Transcriptomic analysis of the early strobilar development of Echinococcus granulosus

AbstractBackgroundEchinococcus granulosus has a complex life cycle involving two mammalian hosts. The transition from one host to another is accompanied by changes in gene expression, and the transcriptional events that underlie these processes have not yet been fully characterized.ResultsIn this study, RNA-seq is used to compare the transcription profiles of four time samples of E. granulosus protoscoleces in vitro induced to strobilar development. We identified 818 differentially expressed genes, which were divided into eight expression clusters formed over the entire 24 hours time course and indicated different transcriptional patterns. An enrichment of gene transcripts with molecular functions of signal transduction, enzymes and protein modifications was observed with progression of development.ConclusionThis transcriptomic study provides insight for understanding the complex life cycle of E. granulosus and contributes for searching for the key genes correlating with the strobilar development, providing interesting hints for further studies.

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Transcriptomic Analysis of the Early Strobilar Development of Echinococcus granulosus

Pathogens ◽

10.3390/pathogens9060465 ◽

2020 ◽

Vol 9 (6) ◽

pp. 465

Author(s):

João Antonio Debarba ◽

Martín Pablo Cancela Sehabiague ◽

Karina Mariante Monteiro ◽

Alexandra Lehmkuhl Gerber ◽

Ana Tereza Ribeiro Vasconcelos ◽

...

Keyword(s):

Life Cycle ◽

Echinococcus Granulosus ◽

Complex Life Cycle ◽

Rna Seq ◽

Time Points ◽

Transcription Profiles ◽

Developmental Progression ◽

Gene Transcripts ◽

Key Genes

Echinococcus granulosus has a complex life cycle involving two mammalian hosts. The transition from one host to another is accompanied by changes in gene expression, and the transcriptional events that underlie this transition have not yet been fully characterized. In this study, RNA-seq was used to compare the transcription profiles of samples from E. granulosus protoscoleces induced in vitro to strobilar development at three time points. We identified 818 differentially expressed genes, which were divided into eight expression clusters formed over the entire 24 h period. An enrichment of gene transcripts with molecular functions of signal transduction, enzymes, and protein modifications was observed upon induction and developmental progression. This transcriptomic study provides insights for understanding the complex life cycle of E. granulosus and contributes for searching for the key genes correlating with the strobilar development, which can be used to identify potential candidates for the development of anthelmintic drugs.

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Transcriptomic profiling of human orbital fat and differentiating orbital fibroblasts

10.1101/2021.05.13.443857 ◽

2021 ◽

Author(s):

Dong Won Kim ◽

Kamil Taneja ◽

Thanh Hoang ◽

Clayton Pio Santiago ◽

Timothy James McCulley ◽

...

Keyword(s):

Gene Expression ◽

Signaling Pathways ◽

Time Course ◽

Principal Component ◽

Developmental Time ◽

Rna Seq ◽

Orbital Fat ◽

Orbital Fibroblasts ◽

Compare Gene Expression

Purpose: Orbital fat hyperplasia has a central role in the manifestations of thyroid-associated orbitopathy (TAO). To better understand the pathways involved in adipogenesis in TAO, we have used transcriptomic methods to analyze gene expression in control and TAO patients, as well as in differentiating orbital fibroblasts (OFs). Methods: We performed bulk RNA sequencing (RNA-Seq) on intraconal orbital fat to compare gene expression in control and TAO patients. We treated cultured OFs derived from TAO patients with media containing dexamethasone, insulin, rosiglitazone, and isobutylmethylxanthine (IBMX) to induce adipogenesis. We used single nuclear RNA-Seq (snRNA-Seq) profiling of treated OFs to compare gene expression over time in order to identify pathways that are involved in orbital adipogenesis in vitro and compared the dynamic patterns of gene expression identify differences in gene expression in control and TAO orbital fat. Results: Orbital fat from TAO and control patients segregate with principal component analysis (PCA). Numerous signaling pathways are enriched in orbital fat isolated from TAO patients. SnRNA-Seq of orbital fibroblasts undergoing adipogenesis reveals differential expression of adipocyte-specific genes over the developmental time course. Furthermore, genes that are enriched in TAO orbital fat are also upregulated in orbital adipocytes that differentiate in vitro, while genes that are enriched in control orbital fat are enriched in orbital fibroblasts prior to differentiation. Conclusions: Differentiating orbital fibroblasts serve as a model to study orbital fat hyperplasia seen in TAO. We demonstrate that the insulin-like growth factor-1 receptor (IGF-1R) and Wnt signaling pathways are differentially expressed early in orbital adipogenesis.

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SPLICE-q: a Python tool for genome-wide quantification of splicing efficiency

BMC Bioinformatics ◽

10.1186/s12859-021-04282-6 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Verônica R. de Melo Costa ◽

Julianus Pfeuffer ◽

Annita Louloupi ◽

Ulf A. V. Ørom ◽

Rosario M. Piro

Keyword(s):

Gene Expression ◽

Cancer Progression ◽

Time Course ◽

Progressive Increase ◽

Rna Seq ◽

Transcript Processing ◽

Aberrant Transcript ◽

Genome Wide ◽

Splicing Efficiency ◽

Nascent Rna

Abstract Background Introns are generally removed from primary transcripts to form mature RNA molecules in a post-transcriptional process called splicing. An efficient splicing of primary transcripts is an essential step in gene expression and its misregulation is related to numerous human diseases. Thus, to better understand the dynamics of this process and the perturbations that might be caused by aberrant transcript processing it is important to quantify splicing efficiency. Results Here, we introduce SPLICE-q, a fast and user-friendly Python tool for genome-wide SPLICing Efficiency quantification. It supports studies focusing on the implications of splicing efficiency in transcript processing dynamics. SPLICE-q uses aligned reads from strand-specific RNA-seq to quantify splicing efficiency for each intron individually and allows the user to select different levels of restrictiveness concerning the introns’ overlap with other genomic elements such as exons of other genes. We applied SPLICE-q to globally assess the dynamics of intron excision in yeast and human nascent RNA-seq. We also show its application using total RNA-seq from a patient-matched prostate cancer sample. Conclusions Our analyses illustrate that SPLICE-q is suitable to detect a progressive increase of splicing efficiency throughout a time course of nascent RNA-seq and it might be useful when it comes to understanding cancer progression beyond mere gene expression levels. SPLICE-q is available at: https://github.com/vrmelo/SPLICE-q

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Single cell RNA sequencing of calvarial and long bone endocortical cells

10.1101/849224 ◽

2019 ◽

Cited By ~ 1

Author(s):

Ugur M. Ayturk ◽

Joseph P. Scollan ◽

Alexander Vesprey ◽

Christina M. Jacobsen ◽

Paola Divieti Pajevic ◽

...

Keyword(s):

Gene Expression ◽

Single Cell ◽

Cultured Cells ◽

Neutralizing Antibody ◽

Long Bone ◽

Appendicular Skeleton ◽

Rna Seq ◽

Isolated Cells

ABSTRACTSingle cell RNA-seq (scRNA-seq) is emerging as a powerful technology to examine transcriptomes of individual cells. We determined whether scRNA-seq could be used to detect the effect of environmental and pharmacologic perturbations on osteoblasts. We began with a commonly used in vitro system in which freshly isolated neonatal mouse calvarial cells are expanded and induced to produce a mineralized matrix. We used scRNA-seq to compare the relative cell type abundances and the transcriptomes of freshly isolated cells to those that had been cultured for 12 days in vitro. We observed that the percentage of macrophage-like cells increased from 6% in freshly isolated calvarial cells to 34% in cultured cells. We also found that Bglap transcripts were abundant in freshly isolated osteoblasts but nearly undetectable in the cultured calvarial cells. Thus, scRNA-seq revealed significant differences between heterogeneity of cells in vivo and in vitro. We next performed scRNA-seq on freshly recovered long bone endocortical cells from mice that received either vehicle or Sclerostin-neutralizing antibody for 1 week. Bone anabolism-associated transcripts were also not significantly increased in immature and mature osteoblasts recovered from Sclerostin-neutralizing antibody treated mice; this is likely a consequence of being underpowered to detect modest changes in gene expression, since only 7% of the sequenced endocortical cells were osteoblasts, and a limited portion of their transcriptomes were sampled. We conclude that scRNA-seq can detect changes in cell abundance, identity, and gene expression in skeletally derived cells. In order to detect modest changes in osteoblast gene expression at the single cell level in the appendicular skeleton, larger numbers of osteoblasts from endocortical bone are required.

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Enhancing droplet-based single-nucleus RNA-seq resolution using the semi-supervised machine learning classifier DIEM

10.1101/786285 ◽

2019 ◽

Cited By ~ 4

Author(s):

Marcus Alvarez ◽

Elior Rahmani ◽

Brandon Jew ◽

Kristina M. Garske ◽

Zong Miao ◽

...

Keyword(s):

Gene Expression ◽

Single Cell ◽

Cell Types ◽

Supervised Machine Learning ◽

Data Sets ◽

Rna Seq ◽

Novel Approach ◽

Single Nucleus ◽

Downstream Analysis

AbstractSingle-nucleus RNA sequencing (snRNA-seq) measures gene expression in individual nuclei instead of cells, allowing for unbiased cell type characterization in solid tissues. Contrary to single-cell RNA seq (scRNA-seq), we observe that snRNA-seq is commonly subject to contamination by high amounts of extranuclear background RNA, which can lead to identification of spurious cell types in downstream clustering analyses if overlooked. We present a novel approach to remove debris-contaminated droplets in snRNA-seq experiments, called Debris Identification using Expectation Maximization (DIEM). Our likelihood-based approach models the gene expression distribution of debris and cell types, which are estimated using EM. We evaluated DIEM using three snRNA-seq data sets: 1) human differentiating preadipocytes in vitro, 2) fresh mouse brain tissue, and 3) human frozen adipose tissue (AT) from six individuals. All three data sets showed various degrees of extranuclear RNA contamination. We observed that existing methods fail to account for contaminated droplets and led to spurious cell types. When compared to filtering using these state of the art methods, DIEM better removed droplets containing high levels of extranuclear RNA and led to higher quality clusters. Although DIEM was designed for snRNA-seq data, we also successfully applied DIEM to single-cell data. To conclude, our novel method DIEM removes debris-contaminated droplets from single-cell-based data fast and effectively, leading to cleaner downstream analysis. Our code is freely available for use at https://github.com/marcalva/diem.

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Identification and classification of cis-regulatory elements in the amphipod crustacean Parhyale hawaiensis

10.1101/2021.09.16.460328 ◽

2021 ◽

Author(s):

Dennis A Sun ◽

Nipam H Patel

Keyword(s):

Gene Expression ◽

Genome Annotation ◽

Time Course ◽

Regulatory Elements ◽

Rna Seq ◽

Genome Wide ◽

Long Read ◽

Amphipod Crustacean ◽

Accessible Chromatin

AbstractEmerging research organisms enable the study of biology that cannot be addressed using classical “model” organisms. The development of novel data resources can accelerate research in such animals. Here, we present new functional genomic resources for the amphipod crustacean Parhyale hawaiensis, facilitating the exploration of gene regulatory evolution using this emerging research organism. We use Omni-ATAC-Seq, an improved form of the Assay for Transposase-Accessible Chromatin coupled with next-generation sequencing (ATAC-Seq), to identify accessible chromatin genome-wide across a broad time course of Parhyale embryonic development. This time course encompasses many major morphological events, including segmentation, body regionalization, gut morphogenesis, and limb development. In addition, we use short- and long-read RNA-Seq to generate an improved Parhyale genome annotation, enabling deeper classification of identified regulatory elements. We leverage a variety of bioinformatic tools to discover differential accessibility, predict nucleosome positioning, infer transcription factor binding, cluster peaks based on accessibility dynamics, classify biological functions, and correlate gene expression with accessibility. Using a Minos transposase reporter system, we demonstrate the potential to identify novel regulatory elements using this approach, including distal regulatory elements. This work provides a platform for the identification of novel developmental regulatory elements in Parhyale, and offers a framework for performing such experiments in other emerging research organisms.Primary Findings-Omni-ATAC-Seq identifies cis-regulatory elements genome-wide during crustacean embryogenesis-Combined short- and long-read RNA-Seq improves the Parhyale genome annotation-ImpulseDE2 analysis identifies dynamically regulated candidate regulatory elements-NucleoATAC and HINT-ATAC enable inference of nucleosome occupancy and transcription factor binding-Fuzzy clustering reveals peaks with distinct accessibility and chromatin dynamics-Integration of accessibility and gene expression reveals possible enhancers and repressors-Omni-ATAC can identify known and novel regulatory elements

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Importance of experimental information (metadata) for archived sequence data: case of specific gene bias due to lag time between sample harvest and RNA protection in RNA sequencing

PeerJ ◽

10.7717/peerj.11875 ◽

2021 ◽

Vol 9 ◽

pp. e11875

Author(s):

Tomoko Matsuda

Keyword(s):

Gene Expression ◽

Rna Sequencing ◽

Time Course ◽

Sequence Data ◽

Specific Gene ◽

Time Interval ◽

Short Time Interval ◽

Rna Seq ◽

Lysis Buffer ◽

Rna Protection

Large volumes of high-throughput sequencing data have been submitted to the Sequencing Read Archive (SRA). The lack of experimental metadata associated with the data makes reuse and understanding data quality very difficult. In the case of RNA sequencing (RNA-Seq), which reveals the presence and quantity of RNA in a biological sample at any moment, it is necessary to consider that gene expression responds over a short time interval (several seconds to a few minutes) in many organisms. Therefore, to isolate RNA that accurately reflects the transcriptome at the point of harvest, raw biological samples should be processed by freezing in liquid nitrogen, immersing in RNA stabilization reagent or lysing and homogenizing in RNA lysis buffer containing guanidine thiocyanate as soon as possible. As the number of samples handled simultaneously increases, the time until the RNA is protected can increase. Here, to evaluate the effect of different lag times in RNA protection on RNA-Seq data, we harvested CHO-S cells after 3, 5, 6, and 7 days of cultivation, added RNA lysis buffer in a time course of 15, 30, 45, and 60 min after harvest, and conducted RNA-Seq. These RNA samples showed high RNA integrity number (RIN) values indicating non-degraded RNA, and sequence data from libraries prepared with these RNA samples was of high quality according to FastQC. We observed that, at the same cultivation day, global trends of gene expression were similar across the time course of addition of RNA lysis buffer; however, the expression of some genes was significantly different between the time-course samples of the same cultivation day; most of these differentially expressed genes were related to apoptosis. We conclude that the time lag between sample harvest and RNA protection influences gene expression of specific genes. It is, therefore, necessary to know not only RIN values of RNA and the quality of the sequence data but also how the experiment was performed when acquiring RNA-Seq data from the database.

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Application of Serial Analysis of Gene Expression to the Study of the Gene Expression Profile ofLeishmania infantum chagasiPromastigote

Journal of Biomedicine and Biotechnology ◽

10.1155/2012/673458 ◽

2012 ◽

Vol 2012 ◽

pp. 1-7 ◽

Cited By ~ 1

Author(s):

Adelino Soares Lima Neto ◽

Osvaldo Pompílio de Melo Neto ◽

Carlos Henrique Nery Costa

Keyword(s):

Gene Expression ◽

Life Cycle ◽

Gene Expression Profile ◽

Expression Profile ◽

Leishmania Infantum ◽

Open Reading Frames ◽

Genomic Sequences ◽

Coding Sequences ◽

Key Genes ◽

Reading Frames

This study describes the application of the LongSAGE methodology to study the gene expression profile in promastigotes ofLeishmania infantum chagasi. A tag library was created using the LongSAGE method and consisted of 14,208 tags of 17 bases. Of these, 8,427 (59.3%) were distinct. BLAST research of the 1,645 most abundant tags showed that 12.8% of them identified the coding sequences of genes, while 82% (1,349/1,645) identified one or more genomic sequences that did not correspond with open reading frames. Only 5.2% (84/1,645) of the tags were not aligned to any position in theL. infantum genome. The UTR size ofLeishmaniaand the lack of CATG sites in some transcripts were decisive for the generation of tags in these regions. Additional analysis will allow a better understanding of the expression profile and discovering the key genes in this life cycle.

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Transcriptional Profile of Aedes aegypti Leucine-Rich Repeat Proteins in Response to Zika and Chikungunya Viruses

International Journal of Molecular Sciences ◽

10.3390/ijms20030615 ◽

2019 ◽

Vol 20 (3) ◽

pp. 615 ◽

Cited By ~ 2

Author(s):

Liming Zhao ◽

Barry Alto ◽

Dongyoung Shin

Keyword(s):

Aedes Aegypti ◽

Zika Virus ◽

Time Course ◽

Developmental Stages ◽

Analysis Data ◽

Leucine Rich Repeat ◽

Rna Seq ◽

Gene Expressions ◽

Transcription Profiles ◽

Time Course Study

Aedes aegypti (L.) is the primary vector of chikungunya, dengue, yellow fever, and Zika viruses. The leucine-rich repeats (LRR)-containing domain is evolutionarily conserved in many proteins associated with innate immunity in invertebrates and vertebrates, as well as plants. We focused on the AaeLRIM1 and AaeAPL1 gene expressions in response to Zika virus (ZIKV) and chikungunya virus (CHIKV) infection using a time course study, as well as the developmental expressions in the eggs, larvae, pupae, and adults. RNA-seq analysis data provided 60 leucine-rich repeat related transcriptions in Ae. aegypti in response to Zika virus (Accession number: GSE118858, accessed on: August 22, 2018, GEO DataSets). RNA-seq analysis data showed that AaeLRIM1 (AAEL012086-RA) and AaeAPL1 (AAEL009520-RA) were significantly upregulated 2.5 and 3-fold during infection by ZIKV 7-days post infection (dpi) of an Ae. aegypti Key West strain compared to an Orlando strain. The qPCR data showed that LRR-containing proteins related genes, AaeLRIM1 and AaeAPL1, and five paralogues were expressed 100-fold lower than other nuclear genes, such as defensin, during all developmental stages examined. Together, these data provide insights into the transcription profiles of LRR proteins of Ae. aegypti during its development and in response to infection with emergent arboviruses.

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