Genomic analysis of post-mating changes in the honey bee queen (Apis mellifera)

<p>Abstract</p> <p>Background</p> <p>The molecular mechanisms underlying the post-mating behavioral and physiological transitions undergone by females have not been explored in great detail. Honey bees represent an excellent model system in which to address these questions because they exhibit a range of "mating states," with two extremes (virgins and egg-laying, mated queens) that differ dramatically in their behavior, pheromone profiles, and physiology. We used an incompletely-mated mating-state to understand the molecular processes that underlie the transition from a virgin to a mated, egg-laying queen. We used same-aged virgins, queens that mated once but did not initiate egg-laying, and queens that mated once and initiated egg-laying.</p> <p>Results</p> <p>Differences in the behavior and physiology among groups correlated with the underlying variance observed in the top 50 predictive genes in the brains and the ovaries. These changes were correlated with either a behaviorally-associated pattern or a physiologically-associated pattern. Overall, these results suggest that the brains and the ovaries of queens are uncoupled or follow different timescales; the initiation of mating triggers immediate changes in the ovaries, while changes in the brain may require additional stimuli or take a longer time to complete. Comparison of our results to previous studies of post-mating changes in <it>Drosophila melanogaster </it>identified common biological processes affected by mating, including stress response and alternative-splicing pathways. Comparison with microarray data sets related to worker behavior revealed no obvious correlation between genes regulated by mating and genes regulated by behavior/physiology in workers.</p> <p>Conclusion</p> <p>Studying the underlying molecular mechanisms of post-mating changes in honey bee queens will not only give us insight into how molecular mechanisms regulate physiological and behavioral changes, but they may also lead to important insights into the evolution of social behavior. Post-mating changes in gene regulation in the brains and ovaries of honey bee queens appear to be triggered by different stimuli and may occur on different timescales, potentially allowing changes in the brains and the ovaries to be uncoupled.</p

The draft genome of a socially polymorphic halictid bee, Lasioglossum albipes

Background: Taxa that harbor natural phenotypic variation are ideal for ecological genomic approaches aimed at understanding how the interplay between genetic and environmental factors can lead to the evolution of complex traits. Lasioglossum albipes is a polymorphic halictid bee that expresses variation in social behavior among populations, and common-garden experiments have suggested that this variation is likely to have a genetic component. Results: We present the L. albipes genome assembly to characterize the genetic and ecological factors associated with the evolution of social behavior. The de novo assembly is comparable to other published social insect genomes, with an N50 scaffold length of 602 kb. Gene families unique to L. albipes are associated with integrin-mediated signaling and DNA-binding domains, and several appear to be expanded in this species, including the glutathione-s-transferases and the inositol monophosphatases. L. albipes has an intact DNA methylation system, and in silico analyses suggest that methylation occurs primarily in exons. Comparisons to other insect genomes indicate that genes associated with metabolism and nucleotide binding undergo accelerated evolution in the halictid lineage. Whole-genome resequencing data from one solitary and one social L. albipes female identify six genes that appear to be rapidly diverging between social forms, including a putative odorant receptor and a cuticular protein. Conclusions: L. albipes represents a novel genetic model system for understanding the evolution of social behavior. It represents the first published genome sequence of a primitively social insect, thereby facilitating comparative genomic studies across the Hymenoptera as a whole

Variation in DNA Methylation Is Not Consistently Reflected by Sociality in Hymenoptera

Changes in gene regulation that underlie phenotypic evolution can be encoded directly in the DNA sequence or mediated by chromatin modifications such as DNA methylation. It has been hypothesized that the evolution of eusocial division of labor is associated with enhanced gene regulatory potential, which may include expansions in DNA methylation in the genomes of Hymenoptera (bees, ants, wasps, and sawflies). Recently, this hypothesis garnered support from analyses of a commonly used metric to estimate DNA methylation in silico, CpG content. Here, we test this hypothesis using direct, nucleotide-level measures of DNA methylation across nine species of Hymenoptera. In doing so, we generated new DNA methylomes for three species of interest, including one solitary and one facultatively eusocial halictid bee and a sawfly. We demonstrate that the strength of correlation between CpG content and DNA methylation varies widely among hymenopteran taxa, highlighting shortcomings in the utility of CpG content as a proxy for DNA methylation in comparative studies of taxa with sparse DNA methylomes. We observed strikingly high levels of DNA methylation in the sawfly relative to other investigated hymenopterans. Analyses of molecular evolution suggest the relatively distinct sawfly DNA methylome may be associated with positive selection on functional DNMT3 domains. Sawflies are an outgroup to all ants, bees, and wasps, and no sawfly species are eusocial. We find no evidence that either global expansions or variation within individual ortholog groups in DNA methylation are consistently associated with the evolution of social behavior

A Search for Parent-of-Origin Effects on Honey Bee Gene Expression

Parent-specific gene expression (PSGE) is little known outside of mammals and plants. PSGE occurs when the expression level of a gene depends on whether an allele was inherited from the mother or the father. Kin selection theory predicts that there should be extensive PSGE in social insects because social insect parents can gain inclusive fitness benefits by silencing parental alleles in female offspring. We searched for evidence of PSGE in honey bees using transcriptomes from reciprocal crosses between European and Africanized strains. We found 46 transcripts with significant parent-of-origin effects on gene expression, many of which overexpressed the maternal allele. Interestingly, we also found a large proportion of genes showing a bias toward maternal alleles in only one of the reciprocal crosses. These results indicate that PSGE may occur in social insects. The nonreciprocal effects could be largely driven by hybrid incompatibility between these strains. Future work will help to determine if these are indeed parent-of-origin effects that can modulate inclusive fitness benefits

Investigating the Viral Ecology of Global Bee Communities with High-Throughput Metagenomics

Bee viral ecology is a fascinating emerging area of research: viruses exert a range of effects on their hosts, exacerbate the impacts of other environmental stressors, and, importantly, are readily shared across multiple bee species in a community. However, our understanding of bee viral communities is limited, as it is primarily derived from studies of North American and European Apis mellifera populations. Here, we examined viruses in populations of A. mellifera and 11 other bee species from 9 countries, across 5 continents and Oceania. We developed a novel pipeline to rapidly, inexpensively, and robustly screen for bee viruses. This pipeline includes purification of encapsulated RNA/DNA viruses, sequence-independent amplification, high throughput sequencing, integrated assembly of contigs, and filtering to identify contigs specifically corresponding to viral sequences. We identified sequences corresponding to (+)ssRNA, (-)ssRNA, dsRNA, and ssDNA viruses. Overall, we found 127 contigs corresponding to novel viruses (i.e. previously not observed in bees), with 29 represented by \u3e0.1% of the reads in a given sample. These viruses and viral families were distributed across multiple regions and species. This study provides a robust pipeline for metagenomics analysis of viruses, and greatly expands our understanding of the diversity of viruses found in bee communities

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts