Parallel bacterial evolution within multiple patients identifies candidate pathogenicity genes

Bacterial pathogens evolve during the infection of their human host(1-8), but separating adaptive and neutral mutations remains challenging(9-11). Here we identify bacterial genes under adaptive evolution by tracking recurrent patterns of mutations in the same pathogenic strain during the infection of multiple individuals. We conducted a retrospective study of a Burkholderia dolosa outbreak among subjects with cystic fibrosis, sequencing the genomes of 112 isolates collected from 14 individuals over 16 years. We find that 17 bacterial genes acquired nonsynonymous mutations in multiple individuals, which indicates parallel adaptive evolution. Mutations in these genes affect important pathogenic phenotypes, including antibiotic resistance and bacterial membrane composition and implicate oxygen-dependent regulation as paramount in lung infections. Several genes have not previously been implicated in pathogenesis and may represent new therapeutic targets. The identification of parallel molecular evolution as a pathogen spreads among multiple individuals points to the key selection forces it experiences within human hosts.     

Chromatin profiling using targeted DNA adenine methyltransferase

Chromatin is the highly complex structure consisting of DNA and hundreds of associated proteins. Most chromatin proteins exert their regulatory and structural functions by binding to specific chromosomal loci. Knowledge of the identity of these in vivo target loci is essential for the understanding of the functions and mechanisms of action of chromatin proteins. We report here large-scale mapping of in vivo binding sites of chromatin proteins, using a novel approach based on a combination of targeted DNA methylation and microarray technology. We show that three distinct chromatin proteins in Drosophila melanogaster cells each associate with specific sets of genes. HP1 binds predominantly to pericentric genes and transposable elements. GAGA factor associates with euchromatic genes that are enriched in (GA)n motifs. A Drosophila homolog of Saccharomyces cerevisiae Sir2p is associated with several active genes and is excluded from heterochromatin. High-resolution, genome-wide maps of target loci of chromatin proteins ('chromatin profiles') provide new insights into chromatin structure and gene regulation.     

A conserved microRNA module exerts homeotic control over Petunia hybrida and Antirrhinum majus floral organ identity

It is commonly thought that deep phylogenetic conservation of plant microRNAs (miRNAs) and their targets indicates conserved regulatory functions. We show that the blind (bl) mutant of Petunia hybrida and the fistulata (fis) mutant of Antirrhinum majus, which have similar homeotic phenotypes, are recessive alleles of two homologous miRNA-encoding genes. The BL and FIS genes control the spatial restriction of homeotic class C genes to the inner floral whorls, but their ubiquitous early floral expression patterns are in contradiction with a potential role in patterning C gene expression. We provide genetic evidence for the unexpected function of the MIRFIS and MIRBL genes in the center of the flower and propose a dynamic mechanism underlying their regulatory role. Notably, Arabidopsis thaliana, a more distantly related species, also contains this miRNA module but does not seem to use it to confine early C gene expression to the center of the flower.     

Identification of ten loci associated with height highlights new biological pathways in human growth

Height is a classic polygenic trait, reflecting the combined influence of multiple as-yet-undiscovered genetic factors. We carried out a meta-analysis of genome-wide association study data of height from 15,821 individuals at 2.2 million SNPs, and followed up the strongest findings in >10,000 subjects. Ten newly identified and two previously reported loci were strongly associated with variation in height (P values from 4 x 10(-7) to 8 x 10(-22)). Together, these 12 loci account for approximately 2% of the population variation in height. Individuals with < or =8 height-increasing alleles and > or =16 height-increasing alleles differ in height by approximately 3.5 cm. The newly identified loci, along with several additional loci with strongly suggestive associations, encompass both strong biological candidates and unexpected genes, and highlight several pathways (let-7 targets, chromatin remodeling proteins and Hedgehog signaling) as important regulators of human stature. These results expand the picture of the biological regulation of human height and of the genetic architecture of this classical complex trait.     

The role of site accessibility in microRNA target recognition

MicroRNAs are key regulators of gene expression, but the precise mechanisms underlying their interaction with their mRNA targets are still poorly understood. Here, we systematically investigate the role of target-site accessibility, as determined by base-pairing interactions within the mRNA, in microRNA target recognition. We experimentally show that mutations diminishing target accessibility substantially reduce microRNA-mediated translational repression, with effects comparable to those of mutations that disrupt sequence complementarity. We devise a parameter-free model for microRNA-target interaction that computes the difference between the free energy gained from the formation of the microRNA-target duplex and the energetic cost of unpairing the target to make it accessible to the microRNA. This model explains the variability in our experiments, predicts validated targets more accurately than existing algorithms, and shows that genomes accommodate site accessibility by preferentially positioning targets in highly accessible regions. Our study thus demonstrates that target accessibility is a critical factor in microRNA function.     

A single gene network accurately predicts phenotypic effects of gene perturbation in Caenorhabditis elegans

The fundamental aim of genetics is to understand how an organism's phenotype is determined by its genotype, and implicit in this is predicting how changes in DNA sequence alter phenotypes. A single network covering all the genes of an organism might guide such predictions down to the level of individual cells and tissues. To validate this approach, we computationally generated a network covering most C. elegans genes and tested its predictive capacity. Connectivity within this network predicts essentiality, identifying this relationship as an evolutionarily conserved biological principle. Critically, the network makes tissue-specific predictions-we accurately identify genes for most systematically assayed loss-of-function phenotypes, which span diverse cellular and developmental processes. Using the network, we identify 16 genes whose inactivation suppresses defects in the retinoblastoma tumor suppressor pathway, and we successfully predict that the dystrophin complex modulates EGF signaling. We conclude that an analogous network for human genes might be similarly predictive and thus facilitate identification of disease genes and rational therapeutic targets.     

Systematic mapping of genetic interactions in Caenorhabditis elegans identifies common modifiers of diverse signaling pathways

Most heritable traits, including disease susceptibility, are affected by interactions between multiple genes. However, we understand little about how genes interact because very few possible genetic interactions have been explored experimentally. We have used RNA interference in Caenorhabditis elegans to systematically test approximately 65,000 pairs of genes for their ability to interact genetically. We identify approximately 350 genetic interactions between genes functioning in signaling pathways that are mutated in human diseases, including components of the EGF/Ras, Notch and Wnt pathways. Most notably, we identify a class of highly connected 'hub' genes: inactivation of these genes can enhance the phenotypic consequences of mutation of many different genes. These hub genes all encode chromatin regulators, and their activity as genetic hubs seems to be conserved across animals. We propose that these genes function as general buffers of genetic variation and that these hub genes may act as modifier genes in multiple, mechanistically unrelated genetic diseases in humans.     

Chromosome stability, in the absence of apoptosis, is critical for suppression of tumorigenesis in Trp53 mutant mice

The p53 protein integrates multiple upstream signals and functions as a tumor suppressor by activating distinct downstream genes. At the cellular level, p53 induces apoptosis, cell cycle arrest and senescence. A rare mutant form of p53 with the amino acid substitution R175P, found in human tumors, is completely defective in initiating apoptosis but still induces cell cycle arrest. To decipher the functional importance of these pathways in spontaneous tumorigenesis, we used homologous recombination to generate mice with mutant p53-R172P (the mouse equivalent of R175P in humans). Mice inheriting two copies of this mutation (Trp53(515C/515C)) escape the early onset of thymic lymphomas that characterize Trp53-null mice. At 7 months of age, 90% of Trp53-null mice had died, but 85% of Trp53(515C/515C) mice were alive and tumor-free, indicating that p53-dependent apoptosis was not required for suppression of early onset of spontaneous tumors. The lymphomas and sarcomas that eventually developed in Trp53(515C/515C) mice retained a diploid chromosome number, in sharp contrast to aneuploidy observed in tumors and cells from Trp53-null mice. The ability of mutant p53-R172P to induce a partial cell cycle arrest and retain chromosome stability are crucial for suppression of early onset tumorigenesis.