Plasticity in gene transcription explains the differential performance of two invasive fish species

Phenotypic plasticity buffers organisms from environmental change and is hypothesized to aid the initial establishment of nonindigenous species in novel environments and postestablishment range expansion. The genetic mechanisms that underpin phenotypically plastic traits are generally poorly characterized; however, there is strong evidence that modulation of gene transcription is an important component of these responses. Here, we use RNA sequencing to examine the transcriptional basis of temperature tolerance for round and tubenose goby, two nonindigenous fish species that differ dramatically in the extent of their Great Lakes invasions despite similar invasion dates. We used generalized linear models of read count data to compare gene transcription responses of organisms exposed to increased and decreased water temperature from those at ambient conditions. We identify greater response in the magnitude of transcriptional changes for the more successful round goby compared with the less successful tubenose goby. Round goby transcriptional responses reflect alteration of biological function consistent with adaptive responses to maintain or regain homeostatic function in other species. In contrast, tubenose goby transcription patterns indicate a response to stressful conditions, but the pattern of change in biological functions does not match those expected for a return to homeostatic status. Transcriptional plasticity plays an important role in the acute thermal tolerance for these species; however, the impaired response to stress we demonstrate in the tubenose goby may contribute to their limited invasion success relative to the round goby. Transcriptional profiling allows the simultaneous assessment of the magnitude of transcriptional response as well as the biological functions involved in the response to environmental stress and is thus a valuable approach for evaluating invasion potential

Generation of a non-small cell lung cancer transcriptome microarray

<p>Abstract</p> <p>Background</p> <p>Non-small cell lung cancer (NSCLC) is the leading cause of cancer mortality worldwide. At present no reliable biomarkers are available to guide the management of this condition. Microarray technology may allow appropriate biomarkers to be identified but present platforms are lacking disease focus and are thus likely to miss potentially vital information contained in patient tissue samples.</p> <p>Methods</p> <p>A combination of large-scale in-house sequencing, gene expression profiling and public sequence and gene expression data mining were used to characterise the transcriptome of NSCLC and the data used to generate a disease-focused microarray – the Lung Cancer DSA research tool.</p> <p>Results</p> <p>Built on the Affymetrix GeneChip platform, the Lung Cancer DSA research tool allows for interrogation of ~60,000 transcripts relevant to Lung Cancer, tens of thousands of which are unavailable on leading commercial microarrays.</p> <p>Conclusion</p> <p>We have developed the first high-density disease specific transcriptome microarray. We present the array design process and the results of experiments carried out to demonstrate the array's utility. This approach serves as a template for the development of other disease transcriptome microarrays, including non-neoplastic diseases.</p

Primate-specific evolution of noncoding element insertion into PLA2G4C and human preterm birth

Background The onset of birth in humans, like other apes, differs from non-primate mammals in its endocrine physiology. We hypothesize that higher primate-specific gene evolution may lead to these differences and target genes involved in human preterm birth, an area of global health significance. Methods We performed a comparative genomics screen of highly conserved noncoding elements and identified PLA2G4C, a phospholipase A isoform involved in prostaglandin biosynthesis as human accelerated. To examine whether this gene demonstrating primate-specific evolution was associated with birth timing, we genotyped and analyzed 8 common single nucleotide polymorphisms (SNPs) in PLA2G4C in US Hispanic (n = 73 preterm, 292 control), US White (n = 147 preterm, 157 control) and US Black (n = 79 preterm, 166 control) mothers. Results Detailed structural and phylogenic analysis of PLA2G4C suggested a short genomic element within the gene duplicated from a paralogous highly conserved element on chromosome 1 specifically in primates. SNPs rs8110925 and rs2307276 in US Hispanics and rs11564620 in US Whites were significant after correcting for multiple tests (p < 0.006). Additionally, rs11564620 (Thr360Pro) was associated with increased metabolite levels of the prostaglandin thromboxane in healthy individuals (p = 0.02), suggesting this variant may affect PLA2G4C activity. Conclusions Our findings suggest that variation in PLA2G4C may influence preterm birth risk by increasing levels of prostaglandins, which are known to regulate labor.Children’s Discovery InstituteMarch of Dimes Birth Defects FoundationNational Institute of General Medical Sciences (U.S.) (grant T32 GM081739)Washington University (Saint Louis, Mo.) (Mr. and Mrs. Spencer T. Olin Fellowship for Women in Graduate Study)Sigrid Jusélius FoundationSigne and Anne Gyllenberg FoundationAcademy of FinlandVanderbilt University (Turner-Hazinski grant award

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. © 2021, The Author(s)

Isolating the 130.4 nm and 135.6 nm emissions in Ganymede’s aurora using broadband optics

We discuss a technique for isolating the two main Far Ultraviolet emission lines in Ganymede’s aurora by adding flight proven transmission filters to a broad- band, wide-field imager design. We find that the ra- tio of OI emissions at 135.6 nm and 130.4 nm can be recovered if the transmission of the filters and other optical elements are well known. This ratio allows constraints to be placed on the relative abundances of O atoms and O2 molecules within Ganymede’s at- mosphere, leading to more accurate models of atmo- spheric composition

Disparities in Antihypertensive Prescribing After Stroke: Linked Data From the Australian Stroke Clinical Registry

Background and Purpose- Despite evidence to support the prescription of antihypertensive medications before hospital discharge to promote medication adherence and prevent recurrent events, many patients with stroke miss out on these medications at discharge. We aimed to examine patient, clinical, and system-level differences in the prescription of antihypertensive medications at hospital discharge after stroke. Methods- Adults with acute ischemic stroke or intracerebral hemorrhage alive at discharge were included (years 2009-2013) from 39 hospitals participating in the Australian Stroke Clinical Registry. Patient comorbidities were identified using the International Statistical Classification of Diseases and Related Health Problems (Tenth Edition, Australian Modification) codes from the hospital admissions and emergency presentation data. The outcome variable and other system factors were derived from the Australian Stroke Clinical Registry dataset. Multivariable, multilevel logistic regression was used to examine factors associated with the prescription of antihypertensive medications at hospital discharge. Results- Of the 10 315 patients included, 79.0% (intracerebral hemorrhage, 74.1%; acute ischemic stroke, 79.8%) were prescribed antihypertensive medications at discharge. Prescription varied between hospital sites, with 6 sites >2 SDs below the national average for provision of antihypertensives at discharge. Prescription was also independently associated with patient and clinical factors including history of hypertension, diabetes mellitus, management in an acute stroke unit, and discharge to rehabilitation. In patients with acute ischemic stroke, females (odds ratio, 0.85; 95% CI, 0.76-0.94), those who had greater stroke severity (odds ratio, 0.81; 95% CI 0.72-0.92), or dementia (odds ratio, 0.65; 95% CI, 0.52-0.81) were less likely to be prescribed. Conclusions- Prescription of antihypertensive medications poststroke varies between hospitals and according to patient factors including age, sex, stroke severity, and comorbidity profile. Implementation of targeted quality improvement initiatives at local hospitals may help to reduce the variation in prescription observed

Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions

Major depression is a debilitating psychiatric illness that is typically associated with low mood, anhedonia and a range of comorbidities. Depression has a heritable component that has remained difficult to elucidate with current sample sizes due to the polygenic nature of the disorder. To maximise sample size, we meta-analysed data on 807,553 individuals (246,363 cases and 561,190 controls) from the three largest genome-wide association studies of depression. We identified 102 independent variants, 269 genes, and 15 gene-sets associated with depression, including both genes and gene-pathways associated with synaptic structure and neurotransmission. Further evidence of the importance of prefrontal brain regions in depression was provided by an enrichment analysis. In an independent replication sample of 1,306,354 individuals (414,055 cases and 892,299 controls), 87 of the 102 associated variants were significant following multiple testing correction. Based on the putative genes associated with depression this work also highlights several potential drug repositioning opportunities. These findings advance our understanding of the complex genetic architecture of depression and provide several future avenues for understanding aetiology and developing new treatment approaches. The data contained in this item is described in a published manuscript located at http://dx.doi.org/10.1038/s41593-018-0326-7Howard, David; Adams, Mark; Clarke, Toni-Kim; Hafferty, Jonathan; Gibson, Jude; Shirali, Masoud; Coleman, Jonathan; Ward, Joey; Wigmore, Eleanor; Alloza, Clara; Shen, Xueyi; Barbu, Miruna; Xu, Eileen; Whalley, Heather; Marioni, Riccardo; Porteous, David; Davies, Gail; Deary, Ian; Hemani, Gibran; Tian, Chao; Hinds, David; 23andMe Research Team; Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium; Trzaskowshi, Maciej; Byrne, Enda; Ripke, Stephan; Smith, Daniel; Sullivan, Patrick; Wray, Naomi; Breen, Gerome; Lewis, Cathryn; McIntosh, Andrew; Howard, David. (2018). Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions, [dataset]. University of Edinburgh. http://dx.doi.org/10.7488/ds/2458