A genome-wide association study identifies five loci influencing facial morphology in Europeans

Inter-individual variation in facial shape is one of the most noticeable phenotypes in humans, and it is clearly under genetic regulation; however, almost nothing is known about the genetic basis of normal human facial morphology. We therefore conducted a genome-wide association study for facial shape phenotypes in multiple discovery and replication cohorts, considering almost ten thousand individuals of European descent from several countries. Phenotyping of facial shape features was based on landmark data obtained from three-dimensional head magnetic resonance images (MRIs) and two-dimensional portrait images. We identified five independent genetic loci associated with different facial phenotypes, suggesting the involvement of five candidate genes-PRDM16, PAX3, TP63, C5orf50, and COL17A1-in the determination of the human face. Three of them have been implicated previously in vertebrate craniofacial development and disease, and the remaining two genes potentially represent novel players in the molecular networks governing facial development. Our finding at PAX3 influencing the position of the nasion replicates a recent GWAS of facial features. In addition to the reported GWA findings, we established links between common DNA variants previously associated with NSCL/P at 2p21, 8q24, 13q31, and 17q22 and normal facial-shape variations based on a candidate gene approach. Overall our study implies that DNA variants in genes essential for craniofacial development contribute with relatively small effect size to the spectrum of normal variation in human facial morphology. This observation has important consequences for future studies aiming to identify more genes involved in the human facial morphology, as well as for potential applications of DNA prediction of facial shape such as in future forensic applications.

Identifying candidate gene effects by restricting search space in a multivariate genetic analysis of white matter microstructure

Several genetic variants are thought to influence white matter (WM) integrity, measured with diffusion tensor imaging (DTI). Voxel based methods can test genetic associations, but heavy multiple comparisons corrections are required to adjust for searching the whole brain and for all genetic variants analyzed. Thus, genetic associations are hard to detect even in large studies. Using a recently developed multi-SNP analysis, we examined the joint predictive power of a group of 18 cholesterol-related single nucleotide polymorphisms (SNPs) on WM integrity, measured by fractional anisotropy. To boost power, we limited the analysis to brain voxels that showed significant associations with total serum cholesterol levels. From this space, we identified two genes with effects that replicated in individual voxel-wise analyses of the whole brain. Multivariate analyses of genetic variants on a reduced anatomical search space may help to identify SNPs with strongest effects on the brain from a broad panel of genes.

Multiple stages classification of Alzheimer’s disease based on structural brain networks using generalized low rank approximations (GLRAM)

To classify each stage for a progressing disease such as Alzheimer’s disease is a key issue for the disease prevention and treatment. In this study, we derived structural brain networks from diffusion-weighted MRI using whole-brain tractography since there is growing interest in relating connectivity measures to clinical, cognitive, and genetic data. Relatively little work has usedmachine learning to make inferences about variations in brain networks in the progression of the Alzheimer’s disease. Here we developed a framework to utilize generalized low rank approximations of matrices (GLRAM) and modified linear discrimination analysis for unsupervised feature learning and classification of connectivity matrices. We apply the methods to brain networks derived from DWI scans of 41 people with Alzheimer’s disease, 73 people with EMCI, 38 people with LMCI, 47 elderly healthy controls and 221 young healthy controls. Our results show that this new framework can significantly improve classification accuracy when combining multiple datasets; this suggests the value of using data beyond the classification task at hand to model variations in brain connectivity.

Estimating the under-reporting of road crash injuries to police using multiple linked data collections

The reliance on police data for the counting of road crash injuries can be problematic, as it is well known that not all road crash injuries are reported to police which under-estimates the overall burden of road crash injuries. The aim of this study was to use multiple linked data sources to estimate the extent of under-reporting of road crash injuries to police in the Australian state of Queensland. Data from the Queensland Road Crash Database (QRCD), the Queensland Hospital Admitted Patients Data Collection (QHAPDC), Emergency Department Information System (EDIS), and the Queensland Injury Surveillance Unit (QISU) for the year 2009 were linked. The completeness of road crash cases reported to police was examined via discordance rates between the police data (QRCD) and the hospital data collections. In addition, the potential bias of this discordance (under-reporting) was assessed based on gender, age, road user group, and regional location. Results showed that the level of under-reporting varied depending on the data set with which the police data was compared. When all hospital data collections are examined together the estimated population of road crash injuries was approximately 28,000, with around two-thirds not linking to any record in the police data. The results also showed that the under-reporting was more likely for motorcyclists, cyclists, males, young people, and injuries occurring in Remote and Inner Regional areas. These results have important implications for road safety research and policy in terms of: prioritising funding and resources; targeting road safety interventions into areas of higher risk; and estimating the burden of road crash injuries.

Grassland productivity limited by multiple nutrients

Terrestrial ecosystem productivity is widely accepted to be nutrient limited1. Although nitrogen (N) is deemed a key determinant of aboveground net primary production (ANPP)2,3, the prevalence of co-limitation by N and phosphorus (P) is increasingly recognized4,​5,​6,​7,​8. However, the extent to which terrestrial productivity is co-limited by nutrients other than N and P has remained unclear. Here, we report results from a standardized factorial nutrient addition experiment, in which we added N, P and potassium (K) combined with a selection of micronutrients (K+μ), alone or in concert, to 42 grassland sites spanning five continents, and monitored ANPP. Nutrient availability limited productivity at 31 of the 42 grassland sites. And pairwise combinations of N, P, and K+μ co-limited ANPP at 29 of the sites. Nitrogen limitation peaked in cool, high latitude sites. Our findings highlight the importance of less studied nutrients, such as K and micronutrients, for grassland productivity, and point to significant variations in the type and degree of nutrient limitation. We suggest that multiple-nutrient constraints must be considered when assessing the ecosystem-scale consequences of nutrient enrichment.

Non-parametric consistency test for multiple-sensing-modality data fusion

Fusing data from multiple sensing modalities, e.g. laser and radar, is a promising approach to achieve resilient perception in challenging environmental conditions. However, this may lead to \emph{catastrophic fusion} in the presence of inconsistent data, i.e. when the sensors do not detect the same target due to distinct attenuation properties. It is often difficult to discriminate consistent from inconsistent data across sensing modalities using local spatial information alone. In this paper we present a novel consistency test based on the log marginal likelihood of a Gaussian process model that evaluates data from range sensors in a relative manner. A new data point is deemed to be consistent if the model statistically improves as a result of its fusion. This approach avoids the need for absolute spatial distance threshold parameters as required by previous work. We report results from object reconstruction with both synthetic and experimental data that demonstrate an improvement in reconstruction quality, particularly in cases where data points are inconsistent yet spatially proximal.

Expression and characterization of digestive enzyme genes from hepatopancreatic transcripts from redclaw crayfish (Cherax quadricarinatus)

Redclaw crayfish, Cherax quadricarinatus, possess a number of biological and commercial attributes that make them ideal for commercial aquaculture. While some studies have investigated digestive enzyme activity and nutritional requirements of this species, little information exists about the expression of digestive enzyme genes and their role in regulating digestive capacity. The current study therefore sequenced and annotated a RNASeq library constructed from a redclaw hepatopancreas to identify genes involved in digestive enzyme production. We observed that most of the transcripts that were annotated as digestive enzyme genes are associated with carbohydrate metabolism, thus confirming that redclaw have an innate capacity to digest a range of carbohydrate substrates. While endoglucanases were the most abundant group of digestive enzymes found, a number of novel transcripts were also detected. Here, we provide the first report for the presence and expression of endo-b-mannanase in freshwater crayfish. This novel gene showed significant alignment with a GH5 family protein from marine Limnoriids, wood borers that do not possess symbiotic microbes in their gut system. Overall, the data generated here provide an important resource to better understand the suite of digestive enzymes in redclaw that are very useful to fully utilize the species’ digestive capacity and will assist development of specific artificial feeds.

Service-learning through multiple client-sponsored projects in an MBA marketing course

This paper outlines an approach for teaching Marketing Principles in an MBA course through service-learning to enable adult learners to connect the lectures’ marketing content to a real-world marketing project. During the course, 40 students in groups of four to five individuals were involved in eight different client-sponsored marketing projects executed simultaneously. The rationale, planning and management of this approach utilised current research on service-learning, living cases and client-sponsored projects in marketing education. The experimental curriculum design is presented in a timeline that mirrors the preparation and management of the group projects and the considerations to be taken into account when initiating and facilitating the projects. Reflections from this iteration of the service-learning design suggest the importance of: detailed project planning, the involvement of students in choosing the projects, the introduction of forms and feedback loops, the role of the instructor in facilitating the students and managing expectations, and the role of the company representative in supporting the groups.

Analysis, characterisation and expression of gill-expressed carbonic anhydrase genes in the freshwater crayfish Cherax quadricarinatus

Changes in water quality parameters such as pH and salinity can have a significant effect on productivity of aquaculture species. Similarly, relative osmotic pressure influences various physiological processes and regulates expression of a number of osmoregulatory genes. Among those, carbonic anhydrase (CA) plays a key role in systemic acid–base balance and ion regulation. Redclaw crayfish (Cherax quadricarinatus) are unique in their ability to thrive in environments with naturally varied pH levels, suggesting unique adaptation to pH stress. To date, however, no studies have focused on identification and characterisation of CA or other osmoregulatory genes in C. quadricarinatus. Here, we analysed the redclaw gill transcriptome and characterized CA genes along with a number of other key osmoregulatory genes that were identified in the transcriptome. We also examined patterns of gene expression of these CA genes when exposed to three pH treatments. In total, 72,382,710 paired end Illumina reads were assembled into 36,128 contigs with an average length of 800 bp. Approximately 37% of contigs received significant BLAST hits and 22% were assigned gene ontology terms. Three full length CA isoforms; cytoplasmic CA (ChqCAc), glycosyl-phosphatidylinositol-linked CA (ChqCAg), and β-CA (ChqCA-beta) as well as two partial CA gene sequences were identified. Both partial CA genes showed high similarity to ChqCAg and appeared to be duplicated from the ChqCAg. Full length coding sequences of Na+/K+-ATPase, V-type H+-ATPase, sarcoplasmic Ca+-ATPase, arginine kinase, calreticulin and Cl− channel protein 2 were also identified. Only the ChqCAc gene showed significant differences in expression across the three pH treatments. These data provide valuable information on the gill expressed CA genes and their expression patterns in freshwater crayfish. Overall our data suggest an important role for the ChqCAc gene in response to changes in pH and in systemic acid–base balance in freshwater crayfish.

Comparative analysis of gill transcriptomes of two freshwater crayfish, Cherax cainii and C. destructor

We undertook deep sequencing of gill transcriptomes from two freshwater crayfish, Cherax cainii and Cherax destructor, in order to generate genomic resources for future genomics research. Over 83 and 100 million high quality (quality score (Q) ≥ 30) paired-end Illumina reads (150 bp) were assembled into 147,101 and 136,622 contigs in C. cainii and C. destructor, respectively. A total of 24,630 and 23,623 contigs received significant BLASTx hits and allowed the identification of multiple gill expressed candidate genes associated with pH and salinity balance. These functionally annotated transcripts will provide a resource to facilitate comparative genomic research in the genus Cherax, and in particular allow insights into respiratory and osmoregulatory physiology of this group of animals.

Multiple sulfur isotope analyses support a magmatic model for the volcanogenic massive sulfide deposits of the Teutonic Bore volcanic complex, Yilgarn Craton, Western Australia

We report sensitive high mass resolution ion microprobe, stable isotopes (SHRIMP SI) multiple sulfur isotope analyses (32S, 33S, 34S) to constrain the sources of sulfur in three Archean VMS deposits—Teutonic Bore, Bentley, and Jaguar—from the Teutonic Bore volcanic complex of the Yilgarn Craton, Western Australia, together with sedimentary pyrites from associated black shales and interpillow pyrites. The pyrites from VMS mineralization are dominated by mantle sulfur but include a small amount of slightly negative mass-independent fractionation (MIF) anomalies, whereas sulfur from the pyrites in the sedimentary rocks has pronounced positive MIF, with ∆33S values that lie between 0.19 and 6.20‰ (with one outlier at −1.62‰). The wall rocks to the mineralization include sedimentary rocks that have contributed no detectable positive MIF sulfur to the VMS deposits, which is difficult to reconcile with the leaching model for the formation of these deposits. The sulfur isotope data are best explained by mixing between sulfur derived from a magmatic-hydrothermal fluid and seawater sulfur as represented by the interpillow pyrites. The massive sulfide lens pyrites have a weighted mean ∆33S value of −0.27 ± 0.05‰ (MSWD = 1.6) nearly identical with −0.31 ± 0.08‰ (MSWD = 2.4) for pyrites from the stringer zone, which requires mixing to have occurred below the sea floor. We employed a two-component mixing model to estimate the contribution of seawater sulfur to the total sulfur budget of the two Teutonic Bore volcanic complex VMS deposits. The results are 15 to 18% for both Teutonic Bore and Bentley, much higher than the 3% obtained by Jamieson et al. (2013) for the giant Kidd Creek deposit. Similar calculations, carried out for other Neoarchean VMS deposits give value between 2% and 30%, which are similar to modern hydrothermal VMS deposits. We suggest that multiple sulfur isotope analyses may be used to predict the size of Archean VMS deposits and to provide a vector to ore deposit but further studies are needed to test these suggestions.

Comparative analysis of genome maintenance genes in naked mole rat, mouse, and human

Genome maintenance (GM) is an essential defense system against aging and cancer, as both are characterized by increased genome instability. Here, we compared the copy number variation and mutation rate of 518 GM-associated genes in the naked mole rat (NMR), mouse, and human genomes. GM genes appeared to be strongly conserved, with copy number variation in only four genes. Interestingly, we found NMR to have a higher copy number of CEBPG, a regulator of DNA repair, and TINF2, a protector of telomere integrity. NMR, as well as human, was also found to have a lower rate of germline nucleotide substitution than the mouse. Together, the data suggest that the long-lived NMR, as well as human, has more robust GM than mouse and identifies new targets for the analysis of the exceptional longevity of the NMR.

A Strength Pareto Evolutionary Algorithm for live migration of multiple interdependent virtual machines in data centers

Although live VM migration has been intensively studied, the problem of live migration of multiple interdependent VMs has hardly been investigated. The most important problem in the live migration of multiple interdependent VMs is how to schedule VM migrations as the schedule will directly affect the total migration time and the total downtime of those VMs. Aiming at minimizing both the total migration time and the total downtime simultaneously, this paper presents a Strength Pareto Evolutionary Algorithm 2 (SPEA2) for the multi-VM migration scheduling problem. The SPEA2 has been evaluated by experiments, and the experimental results show that the SPEA2 can generate a set of VM migration schedules with a shorter total migration time and a shorter total downtime than an existing genetic algorithm, namely Random Key Genetic Algorithm (RKGA). This paper also studies the scalability of the SPEA2.

Association of variants at 1q32 and STAT3 with ankylosing spondylitis suggests genetic overlap with Crohn's disease

Ankylosing spondylitis (AS) is a common inflammatory arthritic condition. Overt inflammatory bowel disease (IBD) occurs in about 10% of AS patients, and in addition 70% of AS cases may have subclinical terminal ileitis. Spondyloarthritis is also common in IBD patients. We therefore tested Crohn's disease susceptibility genes for association with AS, aiming to identify pleiotropic genetic associations with both diseases. Genotyping was carried out using Sequenom and Applied Biosystems TaqMan and OpenArray technologies on 53 markers selected from 30 Crohn's disease associated genomic regions. We tested genotypes in a population of unrelated individual cases (n = 2,773) and controls (n = 2,215) of white European ancestry for association with AS. Statistical analysis was carried out using a Cochran-Armitage test for trend in PLINK. Strong association was detected at chr1q32 near KIF21B (rs11584383, P = 1.66 x 10-10, odds ratio (OR) = 0.74, 95% CI:0.68-0.82). Association with disease was also detected for 2 variants within STAT3 (rs6503695, P = 4.6×10-4. OR = 0.86 (95% CI:0.79-0.93); rs744166, P = 2.6×10-5, OR = 0.84 (95% CI:0.77-0.91)). Association was confirmed for IL23R (rs11465804, P = 1.2×10-5, OR = 0.65 (95% CI:0.54-0.79)), and further associations were detected for IL12B (rs10045431, P = 5.261025, OR = 0.83 (95% CI:0.76-0.91)), CDKAL1 (rs6908425, P = 1.1×10-4, OR = 0.82 (95% CI:0.74-0.91)), LRRK2/MUC19 (rs11175593, P = 9.9×10-5, OR = 1.92 (95% CI: 1.38-2.67)), and chr13q14 (rs3764147, P = 5.9×10-4, OR = 1.19 (95% CI: 1.08-1.31)). Excluding cases with clinical IBD did not significantly affect these findings. This study identifies chr1q32 and STAT3 as ankylosing spondylitis susceptibility loci. It also further confirms association for IL23R and detects suggestive association with another 4 loci. STAT3 is a key signaling molecule within the Th17 lymphocyte differentiation pathway and further enhances the case for a major role of this T-lymphocyte subset in ankylosing spondylitis. Finally these findings suggest common aetiopathogenic pathways for AS and Crohn's disease and further highlight the involvement of common risk variants across multiple diseases.

Genome-wide association study using extreme truncate selection identifies novel genes affecting bone mineral density and fracture risk

Osteoporotic fracture is a major cause of morbidity and mortality worldwide. Low bone mineral density (BMD) is a major predisposing factor to fracture and is known to be highly heritable. Site-, gender-, and age-specific genetic effects on BMD are thought to be significant, but have largely not been considered in the design of genome-wide association studies (GWAS) of BMD to date. We report here a GWAS using a novel study design focusing on women of a specific age (postmenopausal women, age 55-85 years), with either extreme high or low hip BMD (age- and gender-adjusted BMD z-scores of +1.5 to +4.0, n = 1055, or -4.0 to -1.5, n = 900), with replication in cohorts of women drawn from the general population (n = 20,898). The study replicates 21 of 26 known BMD-associated genes. Additionally, we report suggestive association of a further six new genetic associations in or around the genes CLCN7, GALNT3, IBSP, LTBP3, RSPO3, and SOX4, with replication in two independent datasets. A novel mouse model with a loss-of-function mutation in GALNT3 is also reported, which has high bone mass, supporting the involvement of this gene in BMD determination. In addition to identifying further genes associated with BMD, this study confirms the efficiency of extreme-truncate selection designs for quantitative trait association studies. © 2011 Duncan et al.