scholarly journals Measuring complex phenotypes: A flexible high-throughput design for micro-respirometry

2020 ◽  
Author(s):  
Amanda N. DeLiberto ◽  
Melissa K. Drown ◽  
Marjorie F. Oleksiak ◽  
Douglas L. Crawford
Keyword(s):  
High Throughput ◽  
Biological Samples ◽  
Fundulus Heteroclitus ◽  
Tissue Specificity ◽  
Evolutionary Relationship ◽  
Cost Effective ◽  
Throughput Capacity ◽  
Published Data ◽  
Tissue Specific ◽  
Complex Phenotypes

AbstractVariation in tissue-specific metabolism between species and among individuals is thought to be adaptively important; however, understanding this evolutionary relationship requires reliably measuring this trait in many individuals. In most higher organisms, tissue specificity is important because different organs (heart, brain, liver, muscle) have unique ecologically adaptive roles. Current technology and methodology for measuring tissue-specific metabolism is costly and limited by throughput capacity and efficiency. Presented here is the design for a flexible and cost-effective high-throughput micro-respirometer (HTMR) optimized to measure small biological samples. To verify precision and accuracy, substrate specific metabolism was measured in heart ventricles isolated from a small teleost, Fundulus heteroclitus, and in yeast (Saccharomyces cerevisiae). Within the system, results were reproducible between chambers and over time with both teleost hearts and yeast. Additionally, metabolic rates and allometric scaling relationships in Fundulus agree with previously published data measured with lower-throughput equipment. This design reduces cost, but still provides an accurate measure of metabolism in small biological samples. This will allow for high-throughput measurement of tissue metabolism that can enhance understanding of the adaptive importance of complex metabolic traits.

movAPA: modeling and visualization of dynamics of alternative polyadenylation across biological samples

2020 ◽  
Author(s):  
Wenbin Ye ◽  
Tao Liu ◽  
Hongjuan Fu ◽  
Congting Ye ◽  
Guoli Ji ◽  
...  
Keyword(s):  
Biological Samples ◽  
Tissue Specificity ◽  
Single Cells ◽  
Alternative Polyadenylation ◽  
R Package ◽  
Supplementary Information ◽  
Rna Seq ◽  
Mouse Sperm ◽  
High Scalability ◽  
A Site

Abstract Motivation Alternative polyadenylation (APA) has been widely recognized as a widespread mechanism modulated dynamically. Studies based on 3′ end sequencing and/or RNA-seq have profiled poly(A) sites in various species with diverse pipelines, yet no unified and easy-to-use toolkit is available for comprehensive APA analyses. Results We developed an R package called movAPA for modeling and visualization of dynamics of alternative polyadenylation across biological samples. movAPA incorporates rich functions for preprocessing, annotation and statistical analyses of poly(A) sites, identification of poly(A) signals, profiling of APA dynamics and visualization. Particularly, seven metrics are provided for measuring the tissue-specificity or usages of APA sites across samples. Three methods are used for identifying 3′ UTR shortening/lengthening events between conditions. APA site switching involving non-3′ UTR polyadenylation can also be explored. Using poly(A) site data from rice and mouse sperm cells, we demonstrated the high scalability and flexibility of movAPA in profiling APA dynamics across tissues and single cells. Availability and implementation https://github.com/BMILAB/movAPA. Supplementary information Supplementary data are available at Bioinformatics online.

Cooperativity of sequence elements mediates tissue specificity of the rat insulin II gene

1990 ◽  
Vol 10 (4) ◽  
pp. 1784-1788
Author(s):  
Y P Hwung ◽  
Y Z Gu ◽  
M J Tsai
Keyword(s):  
Beta Cell ◽  
Tissue Specificity ◽  
Promoter Element ◽  
Heterologous Promoter ◽  
Specific Expression ◽  
Tissue Specific ◽  
Cis Acting ◽  
Insulin Promoter ◽  
Sequence Elements ◽  
Flanking Region

The 5'-flanking region of the rat insulin II gene (-448 to +50) is sufficient for tissue-specific expression. To further determine the tissue-specific cis-acting element(s), important sequences defined by linker-scanning mutagenesis were placed upstream of a heterologous promoter and transfected into insulin-producing and -nonproducing cells. Rat insulin promoter element 3 (RIPE3), which spans from -125 to -86, was shown to confer beta-cell-specific expression in either orientation. However, two subregions of RIPE3, RIPE3a and RIPE3b (defined by linker-scanning mutations), displayed only marginal activities. These results suggest that the two subregions cooperate to confer tissue specificity, presumably via their cognate binding factors.

scholarly journals Different Amplicon Targets for Sequencing-Based Studies of Fungal Diversity

2017 ◽  
Vol 83 (17) ◽  
Author(s):  
Francesca De Filippis ◽  
Manolo Laiola ◽  
Giuseppe Blaiotta ◽  
Danilo Ercolini
Keyword(s):  
Microbial Ecology ◽  
High Throughput ◽  
Biological Samples ◽  
Fungal Diversity ◽  
High Throughput Sequencing ◽  
Amplicon Sequencing ◽  
Fungal Species ◽  
Fungal Communities ◽  
Its2 Region ◽  
Mock Community

ABSTRACT Target-gene amplicon sequencing is the most exploited high-throughput sequencing application in microbial ecology. The targets are taxonomically relevant genes, with 16S rRNA being the gold standard for bacteria. As for fungi, the most commonly used target is the internal transcribed spacer (ITS). However, the uneven ITS length among species may promote preferential amplification and sequencing and incorrect estimation of their abundance. Therefore, the use of different targets is desirable. We evaluated the use of three different target amplicons for the characterization of fungal diversity. After an in silico primer evaluation, we compared three amplicons (the ITS1-ITS2 region [ITS1-2], 18S ribosomal small subunit RNA, and the D1/D2 domain of the 26S ribosomal large subunit RNA), using biological samples and a mock community of common fungal species. All three targets allowed for accurate identification of the species present. Nevertheless, high heterogeneity in ITS1-2 length was found, and this caused an overestimation of the abundance of species with a shorter ITS, while both 18S and 26S amplicons allowed for more reliable quantification. We demonstrated that ITS1-2 amplicon sequencing, although widely used, may lead to an incorrect evaluation of fungal communities, and efforts should be made to promote the use of different targets in sequencing-based microbial ecology studies. IMPORTANCE Amplicon-sequencing approaches for fungi may rely on different targets affecting the diversity and abundance of the fungal species. An increasing number of studies will address fungal diversity by high-throughput amplicon sequencing. The description of the communities must be accurate and reliable in order to draw useful insights and to address both ecological and biological questions. By analyzing a mock community and several biological samples, we demonstrate that using different amplicon targets may change the results of fungal microbiota analysis, and we highlight how a careful choice of the target is fundamental for a thorough description of the fungal communities.

scholarly journals HiSpike Method for High-Throughput Cost Effective Sequencing of the SARS-CoV-2 Spike Gene

2022 ◽  
Vol 8 ◽  
Author(s):  
Ephraim Fass ◽  
Gal Zizelski Valenci ◽  
Mor Rubinstein ◽  
Paul J. Freidlin ◽  
Shira Rosencwaig ◽  
...  
Keyword(s):  
Real Time ◽  
High Throughput ◽  
Cost Effective ◽  
Developed Countries ◽  
Spike Protein ◽  
Medical Community ◽  
Effective Vaccine ◽  
Gene Variants ◽  
Spike Gene ◽  
Field Samples

The changing nature of the SARS-CoV-2 pandemic poses unprecedented challenges to the world's health systems. Emerging spike gene variants jeopardize global efforts to produce immunity and reduce morbidity and mortality. These challenges require effective real-time genomic surveillance solutions that the medical community can quickly adopt. The SARS-CoV-2 spike protein mediates host receptor recognition and entry into the cell and is susceptible to generation of variants with increased transmissibility and pathogenicity. The spike protein is the primary target of neutralizing antibodies in COVID-19 patients and the most common antigen for induction of effective vaccine immunity. Tight monitoring of spike protein gene variants is key to mitigating COVID-19 spread and generation of vaccine escape mutants. Currently, SARS-CoV-2 sequencing methods are labor intensive and expensive. When sequence demands are high sequencing resources are quickly exhausted. Consequently, most SARS-CoV-2 strains are sequenced in only a few developed countries and rarely in developing regions. This poses the risk that undetected, dangerous variants will emerge. In this work, we present HiSpike, a method for high-throughput cost effective targeted next generation sequencing of the spike gene. This simple three-step method can be completed in < 30 h, can sequence 10-fold more samples compared to conventional methods and at a fraction of their cost. HiSpike has been validated in Israel, and has identified multiple spike variants from real-time field samples including Alpha, Beta, Delta and the emerging Omicron variants. HiSpike provides affordable sequencing options to help laboratories conserve resources for widespread high-throughput, near real-time monitoring of spike gene variants.

scholarly journals (GTG)5-PCR Mediated Molecular Typing of Zoonotic Bacteria

2021 ◽  
Vol 11 (2) ◽  
pp. 279-283
Author(s):  
Daryoush Babazadeh ◽  
Reza Ranjbar
Keyword(s):  
Molecular Typing ◽  
Cost Effective ◽  
Present Review ◽  
Published Data ◽  
Bacterial Isolates ◽  
The Past ◽  
Virulent Strains ◽  
Pcr Method ◽  
Zoonotic Bacteria

The present review aimed to reveal the role of (GTG)5-PCR microbial typing in indicating the routes and source of infections, investigate the outbreaks and genotypes of clinical strains, as well as finding virulent strains and epidemiology of bacterial isolates. All available and published data in Google scholar, PubMed, ResearchGate, and Science Direct during the past two decades that used the (GTG)5-PCR method for genotyping the bacterial isolates were included in the current study. The findings have indicated that (GTG)5-PCR can be recommended as a possible, cost-effective, fast, and easy tool for molecular typing of bacterial isolates.

scholarly journals Analyzing cancer gene expression data through the lens of normal tissue-specificity

2021 ◽  
Author(s):  
H. Robert Frost
Keyword(s):  
Gene Expression ◽  
Normal Tissue ◽  
Tissue Specificity ◽  
Cancer Genomics ◽  
Expression Profiles ◽  
Genetic Alterations ◽  
Cancer Type ◽  
Tissue Specific ◽  
Normal Tissues ◽  
Cancer Types

AbstractThe genetic alterations that underlie cancer development are highly tissue-specific with the majority of driving alterations occurring in only a few cancer types and with alterations common to multiple cancer types often showing a tissue-specific functional impact. This tissue-specificity means that the biology of normal tissues carries important information regarding the pathophysiology of the associated cancers, information that can be leveraged to improve the power and accuracy of cancer genomic analyses. Research exploring the use of normal tissue data for the analysis of cancer genomics has primarily focused on the paired analysis of tumor and adjacent normal samples. Efforts to leverage the general characteristics of normal tissue for cancer analysis has received less attention with most investigations focusing on understanding the tissue-specific factors that lead to individual genomic alterations or dysregulated pathways within a single cancer type. To address this gap and support scenarios where adjacent normal tissue samples are not available, we explored the genome-wide association between the transcriptomes of 21 solid human cancers and their associated normal tissues as profiled in healthy individuals. While the average gene expression profiles of normal and cancerous tissue may appear distinct, with normal tissues more similar to other normal tissues than to the associated cancer types, when transformed into relative expression values, i.e., the ratio of expression in one tissue or cancer relative to the mean in other tissues or cancers, the close association between gene activity in normal tissues and related cancers is revealed. As we demonstrate through an analysis of tumor data from The Cancer Genome Atlas and normal tissue data from the Human Protein Atlas, this association between tissue-specific and cancer-specific expression values can be leveraged to improve the prognostic modeling of cancer, the comparative analysis of different cancer types, and the analysis of cancer and normal tissue pairs.

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