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Stanford Team Develops Fetal Genome Sequencing Method

NEW YORK (GenomeWeb News) – Researchers from Stephen Quake's laboratory at Stanford University have a published a method in Nature describing a way to noninvasively sequence a fetal genome and identify clinically relevant alleles without prior knowledge of paternal genetic data.

The method builds on a previous technique published by the Quake team last year in Nature Biotechnology that uses microfluidics to phase chromosomes.

That technique is used to create a list of alleles from each maternal haplotype — the one transmitted to the fetus and the one not transmitted to the fetus. Then, the researchers use a chromosome counting technique to determine which maternal haplotype is transmitted.

By applying this method to whole-genome sequencing of maternal plasma, the fetal genome can be determined.

Quake's team verified the approach on two different pregnant women, one of whom was carrying a normal fetus and another who was carrying a fetus with a heterozygous deletion on chromosome 22, which is associated with DiGeorge syndrome, a heterogeneous disorder that can cause congenital heart disease, defects in the palate, neuromuscular problems, and learning disabilities, among other problems.

They used their microfluidic phasing technique on three or four cells from each sample and also genotyped cord blood that was collected at delivery to serve as a reference for the fetal genotypes.

The maternal haplotyping method identified the deletion on chromosome 22 from the mother carrying the fetus affected with DiGeorge syndrome.

Next, in order to reconstruct the fetal genome, they sequenced the DNA samples on the Illumina platform to 53-fold haploid genome coverage for the maternal sample with the healthy fetus during the first trimester, 21-fold for the healthy sample during the second trimester, and 1.3-fold for the maternal sample with the affected fetus during the third trimester.

Paternally inherited haplotypes were reconstructed by detecting paternal-specific alleles. The researchers were able to detect between 66 percent and 70 percent of the paternally inherited alleles, and were also able to deduce about 70 percent of paternally inherited haplotypes using imputation.

Next, they wanted to see if they could determine the clinically relevant portions of the fetal genome by applying the counting method to the exome. They tested the method from the sample with the healthy fetus from all three trimesters, sequencing the fetal exome to over 100-fold coverage in each sample.

The greater sequencing depth increased their ability to assign fetal genotypes and detect paternal specific alleles. "In all three trimesters, fetal genotypes could be assigned robustly at loci where the mother is homozygous," the authors wrote.

Additionally, paternal-specific alleles were detected with a sensitivity of 96 percent to 99.8 percent.

The team also found that the percentage of fetal DNA increased throughout pregnancy. In the first trimester, fetal DNA made up just 6.6 percent of total DNA, but that percentage increased to 20.1 percent and 26.3 percent in the second and third trimesters, respectively.

The greater the fetal DNA percentage, the more sensitive the assay was at distinguishing between heterozygous and homozygous SNPs. For instance, maternal heterozygous SNPs could only be detected with 16 percent sensitivity and 90 percent specificity from the first trimester sample, but sensitivity was increased to 93 percent from the third trimester sample.

The authors conclude that their molecular counting and sequencing method "offers a gateway to comprehensive non-invasive prenatal diagnosis of genetic disease." However, they note that the ability to determine an entire fetal genome raises ethical issues, which the study did not address.

Nevertheless, the method could be useful for testing for conditions "that are not survivable or lead to medical complications." Additionally, it will enable "diagnosis of conditions that would benefit from treatment immediately after delivery," including metabolic and immunologic disorders.