Protein intrinsic disorder as a flexible armor and a weapon of HIV-1

Many proteins and protein regions are disordered in their native, biologically active states. These proteins/regions are abundant in different organisms and carry out important biological functions that complement the functional repertoire of ordered proteins. Viruses, with their highly compact genomes, small proteomes, and high adaptability for fast change in their biological and physical environment utilize many of the advantages of intrinsic disorder. In fact, viral proteins are generally rich in intrinsic disorder, and intrinsically disordered regions are commonly used by viruses to invade the host organisms, to hijack various host systems, and to help viruses in accommodation to their hostile habitats and to manage their economic usage of genetic material. In this review, we focus on the structural peculiarities of HIV-1 proteins, on the abundance of intrinsic disorder in viral proteins, and on the role of intrinsic disorder in their functions.     

Extremely low-coverage sequencing and imputation increases power for genome-wide association studies

Genome-wide association studies (GWAS) have proven to be a powerful method to identify common genetic variants contributing to susceptibility to common diseases. Here, we show that extremely low-coverage sequencing (0.1-0.5×) captures almost as much of the common (>5%) and low-frequency (1-5%) variation across the genome as SNP arrays. As an empirical demonstration, we show that genome-wide SNP genotypes can be inferred at a mean r(2) of 0.71 using off-target data (0.24× average coverage) in a whole-exome study of 909 samples. Using both simulated and real exome-sequencing data sets, we show that association statistics obtained using extremely low-coverage sequencing data attain similar P values at known associated variants as data from genotyping arrays, without an excess of false positives. Within the context of reductions in sample preparation and sequencing costs, funds invested in extremely low-coverage sequencing can yield several times the effective sample size of GWAS based on SNP array data and a commensurate increase in statistical power.     

Dominant missense mutations in ABCC9 cause Cantú syndrome

Cantú syndrome is characterized by congenital hypertrichosis, distinctive facial features, osteochondrodysplasia and cardiac defects. By using family-based exome sequencing, we identified a de novo mutation in ABCC9. Subsequently, we discovered novel dominant missense mutations in ABCC9 in 14 of the 16 individuals with Cantú syndrome examined. The ABCC9 protein is part of an ATP-dependent potassium (K(ATP)) channel that couples the metabolic state of a cell with its electrical activity. All mutations altered amino acids in or close to the transmembrane domains of ABCC9. Using electrophysiological measurements, we show that mutations in ABCC9 reduce the ATP-mediated potassium channel inhibition, resulting in channel opening. Moreover, similarities between the phenotype of individuals with Cantú syndrome and side effects from the K(ATP) channel agonist minoxidil indicate that the mutations in ABCC9 result in channel opening. Given the availability of ABCC9 antagonists, our findings may have direct implications for the treatment of individuals with Cantú syndrome.     

Exome sequencing of liver fluke-associated cholangiocarcinoma

Opisthorchis viverrini-related cholangiocarcinoma (CCA), a fatal bile duct cancer, is a major public health concern in areas endemic for this parasite. We report here whole-exome sequencing of eight O. viverrini-related tumors and matched normal tissue. We identified and validated 206 somatic mutations in 187 genes using Sanger sequencing and selected 15 genes for mutation prevalence screening in an additional 46 individuals with CCA (cases). In addition to the known cancer-related genes TP53 (mutated in 44.4% of cases), KRAS (16.7%) and SMAD4 (16.7%), we identified somatic mutations in 10 newly implicated genes in 14.8-3.7% of cases. These included inactivating mutations in MLL3 (in 14.8% of cases), ROBO2 (9.3%), RNF43 (9.3%) and PEG3 (5.6%), and activating mutations in the GNAS oncogene (9.3%). These genes have functions that can be broadly grouped into three biological classes: (i) deactivation of histone modifiers, (ii) activation of G protein signaling and (iii) loss of genome stability. This study provides insight into the mutational landscape contributing to O. viverrini-related CCA.     

Mutations in the RNA exosome component gene EXOSC3 cause pontocerebellar hypoplasia and spinal motor neuron degeneration

RNA exosomes are multi-subunit complexes conserved throughout evolution and are emerging as the major cellular machinery for processing, surveillance and turnover of a diverse spectrum of coding and noncoding RNA substrates essential for viability. By exome sequencing, we discovered recessive mutations in EXOSC3 (encoding exosome component 3) in four siblings with infantile spinal motor neuron disease, cerebellar atrophy, progressive microcephaly and profound global developmental delay, consistent with pontocerebellar hypoplasia type 1 (PCH1; MIM 607596). We identified mutations in EXOSC3 in an additional 8 of 12 families with PCH1. Morpholino knockdown of exosc3 in zebrafish embryos caused embryonic maldevelopment, resulting in small brain size and poor motility, reminiscent of human clinical features, and these defects were largely rescued by co-injection with wild-type but not mutant exosc3 mRNA. These findings represent the first example of an RNA exosome core component gene that is responsible for a human disease and further implicate dysregulation of RNA processing in cerebellar and spinal motor neuron maldevelopment and degeneration.     

Mutations in ISPD cause Walker-Warburg syndrome and defective glycosylation of α-dystroglycan

Walker-Warburg syndrome (WWS) is an autosomal recessive multisystem disorder characterized by complex eye and brain abnormalities with congenital muscular dystrophy (CMD) and aberrant a-dystroglycan glycosylation. Here we report mutations in the ISPD gene (encoding isoprenoid synthase domain containing) as the second most common cause of WWS. Bacterial IspD is a nucleotidyl transferase belonging to a large glycosyltransferase family, but the role of the orthologous protein in chordates is obscure to date, as this phylum does not have the corresponding non-mevalonate isoprenoid biosynthesis pathway. Knockdown of ispd in zebrafish recapitulates the human WWS phenotype with hydrocephalus, reduced eye size, muscle degeneration and hypoglycosylated a-dystroglycan. These results implicate ISPD in a-dystroglycan glycosylation in maintaining sarcolemma integrity in vertebrates.     

Common variants at 12q14 and 12q24 are associated with hippocampal volume

Aging is associated with reductions in hippocampal volume that are accelerated by Alzheimer's disease and vascular risk factors. Our genome-wide association study (GWAS) of dementia-free persons (n = 9,232) identified 46 SNPs at four loci with P values of <4.0 × 10(-7). In two additional samples (n = 2,318), associations were replicated at 12q14 within MSRB3-WIF1 (discovery and replication; rs17178006; P = 5.3 × 10(-11)) and at 12q24 near HRK-FBXW8 (rs7294919; P = 2.9 × 10(-11)). Remaining associations included one SNP at 2q24 within DPP4 (rs6741949; P = 2.9 × 10(-7)) and nine SNPs at 9p33 within ASTN2 (rs7852872; P = 1.0 × 10(-7)); along with the chromosome 12 associations, these loci were also associated with hippocampal volume (P < 0.05) in a third younger, more heterogeneous sample (n = 7,794). The SNP in ASTN2 also showed suggestive association with decline in cognition in a largely independent sample (n = 1,563). These associations implicate genes related to apoptosis (HRK), development (WIF1), oxidative stress (MSR3B), ubiquitination (FBXW8) and neuronal migration (ASTN2), as well as enzymes targeted by new diabetes medications (DPP4), indicating new genetic influences on hippocampal size and possibly the risk of cognitive decline and dementia.     

A mixed-model approach for genome-wide association studies of correlated traits in structured populations

Genome-wide association studies (GWAS) are a standard approach for studying the genetics of natural variation. A major concern in GWAS is the need to account for the complicated dependence structure of the data, both between loci as well as between individuals. Mixed models have emerged as a general and flexible approach for correcting for population structure in GWAS. Here, we extend this linear mixed-model approach to carry out GWAS of correlated phenotypes, deriving a fully parameterized multi-trait mixed model (MTMM) that considers both the within-trait and between-trait variance components simultaneously for multiple traits. We apply this to data from a human cohort for correlated blood lipid traits from the Northern Finland Birth Cohort 1966 and show greatly increased power to detect pleiotropic loci that affect more than one blood lipid trait. We also apply this approach to an Arabidopsis thaliana data set for flowering measurements in two different locations, identifying loci whose effect depends on the environment.