Mouse genome-wide association and systems genetics identifies Lhfp as a regulator of bone mass.

Bone mineral density (BMD) is a strong predictor of osteoporotic fracture. It is also one of the most heritable disease-associated quantitative traits. As a result, there has been considerable effort focused on dissecting its genetic basis. Here, we performed a genome-wide association study (GWAS) in a panel of inbred strains to identify associations influencing BMD. This analysis identified a significant (P = 3.1 x 10-12) BMD locus on Chromosome [email protected] Mbp that replicated in two separate inbred strain panels and overlapped a BMD quantitative trait locus (QTL) previously identified in a F2 intercross. The association mapped to a 300 Kbp region containing four genes; Gm2447, Gm20750, Cog6, and Lhfp. Further analysis found that Lipoma HMGIC Fusion Partner (Lhfp) was highly expressed in bone and osteoblasts. Furthermore, its expression was regulated by a local expression QTL (eQTL), which overlapped the BMD association. A co-expression network analysis revealed that Lhfp was strongly connected to genes involved in osteoblast differentiation. To directly evaluate its role in bone, Lhfp deficient mice (Lhfp-/-) were created using CRISPR/Cas9. Consistent with genetic and network predictions, bone marrow stromal cells (BMSCs) from Lhfp-/- mice displayed increased osteogenic differentiation. Lhfp-/- mice also had elevated BMD due to increased cortical bone mass. Lastly, we identified SNPs in human LHFP that were associated (P = 1.2 x 10-5) with heel BMD. In conclusion, we used GWAS and systems genetics to identify Lhfp as a regulator of osteoblast activity and bone mass

Consequences of concurrent Ascaridia galli and Escherichia coli infections in chickens

Three experiments were carried out to examine the consequences of concurrent infections with Ascaridia galli and Escherichia coli in chickens raised for table egg production. Characteristic pathological lesions including airsacculitis, peritonitis and/or polyserositis were seen in all groups infected with E. coli. Furthermore, a trend for increased mortality rates was observed in groups infected with both organisms which, however, could not be confirmed statistically. The mean worm burden was significantly lower in combined infection groups compared to groups infected only with A. galli. It was also shown that combined infections of E. coli and A. galli had an added significant negative impact on weight gain

Recent evolution of an ice‐cored moraine at the Gentianes Pass, Valais Alps, Switzerland

International audienceLateral moraines located in permafrost environments often preserve large amounts of both glacier and periglacial ice. To understand how ice‐cored moraines located in high alpine environments evolve in a context of both glacier retreat and permafrost degradation, we performed 11 terrestrial laser‐scanning measurement campaigns between 2007 and 2014 on a highly anthropogenic overprinted moraine prone to instability. Resulting comparison of the subsequent 3D models allowed to qualitatively and quantitatively analyze the morphological evolution of the moraine. The comparisons indicate a very high geomorphic activity of the moraine including large areas affected by downslope movements of blocks and 10 landslides with a volume between 24 ± 1 and 1,138 ± 47 m3. Data also indicated a very strong ice melt with a loss of ice thickness locally reaching 17.7 m at the foot of the moraine. These results, compared with resistivity and thermal measurements of the ground, suggest the combined role of ice loss at the foot of the moraine and the permafrost activity/warming in triggering these processes

Functional Genomics Complements Quantitative Genetics in Identifying Disease-Gene Associations

An ultimate goal of genetic research is to understand the connection between genotype and phenotype in order to improve the diagnosis and treatment of diseases. The quantitative genetics field has developed a suite of statistical methods to associate genetic loci with diseases and phenotypes, including quantitative trait loci (QTL) linkage mapping and genome-wide association studies (GWAS). However, each of these approaches have technical and biological shortcomings. For example, the amount of heritable variation explained by GWAS is often surprisingly small and the resolution of many QTL linkage mapping studies is poor. The predictive power and interpretation of QTL and GWAS results are consequently limited. In this study, we propose a complementary approach to quantitative genetics by interrogating the vast amount of high-throughput genomic data in model organisms to functionally associate genes with phenotypes and diseases. Our algorithm combines the genome-wide functional relationship network for the laboratory mouse and a state-of-the-art machine learning method. We demonstrate the superior accuracy of this algorithm through predicting genes associated with each of 1157 diverse phenotype ontology terms. Comparison between our prediction results and a meta-analysis of quantitative genetic studies reveals both overlapping candidates and distinct, accurate predictions uniquely identified by our approach. Focusing on bone mineral density (BMD), a phenotype related to osteoporotic fracture, we experimentally validated two of our novel predictions (not observed in any previous GWAS/QTL studies) and found significant bone density defects for both Timp2 and Abcg8 deficient mice. Our results suggest that the integration of functional genomics data into networks, which itself is informative of protein function and interactions, can successfully be utilized as a complementary approach to quantitative genetics to predict disease risks. All supplementary material is available at http://cbfg.jax.org/phenotype

Age differences in financial decision making: The benefits of more experience and less negative emotions

The emerging literature on aging and decision making posits that decision‐making competence changes with age, as a result of age differences in various cognitive and noncognitive individual‐differences characteristics. In a national life‐span sample from the United Kingdom (N = 926), we examined age differences in financial decisions, including performance measures of sunk cost and credit card repayment decisions, and self‐report measures of money management and financial decision outcomes. Participants also completed four individual‐differences characteristics that have been proposed as relevant to financial decision making, including two cognitive ones (numeracy and experience‐based knowledge) and two noncognitive ones (negative emotions about financial decisions). First, we examined how age was related to the four financial decision‐making measures and the four individual‐differences characteristics. Older age was correlated to better scores on each of the four financial decision‐making measures, more experience‐based knowledge, less negative emotions about financial decisions, whereas numeracy and motivation were not significantly correlated with age. Second, we found that considering both the two cognitive and the two noncognitive individual‐differences characteristics increased predictions of financial decision making, as compared with considering either alone. Third, we examined how these four individual‐differences characteristics contributed to age differences in financial decision making. Older adults' higher levels of experience‐based knowledge and lower levels of negative emotions seemed to especially benefit their financial decision making. We discuss implications for theories on aging and decision making, as well as for interventions targeting financial decisions

Don't tax me? : Determinants of individual attitudes toward progressive taxation

This contribution empirically analyses the individual determinants of tax rate preferences. For that purpose we make use of the representative German General Social Survey (ALLBUS) that offers data on the individual attitudes toward progressive, proportional, and regressive taxation. Our theoretical considerations suggest that beyond self-interest, information, fairness considerations, economic beliefs and several other individual factors drive individual preferences for tax rate structures. Our empirical results indicate that the self-interest view does not offer the sole explanation for the heterogeneity in attitudes toward progressive taxation. Rather, we show that the choice of the favoured tax rate is also driven by fairness considerations

Canonical A-to-I and C-to-U RNA Editing Is Enriched at 3′UTRs and microRNA Target Sites in Multiple Mouse Tissues

RNA editing is a process that modifies RNA nucleotides and changes the efficiency and fidelity of the central dogma. Enzymes that catalyze RNA editing are required for life, and defects in RNA editing are associated with many diseases. Recent advances in sequencing have enabled the genome-wide identification of RNA editing sites in mammalian transcriptomes. Here, we demonstrate that canonical RNA editing (A-to-I and C-to-U) occurs in liver, white adipose, and bone tissues of the laboratory mouse, and we show that apparent non-canonical editing (all other possible base substitutions) is an artifact of current high-throughput sequencing technology. Further, we report that high-confidence canonical RNA editing sites can cause non-synonymous amino acid changes and are significantly enriched in 3′ UTRs, specifically at microRNA target sites, suggesting both regulatory and functional consequences for RNA editing

Assessment of the genetic and clinical determinants of fracture risk: genome wide association and mendelian randomisation study.

OBJECTIVES: To identify the genetic determinants of fracture risk and assess the role of 15 clinical risk factors on osteoporotic fracture risk. DESIGN: Meta-analysis of genome wide association studies (GWAS) and a two-sample mendelian randomisation approach. SETTING: 25 cohorts from Europe, United States, east Asia, and Australia with genome wide genotyping and fracture data. PARTICIPANTS: A discovery set of 37 857 fracture cases and 227 116 controls; with replication in up to 147 200 fracture cases and 150 085 controls. Fracture cases were defined as individuals (>18 years old) who had fractures at any skeletal site confirmed by medical, radiological, or questionnaire reports. Instrumental variable analyses were performed to estimate effects of 15 selected clinical risk factors for fracture in a two-sample mendelian randomisation framework, using the largest previously published GWAS meta-analysis of each risk factor. RESULTS: Of 15 fracture associated loci identified, all were also associated with bone mineral density and mapped to genes clustering in pathways known to be critical to bone biology (eg, SOST, WNT16, and ESR1) or novel pathways (FAM210A, GRB10, and ETS2). Mendelian randomisation analyses showed a clear effect of bone mineral density on fracture risk. One standard deviation decrease in genetically determined bone mineral density of the femoral neck was associated with a 55% increase in fracture risk (odds ratio 1.55 (95% confidence interval 1.48 to 1.63; P=1.5×10-68). Hand grip strength was inversely associated with fracture risk, but this result was not significant after multiple testing correction. The remaining clinical risk factors (including vitamin D levels) showed no evidence for an effect on fracture. CONCLUSIONS: This large scale GWAS meta-analysis for fracture identified 15 genetic determinants of fracture, all of which also influenced bone mineral density. Among the clinical risk factors for fracture assessed, only bone mineral density showed a major causal effect on fracture. Genetic predisposition to lower levels of vitamin D and estimated calcium intake from dairy sources were not associated with fracture risk

Two heads are less bubbly than one: Team decision-making in an experimental asset market

In the world of mutual funds management, responsibility for investment decisions is increasingly entrusted to small teams instead of individuals. Yet the effect of team decision-making in a market environment has never been studied in a controlled experiment. In this paper, we investigate the effect of team decision-making in an asset market experiment that has long been known to reliably generate price bubbles and crashes in markets populated by individuals. We find that this tendency is substantially reduced when each decision-making unit is instead a team of two. This holds across a broad spectrum of measures of the severity of mispricing, both under a continuous double-auction institution and in a call market. The result is not driven by reduced turnover due to time required for deliberation by teams, and continues to hold even when subjects are experienced. Our result also holds not only when our teams treatments are compared to the ‘narrow’ baseline provided by the corresponding individuals treatments, but also when compared more broadly to the results of the large body of previous research on markets of this kind