Document Detail


OMICS in assisted reproduction: possibilities and pitfalls.
MedLine Citation:
PMID:  20538894     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
A key step in assisted reproduction is the assessment of oocyte and embryo developmental potential in order to determine the embryo(s) most likely to result in pregnancy. Currently used embryo assessment strategies are largely based on embryo morphology and cleavage rate. Although these systems have been successful in improving pregnancy rates and reducing multiple gestations, their precision is still insufficient. Therefore, development of an objective, accurate, fast and affordable test that can aid in the assessment of oocyte and embryo developmental potential is a significant aim of reproductive medicine. Recently, global assessment strategies involving genomic, transcriptomic, proteomic or metabolomic profiling of oocytes, granulosa or cumulus cells, embryos or culture media have been applied to assisted reproduction. These technologies are at different stages of development and present unique advantages as well as limitations.
Authors:
Emre Seli; Claude Robert; Marc-Andre Sirard
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Publication Detail:
Type:  Journal Article; Review     Date:  2010-06-10
Journal Detail:
Title:  Molecular human reproduction     Volume:  16     ISSN:  1460-2407     ISO Abbreviation:  Mol. Hum. Reprod.     Publication Date:  2010 Aug 
Date Detail:
Created Date:  2010-07-21     Completed Date:  2010-12-22     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9513710     Medline TA:  Mol Hum Reprod     Country:  England    
Other Details:
Languages:  eng     Pagination:  513-30     Citation Subset:  IM    
Affiliation:
Department of Obstetrics, Gynecology, and Reproductive Sciences, Yale University School of Medicine, New Haven, CT, USA.
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MeSH Terms
Descriptor/Qualifier:
Female
Genetic Predisposition to Disease
Humans
In Situ Hybridization, Fluorescence
Male
Microarray Analysis
Pregnancy
Reproductive Techniques, Assisted* / trends

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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