Control iPSC lines with clinically annotated genetic variants for versatile multi-lineage differentiation
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ABSTRACT: Induced Pluripotent Stem Cells (iPSC) derived from healthy individuals are important controls for disease modeling studies. To create a resource of genetically annotated iPSCs, we reprogrammed footprint-free lines from four volunteers in the Personal Genome Project Canada (PGPC). Multilineage directed differentiation efficiently produced functional cortical neurons, cardiomyocytes and hepatocytes. Pilot users further demonstrated line versatility by generating kidney organoids, T-lymphocytes and sensory neurons. A frameshift knockout was introduced into MYBPC3 and these cardiomyocytes exhibited the expected hypertrophic phenotype. Whole genome sequencing (WGS) based annotation of PGPC lines revealed on average 20 coding variants. Importantly, nearly all annotated PGPC and HipSci lines harboured at least one pre-existing or acquired variant with cardiac, neurological or other disease associations. Overall, PGPC lines were efficiently differentiated by multiple users into cell types found in six tissues for disease modeling, and clinical annotation highlighted variant-preferred lines for use as unaffected controls in specific disease settings.
Project description:Induced Pluripotent Stem Cells (iPSC) derived from healthy individuals are important controls for disease modeling studies. To create a resource of genetically annotated iPSC, we reprogrammed footprint-free lines from four volunteers in the Personal Genome Project Canada (PGPC). Multilineage directed differentiation efficiently produced functional cortical neurons, cardiomyocytes and hepatocytes. Pilot users further demonstrated line versatility by generating kidney organoids, T-cells and sensory neurons. A frameshift knockout was introduced into MYBPC3 and these cardiomyocytes exhibited a hypertrophic phenotype as expected. WGS annotation of PGPC lines revealed on average 20 coding variants. Importantly, nearly all annotated PGPC and HipSci lines harboured at least one pre-existing or acquired variant with cardiac, neurological or other disease associations. Overall, PGPC lines were efficiently differentiated by multiple users into cell types found in six tissues for disease modelling, and clinical annotation highlighted variant-preferred lines for use as unaffected controls in specific disease settings.
Project description:Contains a row for each annotated gene in each sample, indicating whether our analysis called the gene "present" or "absent" in the sample. Gene names and coordinates refer to version 3 of the TIGR annotation as submitted to GenBank (GI numbers 22330780, 22326553, 22331929, 22329272, 22328163). Keywords: other
Project description:Contains a row for each annotated gene in each sample, indicating whether our analysis called the gene "present" or "absent" in the sample. Gene names and coordinates refer to version 3 of the TIGR annotation as submitted to GenBank (GI numbers 22330780, 22326553, 22331929, 22329272, 22328163).
Project description:Contains a row for each annotated gene in each sample, indicating whether our analysis called the region antisense to the coding region of the gene "present" or "absent" in the sample. Gene names and coordinates refer to version 3 of the TIGR annotation as submitted to GenBank (GI numbers 22330780, 22326553, 22331929, 22329272, 22328163). Keywords: other
Project description:Contains a row for each annotated gene in each sample, indicating whether our analysis called the region antisense to the coding region of the gene "present" or "absent" in the sample. Gene names and coordinates refer to version 3 of the TIGR annotation as submitted to GenBank (GI numbers 22330780, 22326553, 22331929, 22329272, 22328163).
Project description:The study of RNA expression is the fastest growing area of genomic research. However, despite the dramatic increase in the number of sequenced transcriptomes, we still do not have accurate estimates of the number and expression levels of non-coding RNA genes. Non-coding transcripts are often overlooked due to incomplete genome annotation. In this study, we use annotation-independent detection of RNA reads generated using a reverse transcriptase with low structure bias to identify non-coding RNA. Transcripts between 20 and 500 nucleotides were filtered and crosschecked with non-coding RNA annotations revealing 115 non-annotated non-coding RNAs expressed in different cell lines and tissues. Inspecting the sequence and structural features of these transcripts indicated that 60% of these transcripts correspond to new tRNA and snoRNA genes. The identified genes exhibited features of their respective families in terms of structure, expression, conservation and response to depletion of interacting proteins. Together, our data reveal a new group of RNA that are difficult to detect using standard gene prediction and RNA sequencing techniques, suggesting that reliance on actual gene annotation and sequencing techniques distort the perceived architecture of the human transcriptome.
Project description:Human embryonic stem cells (hESCs) can be used to generate scalable numbers of cardiomyocytes for studying cardiac biology, disease modeling, drug screens, and potentially for regenerative therapies. Directed differentiation protocols for cardiomyocytes using hESCs are well established, but methods to isolate highly pure population of cardiomyocytes are limited. Reporter cell lines can be valuable for purification and visualization of cells for such applications. We used CRISPR/Cas9 in hESCs to place an mCherry reporter gene into the MYH6 locus, facilitating a simple method to purify cardiomyocytes. MYH6:mCherry positive cells express atrial and ventricular markers and display a range of cardiomyocyte action potential morphologies. At 20 days of differentiation, MYH6:mCherry+ cells show features characteristic of human cardiomyocytes and can be used successfully to monitor drug-induced cardiotoxicity and oleic acid-induced cardiomyocyte arrhythmia. The MYH6:mCherry hESC reporter line should serve as a useful tool for disease modeling and drug development relevant to cardiomyocyte biology.
Project description:Methcathinone (ephedrone) is relatively easily accessible for abuse. Its users develop an extrapyramidal syndrome and it is not known if this is caused by methcathinone itself, by side-ingredients (manganese), or both. In the present study we aimed to clarify molecular mechanisms underlying this condition. We used microarrays to analyze whole genome gene expression patterns of peripheral blood from 20 methcathinone users and 20 matched controls. Gene expression profile data were analyzed by Bayesian modelling and functional annotation. Of 28,869 genes on the microarrays, 326 showed statistically significant differential expression with FDR adjusted p-values below 0.05. Quantitative RT-PCR confirmed differential expression for the most of the genes selected for validation. Functional annotation and network analysis indicated activation of a gene network that included immunological disease, cellular movement and cardiovascular disease functions (enrichment score 42). As HIV and HCV infections were confounding factors, we performed additional stratification of patients. A similar functional activation of the “immunological disease” category was evident when we compared patients according to injection status (past versus current users, balanced for HIV and HCV infection). However, this difference was not large therefore the major effect was related to the HIV status of the patients. Mn-methcathinone abusers have blood RNA expression patterns that mostly reflect their HIV and HCV infections. However, despite the strong confounding effect from infection, some modest drug abuse effects on gene expression were detected. 40 samples, 20 healthy volunteers and 20 illicit methcathinone users