The AllWISE Motion Survey, Part 2

We use the AllWISE Data Release to continue our search for WISE-detected motions. In this paper, we publish another 27,846 motion objects, bringing the total number to 48,000 when objects found during our original AllWISE motion survey are included. We use this list, along with the lists of confirmed WISE-based motion objects from the recent papers by Luhman and by Schneider et al. and candidate motion objects from the recent paper by Gagne et al. to search for widely separated, common-proper-motion systems. We identify 1,039 such candidate systems. All 48,000 objects are further analyzed using color-color and color-mag plots to provide possible characterizations prior to spectroscopic follow-up. We present spectra of 172 of these, supplemented with new spectra of 23 comparison objects from the literature, and provide classifications and physical interpretations of interesting sources. Highlights include: (1) the identification of three G/K dwarfs that can be used as standard candles to study clumpiness and grain size in nearby molecular clouds because these objects are currently moving behind the clouds, (2) the confirmation/discovery of several M, L, and T dwarfs and one white dwarf whose spectrophotometric distance estimates place them 5-20 pc from the Sun, (3) the suggestion that the Na 'D' line be used as a diagnostic tool for interpreting and classifying metal-poor late-M and L dwarfs, (4) the recognition of a triple system including a carbon dwarf and late-M subdwarf, for which model fits of the late-M subdwarf (giving [Fe/H] ~ -1.0) provide a measured metallicity for the carbon star, and (5) a possible 24-pc-distant K5 dwarf + peculiar red L5 system with an apparent physical separation of 0.1 pc.Comment: 62 pages with 80 figures, accepted for publication in The Astrophysical Journal Supplement Series, 23 Mar 2016; second version fixes a few small typos and corrects the footnotes for Table

Searching for Exoplanets Using a Microresonator Astrocomb

Detection of weak radial velocity shifts of host stars induced by orbiting planets is an important technique for discovering and characterizing planets beyond our solar system. Optical frequency combs enable calibration of stellar radial velocity shifts at levels required for detection of Earth analogs. A new chip-based device, the Kerr soliton microcomb, has properties ideal for ubiquitous application outside the lab and even in future space-borne instruments. Moreover, microcomb spectra are ideally suited for astronomical spectrograph calibration and eliminate filtering steps required by conventional mode-locked-laser frequency combs. Here, for the calibration of astronomical spectrographs, we demonstrate an atomic/molecular line-referenced, near-infrared soliton microcomb. Efforts to search for the known exoplanet HD 187123b were conducted at the Keck-II telescope as a first in-the-field demonstration of microcombs

The Massive and Distant Clusters of WISE Survey VI: Stellar Mass Fractions of a Sample of High-Redshift Infrared-selected Clusters

We present measurements of the stellar mass fractions ($f_\star$) for a sample of high-redshift ($0.93 \le z \le 1.32$) infrared-selected galaxy clusters from the Massive and Distant Clusters of WISE Survey (MaDCoWS) and compare them to the stellar mass fractions of Sunyaev-Zel'dovich (SZ) effect-selected clusters in a similar mass and redshift range from the South Pole Telescope (SPT)-SZ Survey. We do not find a significant difference in mean $f_\star$ between the two selection methods, though we do find an unexpectedly large range in $f_\star$ for the SZ-selected clusters. In addition, we measure the luminosity function of the MaDCoWS clusters and find $m^*= 19.41\pm0.07$, similar to other studies of clusters at or near our redshift range. Finally, we present SZ detections and masses for seven MaDCoWS clusters and new spectroscopic redshifts for five MaDCoWS clusters. One of these new clusters, MOO J1521+0452 at $z=1.31$, is the most distant MaDCoWS cluster confirmed to date.Comment: Accepted to Ap

Examining the Relationship Between Genetic Counselors’ Attitudes Toward Deaf People and the Genetic Counseling Session

Given the medical and cultural perspectives on deafness it is important to determine if genetic counselors’ attitudes toward deaf people can affect counseling sessions for deafness genes. One hundred fifty-eight genetic counselors recruited through the National Society of Genetic Counselors Listserv completed an online survey assessing attitudes toward deaf people and scenario-specific comfort levels discussing and offering genetic testing for deafness. Respondents with deaf/Deaf friends or who work in prenatal or pediatric settings had more positive attitudes toward deaf people than those without deaf/Deaf friends or those working in ‘other’ settings. More positive attitudes toward deaf people correlated with higher comfort level talking about genetic testing for the two scenarios involving culturally Deaf clients; and correlated with higher comfort level offering genetic testing to culturally Deaf clients wishing to have a deaf child. Attitudes and comfort level were not correlated in the scenarios involving hearing or non-culturally deaf clients. These results suggest that genetic counselors’ attitudes could affect information provision and the decision making process of culturally Deaf clients. Cultural sensitivity workshops in genetic counseling training programs that incorporate personal interactions with culturally Deaf individuals are recommended. Additional suggestions for fostering personal interactions are provided

An expanded evaluation of protein function prediction methods shows an improvement in accuracy

Background: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. Results: We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. Conclusions: The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent. Keywords: Protein function prediction, Disease gene prioritizationpublishedVersio

An Expanded Evaluation of Protein Function Prediction Methods Shows an Improvement In Accuracy

Background: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. Results: We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. Conclusions: The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent

A Genetic Locus within the FMN1/GREM1 Gene Region Interacts with Body Mass Index in Colorectal Cancer Risk

Colorectal cancer risk can be impacted by genetic, environmental, and lifestyle factors, including diet and obesity. Geneenvironment interactions (G x E) can provide biological insights into the effects of obesity on colorectal cancer risk. Here, we assessed potential genome-wide G x E interactions between body mass index (BMI) and common SNPs for colorectal cancer risk using data from 36,415 colorectal cancer cases and 48,451 controls from three international colorectal cancer consortia (CCFR, CORECT, and GECCO). The G x E tests included the conventional logistic regression using multiplicative terms (one degree of freedom, 1DF test), the two-step EDGE method, and the joint 3DF test, each of which is powerful for detecting G x E interactions under specific conditions. BMI was associated with higher colorectal cancer risk. The two-step approach revealed a statistically significant GxBMI interaction located within the Formin 1/Gremlin 1 (FMN1/GREM1) gene region (rs58349661). This SNP was also identified by the 3DF test, with a suggestive statistical significance in the 1DF test. Among participants with the CC genotype of rs58349661, overweight and obesity categories were associated with higher colorectal cancer risk, whereas null associations were observed across BMI categories in those with the TT genotype. Using data from three large international consortia, this study discovered a locus in the FMN1/GREM1 gene region that interacts with BMI on the association with colorectal cancer risk. Further studies should examine the potential mechanisms through which this locus modifies the etiologic link between obesity and colorectal cancer

Novel Common Genetic Susceptibility Loci for Colorectal Cancer

BACKGROUND: Previous genome-wide association studies (GWAS) have identified 42 loci (P < 5 × 10-8) associated with risk of colorectal cancer (CRC). Expanded consortium efforts facilitating the discovery of additional susceptibility loci may capture unexplained familial risk. METHODS: We conducted a GWAS in European descent CRC cases and control subjects using a discovery-replication design, followed by examination of novel findings in a multiethnic sample (cumulative n = 163 315). In the discovery stage (36 948 case subjects/30 864 control subjects), we identified genetic variants with a minor allele frequency of 1% or greater associated with risk of CRC using logistic regression followed by a fixed-effects inverse variance weighted meta-analysis. All novel independent variants reaching genome-wide statistical significance (two-sided P < 5 × 10-8) were tested for replication in separate European ancestry samples (12 952 case subjects/48 383 control subjects). Next, we examined the generalizability of discovered variants in East Asians, African Americans, and Hispanics (12 085 case subjects/22 083 control subjects). Finally, we examined the contributions of novel risk variants to familial relative risk and examined the prediction capabilities of a polygenic risk score. All statistical tests were two-sided. RESULTS: The discovery GWAS identified 11 variants associated with CRC at P < 5 × 10-8, of which nine (at 4q22.2/5p15.33/5p13.1/6p21.31/6p12.1/10q11.23/12q24.21/16q24.1/20q13.13) independently replicated at a P value of less than .05. Multiethnic follow-up supported the generalizability of discovery findings. These results demonstrated a 14.7% increase in familial relative risk explained by common risk alleles from 10.3% (95% confidence interval [CI] = 7.9% to 13.7%; known variants) to 11.9% (95% CI = 9.2% to 15.5%; known and novel variants). A polygenic risk score identified 4.3% of the population at an odds ratio for developing CRC of at least 2.0. CONCLUSIONS: This study provides insight into the architecture of common genetic variation contributing to CRC etiology and improves risk prediction for individualized screenin