scholarly journals Use of Routinely Collected Amniotic Fluid for Whole-Genome Expression Analysis of Polygenic Disorders

2006 ◽  
Vol 52 (11) ◽  
pp. 2013-2020 ◽  
Author(s):  
Gyula Richárd Nagy ◽  
Balázs Gyõrffy ◽  
Orsolya Galamb ◽  
Béla Molnár ◽  
Bálint Nagy ◽  
...  

Abstract Background: Neural tube defects related to polygenic disorders are the second most common birth defects in the world, but no molecular biologic tests are available to analyze the genes involved in the pathomechanism of these disorders. We explored the use of routinely collected amniotic fluid to characterize the differential gene expression profiles of polygenic disorders. Methods: We used oligonucleotide microarrays to analyze amniotic fluid samples obtained from pregnant women carrying fetuses with neural tube defects diagnosed during ultrasound examination. The control samples were obtained from pregnant women who underwent routine genetic amniocentesis because of advanced maternal age (>35 years). We also investigated specific folate-related genes because maternal periconceptional folic acid supplementation has been found to have a protective effect with respect to neural tube defects. Results: Fetal mRNA from amniocytes was successfully isolated, amplified, labeled, and hybridized to whole-genome transcript arrays. We detected differential gene expression profiles between cases and controls. Highlighted genes such as SLA, LST1, and BENE might be important in the development of neural tube defects. None of the specific folate-related genes were in the top 100 associated transcripts. Conclusions: This pilot study demonstrated that a routinely collected amount of amniotic fluid (as small as 6 mL) can provide sufficient RNA to successfully hybridize to expression arrays. Analysis of the differences in fetal gene expressions might help us decipher the complex genetic background of polygenic disorders.

2016 ◽  
Vol 6 (1_suppl) ◽  
pp. s-0036-1582635-s-0036-1582635 ◽  
Author(s):  
Sibylle Grad ◽  
Ying Zhang ◽  
Olga Rozhnova ◽  
Elena Schelkunova ◽  
Mikhail Mikhailovsky ◽  
...  

2019 ◽  
Vol 20 (23) ◽  
pp. 6098 ◽  
Author(s):  
Amarinder Singh Thind ◽  
Kumar Parijat Tripathi ◽  
Mario Rosario Guarracino

The comparison of high throughput gene expression datasets obtained from different experimental conditions is a challenging task. It provides an opportunity to explore the cellular response to various biological events such as disease, environmental conditions, and drugs. There is a need for tools that allow the integration and analysis of such data. We developed the “RankerGUI pipeline”, a user-friendly web application for the biological community. It allows users to use various rank based statistical approaches for the comparison of full differential gene expression profiles between the same or different biological states obtained from different sources. The pipeline modules are an integration of various open-source packages, a few of which are modified for extended functionality. The main modules include rank rank hypergeometric overlap, enriched rank rank hypergeometric overlap and distance calculations. Additionally, preprocessing steps such as merging differential expression profiles of multiple independent studies can be added before running the main modules. Output plots show the strength, pattern, and trends among complete differential expression profiles. In this paper, we describe the various modules and functionalities of the developed pipeline. We also present a case study that demonstrates how the pipeline can be used for the comparison of differential expression profiles obtained from multiple platforms’ data of the Gene Expression Omnibus. Using these comparisons, we investigate gene expression patterns in kidney and lung cancers.


2009 ◽  
Vol 71 (4) ◽  
pp. 205-222 ◽  
Author(s):  
Ji Hyeong Baek ◽  
Tae Ha Woo ◽  
Chang Bae Kim ◽  
Jong Hwa Park ◽  
Hyojoong Kim ◽  
...  

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