RNA-Seq of amniotic fluid cell-free RNA: a discovery phase study of the pathophysiology of congenital cytomegalovirus infection

BACKGROUND: Congenital cytomegalovirus infection is the most common perinatal infection and a significant cause of sensorineural hearing loss, cerebral palsy, and neurodevelopmental disability. There is a paucity of human gene expression studies examining the pathophysiology of cytomegalovirus infec...

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Veröffentlicht in:AMERICAN JOURNAL OF OBSTETRICS AND GYNECOLOGY 2022-10, Vol.227 (4)
Hauptverfasser: Hui, Lisa, De Catte, Luc, Beard, Sally, Maksimovic, Jovana, Vora, Neeta L, Oshlack, Alicia, Walker, Susan P, Hannan, Natalie J
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Sprache:eng
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Zusammenfassung:BACKGROUND: Congenital cytomegalovirus infection is the most common perinatal infection and a significant cause of sensorineural hearing loss, cerebral palsy, and neurodevelopmental disability. There is a paucity of human gene expression studies examining the pathophysiology of cytomegalovirus infection. OBJECTIVE: This study aimed to perform a whole transcriptomic assessment of amniotic fluid from pregnancies with live fetuses to identify differentially expressed genes and enriched Gene Ontology categories associated with congenital cytomegalovirus infection. STUDY DESIGN: Amniotic fluid supernatant was prospectively collected from pregnant women undergoing amniocentesis for suspected congenital cytomegalovirus infection because of first-trimester maternal primary infection or ultrasound features suggestive of fetal infection. Women who had received therapy to prevent fetal infection were excluded. Congenital cytomegalovirus infection was diagnosed via viral polymerase chain reaction of amniotic fluid; cytomegalovirus-infected fetuses were paired with noninfected controls, matched for gestational age and fetal sex. Paired-end RNA sequencing was performed on amniotic fluid cell-free RNA with the Novaseq 6000 at a depth of 30 million reads per sample. Following quality control and filtering, reads were mapped to the human genome and counts summarized across genes. Differentially expressed genes were identified using 2 approaches: voomWithQualityWeights in conjunction with limma and RUVSeq with edgeR. Genes with a false discovery rate
ISSN:0002-9378