Browsing by Subject "Next generation sequencing"

Now showing 1 - 9 of 9
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    Cardiomyopathy in Children Identifying the Causes
    (Elsevier, 2018-11-06) Ware, Stephanie M.; Pediatrics, School of Medicine
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    Characterizing alternative splicing and long non-coding RNA with high-throughput sequencing technology
    (2018-10) Zhou, Ao; Wu, Huanmei; Liu, Yunlong; Janga, Sarath C.; Liu, Xiaowen
    Several experimental methods has been developed for the study of the central dogma since late 20th century. Protein mass spectrometry and next generation sequencing (including DNA-Seq and RNA-Seq) forms a triangle of experimental methods, corresponding to the three vertices of the central dogma, i.e., DNA, RNA and protein. Numerous RNA sequencing and protein mass spectrometry experiments has been carried out in attempt to understand how the expression change of known genes affect biological functions in various of organisms, however, it has been once overlooked that the result data of these experiments are in fact holograms which also reveals other delicate biological mechanisms, such as RNA splicing and the expression of long non-coding RNAs. In this dissertation, we carried out five studies based on high-throughput sequencing data, in an attempt to understand how RNA splicing and differential expression of long non-coding RNAs is associated biological functions. In the first two studies, we identified and characterized 197 stimulant induced and 477 developmentally regulated alternative splicing events from RNA sequencing data. In the third study, we introduced a method for identifying novel alternative splicing events that were never documented. In the fourth study, we introduced a method for identifying known and novel RNA splicing junctions from protein mass spectrometry data. In the fifth study, we introduced a method for identifying long non-coding RNAs from poly-A selected RNA sequencing data. Taking advantage of these methods, we turned RNA sequencing and protein mass spectrometry data into an information gold mine of splicing and long non-coding RNA activities.
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    Computational modeling for identification of low-frequency single nucleotide variants
    (2015-11-16) Hao, Yangyang; Liu, Yunlong; Edenberg, Howard J.; Li, Lang; Nakshatr, Harikrishna
    Reliable detection of low-frequency single nucleotide variants (SNVs) carries great significance in many applications. In cancer genetics, the frequencies of somatic variants from tumor biopsies tend to be low due to contamination with normal tissue and tumor heterogeneity. Circulating tumor DNA monitoring also faces the challenge of detecting low-frequency variants due to the small percentage of tumor DNA in blood. Moreover, in population genetics, although pooled sequencing is cost-effective compared with individual sequencing, pooling dilutes the signals of variants from any individual. Detection of low frequency variants is difficult and can be cofounded by multiple sources of errors, especially next-generation sequencing artifacts. Existing methods are limited in sensitivity and mainly focus on frequencies around 5%; most fail to consider differential, context-specific sequencing artifacts. To face this challenge, we developed a computational and experimental framework, RareVar, to reliably identify low-frequency SNVs from high-throughput sequencing data. For optimized performance, RareVar utilized a supervised learning framework to model artifacts originated from different components of a specific sequencing pipeline. This is enabled by a customized, comprehensive benchmark data enriched with known low-frequency SNVs from the sequencing pipeline of interest. Genomic-context-specific sequencing error model was trained on the benchmark data to characterize the systematic sequencing artifacts, to derive the position-specific detection limit for sensitive low-frequency SNV detection. Further, a machine-learning algorithm utilized sequencing quality features to refine SNV candidates for higher specificity. RareVar outperformed existing approaches, especially at 0.5% to 5% frequency. We further explored the influence of statistical modeling on position specific error modeling and showed zero-inflated negative binomial as the best-performed statistical distribution. When replicating analyses on an Illumina MiSeq benchmark dataset, our method seamlessly adapted to technologies with different biochemistries. RareVar enables sensitive detection of low-frequency SNVs across different sequencing platforms and will facilitate research and clinical applications such as pooled sequencing, cancer early detection, prognostic assessment, metastatic monitoring, and relapses or acquired resistance identification.
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    Epitranscriptomic code and its alterations in human disease
    (Elsevier, 2018-10) Kadumuri, Rajashekar Varma; Janga, Sarath Chandra; BioHealth Informatics, School of Informatics and Computing
    Innovations in epitranscriptomics have resulted in the identification of more than 160 RNA modifications to date. These developments, together with the recent discovery of writers, readers, and erasers of modifications occurring across a wide range of RNAs and tissue types, have led to a surge in integrative approaches for transcriptome-wide mapping of modifications and protein-RNA interaction profiles of epitranscriptome players. RNA modification maps and crosstalk between them have begun to elucidate the role of modifications as signaling switches, entertaining the notion of an epitranscriptomic code as a driver of the post-transcriptional fate of RNA. Emerging single-molecule sequencing technologies and development of antibodies specific to various RNA modifications could enable charting of transcript-specific epitranscriptomic marks across cell types and their alterations in disease.
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    High-throughput cis-regulatory element discovery in the vector mosquito Aedes aegypti
    (BioMed Central, 2016-05-10) Behura, Susanta K.; Sarro, Joseph; Li, Ping; Mysore, Keshava; Severson, David W.; Emrich, Scott J.; Duman-Scheel, Molly; Department of Medical & Molecular Genetics, IU School of Medicine
    BACKGROUND: Despite substantial progress in mosquito genomic and genetic research, few cis-regulatory elements (CREs), DNA sequences that control gene expression, have been identified in mosquitoes or other non-model insects. Formaldehyde-assisted isolation of regulatory elements paired with DNA sequencing, FAIRE-seq, is emerging as a powerful new high-throughput tool for global CRE discovery. FAIRE results in the preferential recovery of open chromatin DNA fragments that are not bound by nucleosomes, an evolutionarily conserved indicator of regulatory activity, which are then sequenced. Despite the power of the approach, FAIRE-seq has not yet been applied to the study of non-model insects. In this investigation, we utilized FAIRE-seq to profile open chromatin and identify likely regulatory elements throughout the genome of the human disease vector mosquito Aedes aegypti. We then assessed genetic variation in the regulatory elements of dengue virus susceptible (Moyo-S) and refractory (Moyo-R) mosquito strains. RESULTS: Analysis of sequence data obtained through next generation sequencing of FAIRE DNA isolated from A. aegypti embryos revealed >121,000 FAIRE peaks (FPs), many of which clustered in the 1 kb 5' upstream flanking regions of genes known to be expressed at this stage. As expected, known transcription factor consensus binding sites were enriched in the FPs, and of these FoxA1, Hunchback, Gfi, Klf4, MYB/ph3 and Sox9 are most predominant. All of the elements tested in vivo were confirmed to drive gene expression in transgenic Drosophila reporter assays. Of the >13,000 single nucleotide polymorphisms (SNPs) recently identified in dengue virus-susceptible and refractory mosquito strains, 3365 were found to map to FPs. CONCLUSION: FAIRE-seq analysis of open chromatin in A. aegypti permitted genome-wide discovery of CREs. The results of this investigation indicate that FAIRE-seq is a powerful tool for identification of regulatory DNA in the genomes of non-model organisms, including human disease vector mosquitoes.
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    IL-33 Mediated Th2 Effector Functions are Suppressed in Tregs by Bcl6 and Regulated by Sex
    (2024-08) Lee, Kyu Been; Dent, Alexander; Richer, Martin; Robinson, Christopher; Yang, Kai
    Allergic airway inflammation (asthma) is a prevalent and uncurable disease worldwide, affecting many individuals’ quality of life. Although asthma does not form from a singular cause, one primary mediator comes from the exposure to environmental allergens and the improper activation of the T cell subset: T helper 2 (Th2) cells. Th2 cells produce pro-inflammatory cytokines and promote the activation and recruitment of various pro-inflammatory cells into the lung, causing greater damage and inflammatory responses in the organ. Th2 cell’s activation is regulated by another T cell subset, Regulatory T (Treg) cells, by expressing anti-inflammatory cytokines and downregulating the inflammatory response. On the contrary, the release of interleukin-33 (IL-33) from damaged lung epithelial cells transitions Tregs into Th2-like Tregs (ST2+ Tregs) which release both pro-and anti-inflammatory cytokines and cannot suppress the inflammatory disease. However, transcriptional repressor protein B cell lymphoma 6 (Bcl6) provides Tregs a stable follicular phenotype and suppresses the ST2+ Treg transition. Preliminary data revealed that Bcl6 repressive function is dependent on mouse sex, in which Tregs of male mice are more resistant to the ST2+ Treg phenotype than those of female mice. However, the removal of Bcl6 also removed the sex-dependent suppression against the ST2+ Treg transition. The project therefore sought to further confirm and answer whether Bcl6 suppressed the ST2+ Treg phenotype in a sex-dependent manner, ultimately leading to a sex-biased asthma prevalence and severity. We utilized quantitative polymerase chain reaction (qPCR) and next-generation sequencing techniques to uncover which genes Bcl6 regulates, how IL-33 affects chromatin accessibility/gene expression, and what relation sex hormones have with Bcl6 in the expression of Th2 cytokines from Tregs. Currently, we have discovered that estrogen-like chemicals in common cell culturing media may be acting on the estrogen receptor of Tregs and causing differential gene expressions based on media conditions. We also determined that Bcl6 is acting independently of mouse sex to suppress Th2 genes in Tregs, contrary to preliminary findings. Overall, we have obtained insight on the role of the estrogen receptor and Bcl6’s mechanism of suppression in relation to sex.
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    Next generation sequencing in patients with nephrolithiasis: how does it perform compared with standard urine and stone cultures?
    (Sage, 2021-02-22) Nottingham, Charles U.; Assmus, Mark A.; Peters, Alexander W.; Large, Tim; Agarwal, Deepak K.; Rivera, Marcelino E.; Krambeck, Amy E.; Urology, School of Medicine
    Background: Our aim was to compare microorganism detection between standard culture (Ctx) and next generation sequencing (NGS) in patients undergoing surgery for nephrolithiasis; we prospectively compared both urine and stone culture results using these two techniques. Methods: We prospectively compared microorganism detection of urine and stone cultures using Ctx versus NGS in patients undergoing surgery for nephrolithiasis. We analyzed preoperative voided urine (Voided) using both Ctx and NGS. Intraoperatively, renal stone (Stone) cultures were analyzed with Ctx and NGS. The primary outcome was concordance in microorganism detection between Voided Ctx and Stone NGS, as well as between Stone Ctx and Stone NGS. Results: We prospectively evaluated 84 patients. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of Voided Ctx predicting Stone Ctx were 66.7%, 73.7%, 54.5%, and 82.4%, respectively. Concordance of Voided Ctx microorganisms to Stone microorganisms decreased when NGS was used for the Stone compared with Ctx. The sensitivity, specificity, PPV, and NPV of Voided NGS to predict Stone Ctx microorganisms were 85.2%, 24.6%, 34.8%, and 77.8%, respectively. The concordance of Voided NGS to Stone microorganisms improved when the Stone was analyzed via NGS compared with Ctx. Conclusion: NGS has a higher detection rate of microorganisms than standard culture for both preoperative urine and stone cultures. Voided NGS was the most sensitive in predicting a positive Stone sample, but the specificity and PPV were, overall, low. Further correlation of NGS microorganism detection with patient outcomes will determine which clinical situations may benefit most from NGS versus standard culture in patients with urinary-tract stones.
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    Precision Genomic Practice in Oncology: Pharmacist Role and Experience in an Ambulatory Care Clinic
    (MDPI, 2020-03) Raheem, Farah; Kim, Pauline; Grove, Meagan; Kiel, Patrick J.; Medicine, School of Medicine
    Recent advancements in molecular testing, the availability of cost-effective technology, and novel approaches to clinical trial design have facilitated the implementation of tumor genome sequencing into standard of care oncology practices. Current models of precision oncology practice include specialized clinics or consultation services based on a molecular tumor board (MTB) approach. MTBs are comprised of interprofessional teams of clinicians and scientists who evaluate tumors at the molecular level to guide patient-specific targeted therapy. The practice of precision oncology utilizing MTB-based models is an emerging approach, transforming precision genomics from a novel concept into clinical practice. This rapid shift in practice from cytotoxic therapy to targeted medicine poses challenges, yet brings exciting opportunities to clinical pharmacists practicing in hematology and oncology. Only a few precision genomics programs in the United States have a strong pharmacy presence with oncology pharmacists serving in leadership roles in research, interpreting genomic sequencing, making treatment recommendations, and facilitating off-label drug procurement. This article describes the experience of the precision medicine clinic at the Indiana University Health Simon Cancer Center, with emphasis on the role of the pharmacist in the precision oncology initiative.
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    Role of ATF4 in directing gene expression in the basal state and during the unfolded protein response in liver
    (2016-08) Fusakio, Michael Edward; Wek, Ronald C.
    Disturbances in membrane composition and protein folding in the endoplasmic reticulum (ER) trigger the unfolded protein response (UPR). Three UPR sensory proteins, PERK (PEK/EIF2AK3), IRE1, and ATF6 are each activated by ER stress. PERK phosphorylation of the alpha subunit of eIF2 represses global protein synthesis, lowering influx of nascent polypeptides into the stressed ER, coincident with the preferential translation of ATF4 (CREB2). Results from cultured cells demonstrate that ATF4 induces transcriptional expression of genes directed by the PERK arm of the UPR, including genes involved in amino acid metabolism, resistance to oxidative stress, and the proapoptotic transcription factor CHOP (GADD153/DDIT3). In this study, we characterized two ATF4 knockout mouse models and show in liver exposed to ER stress that ATF4 is not required for CHOP expression, but rather ATF6 is a primary inducer. RNA-sequence analysis indicated that ATF4 was responsible for a small portion of the PERK-dependent genes in the UPR. This smaller than expected subset of gene expression lends itself to the relevance of UPR crosstalk, with ATF6, XBP1, and CHOP being capable of upregulating UPR genes in the absence of ATF4. RNA-sequence analysis also revealed a requirement for expression of ATF4 for expression of a comparable number of genes basally, including those involved in oxidative stress response and cholesterol metabolism. Consistent with this pattern of gene expression, loss of ATF4 in our mouse model resulted in enhanced oxidative damage and increased free cholesterol in liver under stress accompanied by lowered cholesterol in sera. Taken together, this study highlights both an expansion of the role of ATF4 in transcriptional regulation of genes involved in metabolism in the basal state and a more specialized role during ER stress. These findings are important for understanding the variances of the UPR signaling between cell culture and in vivo and for a greater understanding of all the roles ATF4 plays within the cell.