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Although typical journal publications take the form of research articles, there are other avenues to publishing that might help with building up your CV or immersing yourself in research. I recently wrote a critical commentary after coming across an article that I had some objections towards. The process was both interesting and educational, and commentaries can be an important step in facilitating dialogues between researchers. Here, I have summarised my hints and tips to help others who might consider this route to publishing.

Despite strong evidence of heritability and growing discovery of genetic markers for major mental illness, little is known about how gene expression in the brain differs across psychiatric diagnoses, or how known genetic risk factors shape these differences. Here we investigate expressed genes and gene transcripts in postmortem subgenual anterior cingulate cortex (sgACC), a key component of limbic circuits linked to mental illness. RNA obtained postmortem from 200 donors diagnosed with bipolar disorder, schizophrenia, major depression, or no psychiatric disorder was deeply sequenced to quantify expression of over 85,000 gene transcripts, many of which were rare. Case–control comparisons detected modest expression differences that were correlated across disorders. Case–case comparisons revealed greater expression differences, with some transcripts showing opposing patterns of expression between diagnostic groups, relative to controls. The ~250 rare transcripts that were differentially-expressed in one or more disorder groups were enriched for genes involved in synapse formation, cell junctions, and heterotrimeric G-protein complexes. Common genetic variants were associated with transcript expression (eQTL) or relative abundance of alternatively spliced transcripts (sQTL). Common genetic variants previously associated with disease risk were especially enriched for sQTLs, which together accounted for disproportionate fractions of diagnosis-specific heritability. Genetic risk factors that shape the brain transcriptome may contribute to diagnostic differences between broad classes of mental illness.

Our Meet the Supervisors section is aimed at connecting postgraduate psychology students with potential supervisors and any corresponding opportunities for PhD, RA or postdoctoral research projects they may have in the future. We want to showcase some of the amazing supervisors and research positions out there. We also aim to humanise the PhD/RA/postdoctoral application process a little! Wouldn’t you like to know a few fun facts about a supervisor before applying to work with them? We hope that our readers find this a useful opportunity to learn more and reach out to one another, building more connections and collaborations across the UK.

It’s easy to spot someone wearing a mask, right? Well, new research suggests that it can be much harder than you think. Masks are a great way to help actors get into character and scare young children at Halloween. Unfortunately, they can also help criminals to commit identity fraud. Hyper-realistic silicone masks of the kind that get torn off in Tom Cruise’s Mission: Impossible movies are being are being used to commit identity crimes.These masks are incredibly detailed, complete with hair, freckles and wrinkles. They cover the head and chest of the wearer, and include holes for the eyes and mouth which blend seamlessly with the wearer’s skin to create a lifelike appearance. There have been a number of prominent cases of people successfully using these masks to fool others. In 2010, CNN reported that an Asian man in his twenties passed through Hong Kong Passport Control undetected, despite wearing a mask that disguised him as an elderly white man which resembled the individual in his stolen passport. He was only detected when a fellow traveller noticed that he had removed the mask during his flight to Canada. The mask wearer was apprehended by the police on landing.

Causal genes and variants within genome-wide association study (GWAS) loci can be identified by integrating GWAS statistics with expression quantitative trait loci (eQTL) and determining which variants underlie both GWAS and eQTL signals. Most analyses, however, consider only the marginal eQTL signal, rather than dissect this signal into multiple conditionally independent signals for each gene. Here we show that analyzing conditional eQTL signatures, which could be important under specific cellular or temporal contexts, leads to improved fine mapping of GWAS associations. Using genotypes and gene expression levels from post-mortem human brain samples (n = 467) reported by the CommonMind Consortium (CMC), we find that conditional eQTL are widespread; 63% of genes with primary eQTL also have conditional eQTL. In addition, genomic features associated with conditional eQTL are consistent with context-specific (e.g., tissue-, cell type-, or developmental time point-specific) regulation of gene expression. Integrating the 2014 Psychiatric Genomics Consortium schizophrenia (SCZ) GWAS and CMC primary and conditional eQTL data reveals 40 loci with strong evidence for co-localization (posterior probability > 0.8), including six loci with co-localization of conditional eQTL. Our co-localization analyses support previously reported genes, identify novel genes associated with schizophrenia risk, and provide specific hypotheses for their functional follow-up.

The Integrated Workload Scale (IWS) is a scale for the assessment of subjective workload in real-time that was specifically designed for use with train traffic controllers. The IWS has nine anchor points that describe the degree of workload – ranging from ‘not demanding’ to ‘work too demanding’ – and captures the multi-dimensionality of workload by incorporating items that reflect time, demand and effort. In this paper, we describe how we translated the IWS into Dutch and subsequently validated the translation by having English-language students, Dutch students and Dutch train traffic controllers rate the individual items of the IWS according to the amount of workload each item conveyed, on a scale ranging from 0 (‘no workload at all’) to 150 (‘complete overload’). A comparison between the ratings of the English and Dutch items showed no significant differences, suggesting that the English and Dutch versions of the IWS are perceived similarly. Moreover, a comparison between the Dutch students and train traffic controllers also showed no apparent differences in the items' ratings. Regression analyses showed a strong linear component reflecting that the items were roughly equidistant on the rating scale. In a final analysis, alternate translations were tested as possible substitutes for some of the original items, but were not considered to substantially improve the scale. In sum, the similarity of the Dutch IWS to the original IWS, as well as the fact that train traffic controllers and students gave similar ratings on the Dutch IWS, suggest that it is a robust and reliable tool for subjective workload assessment across different populations and that it can be reliably translated to other languages.

Schizophrenia and bipolar disorder are serious mental illnesses that affect more than 2% of adults. While large-scale genetics studies have identified genomic regions associated with disease risk, less is known about the molecular mechanisms by which risk alleles with small effects lead to schizophrenia and bipolar disorder. In order to fill this gap between genetics and disease phenotype, we have undertaken a multi-cohort genomics study of postmortem brains from controls, individuals with schizophrenia and bipolar disorder. Here we present a public resource of functional genomic data from the dorsolateral prefrontal cortex (DLPFC; Brodmann areas 9 and 46) of 986 individuals from 4 separate brain banks, including 353 diagnosed with schizophrenia and 120 with bipolar disorder. The genomic data include RNA-seq and SNP genotypes on 980 individuals, and ATAC-seq on 269 individuals, of which 264 are a subset of individuals with RNA-seq. We have performed extensive preprocessing and quality control on these data so that the research community can take advantage of this public resource available on the Synapse platform at http://CommonMind.org., Measurement(s)genotype • assay for transposase-accessible chromatin using sequencing • transcription profiling assay • bipolar disorder • schizophreniaTechnology Type(s)RNA sequencing • genotyping • ATAC-seqFactor Type(s)postmortem interval • age • biological sex • experimental groupSample Characteristic - OrganismHomo sapiens Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.9747479

How do differences in onset, symptoms, and treatment response arise between various mental illnesses despite substantial overlap of genetic risk factors? To address this question, we carried out deep RNA sequencing of human postmortem subgenual anterior cingulate cortex, a key component of limbic circuits linked to mental illness. Samples were obtained from 200 individuals diagnosed with bipolar disorder, schizophrenia, or major depression, and controls. Differential expression analysis in cases versus controls detected modest differences that were similar across disorders, although transcript-level differences were more pronounced. Case-case comparisons revealed greater expression differences between disorders, including many genes and transcripts that were expressed in opposite directions in each diagnostic group, compared to controls. Relative transcript abundances were associated with common genetic variants that accounted for disproportionate fractions of diagnosis-specific heritability. Inherited genetic risk factors shape the brain transcriptome and contribute to diagnostic differences between broad classes of mental illness.

Transcriptomic imputation approaches offer an opportunity to test associations between disease and gene expression in otherwise inaccessible tissues, such as brain, by combining eQTL reference panels with large-scale genotype data. These genic associations could elucidate signals in complex GWAS loci and may disentangle the role of different tissues in disease development. Here, we use the largest eQTL reference panel for the dorso-lateral pre-frontal cortex (DLPFC), collected by the CommonMind Consortium, to create a set of gene expression predictors and demonstrate their utility. We applied these predictors to 40,299 schizophrenia cases and 65,264 matched controls, constituting the largest transcriptomic imputation study of schizophrenia to date. We also computed predicted gene expression levels for 12 additional brain regions, using publicly available predictor models from GTEx. We identified 413 genic associations across 13 brain regions. Stepwise conditioning across the genes and tissues identified 71 associated genes (67 outside the MHC), with the majority of associations found in the DLPFC, and of which 14/67 genes did not fall within previously genome-wide significant loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple pathways associated with porphyric disorders. We investigated developmental expression patterns for all 67 non-MHC associated genes using BRAINSPAN, and identified groups of genes expressed specifically pre-natally or post-natally.

Bipolar disorder is a complex neuropsychiatric disorder presenting with episodic mood disturbances. In this study we use a transcriptomic imputation approach to identify novel genes and pathways associated with bipolar disorder, as well as three diagnostically and genetically distinct subtypes. Transcriptomic imputation approaches leverage well-curated and publicly available eQTL reference panels to create gene-expression prediction models, which may then be applied to “impute” genetically regulated gene expression (GREX) in large GWAS datasets. By testing for association between phenotype and GREX, rather than genotype, we hope to identify more biologically interpretable associations, and thus elucidate more of the genetic architecture of bipolar disorder.We applied GREX prediction models for 13 brain regions (derived from CommonMind Consortium and GTEx eQTL reference panels) to 21,488 bipolar cases and 54,303 matched controls, constituting the largest transcriptomic imputation study of bipolar disorder (BPD) to date. Additionally, we analyzed three specific BPD subtypes, including 14,938 individuals with subtype 1 (BD-I), 3,543 individuals with subtype 2 (BD-II), and 1,500 individuals with schizoaffective subtype (SAB).We identified 125 gene-tissue associations with BPD, of which 53 represent independent associations after FINEMAP analysis. 29/53 associations were novel; i.e., did not lie within 1Mb of a locus identified in the recent PGC-BD GWAS. We identified 37 independent BD-I gene-tissue associations (10 novel), 2 BD-II associations, and 2 SAB associations. Our BPD, BD-I and BD-II associations were significantly more likely to be differentially expressed in post-mortem brain tissue of BPD, BD-I and BD-II cases than we might expect by chance. Together with our pathway analysis, our results support long-standing hypotheses about bipolar disorder risk, including a role for oxidative stress and mitochondrial dysfunction, the post-synaptic density, and an enrichment of circadian rhythm and clock genes within our results.

Causal genes and variants within genome-wide association study (GWAS) loci can be identified by integrating GWAS statistics with expression quantitative trait loci (eQTL) and determining which SNPs underlie both GWAS and eQTL signals. Most analyses, however, consider only the marginal eQTL signal, rather than dissecting this signal into multiple independent eQTL for each gene. Here we show that analyzing conditional eQTL signatures, which could be important under specific cellular or temporal contexts, leads to improved fine mapping of GWAS associations. Using genotypes and gene expression levels from post-mortem human brain samples (N=467) reported by the CommonMind Consortium (CMC), we find that conditional eQTL are widespread; 63% of genes with primary eQTL also have conditional eQTL. In addition, genomic features associated with conditional eQTL are consistent with context specific (i.e. tissue, cell type, or developmental time point specific) regulation of gene expression. Integrating the Psychiatric Genomics Consortium schizophrenia (SCZ) GWAS and CMC conditional eQTL data reveals forty loci with strong evidence for co-localization (posterior probability >0.8), including six loci with co-localization of conditional eQTL. Our co-localization analyses support previously reported genes and identify novel genes for schizophrenia risk, and provide specific hypotheses for their functional follow-up.

Over 100 genetic loci harbor schizophrenia associated variants, yet how these common variants confer risk is uncertain. The CommonMind Consortium has sequenced dorsolateral prefrontal cortex RNA from schizophrenia cases (n=258) and control subjects (n=279), creating the largest publicly available resource to date of gene expression and its genetic regulation; ∼5 times larger than the latest release of GTEx. Using this resource, we find that ∼20% of the schizophrenia risk loci have common variants that could explain regulation of brain gene expression. In five loci, these variants modulate expression of a single gene: FURIN, TSNARE1, CNTN4, CLCN3 or SNAP91. Experimentally altered expression of three of them, FURIN, TSNARE1, and CNTN4, perturbs the proliferation and apoptotic index of neural progenitors and leads to neuroanatomical deficits in zebrafish. Furthermore, shRNA mediated knock-down of FURIN1 in neural progenitor cells derived from human induced pluripotent stem cells produces abnormal neural migration. Although 4.2% of genes (N = 693) display significant differential expression between cases and controls, 44% show some evidence for differential expression. All fold changes are ≤ 1.33, and an independent cohort yields similar differential expression for these 693 genes (r = 0.58). These findings are consistent with schizophrenia being highly polygenic, as has been reported in investigations of common and rare genetic variation. Co-expression analyses identify a gene module that shows enrichment for genetic associations and is thus relevant for schizophrenia. Taken together, these results pave the way for mechanistic interpretations of genetic liability for schizophrenia and other brain diseases.

Over 100 genetic loci harbor schizophrenia-associated variants, yet how these variants confer liability is uncertain. The CommonMind Consortium sequenced RNA from dorsolateral prefrontal cortex of people with schizophrenia (N = 258) and control subjects (N = 279), creating a resource of gene expression and its genetic regulation. Using this resource, ∼20% of schizophrenia loci have variants that could contribute to altered gene expression and liability. In five loci, only a single gene was involved: FURIN, TSNARE1, CNTN4, CLCN3 or SNAP91. Altering expression of FURIN, TSNARE1 or CNTN4 changed neurodevelopment in zebrafish; knockdown of FURIN in human neural progenitor cells yielded abnormal migration. Of 693 genes showing significant case-versus-control differential expression, their fold changes were ≤ 1.33, and an independent cohort yielded similar results. Gene co-expression implicates a network relevant for schizophrenia. Our findings show that schizophrenia is polygenic and highlight the utility of this resource for mechanistic interpretations of genetic liability for brain diseases.

A comprehensive transcriptome assembly for pigeonpea has been developed by analyzing 128.9 million short Illumina GA IIx single end reads, 2.19 million single end FLX/454 reads, and 18 353 Sanger expressed sequenced tags from more than 16 genotypes. The resultant transcriptome assembly, referred to as CcTA v2, comprised 21 434 transcript assembly contigs (TACs) with an N50 of 1510 bp, the largest one being ∼8 kb. Of the 21 434 TACs, 16 622 (77.5%) could be mapped on to the soybean genome build 1.0.9 under fairly stringent alignment parameters. Based on knowledge of intron junctions, 10 009 primer pairs were designed from 5033 TACs for amplifying intron spanning regions (ISRs). By using in silico mapping of BAC-end-derived SSR loci of pigeonpea on the soybean genome as a reference, putative mapping positions at the chromosome level were predicted for 6284 ISR markers, covering all 11 pigeonpea chromosomes. A subset of 128 ISR markers were analyzed on a set of eight genotypes. While 116 markers were validated, 70 markers showed one to three alleles, with an average of 0.16 polymorphism information content (PIC) value. In summary, the CcTA v2 transcript assembly and ISR markers will serve as a useful resource to accelerate genetic research and breeding applications in pigeonpea.

We developed a novel approach for conducting multisample, multigene, ultradeep bisulfite sequencing analysis of DNA methylation patterns in clinical samples. A massively parallel sequencing-by-synthesis method (454 sequencing) was used to directly sequence >100 bisulfite PCR products in a single sequencing run without subcloning. We showed the utility, robustness, and superiority of this approach by analyzing methylation in 25 gene-related CpG rich regions from >40 cases of primary cells, including normal peripheral blood lymphocytes, acute lymphoblastic leukemia (ALL), chronic lymphocytic leukemia (CLL), follicular lymphoma (FL), and mantle cell lymphoma (MCL). A total of 294,631 sequences was generated with an average read length of 131 bp. On average, >1,600 individual sequences were generated for each PCR amplicon far beyond the few clones (

Microarray technologies are enabling measurements of gene expression levels at large scales. Applications of microarrays in medicine, biological engineering and agriculture often depend on quantitative studies of time-series data. For drug delivery, fed batch reactors and crop growth, time series analysis is essential in optimizing controlled biological processes. In particular, it is useful to project discrete time series data into continuous dynamic trajectories with a global gene expression model. Time series microarray data were fitted with differential equations based on Singular Value Decomposition. Using the data from two different organisms, Saccharomyces Cerevisiae and Drosophila melanogaster the local predictive accuracy was assessed with cross-fold validation across all experiments. The equations were integrated and inspected visually. The algorithm for inducing differential equations was found to produce a good fit both globally and locally.

The potato psyllid (PoP) Bactericera cockerelli (Sulc) and Asian citrus psyllid (ACP) Diaphorina citri Kuwayama are the insect vectors of the fastidious plant pathogen, Candidatus Liberibacter solanacearum (CLso) and Ca. L. asiaticus (CLas), respectively. CLso causes Zebra chip disease of potato and vein-greening in solanaceous species, whereas, CLas causes citrus greening disease. The reliance on insecticides for vector management to reduce pathogen transmission has increased interest in alternative approaches, including RNA interference to abate expression of genes essential for psyllid-mediated Ca. Liberibacter transmission. To identify genes with significantly altered expression at different life stages and conditions of CLso/CLas infection, cDNA libraries were constructed for CLso-infected and -uninfected PoP adults and nymphal instars. Illumina sequencing produced 199,081,451 reads that were assembled into 82,224 unique transcripts. PoP and the analogous transcripts from ACP adult and nymphs reported elsewhere were annotated, organized into functional gene groups using the Gene Ontology classification system, and analyzed for differential in silico expression. Expression profiles revealed vector life stage differences and differential gene expression associated with Liberibacter infection of the psyllid host, including invasion, immune system modulation, nutrition, and development.

t was the end of the day, and I had already taught the lesson three times during my earlier twelfth-grade English classes. I posed the question, "How much are you affected or influenced by advertising?" and asked students to rank themselves from one to ten, one being impervious to any type of media persuasion and ten being highly susceptible to media messages. Students assigned themselves a numeric rating and then elaborated in a written explanation. When the students finished writing, I asked them to arrange themselves around the room so that all the ones were on one side and all the tens on the other. During this class, as in each class before, I received a variety of responses. Some students openly admitted that advertising did affect them, citing examples such as buying products they had seen in magazines or getting hungry when they viewed a television commercial for a restaurant. Others were vehemently opposed to the idea that advertising or media could sway their opinions. One student declared, "I don't do anything I don't want to do. Nothing influences the way I make decisions." As he stood there, I could not help but notice that his two closest friends were beside him in the "advertising has no influence" section, and all three of them were wearing different colors of the same name-brand sweatshirt. Obviously, something had swayed their opinions. I wondered how, without lecturing or moralizing on the issue, I could enable my students to see that media influence, like the water in which fish swim in the ocean, is often invisible to us even while we are in the midst of it. No matter how subtle media influence appears, it still can shape our identity, values, and choices. It comes as no surprise to middle and high school teachers that image and identity mean a lot to students. If you have not paid much attention to what your students are wearing, simply walk down the hallways and note the popular styles and name-brand clothing. Not only might you notice that clothing styles often differentiate between those students who are deemed popular and those who are not, but you also may note that specific brand logos either mark or dominate the design of clothing that is considered in style. Last year, I might have had three to four girls wearing oversized, hooded GAP sweatshirts in one class any given day; now I have multiple young men sitting in my classes, confident of their individual style, who are all wearing the same Fox Racing, Abercrombie and Fitch, or Aeropostale t-shirts. While specific brands and student fashion trends ebb and flow like the tide, this phenomenon should not be dismissed as mere adolescent whimsy. The ubiquitous nature of brand advertising not only enables students to instantaneously recognize specific brands, but it encourages students to emotionally connect to these brands and consider them part of their identity, whether that identity is that of an athlete, a skater, a racer, a punk, or a prep. How can we as educators use this real life example to help students see that these advertisements are not naturally occurring phenomenon, but instead, like all media messages, are carefully constructed and aimed at target audiences?

Background Alfalfa, a perennial, outcrossing species, is a widely planted forage legume producing highly nutritious biomass. Currently, improvement of cultivated alfalfa mainly relies on recurrent phenotypic selection. Marker assisted breeding strategies can enhance alfalfa improvement efforts, particularly if many genome-wide markers are available. Transcriptome sequencing enables efficient high-throughput discovery of single nucleotide polymorphism (SNP) markers for a complex polyploid species. Result The transcriptomes of 27 alfalfa genotypes, including elite breeding genotypes, parents of mapping populations, and unimproved wild genotypes, were sequenced using an Illumina Genome Analyzer IIx. De novo assembly of quality-filtered 72-bp reads generated 25,183 contigs with a total length of 26.8 Mbp and an average length of 1,065 bp, with an average read depth of 55.9-fold for each genotype. Overall, 21,954 (87.2%) of the 25,183 contigs represented 14,878 unique protein accessions. Gene ontology (GO) analysis suggested that a broad diversity of genes was represented in the resulting sequences. The realignment of individual reads to the contigs enabled the detection of 872,384 SNPs and 31,760 InDels. High resolution melting (HRM) analysis was used to validate 91% of 192 putative SNPs identified by sequencing. Both allelic variants at about 95% of SNP sites identified among five wild, unimproved genotypes are still present in cultivated alfalfa, and all four US breeding programs also contain a high proportion of these SNPs. Thus, little evidence exists among this dataset for loss of significant DNA sequence diversity from either domestication or breeding of alfalfa. Structure analysis indicated that individuals from the subspecies falcata, the diploid subspecies caerulea, and the tetraploid subspecies sativa (cultivated tetraploid alfalfa) were clearly separated. Conclusion We used transcriptome sequencing to discover large numbers of SNPs segregating in elite breeding populations of alfalfa. Little loss of SNP diversity was evident between unimproved and elite alfalfa germplasm. The EST and SNP markers generated from this study are publicly available at the Legume Information System (http://medsa.comparative-legumes.org/) and can contribute to future alfalfa research and breeding applications.

Cryptophyte and chlorarachniophyte algae are transitional forms in the widespread secondary endosymbiotic acquisition of photosynthesis by engulfment of eukaryotic algae. Unlike most secondary plastid-bearing algae, miniaturized versions of the endosymbiont nuclei (nucleomorphs) persist in cryptophytes and chlorarachniophytes. To determine why, and to address other fundamental questions about eukaryote–eukaryote endosymbiosis, we sequenced the nuclear genomes of the cryptophyte Guillardia theta and the chlorarachniophyte Bigelowiella natans. Both genomes have

Premise of the study The common reed (Phragmites australis), one of the most widely distributed of all angiosperms, uses its rhizomes (underground stems) to invade new territory, making it one of the most successful weedy species worldwide. Characterization of the rhizome transcriptome and proteome is needed to identify candidate genes and proteins involved in rhizome growth, development, metabolism, and invasiveness. Methods We employed next-generation sequencing technologies including 454 and Illumina platforms to characterize the reed rhizome transcriptome and used quantitative proteomics techniques to identify the rhizome proteome. Key results Combining 336514 Roche 454 Titanium reads and 103350802 Illumina paired-end reads in a de novo hybrid assembly yielded 124450 unique transcripts with an average length of 549 bp, of which 54317 were annotated. Rhizome-specific and differentially expressed transcripts were identified between rhizome apical tips (apical meristematic region) and rhizome elongation zones. A total of 1280 nonredundant proteins were identified and quantified using GeLC-MS/MS based label-free proteomics, where 174 and 77 proteins were preferentially expressed in the rhizome elongation zone and apical tip tissues, respectively. Genes involved in allelopathy and in controlling development and potentially invasiveness were identified. Conclusions In addition to being a valuable sequence and protein data resource for studying plant rhizome species, our results provide useful insights into identifying specific genes and proteins with potential roles in rhizome differentiation, development, and function.

Background Follicular lymphoma (FL) is a form of non-Hodgkin's lymphoma (NHL) that arises from germinal center (GC) B-cells. Despite the significant advances in immunotherapy, FL is still not curable. Beyond transcriptional profiling and genomics datasets, there currently is no epigenome-scale dataset or integrative biology approach that can adequately model this disease and therefore identify novel mechanisms and targets for successful prevention and treatment of FL. Methodology/Principal Findings We performed methylation-enriched genome-wide bisulfite sequencing of FL cells and normal CD19+ B-cells using 454 sequencing technology. The methylated DNA fragments were enriched with methyl-binding proteins, treated with bisulfite, and sequenced using the Roche-454 GS FLX sequencer. The total number of bases covered in the human genome was 18.2 and 49.3 million including 726,003 and 1.3 million CpGs in FL and CD19+ B-cells, respectively. 11,971 and 7,882 methylated regions of interest (MRIs) were identified respectively. The genome-wide distribution of these MRIs displayed significant differences between FL and normal B-cells. A reverse trend in the distribution of MRIs between the promoter and the gene body was observed in FL and CD19+ B-cells. The MRIs identified in FL cells also correlated well with transcriptomic data and ChIP-on-Chip analyses of genome-wide histone modifications such as tri-methyl-H3K27, and tri-methyl-H3K4, indicating a concerted epigenetic alteration in FL cells. Conclusions/Significance This study is the first to provide a large scale and comprehensive analysis of the DNA methylation sequence composition and distribution in the FL epigenome. These integrated approaches have led to the discovery of novel and frequent targets of aberrant epigenetic alterations. The genome-wide bisulfite sequencing approach developed here can be a useful tool for profiling DNA methylation in clinical samples.

The Australian government's commitment to equal employment opportunity has resulted in the enactment of anti‐discrimination and affirmative action legislation at both the federal and state level and the development of a number of labour market, training and social policies specifically designed to remove impediments to women's employment. The Affirmative Action (Equal Employment Opportunity for Women) Act 1986 is pivotal to the removal of discrimination in organisations, but its effectiveness has been hindered by the restructuring of organisations on a divisional basis, a lack of understanding of the nature of equal employment opportunity (eeo) and the role of affirmative action programmes among some employers and employees, and the choices women make about their employment and training. A number of innovative policies have been developed by large organisations to deal with these barriers to the effectiveness of affirmative action programmes and the creation of eeo and they provide useful models for other organisations.

The Asian citrus psyllid (ACP) Diaphorina citri Kuwayama (Hemiptera: Psyllidae) is the insect vector of the fastidious bacterium Candidatus Liberibacter asiaticus (CLas), the causal agent of citrus greening disease, or Huanglongbing (HLB). The widespread invasiveness of the psyllid vector and HLB in citrus trees worldwide has underscored the need for non-traditional approaches to manage the disease. One tenable solution is through the deployment of RNA interference technology to silence protein-protein interactions essential for ACP-mediated CLas invasion and transmission. To identify psyllid interactor-bacterial effector combinations associated with psyllid-CLas interactions, cDNA libraries were constructed from CLas-infected and CLas-free ACP adults and nymphs, and analyzed for differential expression. Library assemblies comprised 24,039,255 reads and yielded 45,976 consensus contigs. They were annotated (UniProt), classified using Gene Ontology, and subjected to in silico expression analyses using the Transcriptome Computational Workbench (TCW) (http://www.sohomoptera.org/ACPPoP/). Functional-biological pathway interpretations were carried out using the Kyoto Encyclopedia of Genes and Genomes databases. Differentially expressed contigs in adults and/or nymphs represented genes and/or metabolic/pathogenesis pathways involved in adhesion, biofilm formation, development-related, immunity, nutrition, stress, and virulence. Notably, contigs involved in gene silencing and transposon-related responses were documented in a psyllid for the first time. This is the first comparative transcriptomic analysis of ACP adults and nymphs infected and uninfected with CLas. The results provide key initial insights into host-parasite interactions involving CLas effectors that contribute to invasion-virulence, and to host nutritional exploitation and immune-related responses that appear to be essential for successful ACP-mediated circulative, propagative CLas transmission.

We developed a computational tool, DigitalTree, for displaying a two-dimensional weighted tree of biological data. Existing methods, Radial Layout, Hyperbolic Layout, Phyllotactic Placement, and Force-Directing were integrated into DigitalTree. DigitalTree preserves the distances between nodes in the tree and the trees topology. The tool has been applied in analyzing microarray data and phylogenetic trees. DigitalTree is available for download at http://digbio.missouri.edu/~digtree.

The principle of discrimination‐free behaviour has been established in Australia as the basis for behaviour in organizations. This principle forms the basis of affirmative action legislation and is integrated into industrial relations legislation. Some employers in Australia have recognized that a situation which is free from discrimination and provides equal employment opportunity requires an acknowledgement of the impact of family responsibilities on work behaviour. This has resulted in the implementation of initiatives designed to accommodate work and family needs of employees. However, despite the more general acknowledgement among employers of the value of employing women in a range of positions, developments in the industrial relations arena could threaten the continued creation of equal employment opportunity.

DNA methylation is a type of chemical modification of DNA that adds a methyl group to DNA at the fifth carbon of the cytosine pyrimidine ring. In normal cells, methylation of CpG dinucleotides is extensively found across the genome. However, specific DNA regions known as the CpG islands, short CpG dinucleotide-rich stretches (500 bp - 2000bp), are commonly unmethylated. During tumorigenesis, on the other hand, global de-methylation and CpG island hypermethylation are widely observed. De novo hypermethylation at CpG dinucleotides is typically associated with loss of expression of flanking genes, thus it is believed to be an alternative to mutation and deletion in the inactivation of tumor suppressor genes. In this paper, we report that sequences flanking CpG sites can be used for predicting DNA methylation levels. DNA methylation levels were measured by utilizing a new high throughput sequencing technology (454) to sequence bisulfite treated DNA from four types of primary leukemia and lymphoma cells and normal peripheral blood lymphocytes. After measuring methylation levels at each CpG site, we used 30 bp flanking sequences to characterize methylation susceptibility in terms of character compositions and built predictive models for DNA methylation susceptibility, achieving up to 75% prediction accuracy in 10-fold cross validation tests. Our study is first of its kind to build predictive models for methylation susceptibility by utilizing CpG site specific methylation levels.