29 BRAINVAR DATA SET: WHOLE-GENOME AND RNA SEQUENCING REVEAL VARIATION AND TRANSCRIPTOMIC COORDINATION IN THE DEVELOPING HUMAN PREFRONTAL CORTEX

SummaryVariation in gene expression underlies neurotypical development, while genomic variants contribute to neuropsychiatric disorders. BrainVar is a unique resource of paired whole-genome sequencing and bulk-tissue RNA-sequencing from the human dorsolateral prefrontal cortex of 176 neurotypical individuals across prenatal and postnatal development, providing the opportunity to assay genomic and transcriptomic variation in tandem. Leveraging this resource, we identified rare premature stop codons with commensurate reduced and allele-specific expression of corresponding genes, and common variants that alter gene expression (expression quantitative trait loci, eQTLs). Categorizing eQTLs by prenatal and postnatal effect, genes affected by temporally-specific eQTLs, compared to constitutive eQTLs, are enriched for haploinsufficiency, protein-protein interactions, and neuropsychiatric disorder risk loci. Expression levels of over 12,000 genes rise or fall in a concerted late-fetal transition, with the transitional genes enriched for cell type specific genes and neuropsychiatric disorder loci, underscoring the importance of cataloguing developmental trajectories in understanding cortical physiology and pathology.HighlightsWhole-genome and RNA-sequencing across human prefrontal cortex development in BrainVarGene-specific developmental trajectories characterize the late-fetal transitionIdentification of constitutive, prenatal-specific, postnatal-specific, and rare eQTLsIntegrated analysis reveals genetic and developmental influences on CNS traits and disorders

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Classification of Prefrontal Cortex Activity Based on Functional Near-Infrared Spectroscopy Data upon Olfactory Stimulation

Brain Sciences ◽

10.3390/brainsci11060701 ◽

2021 ◽

Vol 11 (6) ◽

pp. 701

Author(s):

Cheng-Hsuan Chen ◽

Kuo-Kai Shyu ◽

Cheng-Kai Lu ◽

Chi-Wen Jao ◽

Po-Lei Lee

Keyword(s):

Prefrontal Cortex ◽

Infrared Spectroscopy ◽

Near Infrared Spectroscopy ◽

Near Infrared ◽

Kernel Functions ◽

Olfactory Stimulation ◽

Support Vector ◽

Hemodynamic Response Function ◽

Functional Near Infrared Spectroscopy ◽

Data Set

The sense of smell is one of the most important organs in humans, and olfactory imaging can detect signals in the anterior orbital frontal lobe. This study assessed olfactory stimuli using support vector machines (SVMs) with signals from functional near-infrared spectroscopy (fNIRS) data obtained from the prefrontal cortex. These data included odor stimuli and air state, which triggered the hemodynamic response function (HRF), determined from variations in oxyhemoglobin (oxyHb) and deoxyhemoglobin (deoxyHb) levels; photoplethysmography (PPG) of two wavelengths (raw optical red and near-infrared data); and the ratios of data from two optical datasets. We adopted three SVM kernel functions (i.e., linear, quadratic, and cubic) to analyze signals and compare their performance with the HRF and PPG signals. The results revealed that oxyHb yielded the most efficient single-signal data with a quadratic kernel function, and a combination of HRF and PPG signals yielded the most efficient multi-signal data with the cubic function. Our results revealed superior SVM analysis of HRFs for classifying odor and air status using fNIRS data during olfaction in humans. Furthermore, the olfactory stimulation can be accurately classified by using quadratic and cubic kernel functions in SVM, even for an individual participant data set.

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Whole genome transcriptome analysis of the stomach resected in human vertical sleeve gastrectomy: cutting more than calories

Physiological Genomics ◽

10.1152/physiolgenomics.00082.2020 ◽

2021 ◽

Author(s):

William C Dungan ◽

Michael R Garrett ◽

Bradley A. Welch ◽

William J Lawson ◽

Alexandra R Himel ◽

...

Keyword(s):

Body Weight ◽

Sleeve Gastrectomy ◽

Transcriptome Analysis ◽

Gene Signature ◽

Whole Genome ◽

Vertical Sleeve Gastrectomy ◽

Data Set ◽

Tissue Samples ◽

Highly Expressed Genes ◽

A Prospective Study

Background. Vertical sleeve gastrectomy (VSG) is a surgical weight loss procedure that resects 80% of the stomach, creating a tube linking the esophagus to the duodenum. Because of the efficacy and relative simplicity of VSG, it is preferred in the U.S with VSG currently at >61% of bariatric surgeries performed. Surprisingly, there has never been a complete molecular characterization of the human stomach fundus and corpus. Here we compare and contrast the molecular make-up of these regions. Methods. We performed a prospective study to obtain gastric tissue samples from patients undergoing VSG. Paired fundus and corpus samples were obtained Whole genome transcriptome analysis was performed by RNA sequencing, with key findings validated by qPCR. Results. Participants were primarily female (95.8%) and white (79.15%). Mean BMI, body weight, and age were 46.1 kg/m2, 121.6 kg, and 43.29 years, respectively. Overall, 432 gene transcripts were significantly different between the fundus and corpus (p<0.05). A significant correlation was found between the RNAseq data set and qPCR validation, demonstrating robust gene expression differences. Significant genes included: progastricsin, acid chitinase, gastokine 1 and 2 in both fundus and corpus. Of the very highly expressed genes in both regions, 87% were present in both the stomach's fundus and corpus, indicating substantial overlap. Conclusions. Despite significant overlap in the greater curvature gene signature, regional differences exist. Given that the mechanism of VSG is partly unresolved, the potential that the resected tissue may express genes that influence long-term body weight regulation is unknown and could influence VSG outcomes.

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The Whole-Genome Sequence of the Novel Yeast Species Metschnikowia persimmonesis Isolated from Medicinal Plant Diospyros kaki Thunb

G3 Genes|Genome|Genetics ◽

10.1093/g3journal/jkab246 ◽

2021 ◽

Author(s):

Endang Rahmat ◽

Inkyu Park ◽

Youngmin Kang

Keyword(s):

Gc Content ◽

Whole Genome Sequence ◽

Diospyros Kaki ◽

Whole Genome ◽

The Novel ◽

Data Set ◽

Draft Assembly ◽

Future Possibility ◽

Complete Set ◽

New Yeast

Abstract The new yeast Metschnikowia persimmonesis KCTC 12991BP (KIOM G15050 strain) exhibits strong antimicrobial activity against some pathogens. This activity may be related to the medicinal profile of secondary metabolites that could be found in the genome of this species. Therefore, to explore its future possibility of producing some beneficial activities, including medicinal ability, we report high quality whole-genome assembly of M. persimmonesis produced by PacBio RSII sequencer. The final draft assembly consisted of 16 scaffolds with GC content of 45.90% and comprised a fairly complete set (82.8%) of BUSCO result using Saccharomycetales lineage data set. The total length of the genome was 16.473 Mb, with a scaffold N50 of 1.982 Mb. Annotation of the M. persimmonesis genome revealed presence of 7,029 genes and 6,939 functionally annotated proteins. Based on the analysis of phylogenetic relationship and the average nucleotide identities (ANI), M. persimmonesis was proved to a novel species within the Metschnikowia genus. This finding is expected to significantly contribute to the discovery of high-value natural products from M. persimmonesis as well as for genome biology and evolution comparative analysis within Metschnikowia species.

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Pancreatic cancer detection using EpiDetect signatures in plasma-derived cell free DNA in high-risk patients with new onset diabetes.

Journal of Clinical Oncology ◽

10.1200/jco.2021.39.15_suppl.e16265 ◽

2021 ◽

Vol 39 (15_suppl) ◽

pp. e16265-e16265

Author(s):

Gulfem Guler ◽

Anna Bergamaschi ◽

David Haan ◽

Michael Kesling ◽

Yuhong Ning ◽

...

Keyword(s):

Pancreatic Cancer ◽

Early Stage ◽

Model Performance ◽

Training Data ◽

Diabetes Diagnosis ◽

Whole Genome ◽

Data Set ◽

Independent Validation ◽

Onset Diabetes ◽

New Onset

e16265 Background: Pancreatic cancer (PaCa) is the third leading cause of cancer death in the United States despite its low incidence rate, owing to a 5-year survival rate of 10%. It is often asymptomatic in early stage, resulting in the majority of diagnoses occurring when cancer has already metastasized to distant organs. Late diagnosis deprives patients of potentially curative treatments such as surgery and impacts survival rates. Diabetes can be an early symptom of PaCa. Indeed, 25% of PaCa patients had a preceding diabetes diagnosis. Among all people with new onset diabetes (NOD), 0.85% will be diagnosed with PaCa within 3 years, which represents 6-8 fold increased risk for PaCa compared to the general population. Surveillance of the NOD population for PaCa presents an opportunity to shift PaCa diagnosis to earlier stage by finding it sooner. Methods: Whole blood was obtained from a cohort of 117 PaCa patients as well as 800 non-cancer controls with and without NOD. Plasma was processed to isolate cfDNA and 5hmC and low pass whole genome libraries were generated and sequenced. The EpiDetect assay combines 5hmC and whole genome sequencing data and were generated using Bluestar Genomics’s technology platform. Results: To investigate whether PaCa can be detected in plasma, we interrogated plasma-derived cfDNA epigenomic and genomic signal from PaCa patients and non-cancer controls. We first trained stacked ensemble models on PaCa and non-cancer samples utilizing 5hmC, fragmentation and CNV-based biomarkers from cfDNA. These models performed stably with a median of 72.8% sensitivity and 90.1% specificity measured across 25 outer fold iterations using the training data set, which was composed of 50% early stage (Stages I & II) disease. The final binomial ensemble model was trained using all of the training data, yielding an area under the receiver operating characteristic curve (auROC) of 0.9, with 75% sensitivity and 89% specificity. This model was then tested on an independent validation data set from 33 PaCa patients (24 with diabetes, 15 of which was NOD) and 202 non-cancer control patients (76 with diabetes, 51 of which was NOD) and yielded a classification performance auROC of 0.9 with 67% sensitivity at 92% specificity. Lastly, model performance in the subset of patient cohort with NOD only had an auROC of 0.87 with 60% sensitivity at 88% specificity. Conclusions: Our results indicate that 5hmC profiles along with CNV and fragmentation patterns from cfDNA can be used to detect PaCa in plasma-derived cfDNA. Overall, model performance was stable and consistent between the training and independent validation datasets. A larger clinical study is under development to investigate the utility of the model described in this pilot study in identifying occult PaCa within the NOD population, with the aim of shifting diagnosis to early stage and potentially improving patient outcomes.

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F167. Multiplexed Single-Nucleus RNA Sequencing of Postmortem Human Prefrontal Cortex in Schizophrenia and Bipolar Disorder

Biological Psychiatry ◽

10.1016/j.biopsych.2019.03.704 ◽

2019 ◽

Vol 85 (10) ◽

pp. S277-S278

Author(s):

Reed Tso ◽

Makayla Hourihan ◽

Sivan Subburaju ◽

Brad Ruzicka

Keyword(s):

Bipolar Disorder ◽

Prefrontal Cortex ◽

Rna Sequencing ◽

Single Nucleus

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Mitochondrial gene signature in the prefrontal cortex for differential susceptibility to chronic stress

Scientific Reports ◽

10.1038/s41598-020-75326-9 ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Meltem Weger ◽

Daniel Alpern ◽

Antoine Cherix ◽

Sriparna Ghosal ◽

Jocelyn Grosse ◽

...

Keyword(s):

Gene Expression ◽

Mitochondrial Dna ◽

Prefrontal Cortex ◽

Mitochondrial Dysfunction ◽

Chronic Stress ◽

Mitochondrial Gene ◽

Brain Regions ◽

Mitochondrial Gene Expression ◽

Data Set ◽

A Genome

Abstract Mitochondrial dysfunction was highlighted as a crucial vulnerability factor for the development of depression. However, systemic studies assessing stress-induced changes in mitochondria-associated genes in brain regions relevant to depression symptomatology remain scarce. Here, we performed a genome-wide transcriptomic study to examine mitochondrial gene expression in the prefrontal cortex (PFC) and nucleus accumbens (NAc) of mice exposed to multimodal chronic restraint stress. We identified mitochondria-associated gene pathways as most prominently affected in the PFC and with lesser significance in the NAc. A more detailed mitochondrial gene expression analysis revealed that in particular mitochondrial DNA-encoded subunits of the oxidative phosphorylation complexes were altered in the PFC. The comparison of our data with a reanalyzed transcriptome data set of chronic variable stress mice and major depression disorder subjects showed that the changes in mitochondrial DNA-encoded genes are a feature generalizing to other chronic stress-protocols as well and might have translational relevance. Finally, we provide evidence for changes in mitochondrial outputs in the PFC following chronic stress that are indicative of mitochondrial dysfunction. Collectively, our work reinforces the idea that changes in mitochondrial gene expression are key players in the prefrontal adaptations observed in individuals with high behavioral susceptibility and resilience to chronic stress.

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A Method to Detect Differential Gene Expression in Cross-Species Hybridization Experiments at Gene and Probe Level

Biomedical Informatics Insights ◽

10.4137/bii.s3846 ◽

2010 ◽

Vol 3 ◽

pp. BII.S3846 ◽

Cited By ~ 1

Author(s):

Ying Chen ◽

Rebekah Wu ◽

James Felton ◽

David M. Rocke ◽

Anu Chakicherla

Keyword(s):

Gene Expression ◽

Gene Set Analysis ◽

Model Organisms ◽

Whole Genome ◽

Supplementary Data ◽

Genome Sequences ◽

Data Set ◽

Gene Set ◽

Level Data ◽

Species Hybridization

Motivation Whole genome microarrays are increasingly becoming the method of choice to study responses in model organisms to disease, stressors or other stimuli. However, whole genome sequences are available for only some model organisms, and there are still many species whose genome sequences are not yet available. Cross-species studies, where arrays developed for one species are used to study gene expression in a closely related species, have been used to address this gap, with some promising results. Current analytical methods have included filtration of some probes or genes that showed low hybridization activities. But consensus filtration schemes are still not available. Results A novel masking procedure is proposed based on currently available target species sequences to filter out probes and study a cross-species data set using this masking procedure and gene-set analysis. Gene-set analysis evaluates the association of some priori defined gene groups with a phenotype of interest. Two methods, Gene Set Enrichment Analysis (GSEA) and Test of Test Statistics (ToTS) were investigated. The results showed that masking procedure together with ToTS method worked well in our data set. The results from an alternative way to study cross-species hybridization experiments without masking are also presented. We hypothesize that the multi-probes structure of Affymetrix microarrays makes it possible to aggregate the effects of both well-hybridized and poorly-hybridized probes to study a group of genes. The principles of gene-set analysis were applied to the probe-level data instead of gene-level data. The results showed that ToTS can give valuable information and thus can be used as a powerful technique for analyzing cross-species hybridization experiments. Availability Software in the form of R code is available at http://anson.ucdavis.edu/~ychen/cross-species.html Supplementary Data Supplementary data are available at http://anson.ucdavis.edu/~ychen/cross-species.html

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Rapid construction of a whole-genome transposon insertion collection for Shewanella oneidensis by Knockout Sudoku

Nature Communications ◽

10.1038/ncomms13270 ◽

2016 ◽

Vol 7 (1) ◽

Cited By ~ 19

Author(s):

Michael Baym ◽

Lev Shaket ◽

Isao A. Anzai ◽

Oluwakemi Adesina ◽

Buz Barstow

Keyword(s):

Single Gene ◽

Shewanella Oneidensis ◽

Whole Genome ◽

Sequencing Data ◽

Kinetic Measurements ◽

Data Set ◽

Quinone Reduction ◽

Transposon Insertion ◽

Sequencing Library ◽

Technical Effort

Abstract Whole-genome knockout collections are invaluable for connecting gene sequence to function, yet traditionally, their construction has required an extraordinary technical effort. Here we report a method for the construction and purification of a curated whole-genome collection of single-gene transposon disruption mutants termed Knockout Sudoku. Using simple combinatorial pooling, a highly oversampled collection of mutants is condensed into a next-generation sequencing library in a single day, a 30- to 100-fold improvement over prior methods. The identities of the mutants in the collection are then solved by a probabilistic algorithm that uses internal self-consistency within the sequencing data set, followed by rapid algorithmically guided condensation to a minimal representative set of mutants, validation, and curation. Starting from a progenitor collection of 39,918 mutants, we compile a quality-controlled knockout collection of the electroactive microbe Shewanella oneidensis MR-1 containing representatives for 3,667 genes that is functionally validated by high-throughput kinetic measurements of quinone reduction.

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