scholarly journals Comprehensive analysis of circRNAs from cashmere goat skin by next generation RNA sequencing (RNA-seq)

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Yuanyuan Zheng ◽  
Taiyu Hui ◽  
Chang Yue ◽  
Jiaming Sun ◽  
Dan Guo ◽  
...  
2020 ◽  
Author(s):  
Jipan Zhang ◽  
Chengchen Deng ◽  
Jialu Li ◽  
Yong-Ju Zhao

Abstract Background: In Quantitative real-time polymerase chain reaction (qRT-PCR) experiments, accurate and reliable target gene expression data is dependent on optimal amplification of house-keeping genes (HKGs). RNA-seq technology offers a novel approach to detect new HKGs with improved stability. Goat (Capra hircus) is an economically important livestock species and plays an indispensable role in the world animal fiber and meat industry. Unfortunately, uniform and reliable HKGs for use in goat skin research have not been identified. Therefore, this study seeks to identify a set of stable HKGs for the skin tissue of C. hircus using high-throughput sequencing technology.Results: Based on the transcriptome dataset of 39 goat skin tissue samples, 8 genes (SRP68, NCBP3, RRAGA, EIF4H, CTBP2, PTPRA, CNBP, and EEF2) with relatively stable expression levels were identified and selected as new candidate HKGs. Commonly used HKGs including SDHA and YWHAZ from a previous study, and 2 conventional genes (ACTB and GAPDH) were also examined. Four different experimental variables: (1) different development stages, (2) hair follicle cycle stages, (3) breeds and (4) sampling sites, were used for determination and validation. Four algorithms (geNorm, NormFinder, BestKeeper, and ΔCt method) and a comprehensive algorithm (ComprFinder, developed in-house) were used to assess the stability of each HKG. It was shown that NCBP3+SDHA+PTPRA were more stably expressed than previously used genes in all conditions analyzed, and that this combination was effective at normalizing target gene expression. Moreover, a new algorithm for comprehensive analysis, ComprFinder, was developed and released.Conclusion: This study presents the first data of candidate HKGs for C. hircus skin tissues based on an RNA-seq dataset. We propose that the NCBP3+SDHA+PTPRA combination be used as a triplet set of HKGs in skin molecular biology experiments in C. hircus and other closely related species to standardize analyses across studies. In addition, we also encourage researchers who perform candidate HKG evaluations and who have the need for comprehensive analysis to adopt our new algorithm, ComprFinder.


2018 ◽  
Vol 12 (1) ◽  
pp. 41-52 ◽  
Author(s):  
Bradford W. Lee ◽  
Virender B. Kumar ◽  
Pooja Biswas ◽  
Audrey C. Ko ◽  
Ramzi M. Alameddine ◽  
...  

Objective: This study utilized Next Generation Sequencing (NGS) to identify differentially expressed transcripts in orbital adipose tissue from patients with active Thyroid Eye Disease (TED) versus healthy controls. Method: This prospective, case-control study enrolled three patients with severe, active thyroid eye disease undergoing orbital decompression, and three healthy controls undergoing routine eyelid surgery with removal of orbital fat. RNA Sequencing (RNA-Seq) was performed on freshly obtained orbital adipose tissue from study patients to analyze the transcriptome. Bioinformatics analysis was performed to determine pathways and processes enriched for the differential expression profile. Quantitative Reverse Transcriptase-Polymerase Chain Reaction (qRT-PCR) was performed to validate the differential expression of selected genes identified by RNA-Seq. Results: RNA-Seq identified 328 differentially expressed genes associated with active thyroid eye disease, many of which were responsible for mediating inflammation, cytokine signaling, adipogenesis, IGF-1 signaling, and glycosaminoglycan binding. The IL-5 and chemokine signaling pathways were highly enriched, and very-low-density-lipoprotein receptor activity and statin medications were implicated as having a potential role in TED. Conclusion: This study is the first to use RNA-Seq technology to elucidate differential gene expression associated with active, severe TED. This study suggests a transcriptional basis for the role of statins in modulating differentially expressed genes that mediate the pathogenesis of thyroid eye disease. Furthermore, the identification of genes with altered levels of expression in active, severe TED may inform the molecular pathways central to this clinical phenotype and guide the development of novel therapeutic agents.


2020 ◽  
Author(s):  
JIPAN ZHANG ◽  
Chengchen Deng ◽  
Jialu Li ◽  
Yong-Ju Zhao

Abstract Background: In Quantitative real-time polymerase chain reaction (qRT-PCR) experiments, accurate and reliable target gene expression data is dependent on optimal amplification of house-keeping genes (HKGs). RNA-seq technology offers a novel approach to detect new HKGs with improved stability. Goat (Capra hircus) is an economically important livestock species and plays an indispensable role in the world animal fiber and meat industry. Unfortunately, uniform and reliable HKGs for use in goat skin research have not been identified. Therefore, this study seeks to identify a set of stable HKGs for the skin tissue of C. hircus using high-throughput sequencing technology.Results: Based on the transcriptome dataset of 39 goat skin tissue samples, 8 genes (SRP68, NCBP3, RRAGA, EIF4H, CTBP2, PTPRA, CNBP, and EEF2) with relatively stable expression levels were identified and selected as new candidate HKGs. Commonly used HKGs including SDHA and YWHAZ from a previous study, and 2 conventional genes (ACTB and GAPDH) were also examined. Four different experimental variables: (1) different development stages, (2) hair follicle cycle stages, (3) breeds and (4) sampling sites, were used for determination and validation. Four algorithms (geNorm, NormFinder, BestKeeper, and ΔCt method) and a comprehensive algorithm (ComprFinder, developed in-house) were used to assess the stability of each HKG. It was shown that NCBP3+SDHA+PTPRA were more stably expressed than previously used genes in all conditions analysed, and that this combination was effective at normalizing target gene expression. Moreover, a new algorithm for comprehensive analysis, ComprFinder, was developed and released.Conclusion: This study presents the first data of candidate HKGs for C. hircus skin tissues based on an RNA-seq dataset. We propose that the NCBP3+SDHA+PTPRA combination be used as a triplet set of HKGs in skin molecular biology experiments in C. hircus and other closely related species to standardize analyses across studies. In addition, we also encourage researchers who perform candidate HKG evaluations and who have the need for comprehensive analysis to adopt our new algorithm, ComprFinder.


Author(s):  
Afzal Hussain

Next-generation sequencing or massively parallel sequencing describe DNA sequencing, RNA sequencing, or methylation sequencing, which shows its great impact on the life sciences. The recent advances of these parallel sequencing for the generation of huge amounts of data in a very short period of time as well as reducing the computing cost for the same. It plays a major role in the gene expression profiling, chromosome counting, finding out the epigenetic changes, and enabling the future of personalized medicine. Here the authors describe the NGS technologies and its application as well as applying different tools such as TopHat, Bowtie, Cufflinks, Cuffmerge, Cuffdiff for analyzing the high throughput RNA sequencing (RNA-Seq) data.


2012 ◽  
Vol 30 (15_suppl) ◽  
pp. 3065-3065
Author(s):  
Lorenza Mittempergher ◽  
Iris de Rink ◽  
Marja Nieuwland ◽  
Ron M Kerkhoven ◽  
Annuska Glas ◽  
...  

3065 Background: The development of new biomarkers often requires fresh frozen (FF) samples. Recently we showed that microarray gene expression data generated from FFPE material are comparable to data extracted from the FF counterpart, including known signatures such as the 70-gene prognosis signature (Mittempergher L et al., 2011). As described by Luo et al (2010) RNA profiling using next generation sequencing (RNA-Seq) is now applicable to archival FFPE specimens. Methods: Technical performance and the comparison between the RNA-Seq 70-gene read-out and the MammaPrint test (Glas et al., 2006) is evaluated in a series of 15 patients (11/15 with matched FFPE/FF material). RNA-Seq was carried out using minor adjustments of the Illumina TruSeq RNA preparation method. RNA sequencing libraries were prepared starting from 100ng of total RNA. Next, the DSN (Duplex-Specific Nuclease) normalization process was used to remove ribosomal RNA and other abundant transcripts (Luo et al, 2010). The libraries were paired-end sequenced on the Illumina HiSeq 2000 instrument with multiplexing of 4 libraries per lane. The resulting sequences were mapped to the human reference genome (build 37) using TopHat 1.3.1(Trapnell et al., 2009). The HTSeq-count tool was used to generate the total number of uniquely mapped reads for each gene. Results: Between 14% and 45% of the total number of reads were assigned to protein-coding genes. The minimum coverage per 1000bp of CDS was 38 reads. The 70 MammaPrint genes were successfully mapped to the RNA-Seq transcripts. We calculated the Pearson correlation coefficient between the centroids of the original good prognosis template (van’t Veer et al., 2002) and the 70-gene read count determined by RNA-Seq of each sample. Predictions based on the 70-gene RNA-Seq data showed a high agreement with the actual MammaPrint test predictions (>90%), irrespective of whether the RNA-seq was performed on FF or FFPE tissue. Conclusions: New generation RNA-sequencing is a feasible technology to assess diagnostic signatures.


Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 3576-3576
Author(s):  
Noriko Satake ◽  
Sheila Thampi ◽  
Clifford Tepper ◽  
Astra Chang ◽  
Ping Zhou ◽  
...  

Abstract Abstract 3576 Primary leukemia cells are known to be difficult to culture in vitro. Therefore, mouse xenograft models are commonly used to study human leukemia biology and to develop new therapeutics. Leukemia can be maintained and expanded through serial transplantations. Although many mouse models with different types of leukemia, mouse strains, and inoculation methods, have been used, there are very few studies validating the models. We have established acute lymphoblastic leukemia (ALL) mouse models using primary ALL samples and NOD/SCID/IL2Rg null (NSG) mice. In order to increase engraftment efficiency, we transplanted leukemia cells into healthy adult mice via intra-bone marrow (BM) injection (1 to 100 million cells per mouse to tibia bilaterally). To our knowledge, the model with primary ALL samples in NSG mice via intra-BM injection is novel. A total of 9 samples, 2 T cell ALL and 7 precursor B (preB) ALL, were transplanted into cohorts of 3 to 8 mice each. Of these, 1 T cell ALL and 6 preB ALL samples engrafted and 1 T cell and 1 preB ALL sample failed to engraft. Leukemia engraftment was observed between 10 to 33 weeks after transplantation. In each cohort, each mouse developed leukemia at approximately the same time after leukemia transplantation. Necropsy showed significant hepatosplenomegaly and white BM in all mice, indicating leukemia infiltration. Cells were harvested from BM, spleen and other leukemia-infiltrated organs, and confirmed to be human origin by flow cytometry using anti-HLA-ABC and anti- human CD45 antibodies. Nearly 100% of BM was replaced with human leukemia cells. One T cell and 1 preB ALL sample have been serially transplanted using the same method as the primary transplantation to quaternary and tertiary generations, respectively. We observed that the time to develop leukemia became shorter with each transplantation: 16 weeks for the first transplantation and 10 weeks for the tertiary transplantation in a T cell ALL sample. Some mice transplanted with a preB ALL sample developed chloroma. Interestingly, chloroma development was consistently observed with this sample, which was transferred through serial transplantation although the patient did not develop chloroma. Morphology and immunophenotype were similar to the original leukemia. There were some changes in CD expression patterns; however, immunophenotyping was consistent with the original leukemia. To help understand phenotype progression in transplanted leukemia samples, we are currently comparing the transcriptome profiles of leukemia samples obtained from the patient, primary and quaternary mice for T cell ALL, and primary and tertiary mice for preB ALL samples (preB ALL patient sample not available). Next-generation sequencing (NGS)-based RNA-Sequencing (RNA-Seq) is in progress for this analysis. In addition to obtaining digital expression profiles, and differential gene expression, RNA-Seq analysis will reveal the complete repertoire of splice variants, point mutations, and fusion transcripts in the ALL samples. Complete results of these analyses for our mouse models with both T cell and preB ALL will be presented. Thus, this technique will provide the most detailed transcriptomic analysis and no validation studies have yet been reported on ALL samples sequentially engrafted NSG mice using RNA-Seq. Disclosures: No relevant conflicts of interest to declare.


2021 ◽  
Author(s):  
Peter Natesan Pushparaj ◽  
Laila Abdullah Damiati ◽  
Luliana Denetiu ◽  
Sherin Bakhashab ◽  
Muhammad Asif ◽  
...  

Abstract BackgroundThe coronavirus (CoV) disease identified in Wuhan, China in 2019 (COVID-19) was chiefly characterized by atypical pneumonia and severe acute respiratory syndrome (SARS) and caused by SARS CoV-2 that belongs to the family Coronaviridae. COVID-19 symptoms vary from a mild cold to more severe illnesses such as SARS, thrombosis, stroke, organ failure, and in some patients even cause mortality. Deciphering the underlying disease mechanisms is pivotal for the identification and development of COVID-19 specific drugs for effective treatment and prevent human-to-human transmission, disease complications, and mortality. Methodology: Here, the Next Generation RNA Sequencing (RNA Seq) data using Illumina Next Seq 500 from SARS CoV-infected A549 cells and mock-treated A549 cells, were obtained from the gene expression omnibus (GEO) (GSE147507) and the Quality Control (QC) were evaluated using the CLC Genomics Workbench 20.0 (Qiagen, USA) before the RNA Seq analysis. The DEGs were imported into BioJupies to analyze to decipher COVID-19 induced biological, molecular, and cellular processes, pathways, and small molecules derived from chemical synthesis or natural sources to mimic or reverse COVID-19-specific gene signatures. Besides, we have used the iPathwayGuide (Advaita Bioinformatics USA) to identify COVID-19 specific pathways, biological, molecular, and cellular processes, and “druggable” candidates for future therapy. Results: 141 DEGs were identified out of a total of 9665 DEGs obtained from BioJupies analysis of the RNASeq reads of the SARS CoV infected A549 cells and mock-treated A549 cells based on a p-value cut off (0.05) and a fold change cut off 1.5.Conclusion: In conclusion, the present study unravels a novel approach of using next-generation knowledge discovery platforms to discover specific drugs for the amelioration of COVID-19 related disease pathologies.


2020 ◽  
Author(s):  
Jipan Zhang ◽  
Chengchen Deng ◽  
Jialu Li ◽  
Yong-Ju Zhao

Abstract Background: In Quantitative real-time polymerase chain reaction (qRT-PCR) experiments, accurate and reliable target gene expression data is dependent on optimal amplification of house-keeping genes (HKGs). RNA-seq technology offers a novel approach to detect new HKGs with improved stability. Goat (Capra hircus) is an economically important livestock species and plays an indispensable role in the world animal fiber and meat industry. Unfortunately, uniform and reliable HKGs for use in goat skin research have not been identified. Therefore, this study seeks to identify a set of stable HKGs for the skin tissue of C. hircus using high-throughput sequencing technology.Results: Based on the transcriptome dataset of 39 goat skin tissue samples, 8 genes (SRP68, NCBP3, RRAGA, EIF4H, CTBP2, PTPRA, CNBP, and EEF2) with relatively stable expression levels were identified and selected as new candidate HKGs. Commonly used HKGs including SDHA and YWHAZ from a previous study, and 2 conventional genes (ACTB and GAPDH) were also examined. Four different experimental variables: (1) different development stages, (2) hair follicle cycle stages, (3) breeds and (4) sampling sites, were used for determination and validation. Four algorithms (geNorm, NormFinder, BestKeeper, and ΔCt method) and a comprehensive algorithm (ComprFinder, developed in-house) were used to assess the stability of each HKG. It was shown that NCBP3+SDHA+PTPRA were more stably expressed than previously used genes in all conditions analyzed, and that this combination was effective at normalizing target gene expression. Moreover, a new algorithm for comprehensive analysis, ComprFinder, was developed and released.Conclusion: This study presents the first data of candidate HKGs for C. hircus skin tissues based on an RNA-seq dataset. We propose that the NCBP3+SDHA+PTPRA combination be used as a triplet set of HKGs in skin molecular biology experiments in C. hircus and other closely related species to standardize analyses across studies. In addition, we also encourage researchers who perform candidate HKG evaluations and who have the need for comprehensive analysis to adopt our new algorithm, ComprFinder.


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