Duplicate genes increase gene expression diversity within and between species

Using microarray gene expression data from several Drosophila species and strains, we show that duplicated genes, compared with single-copy genes, significantly increase gene expression diversity during development. We show further that duplicate genes tend to cause expression divergences between Drosophila species (or strains) to evolve faster than do single-copy genes. This conclusion is also supported by data from different yeast strains.     

A syndrome of altered cardiovascular, craniofacial, neurocognitive and skeletal development caused by mutations in TGFBR1 or TGFBR2

We report heterozygous mutations in the genes encoding either type I or type II transforming growth factor beta receptor in ten families with a newly described human phenotype that includes widespread perturbations in cardiovascular, craniofacial, neurocognitive and skeletal development. Despite evidence that receptors derived from selected mutated alleles cannot support TGFbeta signal propagation, cells derived from individuals heterozygous with respect to these mutations did not show altered kinetics of the acute phase response to administered ligand. Furthermore, tissues derived from affected individuals showed increased expression of both collagen and connective tissue growth factor, as well as nuclear enrichment of phosphorylated Smad2, indicative of increased TGFbeta signaling. These data definitively implicate perturbation of TGFbeta signaling in many common human phenotypes, including craniosynostosis, cleft palate, arterial aneurysms, congenital heart disease and mental retardation, and suggest that comprehensive mechanistic insight will require consideration of both primary and compensatory events.     

Prediction of central nervous system embryonal tumour outcome based on gene expression.

Embryonal tumours of the central nervous system (CNS) represent a heterogeneous group of tumours about which little is known biologically, and whose diagnosis, on the basis of morphologic appearance alone, is controversial. Medulloblastomas, for example, are the most common malignant brain tumour of childhood, but their pathogenesis is unknown, their relationship to other embryonal CNS tumours is debated, and patients' response to therapy is difficult to predict. We approached these problems by developing a classification system based on DNA microarray gene expression data derived from 99 patient samples. Here we demonstrate that medulloblastomas are molecularly distinct from other brain tumours including primitive neuroectodermal tumours (PNETs), atypical teratoid/rhabdoid tumours (AT/RTs) and malignant gliomas. Previously unrecognized evidence supporting the derivation of medulloblastomas from cerebellar granule cells through activation of the Sonic Hedgehog (SHH) pathway was also revealed. We show further that the clinical outcome of children with medulloblastomas is highly predictable on the basis of the gene expression profiles of their tumours at diagnosis.     

Chromatin-IgG complexes activate B cells by dual engagement of IgM and Toll-like receptors

Autoreactive B cells are present in the lymphoid tissues of healthy individuals, but typically remain quiescent. When this homeostasis is perturbed, the formation of self-reactive antibodies can have serious pathological consequences. B cells expressing an antigen receptor specific for self-immunoglobulin-gamma (IgG) make a class of autoantibodies known as rheumatoid factor (RF). Here we show that effective activation of RF+ B cells is mediated by IgG2a-chromatin immune complexes and requires the synergistic engagement of the antigen receptor and a member of the MyD88-dependent Toll-like receptor (TLR) family. Inhibitor studies implicate TLR9. These data establish a critical link between the innate and adaptive immune systems in the development of systemic autoimmune disease and explain the preponderance of autoantibodies reactive with nucleic acid-protein particles. The unique features of this dual-engagement pathway should facilitate the development of therapies that specifically target autoreactive B cells.     

Evidence for recent climate change on Mars from the identification of youthful near-surface ground ice

Ground ice in the crust and soil may be one of the largest reservoirs of water on Mars. Near-surface ground ice is predicted to be stable at latitudes higher than 40 degrees (ref. 4), where a number of geomorphologic features indicative of viscous creep and hence ground ice have been observed. Mid-latitude soils have also been implicated as a water-ice reservoir, the capacity of which is predicted to vary on a 100,000-year timescale owing to orbitally driven variations in climate. It is uncertain, however, whether near-surface ground ice currently exists at these latitudes, and how it is changing with time. Here we report observational evidence for a mid-latitude reservoir of near-surface water ice occupying the pore space of soils. The thickness of the ice-occupied soil reservoir (1-10 m) and its distribution in the 30 degrees to 60 degrees latitude bands indicate a reservoir of (1.5-6.0) x 104 km3, equivalent to a global layer of water 10-40 cm thick. We infer that the reservoir was created during the last phase of high orbital obliquity less than 100,000 years ago, and is now being diminished.     

Extracellular microfibrils in development and disease

Fibrillins are the structural components of extracellular microfibrils that impart physical properties to tissues, alone or together with elastin as elastic fibers. Genetic studies in mice have revealed that fibrillin-rich microfibrils are also involved in regulating developmental programs and homeostatic processes through the modulation of TGF-β/BMP signaling events. A new paradigm has thus emerged whereby the spatiotemporal organization of microfibrils dictates both the cellular activities and physical properties of connective tissues. These observations have paved the way to novel therapeutic approaches aimed at counteracting the life-threatening complications in human conditions caused by dysfunctions of fibrillin-rich microfibrils. Received 2 April 2007; received after revision 23 May 2007; accepted 24 May 2007     

General conditions for predictivity in learning theory

Developing theoretical foundations for learning is a key step towards understanding intelligence. 'Learning from examples' is a paradigm in which systems (natural or artificial) learn a functional relationship from a training set of examples. Within this paradigm, a learning algorithm is a map from the space of training sets to the hypothesis space of possible functional solutions. A central question for the theory is to determine conditions under which a learning algorithm will generalize from its finite training set to novel examples. A milestone in learning theory was a characterization of conditions on the hypothesis space that ensure generalization for the natural class of empirical risk minimization (ERM) learning algorithms that are based on minimizing the error on the training set. Here we provide conditions for generalization in terms of a precise stability property of the learning process: when the training set is perturbed by deleting one example, the learned hypothesis does not change much. This stability property stipulates conditions on the learning map rather than on the hypothesis space, subsumes the classical theory for ERM algorithms, and is applicable to more general algorithms. The surprising connection between stability and predictivity has implications for the foundations of learning theory and for the design of novel algorithms, and provides insights into problems as diverse as language learning and inverse problems in physics and engineering.