Amniocentesis is a common medical procedure used in the investigation of chromosomal abnormalities, birth defects and other genetic conditions of the fetus. Despite the low false-positive rate of this diagnostic test, it can only detect a few single- to multi-base defects in the fetal genome. Previous studies have provided strong evidence that coding variants within a large set of genes are associated with autism, severe intellectual disability, and other congenital disabilities. Hence, it can be inferred that the examination of a few genes or detection of large chromosomal changes is insufficient for the detection of many severe disease-causing genetic defects. Although whole exome and genome sequencing have become more common in clinincal settings, few studies have analyzed the amniotic fluid beyond detection of large structural variations or a few targeted regions of the fetal genome.
Recently Brock Peters, Qing Mao, and colleagues at Complete Genomics Inc: Robert Chin, Rebecca Yu Zhang, Natali Gulbahce, and Radoje Drmanac in collaboration with Weiwei Xie, Wenwei Zhang, Huixin Xu, Quan Shi, Zhenyu Li and Fang Chen at BGI Shenzhen and also Yuqing Deng from Peking University Shenzhen Hospital and Erin Peters from the University of Southern California developed an accurate whole-genome sequencing (WGS) strategy for analysis of the fetal genome using either the cellular or cell-free DNA (cfDNA) components of an amniotic sample. This work was recently published in the peer-reviewed journal, Clinical Chemistry.
The authors found that high-quality fetal genomes can be generated from cfDNA or cell pellet DNA samples to enable advanced genome analysis. Importantly, comparing variant calls from WGS of cfDNA and the cell pellet of the same samples showed extremely high concordance. In addition, there was no systematic bias in the de novo mutation (DNM) calls made between the two different sources of DNA. Although WGS detected two fetuses with an extra copy of chromosome 21, the three fetal genomes with a known benign polymorphism in heterochromatin and satellite DNA were poorly detected using WGS. This is not surprising as highly repetitive sequences are known to be difficult to analyze with WGS. However, the authors observed that most of the copy number variants/structural variants (CNV/SV) calls made between the two different sources of DNA and the parental libraries were true positives.
Additionally, the fetal genomes of 6 different families were identified to have had autosomal recessive deafness alleles in genes GJB2 and TMPRSS3. They also identified two detrimental DNM variants in chromodomain helicase DNA binding protein 8 and LDL receptor-related protein 1. DNMs and certain coding variants in these genes have been associated with autism spectrum disorder and keratosis pilaris atrophicans, respecitively, although it is unclear if these particular DNMs would cause disease.
The authors also reported that every genome they analyzed in this study had at least one variant that resulted in the complete loss of a single copy of a gene found in a database of drug-gene interactions. This kind of information could be important for determining if a patient should use a particular drug and at what does they should use it. Importantly, four rare damaging variants were found in the genes RYR1 and CACNA1S. Variants in these genes have been associated with malignant hyperthermia, a potentially fatal response to certain types of anesthesia.
This study demonstrated that high-quality fetal genomes can be obtained from cfDNA or cell pellet DNA samples for advanced genome analysis and that the information obtained in these genomes is valuable for the entire life of the newborn. This novel method can be used to augment current karyotyping data and identify the various causes of birth defects that are currently undetected. Furthermore, their findings will advance further studies on the use of amniotic material for the accurate analysis of the fetal genome.
Mao, Q., Chin, R., Xie, W., Deng, Y., Zhang, W., Xu, H., Zhang, R.Y., Shi, Q., Peters, E.E., Gulbahce, N., Li, Z., Chen, F., Drmanac, R., and Peters, B.A. Advanced Whole-Genome Sequencing and Analysis of Fetal Genomes from Amniotic Fluid, Clinical Chemistry 64:4 (2018) 715-725