestone for systems biology: the construction of a set of rich reference networks for key model organisms.

Functional genome annotation through phylogenomic mapping.

Accurate determination of functional interactions among proteins at the genome level remains a challenge for genomic research. Here we introduce a genome-scale approach to functional protein annotation--phylogenomic mapping--that requires only sequence data, can be applied equally well to both finished and unfinished genomes, and can be extended beyond single genomes to annotate multiple genomes simultaneously. We have developed and applied it to more than 200 sequenced bacterial genomes. Proteins with similar evolutionary histories were grouped together, placed on a three dimensional map and visualized as a topographical landscape. The resulting phylogenomic maps display thousands of proteins clustered in mountains on the basis of coinheritance, a strong indicator of shared function. In addition to systematic computational validation, we have experimentally confirmed the ability of phylogenomic maps to predict both mutant phenotype and gene function in the delta proteobacterium Myxococcus xanthus.

Knowledge and attitudes regarding expanded genetic carrier screening among women's healthcare providers.

OBJECTIVE: To determine women's healthcare providers' knowledge and attitudes regarding genetic disorders and expanded genetic screening. DESIGN: Survey of American Society for Reproductive Medicine 2010 and American College of Obstetricians and Gynecologists 2011 Annual Meeting attendees. The survey included 60 items (12 demographic, 10 knowledge, and 38 attitude). Attitudes were assessed with a 5-point Likert scale. Chi-square or t tests determined significance. SETTING: American Society for Reproductive Medicine 2010 and American College of Obstetricians and Gynecologists 2011 Annual Meeting. PATIENT(S): A total of 203 participants completed the survey. Of these, 48% were male, 61% were physicians, 73% were Caucasian, and 42% were aged 35-50 years. INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): None. RESULT(S): Physicians had better knowledge scores than other participants (87% vs. 79%). Knowledge was not influenced by prior personal/family experience with genetic screening. Fewer correct answers were observed for the probability of a positive test (65.2%), the risk of transmitting a gene mutation (62.2%), and the risk of having an affected child (56.2%). Very few participants (18.3%) disagreed with the notion of carrier screening as socially responsible behavior. Some had concerns about test result confidentiality (40.1%) and resulting insurance rate increases (37.0%). Assuming equal costs, most participants preferred to be tested for a larger number of diseases (77.7%) and believed posttest counseling to be helpful (83.7%). CONCLUSION(S): Women's healthcare providers generally had good knowledge and positive attitudes about genetic disorders and expanded genetic screening. Specific misperceptions, both medical and legal, require education.

Automatic parameter learning for multiple local network alignment.

We developed Graemlin 2.0, a new multiple network aligner with (1) a new multi-stage approach to local network alignment; (2) a novel scoring function that can use arbitrary features of a multiple network alignment, such as protein deletions, protein duplications, protein mutations, and interaction losses; (3) a parameter learning algorithm that uses a training set of known network alignments to learn parameters for our scoring function and thereby adapt it to any set of networks; and (4) an algorithm that uses our scoring function to find approximate multiple network alignments in linear time. We tested Graemlin 2.0's accuracy on protein interaction networks from IntAct, DIP, and the Stanford Network Database. We show that, on each of these datasets, Graemlin 2.0 has higher sensitivity and specificity than existing network aligners. Graemlin 2.0 is available under the GNU public license at http://graemlin.stanford.edu .

Signals of recent positive selection in a worldwide sample of human populations.

Genome-wide scans for recent positive selection in humans have yielded insight into the mechanisms underlying the extensive phenotypic diversity in our species, but have focused on a limited number of populations. Here, we present an analysis of recent selection in a global sample of 53 populations, using genotype data from the Human Genome Diversity-CEPH Panel. We refine the geographic distributions of known selective sweeps, and find extensive overlap between these distributions for populations in the same continental region but limited overlap between populations outside these groupings. We present several examples of previously unrecognized candidate targets of selection, including signals at a number of genes in the NRG-ERBB4 developmental pathway in non-African populations. Analysis of recently identified genes involved in complex diseases suggests that there has been selection on loci involved in susceptibility to type II diabetes. Finally, we search for local adaptation between geographically close populations, and highlight several examples.

Methods for analysis in pharmacogenomics: lessons from the Pharmacogenetics Research Network Analysis Group.

Each year, the Pharmacogenetics Research Network (PGRN) holds an analysis workshop for the members of the PGRN to share new methodologies, study design approaches and to discuss real data applications. This event is closed to members of the PGRN, but the methods presented are relevant to others conducting pharmacogenomics research. This special report describes many of the novel approaches discussed at the workshop and provides a resource for investigators in the field performing pharmacogenomics data analysis. While the focus is pharmacogenomics, the methods discussed are far ranging and have relevance to all types of genetic association studies: identifying noncoding variants and tag-SNPs, haplotype analysis, multivariate techniques, quantitative trait analysis, gene-gene and gene-environment interactions, and genome-wide association studies. The goal is to introduce readers to the topics discussed at the workshop and provide a direction for future development of analysis tools and methods for analysis of pharmacogenomic data.

Evidence for intelligent (algorithm) design.

: A report on the 10th annual Research in Computational Molecular Biology (RECOMB) Conference, Venice, Italy, 2-5 April 2006.

Graemlin: general and robust alignment of multiple large interaction networks.

The recent proliferation of protein interaction networks has motivated research into network alignment: the cross-species comparison of conserved functional modules. Previous studies have laid the foundations for such comparisons and demonstrated their power on a select set of sparse interaction networks. Recently, however, new computational techniques have produced hundreds of predicted interaction networks with interconnection densities that push existing alignment algorithms to their limits. To find conserved functional modules in these new networks, we have developed Graemlin, the first algorithm capable of scalable multiple network alignment. Graemlin's explicit model of functional evolution allows both the generalization of existing alignment scoring schemes and the location of conserved network topologies other than protein complexes and metabolic pathways. To assess Graemlin's performance, we have developed the first quantitative benchmarks for network alignment, which allow comparisons of algorithms in terms of their ability to recapitulate the KEGG database of conserved functional modules. We find that Graemlin achieves substantial scalability gains over previous methods while improving sensitivity.