Common variation near CDKN1A, POLD3 and SHROOM2 influences colorectal cancer risk

We performed a meta-analysis of five genome-wide association studies to identify common variants influencing colorectal cancer (CRC) risk comprising 8,682 cases and 9,649 controls. Replication analysis was performed in case-control sets totaling 21,096 cases and 19,555 controls. We identified three new CRC risk loci at 6p21 (rs1321311, near CDKN1A; P = 1.14 × 10(-10)), 11q13.4 (rs3824999, intronic to POLD3; P = 3.65 × 10(-10)) and Xp22.2 (rs5934683, near SHROOM2; P = 7.30 × 10(-10)) This brings the number of independent loci associated with CRC risk to 20 and provides further insight into the genetic architecture of inherited susceptibility to CRC.     

Association of a functional variant downstream of TNFAIP3 with systemic lupus erythematosus

Systemic lupus erythematosus (SLE, MIM152700) is an autoimmune disease characterized by self-reactive antibodies resulting in systemic inflammation and organ failure. TNFAIP3, encoding the ubiquitin-modifying enzyme A20, is an established susceptibility locus for SLE. By fine mapping and genomic re-sequencing in ethnically diverse populations, we fully characterized the TNFAIP3 risk haplotype and identified a TT>A polymorphic dinucleotide (deletion T followed by a T to A transversion) associated with SLE in subjects of European (P = 1.58 × 10(-8), odds ratio = 1.70) and Korean (P = 8.33 × 10(-10), odds ratio = 2.54) ancestry. This variant, located in a region of high conservation and regulatory potential, bound a nuclear protein complex composed of NF-κB subunits with reduced avidity. Further, compared with the non-risk haplotype, the haplotype carrying this variant resulted in reduced TNFAIP3 mRNA and A20 protein expression. These results establish this TT>A variant as the most likely functional polymorphism responsible for the association between TNFAIP3 and SLE.     

Genome-wide association study identifies a susceptibility locus for thoracic aortic aneurysms and aortic dissections spanning FBN1 at 15q21.1

Although thoracic aortic aneurysms and dissections (TAAD) can be inherited as a single-gene disorder, the genetic predisposition in the majority of affected people is poorly understood. In a multistage genome-wide association study (GWAS), we compared 765 individuals who had sporadic TAAD (STAAD) with 874 controls and identified common SNPs at a 15q21.1 locus that were associated with STAAD, with odds ratios of 1.6-1.8 that achieved genome-wide significance. We followed up 107 SNPs associated with STAAD with P < 1 × 10(-5) in the region, in two separate STAAD cohorts. The associated SNPs fall into a large region of linkage disequilibrium encompassing FBN1, which encodes fibrillin-1. FBN1 mutations cause Marfan syndrome, whose major cardiovascular complication is TAAD. This study shows that common genetic variants at 15q21.1 that probably act via FBN1 are associated with STAAD, suggesting a common pathogenesis of aortic disease in Marfan syndrome and STAAD.     

Exome sequencing identifies MAX mutations as a cause of hereditary pheochromocytoma

Hereditary pheochromocytoma (PCC) is often caused by germline mutations in one of nine susceptibility genes described to date, but there are familial cases without mutations in these known genes. We sequenced the exomes of three unrelated individuals with hereditary PCC (cases) and identified mutations in MAX, the MYC associated factor X gene. Absence of MAX protein in the tumors and loss of heterozygosity caused by uniparental disomy supported the involvement of MAX alterations in the disease. A follow-up study of a selected series of 59 cases with PCC identified five additional MAX mutations and suggested an association with malignant outcome and preferential paternal transmission of MAX mutations. The involvement of the MYC-MAX-MXD1 network in the development and progression of neural crest cell tumors is further supported by the lack of functional MAX in rat PCC (PC12) cells and by the amplification of MYCN in neuroblastoma and suggests that loss of MAX function is correlated with metastatic potential.     

Tedania (Porifera: Demospongiae: Poecilosclerida) from the Mexican Pacific with the description of two new species

Two new species of Tedania (Porifera: Demospongiae: Poecilosclerida) are described from the Mexican Pacific. Tedania (Tedania) tropicalis sp. nov. is an encrusting to massive sponge having ectosomal tylotes with microspined heads, choanosomal styles and onychaetes. Tedania (Tedania) fulvum sp. nov. is a thinly encrusting sponge having ectosomal tylotes with smooth heads, choanosomal styles and onychaetes. Tables for all the Tedania (subgenera Tedania and Tedaniopsis) and Trachytedania species described worldwide are included. We suggest that species of Tedania and Trachytedania bearing ectosomal diactinal spicules (excluding Tedania (Stylotedania)) can be separated in two main groups: those having choanosomal monactinal spicules and those with choanosomal diactinal spicules.

www.zoobank.org/urn:lsid:zoobank.org:pub:5B212DC3-3827-44D5-8E63-3E652BCB29E6     

Natural selection has driven population differentiation in modern humans

The considerable range of observed phenotypic variation in human populations may reflect, in part, distinctive processes of natural selection and adaptation to variable environmental conditions. Although recent genome-wide studies have identified candidate regions under selection, it is not yet clear how natural selection has shaped population differentiation. Here, we have analyzed the degree of population differentiation at 2.8 million Phase II HapMap single-nucleotide polymorphisms. We find that negative selection has globally reduced population differentiation at amino acid-altering mutations, particularly in disease-related genes. Conversely, positive selection has ensured the regional adaptation of human populations by increasing population differentiation in gene regions, primarily at nonsynonymous and 5'-UTR variants. Our analyses identify a fraction of loci that have contributed, and probably still contribute, to the morphological and disease-related phenotypic diversity of current human populations.     

A Proposal for Robust Curve Clustering

Functional data sets appear in many areas of science. Although each data point may be seen as a large finite-dimensional vector it is preferable to think of them as functions, and many classical multivariate techniques have been generalized for this kind of data. A widely used technique for dealing with functional data is to choose a finite-dimensional basis and find the best projection of each curve onto this basis. Therefore, given a functional basis, an approach for doing curve clustering relies on applying the k-means methodology to the fitted basis coefficients corresponding to all the curves in the data set. Unfortunately, a serious drawback follows from the lack of robustness of k-means. Trimmed k-means clustering (Cuesta-Albertos, Gordaliza, and Matran 1997) provides a robust alternative to the use of k-means and, consequently, it may be successfully used in this functional framework. The proposed approach will be exemplified by considering cubic B-splines bases, but other bases can be applied analogously depending on the application at hand.     

Expressed protein ligation: a resourceful tool to study protein structure and function

This review outlines the use of expressed protein ligation (EPL) to study protein structure, function and stability. EPL is a chemoselective ligation method that allows the selective ligation of unprotected polypeptides from synthetic and recombinant origin for the production of semi-synthetic protein samples of well-defined and homogeneous chemical composition. This method has been extensively used for the site-specific introduction of biophysical probes, unnatural amino acids, and increasingly complex post-translational modifications. Since it was introduced 10 years ago, EPL applications have grown increasingly more sophisticated in order to address even more complex biological questions. In this review, we highlight how this powerful technology combined with standard biochemical analysis techniques has been used to improve our ability to understand protein structure and function.