↓ Skip to main content

PLOS

Prenatal Detection of Aneuploidy and Imbalanced Chromosomal Arrangements by Massively Parallel Sequencing

Overview of attention for article published in PLOS ONE, February 2012
Altmetric Badge

Mentioned by

twitter
2 X users
patent
22 patents

Citations

dimensions_citation
29 Dimensions

Readers on

mendeley
82 Mendeley
Title
Prenatal Detection of Aneuploidy and Imbalanced Chromosomal Arrangements by Massively Parallel Sequencing
Published in
PLOS ONE, February 2012
DOI 10.1371/journal.pone.0027835
Pubmed ID
Authors

Shan Dan, Fang Chen, Kwong Wai Choy, Fuman Jiang, Jingrong Lin, Zhaoling Xuan, Wei Wang, Shengpei Chen, Xuchao Li, Hui Jiang, Tak Yeung Leung, Tze Kin Lau, Yue Su, Weiyuan Zhang, Xiuqing Zhang

Abstract

Fetal chromosomal abnormalities are the most common reasons for invasive prenatal testing. Currently, G-band karyotyping and several molecular genetic methods have been established for diagnosis of chromosomal abnormalities. Although these testing methods are highly reliable, the major limitation remains restricted resolutions or can only achieve limited coverage on the human genome at one time. The massively parallel sequencing (MPS) technologies which can reach single base pair resolution allows detection of genome-wide intragenic deletions and duplication challenging karyotyping and microarrays as the tool for prenatal diagnosis. Here we reported a novel and robust MPS-based method to detect aneuploidy and imbalanced chromosomal arrangements in amniotic fluid (AF) samples. We sequenced 62 AF samples on Illumina GAIIx platform and with averagely 0.01× whole genome sequencing data we detected 13 samples with numerical chromosomal abnormalities by z-test. With up to 2× whole genome sequencing data we were able to detect microdeletion/microduplication (ranged from 1.4 Mb to 37.3 Mb of 5 samples from chorionic villus sampling (CVS) using SeqSeq algorithm. Our work demonstrated MPS is a robust and accurate approach to detect aneuploidy and imbalanced chromosomal arrangements in prenatal samples.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 82 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
Hong Kong 1 1%
Sweden 1 1%
Unknown 78 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 22 27%
Student > Master 10 12%
Student > Bachelor 8 10%
Other 7 9%
Student > Ph. D. Student 7 9%
Other 17 21%
Unknown 11 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 41 50%
Medicine and Dentistry 14 17%
Biochemistry, Genetics and Molecular Biology 9 11%
Computer Science 2 2%
Nursing and Health Professions 1 1%
Other 6 7%
Unknown 9 11%