Search

Genome-wide association studies (GWAS) have identified hundreds of SNPs responsible for variation in human quantitative traits. However, genome-wide-significant associations often fail to replicate across independent cohorts, in apparent inconsistency with their apparent strong effects in discovery cohorts. This limited success of replication raises pervasive questions about the utility of the GWAS field. We identify all 332 studies of quantitative traits from the NHGRI-EBI GWAS Database with attempted replication. We find that the majority of studies provide insufficient data to evaluate replication rates. The remaining papers replicate significantly worse than expected (p < 10−14), even when adjusting for regression-to-the-mean of effect size between discovery- and replication-cohorts termed the Winner’s Curse (p < 10−16). We show this is due in part to misreporting replication cohort-size as a maximum number, rather than per-locus one. In 39 studies accurately reporting per-locus cohort-size for attempted replication of 707 loci in samples with similar ancestry, replication rate matched expectation (predicted 458, observed 457, p = 0.94). In contrast, ancestry differences between replication and discovery (13 studies, 385 loci) cause the most highly-powered decile of loci to replicate worse than expected, due to difference in linkage disequilibrium. [ABSTRACT FROM AUTHOR]

In recent years, genome and exome sequencing studies have implicated a plethora of new disease genes with rare causal variants. Here, I review 150 exome sequencing studies that claim to have discovered that a disease can be caused by different rare variants in the same gene, and I determine whether their methods followed the current best-practice guidelines in the interpretation of their data. Specifically, I assess whether studies appropriately assess controls for rare variants throughout the entire gene or implicated region as opposed to only investigating the specific rare variants identified in the cases, and I assess whether studies present sufficient co-segregation data for statistically significant linkage. I find that the proportion of studies performing gene-based analyses has increased with time, but that even in 2015 fewer than 40% of the reviewed studies used this method, and only 10% presented statistically significant co-segregation data. Furthermore, I find that the genes reported in these papers are explaining a decreasing proportion of cases as the field moves past most of the low-hanging fruit, with 50% of the genes from studies in 2014 and 2015 having variants in fewer than 5% of cases. As more studies focus on genes explaining relatively few cases, the importance of performing appropriate gene-based analyses is increasing. It is becoming increasingly important for journal editors and reviewers to require stringent gene-based evidence to avoid an avalanche of misleading disease gene discovery papers. [ABSTRACT FROM AUTHOR]

The prediction of phenotypic traits using high-density genomic data has many applications such as the selection of plants and animals of commercial interest; and it is expected to play an increasing role in medical diagnostics. Statistical models used for this task are usually tested using cross-validation, which implicitly assumes that new individuals (whose phenotypes we would like to predict) originate from the same population the genomic prediction model is trained on. In this paper we propose an approach based on clustering and resampling to investigate the effect of increasing genetic distance between training and target populations when predicting quantitative traits. This is important for plant and animal genetics, where genomic selection programs rely on the precision of predictions in future rounds of breeding. Therefore, estimating how quickly predictive accuracy decays is important in deciding which training population to use and how often the model has to be recalibrated. We find that the correlation between true and predicted values decays approximately linearly with respect to either FST or mean kinship between the training and the target populations. We illustrate this relationship using simulations and a collection of data sets from mice, wheat and human genetics. [ABSTRACT FROM AUTHOR]

Facial attractiveness is a complex human trait of great interest in both academia and industry. Literature on sociological and phenotypic factors associated with facial attractiveness is rich, but its genetic basis is poorly understood. In this paper, we conducted a genome-wide association study to discover genetic variants associated with facial attractiveness using 4,383 samples in the Wisconsin Longitudinal Study. We identified two genome-wide significant loci, highlighted a handful of candidate genes, and demonstrated enrichment for heritability in human tissues involved in reproduction and hormone synthesis. Additionally, facial attractiveness showed strong and negative genetic correlations with BMI in females and with blood lipids in males. Our analysis also suggested sex-specific selection pressure on variants associated with lower male attractiveness. These results revealed sex-specific genetic architecture of facial attractiveness and provided fundamental new insights into its genetic basis. [ABSTRACT FROM AUTHOR]

Although genome-wide association studies (GWASs) have discovered numerous novel genetic variants associated with many complex traits and diseases, those genetic variants typically explain only a small fraction of phenotypic variance. Factors that account for phenotypic variance include environmental factors and gene-by-environment interactions (GEIs). Recently, several studies have conducted genome-wide gene-by-environment association analyses and demonstrated important roles of GEIs in complex traits. One of the main challenges in these association studies is to control effects of population structure that may cause spurious associations. Many studies have analyzed how population structure influences statistics of genetic variants and developed several statistical approaches to correct for population structure. However, the impact of population structure on GEI statistics in GWASs has not been extensively studied and nor have there been methods designed to correct for population structure on GEI statistics. In this paper, we show both analytically and empirically that population structure may cause spurious GEIs and use both simulation and two GWAS datasets to support our finding. We propose a statistical approach based on mixed models to account for population structure on GEI statistics. We find that our approach effectively controls population structure on statistics for GEIs as well as for genetic variants. [ABSTRACT FROM AUTHOR]

Results from Genome-Wide Association Studies (GWAS) have shown that complex diseases are often affected by many genetic variants with small or moderate effects. Identifications of these risk variants remain a very challenging problem. There is a need to develop more powerful statistical methods to leverage available information to improve upon traditional approaches that focus on a single GWAS dataset without incorporating additional data. In this paper, we propose a novel statistical approach, GPA (Genetic analysis incorporating Pleiotropy and Annotation), to increase statistical power to identify risk variants through joint analysis of multiple GWAS data sets and annotation information because: (1) accumulating evidence suggests that different complex diseases share common risk bases, i.e., pleiotropy; and (2) functionally annotated variants have been consistently demonstrated to be enriched among GWAS hits. GPA can integrate multiple GWAS datasets and functional annotations to seek association signals, and it can also perform hypothesis testing to test the presence of pleiotropy and enrichment of functional annotation. Statistical inference of the model parameters and SNP ranking is achieved through an EM algorithm that can handle genome-wide markers efficiently. When we applied GPA to jointly analyze five psychiatric disorders with annotation information, not only did GPA identify many weak signals missed by the traditional single phenotype analysis, but it also revealed relationships in the genetic architecture of these disorders. Using our hypothesis testing framework, statistically significant pleiotropic effects were detected among these psychiatric disorders, and the markers annotated in the central nervous system genes and eQTLs from the Genotype-Tissue Expression (GTEx) database were significantly enriched. We also applied GPA to a bladder cancer GWAS data set with the ENCODE DNase-seq data from 125 cell lines. GPA was able to detect cell lines that are biologically more relevant to bladder cancer. The R implementation of GPA is currently available at . [ABSTRACT FROM AUTHOR]

Phosphohexomutase superfamily enzymes catalyze the reversible intramolecular transfer of a phosphoryl moiety on hexose sugars. Bacillus subtilis phosphoglucomutase PgcA catalyzes the reversible interconversion of glucose 6-phosphate (Glc-6-P) and glucose 1-phosphate (Glc-1-P), a precursor of UDP-glucose (UDP-Glc). B. subtilis phosphoglucosamine mutase (GlmM) is a member of the same enzyme superfamily that converts glucosamine 6-phosphate (GlcN-6-P) to glucosamine 1-phosphate (GlcN-1-P), a precursor of the amino sugar moiety of peptidoglycan. Here, we present evidence that B. subtilis PgcA possesses activity as a phosphoglucosamine mutase that contributes to peptidoglycan biosynthesis. This activity was made genetically apparent by the synthetic lethality of pgcA with glmR, a positive regulator of amino sugar biosynthesis, which can be specifically suppressed by overproduction of GlmM. A gain-of-function mutation in a substrate binding loop (PgcA G47S) increases this secondary activity and suppresses a glmR mutant. Our results demonstrate that bacterial phosphoglucomutases may possess secondary phosphoglucosamine mutase activity, and that this dual activity may provide some level of functional redundancy for the essential peptidoglycan biosynthesis pathway. [ABSTRACT FROM AUTHOR]

Mitochondria have been increasingly recognized as a central regulatory nexus for multiple metabolic pathways, in addition to ATP production via oxidative phosphorylation (OXPHOS). Here we show that inducing mitochondrial DNA (mtDNA) stress in Drosophila using a mitochondrially-targeted Type I restriction endonuclease (mtEcoBI) results in unexpected metabolic reprogramming in adult flies, distinct from effects on OXPHOS. Carbohydrate utilization was repressed, with catabolism shifted towards lipid oxidation, accompanied by elevated serine synthesis. Cleavage and translocation, the two modes of mtEcoBI action, repressed carbohydrate rmetabolism via two different mechanisms. DNA cleavage activity induced a type II diabetes-like phenotype involving deactivation of Akt kinase and inhibition of pyruvate dehydrogenase, whilst translocation decreased post-translational protein acetylation by cytonuclear depletion of acetyl-CoA (AcCoA). The associated decease in the concentrations of ketogenic amino acids also produced downstream effects on physiology and behavior, attributable to decreased neurotransmitter levels. We thus provide evidence for novel signaling pathways connecting mtDNA to metabolism, distinct from its role in supporting OXPHOS. [ABSTRACT FROM AUTHOR]

Plant trichomes originate from epidermal cell, forming protective structure from abiotic and biotic stresses. Different from the unicellular trichome in Arabidopsis, tomato trichomes are multicellular structure and can be classified into seven different types based on cell number, shape and the presence of glandular cells. Despite the importance of tomato trichomes in insect resistance, our understanding of the tomato trichome morphogenesis remains elusive. In this study, we quantitatively analyzed morphological traits of trichomes in tomato and further performed live imaging of cytoskeletons in stably transformed lines with actin and microtubule markers. At different developmental stages, two types of cytoskeletons exhibited distinct patterns in different trichome cells, ranging from transverse, spiral to longitudinal. This gradual transition of actin filament angle from basal to top cells could correlate with the spatial expansion mode in different cells. Further genetic screen for aberrant trichome morphology led to the discovery of a number of independent mutations in SCAR/WAVE and ARP2/3 complex, which resulted in actin bundling and distorted trichomes. Disruption of microtubules caused isotropic expansion while abolished actin filaments entirely inhibited axial extension of trichomes, indicating that microtubules and actin filaments may control distinct aspects of trichome cell expansion. Our results shed light on the roles of cytoskeletons in the formation of multicellular structure of tomato trichomes. [ABSTRACT FROM AUTHOR]

Variation in steroid hormone levels has wide implications for health and disease. The genes encoding the proteins involved in steroid disposition represent key determinants of interindividual variation in steroid levels and ultimately, their effects. Beginning with metabolomic data from genome-wide association studies (GWAS), we observed that genetic variants in the orphan transporter, SLC22A24 were significantly associated with levels of androsterone glucuronide and etiocholanolone glucuronide (sentinel SNPs p-value <1x10-30). In cells over-expressing human or various mammalian orthologs of SLC22A24, we showed that steroid conjugates and bile acids were substrates of the transporter. Phylogenetic, genomic, and transcriptomic analyses suggested that SLC22A24 has a specialized role in the kidney and appears to function in the reabsorption of organic anions, and in particular, anionic steroids. Phenome-wide analysis showed that functional variants of SLC22A24 are associated with human disease such as cardiovascular diseases and acne, which have been linked to dysregulated steroid metabolism. Collectively, these functional genomic studies reveal a previously uncharacterized protein involved in steroid homeostasis, opening up new possibilities for SLC22A24 as a pharmacological target for regulating steroid levels. [ABSTRACT FROM AUTHOR]

Comprehensive information on the timing and location of gene expression is fundamental to our understanding of embryonic development and tissue formation. While high-throughput in situ hybridization projects provide invaluable information about developmental gene expression patterns for model organisms like Drosophila, the output of these experiments is primarily qualitative, and a high proportion of protein coding genes and most non-coding genes lack any annotation. Accurate data-centric predictions of spatio-temporal gene expression will therefore complement current in situ hybridization efforts. Here, we applied a machine learning approach by training models on all public gene expression and chromatin data, even from whole-organism experiments, to provide genome-wide, quantitative spatio-temporal predictions for all genes. We developed structured in silico nano-dissection, a computational approach that predicts gene expression in >200 tissue-developmental stages. The algorithm integrates expression signals from a compendium of 6,378 genome-wide expression and chromatin profiling experiments in a cell lineage-aware fashion. We systematically evaluated our performance via cross-validation and experimentally confirmed 22 new predictions for four different embryonic tissues. The model also predicts complex, multi-tissue expression and developmental regulation with high accuracy. We further show the potential of applying these genome-wide predictions to extract tissue specificity signals from non-tissue-dissected experiments, and to prioritize tissues and stages for disease modeling. This resource, together with the exploratory tools are freely available at our webserver , which provides a valuable tool for a range of applications, from predicting spatio-temporal expression patterns to recognizing tissue signatures from differential gene expression profiles. [ABSTRACT FROM AUTHOR]

The capacity of organisms to tune their development in response to environmental cues is pervasive in nature. This phenotypic plasticity is particularly striking in plants, enabled by their modular and continuous development. A good example is the activation of lateral shoot branches in Arabidopsis, which develop from axillary meristems at the base of leaves. The activity and elongation of lateral shoots depends on the integration of many signals both external (e.g. light, nutrient supply) and internal (e.g. the phytohormones auxin, strigolactone and cytokinin). Here, we characterise natural variation in plasticity of shoot branching in response to nitrate supply using two diverse panels of Arabidopsis lines. We find extensive variation in nitrate sensitivity across these lines, suggesting a genetic basis for variation in branching plasticity. High plasticity is associated with extreme branching phenotypes such that lines with the most branches on high nitrate have the fewest under nitrate deficient conditions. Conversely, low plasticity is associated with a constitutively moderate level of branching. Furthermore, variation in plasticity is associated with alternative life histories with the low plasticity lines flowering significantly earlier than high plasticity lines. In Arabidopsis, branching is highly correlated with fruit yield, and thus low plasticity lines produce more fruit than high plasticity lines under nitrate deficient conditions, whereas highly plastic lines produce more fruit under high nitrate conditions. Low and high plasticity, associated with early and late flowering respectively, can therefore be interpreted alternative escape vs mitigate strategies to low N environments. The genetic architecture of these traits appears to be highly complex, with only a small proportion of the estimated genetic variance detected in association mapping. [ABSTRACT FROM AUTHOR]

Most current methods for detecting natural selection from DNA sequence data are limited in that they are either based on summary statistics or a composite likelihood, and as a consequence, do not make full use of the information available in DNA sequence data. We here present a new importance sampling approach for approximating the full likelihood function for the selection coefficient. Our method treats the ancestral recombination graph (ARG) as a latent variable that is integrated out using previously published Markov Chain Monte Carlo (MCMC) methods. The method can be used for detecting selection, estimating selection coefficients, testing models of changes in the strength of selection, estimating the time of the start of a selective sweep, and for inferring the allele frequency trajectory of a selected or neutral allele. We perform extensive simulations to evaluate the method and show that it uniformly improves power to detect selection compared to current popular methods such as nSL and SDS, and can provide reliable inferences of allele frequency trajectories under many conditions. We also explore the potential of our method to detect extremely recent changes in the strength of selection. We use the method to infer the past allele frequency trajectory for a lactase persistence SNP (MCM6) in Europeans. We also infer the trajectory of a SNP (EDAR) in Han Chinese, finding evidence that this allele’s age is much older than previously claimed. We also study a set of 11 pigmentation-associated variants. Several genes show evidence of strong selection particularly within the last 5,000 years, including ASIP, KITLG, and TYR. However, selection on OCA2/HERC2 seems to be much older and, in contrast to previous claims, we find no evidence of selection on TYRP1. [ABSTRACT FROM AUTHOR]

There has been much effort to prioritize genomic variants with respect to their impact on “function”. However, function is often not precisely defined: sometimes it is the disease association of a variant; on other occasions, it reflects a molecular effect on transcription or epigenetics. Here, we coupled multiple genomic predictors to build GRAM, a GeneRAlized Model, to predict a well-defined experimental target: the expression-modulating effect of a non-coding variant on its associated gene, in a transferable, cell-specific manner. Firstly, we performed feature engineering: using LASSO, a regularized linear model, we found transcription factor (TF) binding most predictive, especially for TFs that are hubs in the regulatory network; in contrast, evolutionary conservation, a popular feature in many other variant-impact predictors, has almost no contribution. Moreover, TF binding inferred from in vitro SELEX is as effective as that from in vivo ChIP-Seq. Second, we implemented GRAM integrating only SELEX features and expression profiles; thus, the program combines a universal regulatory score with an easily obtainable modifier reflecting the particular cell type. We benchmarked GRAM on large-scale MPRA datasets, achieving AUROC scores of 0.72 in GM12878 and 0.66 in a multi-cell line dataset. We then evaluated the performance of GRAM on targeted regions using luciferase assays in the MCF7 and K562 cell lines. We noted that changing the insertion position of the construct relative to the reporter gene gave very different results, highlighting the importance of carefully defining the exact prediction target of the model. Finally, we illustrated the utility of GRAM in fine-mapping causal variants and developed a practical software pipeline to carry this out. In particular, we demonstrated in specific examples how the pipeline could pinpoint variants that directly modulate gene expression within a larger linkage-disequilibrium block associated with a phenotype of interest (e.g., for an eQTL). [ABSTRACT FROM AUTHOR]

5’ ends are important for determining the fate of RNA molecules. BCDIN3D is an RNA phospho-methyltransferase that methylates the 5’ monophosphate of specific RNAs. In order to gain new insights into the molecular function of BCDIN3D, we performed an unbiased analysis of its interacting RNAs by Thermostable Group II Intron Reverse Transcriptase coupled to next generation sequencing (TGIRT-seq). Our analyses showed that BCDIN3D interacts with full-length phospho-methylated tRNAHis and miR-4454. Interestingly, we found that miR-4454 is not synthesized from its annotated genomic locus, which is a primer-binding site for an endogenous retrovirus, but rather by Dicer cleavage of mature tRNAHis. Sequence analysis revealed that miR-4454 is identical to the 3’ end of tRNAHis. Moreover, we were able to generate this ‘miRNA’ in vitro through incubation of mature tRNAHis with Dicer. As found previously for several pre-miRNAs, a 5’P-tRNAHis appears to be a better substrate for Dicer cleavage than a phospho-methylated tRNAHis. Moreover, tRNAHis 3’-fragment/’miR-4454’ levels increase in cells depleted for BCDIN3D. Altogether, our results show that in addition to microRNAs, BCDIN3D regulates tRNAHis 3’-fragment processing without negatively affecting tRNAHis’s canonical function of aminoacylation. [ABSTRACT FROM AUTHOR]

Development of eye tissue is initiated by a conserved set of transcription factors termed retinal determination network (RDN). In the fruit fly Drosophila melanogaster, the zinc-finger transcription factor Glass acts directly downstream of the RDN to control identity of photoreceptor as well as non-photoreceptor cells. Tight control of spatial and temporal gene expression is a critical feature during development, cell-fate determination as well as maintenance of differentiated tissues. The molecular mechanisms that control expression of glass, however, remain largely unknown. We here identify complex regulatory mechanisms controlling expression of the glass locus. All information to recapitulate glass expression are contained in a compact 5.2 kb cis-acting genomic element by combining different cell-type specific and general enhancers with repressor elements. Moreover, the immature RNA of the locus contains an alternative small open reading frame (smORF) upstream of the actual glass translation start, resulting in a small peptide instead of the three possible Glass protein isoforms. CRISPR/Cas9-based mutagenesis shows that the smORF is not required for the formation of functioning photoreceptors, but is able to attenuate effects of glass misexpression. Furthermore, editing the genome to generate glass loci eliminating either one or two isoforms shows that only one of the three proteins is critical for formation of functioning photoreceptors, while removing the two other isoforms did not cause defects in developmental or photoreceptor function. Our results show that eye development and function is largely unaffected by targeted manipulations of critical features of the glass transcript, suggesting a strong selection pressure to allow the formation of a functioning eye. [ABSTRACT FROM AUTHOR]

Despite intensive study, most of the specific genetic factors that contribute to variation in human height remain undiscovered. We conducted a family-based linkage study of height in a unique cohort of very large nuclear families from a founder (Jewish) population. This design allowed for increased power to detect linkage, compared to previous family-based studies. Loci we identified in discovery families could explain an estimated lower bound of 6% of the variance in height in validation families. We showed that these loci are not tagging known common variants associated with height. Rather, we suggest that the observed signals arise from variants with large effects that are rare globally but elevated in frequency in the Jewish population. [ABSTRACT FROM AUTHOR]

Postpartum depression is a severe emotional and mental disorder that involves maternal care defects and psychiatric illness. Postpartum depression is closely associated with a combination of physical changes and physiological stress during pregnancy or after parturition in stress-sensitive women. Although postpartum depression is relatively well known to have deleterious effects on the developing fetus, the influence of genetic risk factors on the development of postpartum depression remains unclear. In this study, we discovered a novel function of T cell death-associated gene 51 (TDAG51/PHLDA1) in the regulation of maternal and depressive-like behavior. After parturition, TDAG51-deficient dams showed impaired maternal behavior in pup retrieving, nursing and nest building tests. In contrast to the normal dams, the TDAG51-deficient dams also exhibited more sensitive depressive-like behaviors after parturition. Furthermore, changes in the expression levels of various maternal and depressive-like behavior-associated genes regulating neuroendocrine factor and monoamine neurotransmitter levels were observed in TDAG51-deficient postpartum brain tissues. These findings indicate that TDAG51 plays a protective role against maternal care defects and depressive-like behavior after parturition. Thus, TDAG51 is a maternal care-associated gene that functions as a crucial regulator of maternal and depressive-like behavior after parturition. [ABSTRACT FROM AUTHOR]

Telomerase, particularly its main subunit, the reverse transcriptase, TERT, prevents DNA erosion during eukaryotic chromosomal replication, but also has poorly understood non-canonical functions. Here, in the model social amoeba Dictyostelium discoideum, we show that the protein encoded by tert has telomerase-like motifs, and regulates, non-canonically, important developmental processes. Expression levels of wild-type (WT) tert were biphasic, peaking at 8 and 12 h post-starvation, aligning with developmental events, such as the initiation of streaming (~7 h) and mound formation (~10 h). In tert KO mutants, however, aggregation was delayed until 16 h. Large, irregular streams formed, then broke up, forming small mounds. The mound-size defect was not induced when a KO mutant of countin (a master size-regulating gene) was treated with TERT inhibitors, but anti-countin antibodies did rescue size in the tert KO. Although, conditioned medium (CM) from countin mutants failed to rescue size in the tert KO, tert KO CM rescued the countin KO phenotype. These and additional observations indicate that TERT acts upstream of smlA/countin: (i) the observed expression levels of smlA and countin, being respectively lower and higher (than WT) in the tert KO; (ii) the levels of known size-regulation intermediates, glucose (low) and adenosine (high), in the tert mutant, and the size defect’s rescue by supplemented glucose or the adenosine-antagonist, caffeine; (iii) the induction of the size defect in the WT by tert KO CM and TERT inhibitors. The tert KO’s other defects (delayed aggregation, irregular streaming) were associated with changes to cAMP-regulated processes (e.g. chemotaxis, cAMP pulsing) and their regulatory factors (e.g. cAMP; acaA, carA expression). Overexpression of WT tert in the tert KO rescued these defects (and size), and restored a single cAMP signaling centre. Our results indicate that TERT acts in novel, non-canonical and upstream ways, regulating key developmental events in Dictyostelium. [ABSTRACT FROM AUTHOR]

Pathogenic Salmonella strains that cause gastroenteritis are able to colonize and replicate within the intestines of multiple host species. In general, these strains have retained an ability to form the rdar morphotype, a resistant biofilm physiology hypothesized to be important for Salmonella transmission. In contrast, Salmonella strains that are host-adapted or even host-restricted like Salmonella enterica serovar Typhi, tend to cause systemic infections and have lost the ability to form the rdar morphotype. Here, we investigated the rdar morphotype and CsgD-regulated biofilm formation in two non-typhoidal Salmonella (NTS) strains that caused invasive disease in Malawian children, S. Typhimurium D23580 and S. Enteritidis D7795, and compared them to a panel of NTS strains associated with gastroenteritis, as well as S. Typhi strains. Sequence comparisons combined with luciferase reporter technology identified key SNPs in the promoter region of csgD that either shut off biofilm formation completely (D7795) or reduced transcription of this key biofilm regulator (D23580). Phylogenetic analysis showed that these SNPs are conserved throughout the African clades of invasive isolates, dating as far back as 80 years ago. S. Typhi isolates were negative for the rdar morphotype due to truncation of eight amino acids from the C-terminus of CsgD. We present new evidence in support of parallel evolution between lineages of nontyphoidal Salmonella associated with invasive disease in Africa and the archetypal host-restricted invasive serovar; S. Typhi. We hypothesize that the African invasive isolates are becoming human-adapted and ‘niche specialized’ with less reliance on environmental survival, as compared to gastroenteritis-causing isolates. [ABSTRACT FROM AUTHOR]

The metabolic symbiosis with photosynthetic algae allows corals to thrive in the oligotrophic environments of tropical seas. Different aspects of this relationship have been investigated using the emerging model organism Aiptasia. However, many fundamental questions, such as the nature of the symbiotic relationship and the interactions of nutrients between the partners remain highly debated. Using a meta-analysis approach, we identified a core set of 731 high-confidence symbiosis-associated genes that revealed host-dependent recycling of waste ammonium and amino acid synthesis as central processes in this relationship. Subsequent validation via metabolomic analyses confirmed that symbiont-derived carbon enables host recycling of ammonium into nonessential amino acids. We propose that this provides a regulatory mechanism to control symbiont growth through a carbon-dependent negative feedback of nitrogen availability to the symbiont. The dependence of this mechanism on symbiont-derived carbon highlights the susceptibility of this symbiosis to changes in carbon translocation, as imposed by environmental stress. [ABSTRACT FROM AUTHOR]

The article offers information on the problem of missing heritability. It mentions that heritability measures the overall importance of genetic inheritance in shaping differences between individuals and is defined as the fraction of trait variation in a population due to genetic inheritance; and also mentions the deepest solution to the missing heritability problem would involve identifying all of the casual genetic variants and measuring how much trait variation they explain.

The rapid digitization of genealogical and medical records enables the assembly of extremely large pedigree records spanning millions of individuals and trillions of pairs of relatives. Such pedigrees provide the opportunity to investigate the sociological and epidemiological history of human populations in scales much larger than previously possible. Linear mixed models (LMMs) are routinely used to analyze extremely large animal and plant pedigrees for the purposes of selective breeding. However, LMMs have not been previously applied to analyze population-scale human family trees. Here, we present Sparse Cholesky factorIzation LMM (Sci-LMM), a modeling framework for studying population-scale family trees that combines techniques from the animal and plant breeding literature and from human genetics literature. The proposed framework can construct a matrix of relationships between trillions of pairs of individuals and fit the corresponding LMM in several hours. We demonstrate the capabilities of Sci-LMM via simulation studies and by estimating the heritability of longevity and of reproductive fitness (quantified via number of children) in a large pedigree spanning millions of individuals and over five centuries of human history. Sci-LMM provides a unified framework for investigating the epidemiological history of human populations via genealogical records. [ABSTRACT FROM AUTHOR]

Despite ongoing large-scale population-based whole-genome sequencing (WGS) projects such as the NIH NHLBI TOPMed program and the NHGRI Genome Sequencing Program, WGS-based association analysis of complex traits remains a tremendous challenge due to the large number of rare variants, many of which are non-trait-associated neutral variants. External biological knowledge, such as functional annotations based on the ENCODE, Epigenomics Roadmap and GTEx projects, may be helpful in distinguishing causal rare variants from neutral ones; however, each functional annotation can only provide certain aspects of the biological functions. Our knowledge for selecting informative annotations a priori is limited, and incorporating non-informative annotations will introduce noise and lose power. We propose FunSPU, a versatile and adaptive test that incorporates multiple biological annotations and is adaptive at both the annotation and variant levels and thus maintains high power even in the presence of noninformative annotations. In addition to extensive simulations, we illustrate our proposed test using the TWINSUK cohort (n = 1,752) of UK10K WGS data based on six functional annotations: CADD, RegulomeDB, FunSeq, Funseq2, GERP++, and GenoSkyline. We identified genome-wide significant genetic loci on chromosome 19 near gene TOMM40 and APOC4-APOC2 associated with low-density lipoprotein (LDL), which are replicated in the UK10K ALSPAC cohort (n = 1,497). These replicated LDL-associated loci were missed by existing rare variant association tests that either ignore external biological information or rely on a single source of biological knowledge. We have implemented the proposed test in an R package “FunSPU”. [ABSTRACT FROM AUTHOR]

The roles of histone demethylation in the regulation of plant flowering, disease resistance, rhythmical response, and seed germination have been elucidated recently; however, how histone demethylation affects leaf senescence remains largely unclear. In this study, we exploited yeast one-hybrid (Y1H) to screen for the upstream regulators of NONYELLOWING1 (NYE1), and identified RELATIVE OF EARLY FLOWERING6 (REF6), a histone H3 lysine 27 tri-methylation (H3K27me3) demethylase, as a putative binding protein of NYE1 promoter. By in vivo and in vitro analyses, we demonstrated that REF6 directly binds to the motif CTCGYTY in NYE1/2 promoters through its zinc finger domain and positively regulates their expression. Loss-of-function of REF6 delayed chlorophyll (Chl) degradation, whereas overexpression of REF6 accelerated Chl degradation. Subsequently, we revealed that REF6 positively regulates the general senescence process by directly up-regulating ETHYLENE INSENSITIVE 2 (EIN2), ORESARA1 (ORE1), NAC-LIKE, ACTIVATED BY AP3/PI (NAP), PYRUVATE ORTHOPHOSPHATE DIKINASE (PPDK), PHYTOALEXIN DEFICIENT 4 (PAD4), LIPOXYGENASE 1 (LOX1), NAC DOMAIN CONTAINING PROTEIN 3 (AtNAC3), and NAC TRANSCRIPTION FACTOR-LIKE 9 (NTL9), the key regulatory and functional genes predominantly involved in the regulation of developmental leaf senescence. Importantly, loss-of-function of REF6 increased H3K27me3 levels at all the target Senescence associated genes (SAGs). We therefore conclusively demonstrate that H3K27me3 methylation represents an epigenetic mechanism prohibiting the premature transcriptional activation of key developmentally up-regulated senescence regulatory as well as functional genes in Arabidopsis. [ABSTRACT FROM AUTHOR]

At the molecular level, the evolution of new traits can be broadly divided between changes in gene expression and changes in protein-coding sequence. For proteins, the evolution of novel functions is generally thought to proceed through sequential point mutations or recombination of whole functional units. In Saccharomyces, the uptake of the sugar maltotriose into the cell is the primary limiting factor in its utilization, but maltotriose transporters are relatively rare, except in brewing strains. No known wild strains of Saccharomyces eubayanus, the cold-tolerant parent of hybrid lager-brewing yeasts (Saccharomyces cerevisiae x S. eubayanus), are able to consume maltotriose, which limits their ability to fully ferment malt extract. In one strain of S. eubayanus, we found a gene closely related to a known maltotriose transporter and were able to confer maltotriose consumption by overexpressing this gene or by passaging the strain on maltose. Even so, most wild strains of S. eubayanus lack native maltotriose transporters. To determine how this rare trait could evolve in naive genetic backgrounds, we performed an adaptive evolution experiment for maltotriose consumption, which yielded a single strain of S. eubayanus able to grow on maltotriose. We mapped the causative locus to a gene encoding a novel chimeric transporter that was formed by an ectopic recombination event between two genes encoding transporters that are unable to import maltotriose. In contrast to classic models of the evolution of novel protein functions, the recombination breakpoints occurred within a single functional domain. Thus, the ability of the new protein to carry maltotriose was likely acquired through epistatic interactions between independently evolved substitutions. By acquiring multiple mutations at once, the transporter rapidly gained a novel function, while bypassing potentially deleterious intermediate steps. This study provides an illuminating example of how recombination between paralogs can establish novel interactions among substitutions to create adaptive functions. [ABSTRACT FROM AUTHOR]

Saccharomyces eubayanus is the non-S. cerevisiae parent of the lager-brewing hybrid S. pastorianus. In contrast to most S. cerevisiae and Frohberg-type S. pastorianus strains, S. eubayanus cannot utilize the α-tri-glucoside maltotriose, a major carbohydrate in brewer’s wort. In Saccharomyces yeasts, utilization of maltotriose is encoded by the subtelomeric MAL gene family, and requires transporters for maltotriose uptake. While S. eubayanus strain CBS 12357T harbors four SeMALT genes which enable uptake of the α-di-glucoside maltose, it lacks maltotriose transporter genes. In S. cerevisiae, sequence identity indicates that maltotriose and maltose transporters likely evolved from a shared ancestral gene. To study the evolvability of maltotriose utilization in S. eubayanus CBS 12357T, maltotriose-assimilating mutants obtained after UV mutagenesis were subjected to laboratory evolution in carbon-limited chemostat cultures on maltotriose-enriched wort. An evolved strain showed improved maltose and maltotriose fermentation in 7 L fermenter experiments on industrial wort. Whole-genome sequencing revealed a novel mosaic SeMALT413 gene, resulting from repeated gene introgressions by non-reciprocal translocation of at least three SeMALT genes. The predicted tertiary structure of SeMalT413 was comparable to the original SeMalT transporters, but overexpression of SeMALT413 sufficed to enable growth on maltotriose, indicating gene neofunctionalization had occurred. The mosaic structure of SeMALT413 resembles the structure of S. pastorianus maltotriose-transporter gene SpMTY1, which has high sequences identity to alternatingly S. cerevisiae MALx1, S. paradoxus MALx1 and S. eubayanus SeMALT3. Evolution of the maltotriose transporter landscape in hybrid S. pastorianus lager-brewing strains is therefore likely to have involved mechanisms similar to those observed in the present study. [ABSTRACT FROM AUTHOR]

A common complementary strategy in Genome-Wide Association Studies (GWAS) is to perform Gene Set Analysis (GSA), which tests for the association between one phenotype of interest and an entire set of Single Nucleotide Polymorphisms (SNPs) residing in selected genes. While there exist many tools for performing GSA, popular methods often include a number of ad-hoc steps that are difficult to justify statistically, provide complicated interpretations based on permutation inference, and demonstrate poor operating characteristics. Additionally, the lack of gold standard gene set lists can produce misleading results and create difficulties in comparing analyses even across the same phenotype. We introduce the Generalized Berk-Jones (GBJ) statistic for GSA, a permutation-free parametric framework that offers asymptotic power guarantees in certain set-based testing settings. To adjust for confounding introduced by different gene set lists, we further develop a GBJ step-down inference technique that can discriminate between gene sets driven to significance by single genes and those demonstrating group-level effects. We compare GBJ to popular alternatives through simulation and re-analysis of summary statistics from a large breast cancer GWAS, and we show how GBJ can increase power by incorporating information from multiple signals in the same gene. In addition, we illustrate how breast cancer pathway analysis can be confounded by the frequency of FGFR2 in pathway lists. Our approach is further validated on two other datasets of summary statistics generated from GWAS of height and schizophrenia. [ABSTRACT FROM AUTHOR]

Dipteran or “true” flies occupy nearly every terrestrial habitat, and have evolved to feed upon a wide variety of sources including fruit, pollen, decomposing animal matter, and even vertebrate blood. Here we analyze the molecular, genetic and cellular basis of odor response in the tsetse fly Glossina morsitans, which feeds on the blood of humans and their livestock, and is a vector of deadly trypanosomes. The G. morsitans antenna contains specialized subtypes of sensilla, some of which line a sensory pit not found in the fruit fly Drosophila. We characterize distinct patterns of G. morsitans Odor receptor (GmmOr) gene expression in the antenna. We devise a new version of the “empty neuron” heterologous expression system, and use it to functionally express several GmmOrs in a mutant olfactory receptor neuron (ORN) of Drosophila. GmmOr35 responds to 1-hexen-3-ol, an odorant found in human emanations, and also alpha-pinene, a compound produced by malarial parasites. Another receptor, GmmOr9, which is expressed in the sensory pit, responds to acetone, 2-butanone and 2-propanol. We confirm by electrophysiological recording that neurons of the sensory pit respond to these odorants. Acetone and 2-butanone are strong attractants long used in the field to trap tsetse. We find that 2-propanol is also an attractant for both G. morsitans and the related species G. fuscipes, a major vector of African sleeping sickness. The results identify 2-propanol as a candidate for an environmentally friendly and practical tsetse attractant. Taken together, this work characterizes the olfactory system of a highly distinct kind of fly, and it provides an approach to identifying new agents for controlling the fly and the devastating diseases that it carries. [ABSTRACT FROM AUTHOR]

Most of the current knowledge on the genetic basis of adaptive evolution is based on the analysis of single nucleotide polymorphisms (SNPs). Despite increasing evidence for their causal role, the contribution of structural variants to adaptive evolution remains largely unexplored. In this work, we analyzed the population frequencies of 1,615 Transposable Element (TE) insertions annotated in the reference genome of Drosophila melanogaster, in 91 samples from 60 worldwide natural populations. We identified a set of 300 polymorphic TEs that are present at high population frequencies, and located in genomic regions with high recombination rate, where the efficiency of natural selection is high. The age and the length of these 300 TEs are consistent with relatively young and long insertions reaching high frequencies due to the action of positive selection. Besides, we identified a set of 21 fixed TEs also likely to be adaptive. Indeed, we, and others, found evidence of selection for 84 of these reference TE insertions. The analysis of the genes located nearby these 84 candidate adaptive insertions suggested that the functional response to selection is related with the GO categories of response to stimulus, behavior, and development. We further showed that a subset of the candidate adaptive TEs affects expression of nearby genes, and five of them have already been linked to an ecologically relevant phenotypic effect. Our results provide a more complete understanding of the genetic variation and the fitness-related traits relevant for adaptive evolution. Similar studies should help uncover the importance of TE-induced adaptive mutations in other species as well. [ABSTRACT FROM AUTHOR]

Complex chromosomal rearrangements (CCRs) are rearrangements involving more than two chromosomes or more than two breakpoints. Whole genome sequencing (WGS) allows for outstanding high resolution characterization on the nucleotide level in unique sequences of such rearrangements, but problems remain for mapping breakpoints in repetitive regions of the genome, which are known to be prone to rearrangements. Hence, multiple complementary WGS experiments are sometimes needed to solve the structures of CCRs. We have studied three individuals with CCRs: Case 1 and Case 2 presented with de novo karyotypically balanced, complex interchromosomal rearrangements (46,XX,t(2;8;15)(q35;q24.1;q22) and 46,XY,t(1;10;5)(q32;p12;q31)), and Case 3 presented with a de novo, extremely complex intrachromosomal rearrangement on chromosome 1. Molecular cytogenetic investigation revealed cryptic deletions in the breakpoints of chromosome 2 and 8 in Case 1, and on chromosome 10 in Case 2, explaining their clinical symptoms. In Case 3, 26 breakpoints were identified using WGS, disrupting five known disease genes. All rearrangements were subsequently analyzed using optical maps, linked-read WGS, and short-read WGS. In conclusion, we present a case series of three unique de novo CCRs where we by combining the results from the different technologies fully solved the structure of each rearrangement. The power in combining short-read WGS with long-molecule sequencing or optical mapping in these unique de novo CCRs in a clinical setting is demonstrated. [ABSTRACT FROM AUTHOR]

Linear mixed effect models are powerful tools used to account for population structure in genome-wide association studies (GWASs) and estimate the genetic architecture of complex traits. However, fully-specified models are computationally demanding and common simplifications often lead to reduced power or biased inference. We describe (), an extendable algorithm for repeatedly fitting complex linear models that account for multiple sources of heterogeneity, such as additive and non-additive genetic variance, spatial heterogeneity, and genotype-environment interactions. can compute approximate (yet highly accurate) frequentist test statistics or Bayesian posterior summaries at a genome-wide scale in a fraction of the time compared to existing general-purpose methods. We apply to two types of quantitative genetic analyses. The first is focused on accounting for spatial variability and non-additive genetic variance while scanning for QTL; and the second aims to identify gene expression traits affected by non-additive genetic variation. In both cases, modeling multiple sources of heterogeneity leads to new discoveries. [ABSTRACT FROM AUTHOR]

Many bacteria have complex cell shapes, but the mechanisms producing their distinctive morphologies are still poorly understood. Caulobacter crescentus, for instance, exhibits a stalk-like extension that carries an adhesive holdfast mediating surface attachment. This structure forms through zonal peptidoglycan biosynthesis at the old cell pole and elongates extensively under phosphate-limiting conditions. We analyzed the composition of cell body and stalk peptidoglycan and identified significant differences in the nature and proportion of peptide crosslinks, indicating that the stalk represents a distinct subcellular domain with specific mechanical properties. To identify factors that participate in stalk formation, we systematically inactivated and localized predicted components of the cell wall biosynthetic machinery of C. crescentus. Our results show that the biosynthesis of stalk peptidoglycan involves a dedicated peptidoglycan biosynthetic complex that combines specific components of the divisome and elongasome, suggesting that the repurposing of preexisting machinery provides a straightforward means to evolve new morphological traits. [ABSTRACT FROM AUTHOR]

Mendelian randomization (MR) has been used to estimate the causal effect of body mass index (BMI) on particular traits thought to be affected by BMI. However, BMI may also be a modifiable, causal risk factor for outcomes where there is no prior reason to suggest that a causal effect exists. We performed a MR phenome-wide association study (MR-pheWAS) to search for the causal effects of BMI in UK Biobank (n = 334 968), using the PHESANT open-source phenome scan tool. A subset of identified associations were followed up with a formal two-stage instrumental variable analysis in UK Biobank, to estimate the causal effect of BMI on these phenotypes. Of the 22 922 tests performed, our MR-pheWAS identified 587 associations below a stringent P value threshold corresponding to a 5% estimated false discovery rate. These included many previously identified causal effects, for instance, an adverse effect of higher BMI on risk of diabetes and hypertension. We also identified several novel effects, including protective effects of higher BMI on a set of psychosocial traits, identified initially in our preliminary MR-pheWAS in circa 115,000 UK Biobank participants and replicated in a different subset of circa 223,000 UK Biobank participants. Our comprehensive MR-pheWAS identified potential causal effects of BMI on a large and diverse set of phenotypes. This included both previously identified causal effects, and novel effects such as a protective effect of higher BMI on feelings of nervousness. [ABSTRACT FROM AUTHOR]

Boundary domains play important roles during morphogenesis in plants and animals, but how they contribute to patterning and growth coordination in plants is not understood. The CUC genes determine the boundary domains in the aerial part of the plants and, in particular, they have a conserved role in regulating leaf complexity across Angiosperms. Here, we used tooth formation at the Arabidopsis leaf margin controlled by the CUC2 transcription factor to untangle intertwined events during boundary-controlled morphogenesis in plants. Combining conditional restoration of CUC2 function with morphometrics as well as quantification of gene expression and hormone signaling, we first established that tooth morphogenesis involves a patterning phase and a growth phase. These phases can be separated, as patterning requires CUC2 while growth can occur independently of CUC2. Next, we show that CUC2 acts as a trigger to promote growth through the activation of three functional relays. In particular, we show that KLUH acts downstream of CUC2 to modulate auxin response and that expressing KLUH can compensate for deficient CUC2 expression during tooth growth. Together, we reveal a genetic and molecular network that allows coordination of patterning and growth by CUC2-defined boundaries during morphogenesis at the leaf margin. [ABSTRACT FROM AUTHOR]

Integration of genome-wide association studies (GWAS) and expression quantitative trait loci (eQTL) studies is needed to improve our understanding of the biological mechanisms underlying GWAS hits, and our ability to identify therapeutic targets. Gene-level association methods such as PrediXcan can prioritize candidate targets. However, limited eQTL sample sizes and absence of relevant developmental and disease context restrict our ability to detect associations. Here we propose an efficient statistical method (MultiXcan) that leverages the substantial sharing of eQTLs across tissues and contexts to improve our ability to identify potential target genes. MultiXcan integrates evidence across multiple panels using multivariate regression, which naturally takes into account the correlation structure. We apply our method to simulated and real traits from the UK Biobank and show that, in realistic settings, we can detect a larger set of significantly associated genes than using each panel separately. To improve applicability, we developed a summary result-based extension called S-MultiXcan, which we show yields highly concordant results with the individual level version when LD is well matched. Our multivariate model-based approach allowed us to use the individual level results as a gold standard to calibrate and develop a robust implementation of the summary-based extension. Results from our analysis as well as software and necessary resources to apply our method are publicly available. [ABSTRACT FROM AUTHOR]

Multiple sclerosis (MS) is an autoimmune disease with high prevalence among populations of northern European ancestry. Past studies have shown that exposure to ultraviolet radiation could explain the difference in MS prevalence across the globe. In this study, we investigate whether the difference in MS prevalence could be explained by European genetic risk factors. We characterized the ancestry of MS-associated alleles using RFMix, a conditional random field parameterized by random forests, to estimate their local ancestry in the largest assembled admixed population to date, with 3,692 African Americans, 4,915 Asian Americans, and 3,777 Hispanics. The majority of MS-associated human leukocyte antigen (HLA) alleles, including the prominent HLA-DRB1*15:01 risk allele, exhibited cosmopolitan ancestry. Ancestry-specific MS-associated HLA alleles were also identified. Analysis of the HLA-DRB1*15:01 risk allele in African Americans revealed that alleles on the European haplotype conferred three times the disease risk compared to those on the African haplotype. Furthermore, we found evidence that the European and African HLA-DRB1*15:01 alleles exhibit single nucleotide polymorphism (SNP) differences in regions encoding the HLA-DRB1 antigen-binding heterodimer. Additional evidence for increased risk of MS conferred by the European haplotype were found for HLA-B*07:02 and HLA-A*03:01 in African Americans. Most of the 200 non-HLA MS SNPs previously established in European populations were not significantly associated with MS in admixed populations, nor were they ancestrally more European in cases compared to controls. Lastly, a genome-wide search of association between European ancestry and MS revealed a region of interest close to the ZNF596 gene on chromosome 8 in Hispanics; cases had a significantly higher proportion of European ancestry compared to controls. In conclusion, our study established that the genetic ancestry of MS-associated alleles is complex and implicated that difference in MS prevalence could be explained by the ancestry of MS-associated alleles. [ABSTRACT FROM AUTHOR]

The ability to resist copper toxicity is important for microbial pathogens to survive attack by innate immune cells. A sur7Δ mutant of the fungal pathogen Candida albicans exhibits decreased virulence that correlates with increased sensitivity to copper, as well as defects in other stress responses and morphogenesis. Previous studies indicated that copper kills sur7Δ cells by a mechanism distinct from the known resistance pathways involving the Crp1 copper exporter or the Cup1 metallothionein. Since Sur7 resides in punctate plasma membrane domains known as MCC/eisosomes, we examined overexpression of SUR7 and found that it rescued the copper sensitivity of a mutant that fails to form MCC/eisosomes (pil1Δ lsp1Δ), indicating that these domains act to facilitate Sur7 function. Genetic screening identified new copper-sensitive mutants, the strongest of which were similar to sur7Δ in having altered plasma membranes due to defects in membrane trafficking, cortical actin, and morphogenesis (rvs161Δ, rvs167Δ, and arp2Δ arp3Δ). Consistent with the mutants having altered in plasma membrane organization, they were all more readily permeabilized by copper, which is known to bind phosphatidylserine and phosphatidylethanolamine and cause membrane damage. Although these phospholipids are normally localized to the intracellular leaflet of the plasma membrane, their exposure on the surface of the copper-sensitive mutants was indicated by increased susceptibility to membrane damaging agents that bind to these phospholipids. Increased copper sensitivity was also detected for a drs2Δ mutant, which lacks a phospholipid flippase that is involved in maintaining phospholipid asymmetry. Copper binds phosphatidylserine with very high affinity, and deleting CHO1 to prevent phosphatidylserine synthesis rescued the copper sensitivity of sur7Δ cells, confirming a major role for phosphatidylserine in copper sensitivity. These results highlight how proper plasma membrane architecture protects fungal pathogens from copper and attack by the immune system, thereby opening up new avenues for therapeutic intervention. [ABSTRACT FROM AUTHOR]

Many animals exploit several niches sequentially during their life cycles, a fitness referred to as ontogenetic niche shift (ONS). To successfully accomplish ONS, transition between development stages is often coupled with changes in one or more primitive, instinctive behaviors. Yet, the underlining molecular mechanisms remain elusive. We show here that Leptinotarsa decemlineata larvae finish their ONS at the wandering stage by leaving the plant and pupating in soil. At middle wandering phase, larvae also switch their phototactic behavior, from photophilic at foraging period to photophobic. We find that enhancement of juvenile hormone (JH) signal delays the phototactic switch, and vise verse. Moreover, RNA interference (RNAi)-aided knockdown of LdPTTH (prothoracicotropic hormone gene) or LdTorso (PTTH receptor gene) impairs avoidance response to light, a phenotype nonrescuable by 20-hydroxyecdysone. Consequently, the RNAi beetles pupate at the soil surface or in shallow layer of soil, with most of them failing to construct pupation chambers. Furthermore, a combination of depletion of LdPTTH/LdTorso and disturbance of JH signal causes no additive effects on light avoidance response and pupation site selection. Finally, we establish that TrpA1 (transient receptor potential (TRP) cation channel) is necessary for light avoidance behavior, acting downstream of PTTH. We conclude that JH/PTTH cascade concomitantly regulates metamorphosis and the phototaxis switch, to drive ONS of the wandering beetles from plant into soil to start the immobile pupal stage. [ABSTRACT FROM AUTHOR]

GWAS identified variants associated with birth weight (BW), childhood obesity (CO) and childhood BMI (CBMI), and placenta is a critical organ for fetal development and postnatal health. We examined the role of placental transcriptome and eQTLs in mediating the genetic causes for BW, CO and CBMI, and applied integrative analysis (Colocalization and MetaXcan). GWAS loci associated with BW, CO, and CBMI were substantially enriched for placenta eQTLs (6.76, 4.83 and 2.26 folds, respectively). Importantly, compared to eQTLs of adult tissues, only placental eQTLs contribute significantly to both anthropometry outcomes at birth (BW) and childhood phenotypes (CO/CBMI). Eight, six and one transcripts colocalized with BW, CO and CBMI risk loci, respectively. Our study reveals that placental transcription in utero likely plays a key role in determining postnatal body size, and as such may hold new possibilities for therapeutic interventions to prevent childhood obesity. [ABSTRACT FROM AUTHOR]

Sequencing of whole cancer genomes has revealed an abundance of recurrent mutations in gene-regulatory promoter regions, in particular in melanoma where strong mutation hotspots are observed adjacent to ETS-family transcription factor (TF) binding sites. While sometimes interpreted as functional driver events, these mutations are commonly believed to be due to locally inhibited DNA repair. Here, we first show that low-dose UV light induces mutations preferably at a known ETS promoter hotspot in cultured cells even in the absence of global or transcription-coupled nucleotide excision repair (NER). Further, by genome-wide mapping of cyclobutane pyrimidine dimers (CPDs) shortly after UV exposure and thus before DNA repair, we find that ETS-related mutation hotspots exhibit strong increases in CPD formation efficacy in a manner consistent with tumor mutation data at the single-base level. Analysis of a large whole genome cohort illustrates the widespread contribution of this effect to recurrent mutations in melanoma. While inhibited NER underlies a general increase in somatic mutation burden in regulatory elements including ETS sites, our data supports that elevated DNA damage formation at specific genomic bases is at the core of the prominent promoter mutation hotspots seen in skin cancers, thus explaining a key phenomenon in whole-genome cancer analyses. [ABSTRACT FROM AUTHOR]

Population structure in genotype data has been extensively studied, and is revealed by looking at the principal components of the genotype matrix. However, no similar analysis of population structure in gene expression data has been conducted, in part because a naïve principal components analysis of the gene expression matrix does not cluster by population. We identify a linear projection that reveals population structure in gene expression data. Our approach relies on the coupling of the principal components of genotype to the principal components of gene expression via canonical correlation analysis. Our method is able to determine the significance of the variance in the canonical correlation projection explained by each gene. We identify 3,571 significant genes, only 837 of which had been previously reported to have an associated eQTL in the GEUVADIS results. We show that our projections are not primarily driven by differences in allele frequency at known cis-eQTLs and that similar projections can be recovered using only several hundred randomly selected genes and SNPs. Finally, we present preliminary work on the consequences for eQTL analysis. We observe that using our projection co-ordinates as covariates results in the discovery of slightly fewer genes with eQTLs, but that these genes replicate in GTEx matched tissue at a slightly higher rate. [ABSTRACT FROM AUTHOR]

From genomic association studies, quantitative trait loci analysis, and epigenomic mapping, it is evident that significant efforts are necessary to define genetic-epigenetic interactions and understand their role in disease susceptibility and progression. For this reason, an analysis of the effects of genetic variation on gene expression and DNA methylation in human placentas at high resolution and whole-genome coverage will have multiple mechanistic and practical implications. By producing and analyzing DNA sequence variation (n = 303), DNA methylation (n = 303) and mRNA expression data (n = 80) from placentas from healthy women, we investigate the regulatory landscape of the human placenta and offer analytical approaches to integrate different types of genomic data and address some potential limitations of current platforms. We distinguish two profiles of interaction between expression and DNA methylation, revealing linear or bimodal effects, reflecting differences in genomic context, transcription factor recruitment, and possibly cell subpopulations. These findings help to clarify the interactions of genetic, epigenetic, and transcriptional regulatory mechanisms in normal human placentas. They also provide strong evidence for genotype-driven modifications of transcription and DNA methylation in normal placentas. In addition to these mechanistic implications, the data and analytical methods presented here will improve the interpretability of genome-wide and epigenome-wide association studies for human traits and diseases that involve placental functions. [ABSTRACT FROM AUTHOR]

Loss of gut integrity is linked to various human diseases including inflammatory bowel disease. However, the mechanisms that lead to loss of barrier function remain poorly understood. Using D. melanogaster, we demonstrate that dietary restriction (DR) slows the age-related decline in intestinal integrity by enhancing enterocyte cellular fitness through up-regulation of dMyc in the intestinal epithelium. Reduction of dMyc in enterocytes induced cell death, which leads to increased gut permeability and reduced lifespan upon DR. Genetic mosaic and epistasis analyses suggest that cell competition, whereby neighboring cells eliminate unfit cells by apoptosis, mediates cell death in enterocytes with reduced levels of dMyc. We observed that enterocyte apoptosis was necessary for the increased gut permeability and shortened lifespan upon loss of dMyc. Furthermore, moderate activation of dMyc in the post-mitotic enteroblasts and enterocytes was sufficient to extend health-span on rich nutrient diets. We propose that dMyc acts as a barometer of enterocyte cell fitness impacting intestinal barrier function in response to changes in diet and age. [ABSTRACT FROM AUTHOR]

Mitochondrial DNA (mtDNA) is useful to assist with identification of the source of a biological sample, or to confirm matrilineal relatedness. Although the autosomal genome is much larger, mtDNA has an advantage for forensic applications of multiple copy number per cell, allowing better recovery of sequence information from degraded samples. In addition, biological samples such as fingernails, old bones, teeth and hair have mtDNA but little or no autosomal DNA. The relatively low mutation rate of the mitochondrial genome (mitogenome) means that there can be large sets of matrilineal-related individuals sharing a common mitogenome. Here we present the simulation software that we use to describe the distribution of the number of mitogenomes in a population that match a given mitogenome, and investigate its dependence on population size and growth rate, and on a database count of the mitogenome. Further, we report on the distribution of the number of meioses separating pairs of individuals with matching mitogenome. Our results have important implications for assessing the weight of mtDNA profile evidence in forensic science, but mtDNA analysis has many non-human applications, for example in tracking the source of ivory. Our methods and software can also be used for simulations to help validate models of population history in human or non-human populations. [ABSTRACT FROM AUTHOR]

Two-component signaling systems (TCS) regulate bacterial responses to environmental signals through the process of protein phosphorylation. Specifically, sensor histidine kinases (SK) recognize signals and propagate the response via phosphorylation of a cognate response regulator (RR) that functions to initiate transcription of specific genes. Signaling within a single TCS is remarkably specific and cross-talk between TCS is limited. However, regulation of the flow of information through complex signaling networks that include closely related TCS remains largely unknown. Additionally, many bacteria utilize multi-component signaling networks which provide additional genetic and biochemical interactions that must be regulated for signaling fidelity, input and output specificity, and phosphorylation kinetics. Here we describe the characterization of an NtrC-like RR that participates in regulation of Type-IV pilus-dependent motility of Myxococcus xanthus and is thus named NmpR, trC odulator of ili egulator. A complex multi-component signaling system including NmpR was revealed by suppressor mutations that restored motility to cells lacking PilR, an evolutionarily conserved RR required for expression of pilA encoding the major Type-IV pilus monomer found in many bacterial species. The system contains at least four signaling proteins: a SK with a protoglobin sensor domain (NmpU), a hybrid SK (NmpS), a phospho-sink protein (NmpT), and an NtrC-like RR (NmpR). We demonstrate that ΔpilR bypass suppressor mutations affect regulation of the NmpRSTU multi-component system, such that NmpR activation is capable of restoring expression of pilA in the absence of PilR. Our findings indicate that pilus gene expression in M. xanthus is regulated by an extended network of TCS which interact to refine control of pilus function. [ABSTRACT FROM AUTHOR]

Plant roots are constantly exposed to a variety of abiotic stresses, and high salinity is one of the major limiting conditions that impose constraints on plant growth. In this study, we describe that OsMADS25 is required for the root growth as well as salinity tolerance, via maintaining ROS homeostasis in rice (Oryza sativa). Overexpression of OsMADS25 remarkably enhanced the primary root (PR) length and lateral root (LR) density, whereas RNAi silence of this gene reduced PR elongation significantly, with altered ROS accumulation in the root tip. Transcriptional activation assays indicated that OsMADS25 activates OsGST4 (glutathione S–transferase) expression directly by binding to its promoter. Meanwhile, osgst4 mutant exhibited repressed growth and high sensitivity to salinity and oxidative stress, and recombinant OsGST4 protein was found to have ROS–scavenging activity in vitro. Expectedly, overexpression of OsMADS25 significantly enhanced the tolerance to salinity and oxidative stress in rice plants, with the elevated activity of antioxidant enzymes, increased accumulation of osmoprotective solute proline and reduced frequency of open stoma. Furthermore, OsMADS25 specifically activated the transcription of OsP5CR, a key component of proline biosynthesis, by binding to its promoter. Interestingly, overexpression of OsMADS25 raised the root sensitivity to exogenous ABA, and the expression of ABA–dependent stress–responsive genes was elevated greatly in overexpression plants under salinity stress. In addition, OsMADS25 seemed to promote auxin signaling by activating OsYUC4 transcription. Taken together, our findings reveal that OsMADS25 might be an important transcriptional regulator that regulates the root growth and confers salinity tolerance in rice via the ABA–mediated regulatory pathway and ROS scavenging. [ABSTRACT FROM AUTHOR]

Genome-wide association studies have shown that pleiotropy is a common phenomenon that can potentially be exploited for enhanced detection of susceptibility loci. We propose heritability informed power optimization (HIPO) for conducting powerful pleiotropic analysis using summary-level association statistics. We find optimal linear combinations of association coefficients across traits that are expected to maximize non-centrality parameter for the underlying test statistics, taking into account estimates of heritability, sample size variations and overlaps across the traits. Simulation studies show that the proposed method has correct type I error, robust to population stratification and leads to desired genome-wide enrichment of association signals. Application of the proposed method to publicly available data for three groups of genetically related traits, lipids (N = 188,577), psychiatric diseases (Ncase = 33,332, Ncontrol = 27,888) and social science traits (N ranging between 161,460 to 298,420 across individual traits) increased the number of genome-wide significant loci by 12%, 200% and 50%, respectively, compared to those found by analysis of individual traits. Evidence of replication is present for many of these loci in subsequent larger studies for individual traits. HIPO can potentially be extended to high-dimensional phenotypes as a way of dimension reduction to maximize power for subsequent genetic association testing. [ABSTRACT FROM AUTHOR]