Gene expression profiles based on maternal plasma cfDNA nucleosome footprints indicate fetal development and maternal immunity changes during pregnancy progress.

Background: Pregnancy significantly alters the maternal immune system, affecting fetal development. The collection of tissues from the human placenta and fetus is not ethically or practically feasible at various gestational stages, thus limiting the study of gene expression in the fetus and placenta. Recent studies have shown that plasma cell-free DNA (cfDNA) nucleosome patterns can predict gene expression in the source tissue, offering insights into an individual's health status.

Integrative analyses of maternal plasma cell-free DNA nucleosome footprint differences reveal chromosomal aneuploidy fetuses gene expression profile.

Background: Chromosomal aneuploidy is the most common birth defect. However, the developmental mechanism and gene expression profile of fetuses with chromosomal aneuploidy are relatively unknown, and the maternal immune changes induced by fetal aneuploidy remain unclear. The inability to obtain the placenta multiple times in real-time is a bottleneck in research on aneuploid pregnancies.

Simulated confined placental mosaicism proportion (SCPMP) based on cell-free fetal DNA fraction enrichment can reduce false-positive results in non-invasive prenatal testing.

Objective: To decrease the false-positive rate of NIPT using cell-free fetal DNA (cffDNA) fraction enrichment and the simulated confined placental mosaicism proportion (SCPMP) threshold application via cffDNA quantification.

Method: Using a cffDNA enrichment method, 303 plasma samples with positive NIPT results (Z-score > 3.0; 200 true-positive and 103 false-positive cases) were re-sequenced.

A Deep-Learning Pipeline for TSS Coverage Imputation From Shallow Cell-Free DNA Sequencing.

Cell-free DNA (cfDNA) serves as a footprint of the nucleosome occupancy status of transcription start sites (TSSs), and has been subject to wide development for use in noninvasive health monitoring and disease detection. However, the requirement for high sequencing depth limits its clinical use. Here, we introduce a deep-learning pipeline designed for TSS coverage profiles generated from shallow cfDNA sequencing called the Autoencoder of cfDNA TSS (AECT) coverage profile.

Noninvasive discrimination of benign and malignant breast lesions using genome-wide nucleosome profiles of plasma cell-free DNA.

Background: Breast malignancy is the most frequently diagnosed malignancy in women worldwide, and the diagnosis relies on invasive examinations. However, most clinical breast changes in women are benign, and invasive diagnostic approaches cause unnecessary suffering for the patients. Thus, a novel noninvasive approach for discriminating malignant breast lesions from benign lesions is needed.

Noninvasive inferring expressed genes and in vivo monitoring of the physiology and pathology of pregnancy using cell-free DNA.

Background: Noninvasive monitoring of fetal development and the early detection of pregnancy-associated complications is challenging, largely because of the lack of information about the molecular spectrum during pregnancy. Recently, cell-free DNA in plasma was found to reflect the global nucleosome footprint and status of gene expression and showed potential for noninvasive health monitoring during pregnancy.

Objective: We aimed to test the relationships between plasma cell-free DNA profiles and pregnancy biology and evaluate the use of a cell-free DNA profile as a noninvasive method for physiological and pathologic status monitoring during pregnancy.

Simultaneous detection of target CNVs and SNVs of thalassemia by multiplex PCR and next‑generation sequencing.

Thalassemia is caused by complex mechanisms, including copy number variants (CNVs) and single nucleotide variants (SNVs). The CNV types of α‑thalassemia are typically detected by gap‑polymerase chain reaction (PCR). The SNV types are detected by Sanger sequencing.