A polychromatic 'greenbeard' locus determines patterns of cooperation in a social amoeba

Cheaters disrupt cooperation by reaping the benefits without paying their fair share of associated costs. Cheater impact can be diminished if cooperators display a tag (‘greenbeard’) and recognise and preferentially direct cooperation towards other tag carriers. Despite its popular appeal, the feasibility of such greenbeards has been questioned because the complex patterns of partner-specific cooperative behaviours seen in nature require greenbeards to come in different colours. Here we show that a locus (‘Tgr’) of a social amoeba represents a polychromatic greenbeard. Patterns of natural Tgr locus sequence polymorphisms predict partner-specific patterns of cooperation by underlying variation in partner-specific protein–protein binding strength and recognition specificity. Finally, Tgr locus polymorphisms increase fitness because they help avoid potential costs of cooperating with incompatible partners. These results suggest that a polychromatic greenbeard can provide a key mechanism for the evolutionary maintenance of cooperation

Type II Supernovae as Probes of Cosmology

- Constraining the cosmological parameters and understanding Dark Energy have tremendous implications for the nature of the Universe and its physical laws. - The pervasive limit of systematic uncertainties reached by cosmography based on Cepheids and Type Ia supernovae (SNe Ia) warrants a search for complementary approaches. - Type II SNe have been shown to offer such a path. Their distances can be well constrained by luminosity-based or geometric methods. Competing, complementary, and concerted efforts are underway, to explore and exploit those objects that are extremely well matched to next generation facilities. Spectroscopic follow-up will be enabled by space- based and 20-40 meter class telescopes. - Some systematic uncertainties of Type II SNe, such as reddening by dust and metallicity effects, are bound to be different from those of SNe Ia. Their stellar progenitors are known, promising better leverage on cosmic evolution. In addition, their rate - which closely tracks the ongoing star formation rate - is expected to rise significantly with look- back time, ensuring an adequate supply of distant examples. - These data will competitively constrain the dark energy equation of state, allow the determination of the Hubble constant to 5%, and promote our understanding of the processes involved in the last dramatic phases of massive stellar evolution.Comment: Science white paper, submitted to the Decadal committee Astro201

Raman signal from a hindered hydrogen rotor

We present a method for calculation of Raman modes of the quantum solid phase I hydrogen and deuterium. We use the mean-field assumption that the quantized excitations are localized on one molecule. This is done by explicit solution of the time-dependent Schroedinger equation in an angle-dependent potential, and direct calculation of the polarization. We show that in the free rotor limit, the H₂ and D₂ frequencies differ by a factor of 2, which evolves toward √2 as the modes acquire librational character due to stronger interactions. The ratio overshoots √2 if anharmonic terms weaken the harmonic potential. We also use density functional theory and molecular dynamics to calculate the E_(2g) optical phonon frequency and the Raman linewidths. The molecular dynamics shows that the molecules are not free rotors except at very low pressure and high temperature, and become like oscillators as phase II is approached. We fit the interaction strengths to experimental frequencies, but good agreement for intensities requires us to also include strong preferred orientation and stimulated Raman effects between S₀ (1) and S₀ (0) contributions. The experimental Raman spectrum for phase II cannot be reproduced, suggesting that the mean-field assumption is invalid in that case

Bim and Bmf synergize to induce apoptosis in Neisseria gonorrhoeae infection

Abstract: Bcl-2 family proteins including the pro-apoptotic BH3-only proteins are central regulators of apoptotic cell death. Here we show by a focused siRNA miniscreen that the synergistic action of the BH3-only proteins Bim and Bmf is required for apoptosis induced by infection with Neisseria gonorrhoeae (Ngo). While Bim and Bmf were associated with the cytoskeleton of healthy cells, they both were released upon Ngo infection. Loss of Bim and Bmf from the cytoskeleton fraction required the activation of Jun-N-terminal kinase-1 (JNK-1), which in turn depended on Rac-1. Depletion and inhibition of Rac-1, JNK-1, Bim, or Bmf prevented the activation of Bak and Bax and the subsequent activation of caspases. Apoptosis could be reconstituted in Bim-depleted and Bmf-depleted cells by additional silencing of antiapoptotic Mcl-1 and Bcl-XL, respectively. Our data indicate a synergistic role for both cytoskeletal-associated BH3-only proteins, Bim, and Bmf, in an apoptotic pathway leading to the clearance of Ngo-infected cells. Author Summary: A variety of physiological death signals, as well as pathological insults, trigger apoptosis, a genetically programmed form of cell death. Pathogens often induce host cell apoptosis to establish a successful infection. Neisseria gonorrhoeae (Ngo), the etiological agent of the sexually transmitted disease gonorrhoea, is a highly adapted obligate human-specific pathogen and has been shown to induce apoptosis in infected cells. Here we unveil the molecular mechanisms leading to apoptosis of infected cells. We show that Ngo-mediated apoptosis requires a special subset of proapoptotic proteins from the group of BH3-only proteins. BH3-only proteins act as stress sensors to translate toxic environmental signals to the initiation of apoptosis. In a siRNA-based miniscreen, we found Bim and Bmf, BH3-only proteins associated with the cytoskeleton, necessary to induce host cell apoptosis upon infection. Bim and Bmf inactivated different inhibitors of apoptosis and thereby induced cell death in response to infection. Our data unveil a novel pathway of infection-induced apoptosis that enhances our understanding of the mechanism by which BH3-only proteins control apoptotic cell death

Poverty moderates the association between gender and school dropout in South African adolescents

This study examined prospective associations between poverty, gender, and school dropout in a large community sample of South African adolescents (baseline: n = 3515, follow-up: n = 3401, 57% female, age range at baseline: 10–17 years, mean age at baseline = 13.45). School dropout was defined as being enrolled in school at baseline assessment but no longer enrolled in school at follow-up assessment. Poverty was measured at baseline assessment using an index of access to the eight highest socially perceived necessities for South African children and adolescents. Demographic characteristics including child gender and age, province, and urban versus rural location were recorded at baseline assessment and controlled for in the analysis. As predicted, higher poverty scores (AOR = 2.01, p < .001) were associated with increased odds of school dropout 1 year later. Gender was not a significant predictor of school dropout (AOR = 1.56, p = .07) but did interact with poverty (AOR = 0.66, p = .04) in predicting school dropout. However, our initial hypothesis that the impact of poverty on school dropout would be stronger for girls than boys was not supported. Instead, results indicated that while girls were at elevated risk of school dropout at low and mean levels of poverty, at high levels of poverty this gender difference was no longer evident. Findings suggest that vulnerable boys should not be neglected in policies to improve retention in education in contexts of extreme poverty

Profiling allele-specific gene expression in brains from individuals with autism spectrum disorder reveals preferential minor allele usage.

One fundamental but understudied mechanism of gene regulation in disease is allele-specific expression (ASE), the preferential expression of one allele. We leveraged RNA-sequencing data from human brain to assess ASE in autism spectrum disorder (ASD). When ASE is observed in ASD, the allele with lower population frequency (minor allele) is preferentially more highly expressed than the major allele, opposite to the canonical pattern. Importantly, genes showing ASE in ASD are enriched in those downregulated in ASD postmortem brains and in genes harboring de novo mutations in ASD. Two regions, 14q32 and 15q11, containing all known orphan C/D box small nucleolar RNAs (snoRNAs), are particularly enriched in shifts to higher minor allele expression. We demonstrate that this allele shifting enhances snoRNA-targeted splicing changes in ASD-related target genes in idiopathic ASD and 15q11-q13 duplication syndrome. Together, these results implicate allelic imbalance and dysregulation of orphan C/D box snoRNAs in ASD pathogenesis

A Systematic Mapping Approach of 16q12.2/FTO and BMI in More Than 20,000 African Americans Narrows in on the Underlying Functional Variation: Results from the Population Architecture using Genomics and Epidemiology (PAGE) Study

Genetic variants in intron 1 of the fat mass- and obesity-associated (FTO) gene have been consistently associated with body mass index (BMI) in Europeans. However, follow-up studies in African Americans (AA) have shown no support for some of the most consistently BMI-associated FTO index single nucleotide polymorphisms (SNPs). This is most likely explained by different race-specific linkage disequilibrium (LD) patterns and lower correlation overall in AA, which provides the opportunity to fine-map this region and narrow in on the functional variant. To comprehensively explore the 16q12.2/FTO locus and to search for second independent signals in the broader region, we fine-mapped a 646-kb region, encompassing the large FTO gene and the flanking gene RPGRIP1L by investigating a total of 3,756 variants (1,529 genotyped and 2,227 imputed variants) in 20,488 AAs across five studies. We observed associations between BMI and variants in the known FTO intron 1 locus: the SNP with the most significant p-value, rs56137030 (8.3×10-6) had not been highlighted in previous studies. While rs56137030was correlated at r2>0.5 with 103 SNPs in Europeans (including the GWAS index SNPs), this number was reduced to 28 SNPs in AA. Among rs56137030 and the 28 correlated SNPs, six were located within candidate intronic regulatory elements, including rs1421085, for which we predicted allele-specific binding affinity for the transcription factor CUX1, which has recently been implicated in the regulation of FTO. We did not find strong evidence for a second independent signal in the broader region. In summary, this large fine-mapping study in AA has substantially reduced the number of common alleles that are likely to be functional candidates of the known FTO locus. Importantly our study demonstrated that comprehensive fine-mapping in AA provides a powerful approach to narrow in on the functional candidate(s) underlying the initial GWAS findings in European populations

Genetics of callous-unemotional behavior in children

Callous-unemotional behavior (CU) is currently under consideration as a subtyping index for conduct disorder diagnosis. Twin studies routinely estimate the heritability of CU as greater than 50%. It is now possible to estimate genetic influence using DNA alone from samples of unrelated individuals, not relying on the assumptions of the twin method. Here we use this new DNA method (implemented in a software package called Genome-wide Complex Trait Analysis, GCTA) for the first time to estimate genetic influence on CU. We also report the first genome-wide association (GWA) study of CU as a quantitative trait. We compare these DNA results to those from twin analyses using the same measure and the same community sample of 2,930 children rated by their teachers at ages 7, 9 and 12. GCTA estimates of heritability were near zero, even though twin analysis of CU in this sample confirmed the high heritability of CU reported in the literature, and even though GCTA estimates of heritability were substantial for cognitive and anthropological traits in this sample. No significant associations were found in GWA analysis, which, like GCTA, only detects additive effects of common DNA variants. The phrase ‘missing heritability’ was coined to refer to the gap between variance associated with DNA variants identified in GWA studies versus twin study heritability. However, GCTA heritability, not twin study heritability, is the ceiling for GWA studies because both GCTA and GWA are limited to the overall additive effects of common DNA variants, whereas twin studies are not. This GCTA ceiling is very low for CU in our study, despite its high twin study heritability estimate. The gap between GCTA and twin study heritabilities will make it challenging to identify genes responsible for the heritability of CU

A Flexible and Accurate Genotype Imputation Method for the Next Generation of Genome-Wide Association Studies

Genotype imputation methods are now being widely used in the analysis of genome-wide association studies. Most imputation analyses to date have used the HapMap as a reference dataset, but new reference panels (such as controls genotyped on multiple SNP chips and densely typed samples from the 1,000 Genomes Project) will soon allow a broader range of SNPs to be imputed with higher accuracy, thereby increasing power. We describe a genotype imputation method (IMPUTE version 2) that is designed to address the challenges presented by these new datasets. The main innovation of our approach is a flexible modelling framework that increases accuracy and combines information across multiple reference panels while remaining computationally feasible. We find that IMPUTE v2 attains higher accuracy than other methods when the HapMap provides the sole reference panel, but that the size of the panel constrains the improvements that can be made. We also find that imputation accuracy can be greatly enhanced by expanding the reference panel to contain thousands of chromosomes and that IMPUTE v2 outperforms other methods in this setting at both rare and common SNPs, with overall error rates that are 15%–20% lower than those of the closest competing method. One particularly challenging aspect of next-generation association studies is to integrate information across multiple reference panels genotyped on different sets of SNPs; we show that our approach to this problem has practical advantages over other suggested solutions