Nancy B Y Tsui1, Peiyong Jiang1, Yuen Fei Wong1, Tak Y Leung2, K C Allen Chan1, Rossa W K Chiu1, Hao Sun1, Y M Dennis Lo3. 1. Centre for Research into Circulating Fetal Nucleic Acids, Li Ka Shing Institute of Health Sciences, Department of Chemical Pathology, and. 2. Department of Obstetrics and Gynaecology, The Chinese University of Hong Kong, Hong Kong SAR, China. 3. Centre for Research into Circulating Fetal Nucleic Acids, Li Ka Shing Institute of Health Sciences, Department of Chemical Pathology, and loym@cuhk.edu.hk.
Abstract
BACKGROUND: Analysis of circulating RNA in the plasma of pregnant women has the potential to serve as a powerful tool for noninvasive prenatal testing and research. However, detection of circulating RNA in the plasma in an unbiased and high-throughput manner has been technically challenging. Therefore, only a limited number of circulating RNA species in maternal plasma have been validated as pregnancy- and placenta-specific biomarkers. METHODS: We explored the use of massively parallel sequencing for plasma transcriptome profiling in first-, second-, and third-trimester pregnant women. Genotyping was performed for amniotic fluid, placental tissues, and maternal blood cells, with exome-enriched sequencing. RESULTS: In the early pregnancy group comprising 1 first- and 1 second-trimester pregnancy cases, the fetal contribution to the RNA pool in maternal plasma was 3.70%. The relative proportion of fetal contribution was increased to 11.28% in the late pregnancy group comprising 2 third-trimester pregnancy cases. The placental biallelic expression pattern of PAPPA (pregnancy-associated plasma protein A, pappalysin 1), a known pregnancy-specific gene, and the monoallelic expression pattern of H19 [H19, imprinted maternally expressed transcript (non-protein coding)], an imprinted maternally expressed gene, were also detected in the maternal plasma. Furthermore, by direct examination of the maternal plasma transcriptomic profiles before and after delivery, we identified a panel of pregnancy-associated genes. CONCLUSIONS: Plasma RNA sequencing provides a holistic view of the maternal plasma transcriptomic repertoire. This technology is potentially valuable for using circulating plasma nucleic acids for prenatal testing and research.
BACKGROUND: Analysis of circulating RNA in the plasma of pregnant women has the potential to serve as a powerful tool for noninvasive prenatal testing and research. However, detection of circulating RNA in the plasma in an unbiased and high-throughput manner has been technically challenging. Therefore, only a limited number of circulating RNA species in maternal plasma have been validated as pregnancy- and placenta-specific biomarkers. METHODS: We explored the use of massively parallel sequencing for plasma transcriptome profiling in first-, second-, and third-trimester pregnant women. Genotyping was performed for amniotic fluid, placental tissues, and maternal blood cells, with exome-enriched sequencing. RESULTS: In the early pregnancy group comprising 1 first- and 1 second-trimester pregnancy cases, the fetal contribution to the RNA pool in maternal plasma was 3.70%. The relative proportion of fetal contribution was increased to 11.28% in the late pregnancy group comprising 2 third-trimester pregnancy cases. The placental biallelic expression pattern of PAPPA (pregnancy-associated plasma protein A, pappalysin 1), a known pregnancy-specific gene, and the monoallelic expression pattern of H19 [H19, imprinted maternally expressed transcript (non-protein coding)], an imprinted maternally expressed gene, were also detected in the maternal plasma. Furthermore, by direct examination of the maternal plasma transcriptomic profiles before and after delivery, we identified a panel of pregnancy-associated genes. CONCLUSIONS: Plasma RNA sequencing provides a holistic view of the maternal plasma transcriptomic repertoire. This technology is potentially valuable for using circulating plasma nucleic acids for prenatal testing and research.
Authors: Kun Sun; Peiyong Jiang; K C Allen Chan; John Wong; Yvonne K Y Cheng; Raymond H S Liang; Wai-kong Chan; Edmond S K Ma; Stephen L Chan; Suk Hang Cheng; Rebecca W Y Chan; Yu K Tong; Simon S M Ng; Raymond S M Wong; David S C Hui; Tse Ngong Leung; Tak Y Leung; Paul B S Lai; Rossa W K Chiu; Yuk Ming Dennis Lo Journal: Proc Natl Acad Sci U S A Date: 2015-09-21 Impact factor: 11.205
Authors: Jason C H Tsang; Joaquim S L Vong; Lu Ji; Liona C Y Poon; Peiyong Jiang; Kathy O Lui; Yun-Bi Ni; Ka Fai To; Yvonne K Y Cheng; Rossa W K Chiu; Yuk Ming Dennis Lo Journal: Proc Natl Acad Sci U S A Date: 2017-08-22 Impact factor: 11.205
Authors: Caitlin M Stewart; Prachi D Kothari; Florent Mouliere; Richard Mair; Saira Somnay; Ryma Benayed; Ahmet Zehir; Britta Weigelt; Sarah-Jane Dawson; Maria E Arcila; Michael F Berger; Dana Wy Tsui Journal: J Pathol Date: 2018-03-12 Impact factor: 7.996
Authors: Louise C Laurent; Asim B Abdel-Mageed; P David Adelson; Jorge Arango; Leonora Balaj; Xandra Breakefield; Elizabeth Carlson; Bob S Carter; Blanca Majem; Clark C Chen; Emanuele Cocucci; Kirsty Danielson; Amanda Courtright; Saumya Das; Zakaria Y Abd Elmageed; Daniel Enderle; Alan Ezrin; Marc Ferrer; Jane Freedman; David Galas; Roopali Gandhi; Matthew J Huentelman; Kendall Van Keuren-Jensen; Yashar Kalani; Yong Kim; Anna M Krichevsky; Charles Lai; Madhu Lal-Nag; Clara D Laurent; Trevor Leonardo; Feng Li; Ivana Malenica; Debasis Mondal; Parham Nejad; Tushar Patel; Robert L Raffai; Renee Rubio; Johan Skog; Robert Spetzler; Jie Sun; Kahraman Tanriverdi; Kasey Vickers; Liang Wang; Yaoyu Wang; Zhiyun Wei; Howard L Weiner; David Wong; Irene K Yan; Ashish Yeri; Stephen Gould Journal: J Extracell Vesicles Date: 2015-08-28