Network-based integrative analysis of lithium response in bipolar disorder using transcriptomic and GWAS data

Lithium (Li) is one of the most effective drugs for treating bipolar disorder (BD), however, there is presently no way to predict response to guide treatment. The aim of this study is to identify functional genes and pathways that distinguish BD Li responders (LR) from BD Li non-responders (NR). An initial Pharmacogenomics of Bipolar Disorder study (PGBD) GWAS of lithium response did not provide any significant results. As a result, we then employed network-based integrative analysis of transcriptomic and genomic data. In transcriptomic study of iPSC-derived neurons, 41 significantly differentially expressed (DE) genes were identified in LR vs NR regardless of lithium exposure. In the PGBD, post-GWAS gene prioritization using the GWA-boosting (GWAB) approach identified 1119 candidate genes. Following DE-derived network propagation, there was a highly significant overlap of genes between the top 500- and top 2000-proximal gene networks and the GWAB gene list (Phypergeometric=1.28E-09 and 4.10E-18, respectively). Functional enrichment analyses of the top 500 proximal network genes identified focal adhesion and the extracellular matrix (ECM) as the most significant functions. Our findings suggest that the difference between LR and NR was a much greater effect than that of lithium. The direct impact of dysregulation of focal adhesion on axon guidance and neuronal circuits could underpin mechanisms of response to lithium, as well as underlying BD. It also highlights the power of integrative multi-omics analysis of transcriptomic and genomic profiling to gain molecular insights into lithium response in BD.

Select and Sequence of a Segregating Sugar Beet Population Provides Genomic Perspective of Host Resistance to Seedling Rhizoctonia solani Infection

Understanding the genetic basis of polygenic traits is a major challenge in agricultural species, especially in non-model systems. Select and sequence (SnS) experiments carried out within existing breeding programs provide a means to simultaneously identify the genomic background of a trait while improving the mean phenotype for a population. Using pooled whole genome sequencing (WGS) of selected and unselected bulks derived from a synthetic outcrossing sugar beet population EL57 (PI 663212), which segregates for seedling rhizoctonia resistance, we identified a putative genomic background involved in conditioning a resistance phenotype. Population genomic parameters were estimated to measure fixation (He), genome divergence (FST), and allele frequency changes between bulks (DeltaAF). We report on the genome wide patterns of variation resulting from selection and highlight specific genomic features associated with resistance. Expected heterozygosity (He) showed an increased level of fixation in the resistant bulk, indicating a greater selection pressure was applied. In total, 1,311 biallelic loci were detected as significant FST outliers (p < 0.01) in comparisons between the resistant and susceptible bulks. These loci were detected in 206 regions along the chromosomes and contained 275 genes. We estimated changes in allele frequency between bulks resulting from selection for resistance by leveraging the allele frequencies of an unselected bulk. DeltaAF was a more stringent test of selection and recovered 186 significant loci, representing 32 genes, all of which were also detected using FST. Estimates of population genetic parameters and statistical significance were visualized with respect to the EL10.2 physical map and produced a candidate gene list that was enriched for function in cell wall metabolism and plant disease resistance, including pathogen perception, signal transduction, and pathogen response. Specific variation associated with these genes was also reported and represents genetic markers for validation and prediction of resistance to Rhizoctonia. Select and sequence experiments offer a means to characterize the genetic base of sugar beet, inform selection within breeding programs, and prioritize candidate variation for functional studies.

Complete genomic profiles of 1,496 Taiwanese reveal curated medical insights

Background Taiwan Biobank (TWB) project has built a nationwide database to facilitate the basic and clinical collaboration within the island and internationally, which is one of the valuable public datasets of the East Asian population. This study provided comprehensive genomic medicine findings from 1,496 WGS data from TWB. Methods We reanalyzed 1,496 Illumina-based whole genome sequences (WGS) of Taiwanese participants with at least 30X depth of coverage by Sentieon DNAscope, a precisionFDA challenge winner method. All single nucleotide variants (SNV) and small insertions/deletions 1 (Indel) have been jointly called and recalibrated as one cohort dataset. Multiple practicing clinicians have reviewed clinically significant variants. Results We found that each Taiwanese has 6,870.7 globally novel variants and classified all genomic positions according to the recalibrated sequence qualities. The variant quality score helps distinguish actual genetic variants among the technical false-positive variants, making the accurate variant minor allele frequency (MAF). All variant annotation information can be browsed at TaiwanGenomes (https://genomes.tw). We detected 54 PharmGKB-reported Cytochrome P450 (CYP) genes haplotype-drug pairs with MAF over 10% in the TWB cohort and 39.8% (439/1103) Taiwanese harbored at least one PharmGKB-reported human leukocyte antigen (HLA) risk allele. We also identified 23 variants located at ACMG secondary finding V3 gene list from 25 participants, indicating 1.67% of the population is harboring at least one medical actionable variant. For carrier status of all known pathogenic variants, we estimated one in 22 couples (4.52%) would be under the risk of having offspring with at least one pathogenic variant, which is in line with Japanese (JPN) and Singaporean (SGN) populations. We also detected 6.88% and 2.02% of carrier rates for alpha thalassemia and spinal muscular atrophy (SMA) for copy number pathogenic variants, respectively. Conclusion As WGS has become affordable for everyone, a person only needs to test once for a lifetime; comprehensive WGS data reanalysis of the genomic profile will have a significant clinical impact. Our study highlights the overall picture of a complete genomic profile with medical information for a population and individuals.

Exploring the Contribution to ADHD of Genes Involved in Mendelian Disorders Presenting with Hyperactivity and/or Inattention

Attention-deficit hyperactivity disorder (ADHD) is a complex neurodevelopmental disorder characterized by hyperactivity, impulsivity, and/or inattention, which are symptoms also observed in many rare genetic disorders. We searched for genes involved in Mendelian disorders presenting with ADHD symptoms in the Online Mendelian Inheritance in Man (OMIM) database, to curate a list of new candidate risk genes for ADHD. We explored the enrichment of functions and pathways in this gene list, and tested whether rare or common variants in these genes are associated with ADHD or with its comorbidities. We identified 139 genes, causal for 137 rare disorders, mainly related to neurodevelopmental and brain function. Most of these Mendelian disorders also present with other psychiatric traits that are often comorbid with ADHD. Using whole exome sequencing (WES) data from 668 ADHD cases, we found rare variants associated with the dimension of the severity of inattention symptoms in three genes: KIF11, WAC, and CRBN. Then, we focused on common variants and identified six genes associated with ADHD (in 19,099 cases and 34,194 controls): MANBA, UQCC2, HIVEP2, FOPX1, KANSL1, and AUH. Furthermore, HIVEP2, FOXP1, and KANSL1 were nominally associated with autism spectrum disorder (ASD) (18,382 cases and 27,969 controls), as well as HIVEP2 with anxiety (7016 cases and 14,475 controls), and FOXP1 with aggression (18,988 individuals), which is in line with the symptomatology of the rare disorders they are responsible for. In conclusion, inspecting Mendelian disorders and the genes responsible for them constitutes a valuable approach for identifying new risk genes and the mechanisms of complex disorders.

Transcriptomic-Based Quantification of the Epithelial-Hybrid-Mesenchymal Spectrum Across Biological Contexts

Epithelial-mesenchymal plasticity (EMP) underlies embryonic development, wound healing, and cancer metastasis and fibrosis. Cancer cells exhibiting EMP often have more aggressive behavior, characterized by drug resistance, and tumor-initiating and immuno-evasive traits. Thus, the EMP status of cancer cells can be a critical indicator of patient prognosis. Here, we compare three distinct transcriptomic-based metrics—each derived using a different gene list and algorithm—that quantify the EMP spectrum. Our results for over 80 cancer-related RNA-seq datasets reveal a high degree of concordance among these metrics in quantifying the extent of EMP. Moreover, each metric, despite being trained on cancer expression profiles, recapitulates the expected changes in EMP scores for non-cancer contexts such as lung fibrosis and cellular reprogramming into induced pluripotent stem cells. Thus, we offer a scoring platform to quantify the extent of EMP in vitro and in vivo for diverse biological applications including cancer.

Genetic Diagnosis Spectrum and Multigenic Burden of Exome-Level Rare Variants in a Childhood Epilepsy Cohort

Childhood epilepsy is a considerably heterogeneous neurological condition with a high worldwide incidence. Genetic diagnosis of childhood epilepsy provides the most accurate pathogenetic evidence; however, a large proportion of highly suspected cases remain undiagnosed. Accumulation of rare variants at the exome level as a multigenic burden contributing to childhood epilepsy should be further evaluated. In this retrospective analysis, exome-level sequencing was used to depict the mutation spectra of 294 childhood epilepsy patients from Shanghai Children’s Medical Center, Department of Neurology. Furthermore, variant information from exome sequencing data was analyzed apart from monogenic diagnostic purposes to elucidate the possible multigenic burden of rare variants related to epilepsy pathogenesis. Exome sequencing reached a diagnostic rate of 30.61% and identified six genes not currently listed in the epilepsy-associated gene list. A multigenic burden study revealed a three-fold possibility that deleterious missense mutations in ion channel and synaptic genes in the undiagnosed cohort may contribute to the genetic risk of childhood epilepsy, whereas variants in the gene categories of cell growth, metabolic, and regulatory function showed no significant difference. Our study provides a comprehensive overview of the genetic diagnosis of a Chinese childhood epilepsy cohort and provides novel insights into the genetic background of these patients. Harmful missense mutations in genes related to ion channels and synapses are most likely to produce a multigenic burden in childhood epilepsy.

Preterm birth alters the maturation of the GABAergic system in the human prefrontal cortex

Developmental changes in GABAergic and glutamatergic systems during frontal lobe development have been hypothesized to play a key role in neurodevelopmental disorders seen in children born very preterm or low birth weight, but the associated cellular changes have not yet been identified. Here we studied the molecular development of the GABAergic system specifically in the dorsolateral prefrontal cortex, a region that that has been implicated in neurodevelopmental and psychiatric disorders. The maturation state of the GABAergic system in this region was assessed in human post-mortem brain samples, from term infants ranging in age from 0 to 8 months (n=17 male, 9 female). Gene expression was measured for 47 GABAergic genes and used to calculate a maturation index. This maturation index was significantly more dynamic in male than female infants. To evaluate the impact of premature birth on the GABAergic system development, samples from one-month-old term (n=9 male, 4 female) and one-month corrected-age (n=8 male, 6 female) very preterm infants, were compared using the same gene list and methodology. The maturation index for the GABAergic system was significantly lower in male preterm infants, with major alterations in genes linked to GABAergic function in astrocytes, suggesting astrocytic GABAergic developmental changes as a new cellular mechanism underlying preterm brain injury.

Prediction and enrichment analyses of the Homo sapiens−Drosophila melanogaster COPD-related orthologs

The significant similarities in airway epithelial cells between mammals and the fruit fly Drosophila melanogaster have rendered the latter an important model organism for studies of chronic inflammatory lung diseases. Focusing on the chronic obstructive pulmonary disease (COPD), we here mapped human gene orthologs associated with this disease in D. melanogaster to identify functionally equivalent genes for immediate, further screening with the fruit fly model. The DIOPT-DIST tool was accessed for the prediction of the COPD-associated orthologs between humans and Drosophila. Enrichment analyses with respect to pathways of the retrieved functional homologs were performed using the ToppFun and FlyMine tools, identifying 73 unique human genes as well as 438 fruit fly genes. The ToppFun analysis verified that the human gene list is associated with COPD phenotypes. Further, the FlyMine investigation highlighted that the Drosophila genes are functionally connected mainly with the 'ABC-family proteins mediated transport' and the 'beta-catenin independent WNT signaling pathway'. These results suggest an evolutionarily conserved role towards responses to inhaled toxicants and CO2 in both species. We reason that the predicted orthologous genes should be further studied in the Drosophila models of cigarette smoke-induced COPD.

SubcellulaRVis: an app to visualize subcellular compartment enrichment

High-throughput 'omics methods result in lists of differentially regulated or expressed genes or proteins, whose function is generally studied through statistical methods such as enrichment analyses. One aspect of protein regulation is subcellular localization, which is crucial for their correct processing and function and can change in response to various cellular stimuli. Enrichment of proteins for subcellular compartments is often based on Gene Ontology Cellular Compartment annotations. Results of enrichment are typically visualized using bar-charts, however enrichment analyses can result in a long list of significant annotations which are highly specific, preventing researchers from gaining a broad understanding of the subcellular compartments their proteins of interest may be located in. Schematic visualization of known subcellular locations has become increasingly available for single proteins via the UniProt and COMPARTMENTS platforms. However, it is not currently available for a list of proteins (e.g. from the same experiment) or for visualizing the results of enrichment analyses. To generate an easy-to-interpret visualization of protein subcellular localization after enrichment we developed the SubcellulaRVis web app, which visualizes the enrichment of subcellular locations of gene lists in an easy and impactful manner. SubcellulaRVis projects the results of enrichment analysis on a graphical representation of a eukaryotic cell. Implemented as a web app and an R package, this tool is user-friendly, provides exportable results in different formats, and can be used for gene lists derived from multiple organisms. Here, we show the power of SubcellulaRVis to assign proteins to the correct subcellular compartment using gene list enriched in previously published spatial proteomics datasets. We envision SubcellulaRVis will be useful for cell biologists with limited bioinformatics expertise wanting to perform precise and quick enrichment analysis and immediate visualization of gene lists.

Construction of miRNA-mRNA-TF Regulatory Network for Diagnosis of Gastric Cancer

Gastric cancer (GC), as an epidemic cancer worldwide, has more than 1 million new cases and an estimated 769,000 deaths worldwide in 2020, ranking fifth and fourth in global morbidity and mortality. In mammals, both miRNAs and transcription factors (TFs) play a partial role in gene expression regulation. The mRNA expression profile and miRNA expression profile of GEO database were screened by GEO2R for differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs). Then, DAVID annotated the functions of DEGs to understand the functions played in biological processes. The prediction of potential target genes of miRNA and key TFs of mRNA was performed by mipathDB V2.0 and CHEA3, respectively, and the gene list comparison was performed to look for overlapping genes coregulated by key TFs and DEMs. Finally, the obtained miRNAs, TF, and overlapping genes were used to construct the miRNA-mRNA-TF regulatory network, which was verified by RT-qPCR. 76 upregulated DEGs, 199 downregulated DEGs, and 3 upregulated miRNAs (miR-199a-3p/miR-199b-3p, miR-125b-5p, and miR-199a-5p) were identified from the expression profiles of mRNA (GSE26899, GSE29998, GSE51575, and GSE13911) and miRNA (GSE93415), respectively. Through database prediction and gene list comparison, it was found that among the 199 downregulated DEGs, 61, 71, and 69 genes were the potential targets of miR-199a-3p/miR-199b-3p, miR-125b-5p, and miR-199a-5p, respectively. 199 downregulated DEGs were used as the gene list for the prediction of key TFs, and the results showed that RFX6 ranked the highest. The potential target overlap genes of miR-199a-3p/miR-199b-3p, miR-125b-5p, and miR-199a-5p were 4 genes (SH3GL2, ATP4B, CTSE, and SORBS2), 7 genes (SLC7A8, RNASE4, ESRRG, PGC, MUC6, Fam3B, and FMO5), and 6 genes (CHGA, PDK4, TMPRSS2, CLIC6, GPX3, and PSCA), respectively. Finally, we constructed a miRNA-mRNA-TF regulatory network based on the above 17 mRNAs, 3 miRNAs, and 1 TF and verified by RT-qPCR and western blot results that the expression of RFX6 was downregulated in GC tissues. These identified miRNAs, mRNAs, and TF have a certain reference value for further exploration of the regulatory mechanism of GC.