Genetic defects including single-gene Mendelian disorders and aneuploidies are among the leading causes of miscarriages and congenital birth disorders. Non-invasive prenatal testing (NIPT) is currently used to detect aneuploidies, but given the falling cost of next-generation sequencing (NGS), growing sophistication in molecular/biochemical methods, and ever increasing computational power, complete determination of the fetal genome (i.e., genotypes and haplotypes at the level of both SNVs and large aneuploidies) seems within reach. In this regard, cell-free DNA (cfDNA) in the maternal plasma has been targeted for non-invasive detection and diagnosis of fetal genetic defects, as cfDNA contains a mixture of genetic material derived from both the mother and the fetus. But because the fraction of cfDNA derived from the fetus is small (~10-15%), and consists of DNA that is highly fragmented, determination of fetal genotypes to the level of single-nucleotide variants (SNV) remains challenging, and presently involves excessively costly deep sequencing of cfDNA (up to 70X). In addition to knowledge of genotypes for diagnosing single gene Mendelian disorders, non-invasive deconvolution of fetal haplotypes is likely necessary for assessing the risk for complex multi-genic disorders. Efforts have been made to determine fetal genome with parental haplotypes, but the current methods to haplotype parents generally suffer from excessive costs, methodological and instrumentation complexity, and/or reliance on genetic material that is difficult or impossible to obtain; and they provide only partial haplotype information (short haplotype blocks and incomplete phasing of variants), hindering their utility in cost-effective complete fetal genome determination. Our team previously developed an innovative approach, HaploSeq, that can solve this problem. The HaploSeq method preserves haplotype information by preferentially recovering physically linked DNA variants on a homologous chromosome via proximity-ligation and NGS as per the established HiC protocol. HaploSeq achieves truly chromosome-spanning haplotypes, resolving the vast majority of alleles (>93%) at high accuracy (~99%) in human genomes, thus constituting the first scalable, cost-effective method for assembling complete human haplotypes. Here, we propose an innovative approach, HaploSeq-Ft, for non-invasive determination of complete fetal genotype and haplotype, using HaploSeq to generate chromosome-spanning parental haplotypes from blood samples. In addition, HaploSeq's whole-genome phasing capabilities also facilitate utilization of very low-depth cfDNA sequencing from maternal plasma for complete fetal genotype and haplotype determination. Taken together, by leveraging our proprietary haplotyping technology to inform novel cfDNA sequencing analysis algorithms, one HaploSeq- Ft blood test will enable parents to know the complete genotype and haplotype of their fetus in a cost-effective manner that does not endanger the pregnancy.

Public Health Relevance

With the concurrent rise of next-generation sequencing (NGS) technologies and non-invasive prenatal testing (NIPT), the development of a cost-effective NGS-based assay that enables non-invasive determination of a complete fetal genome will be essential for the future of timely diagnosis of fetal genetic disorders. We propose a novel method, HaploSeq-Ft that leverages our proprietary haplotyping technology and new computational approaches to provide precision medicine for prenatal clinical care. HaploSeq-Ft will be developed as a simple, non-invasive, cost-effective blood test that enables parents to know the complete genotype and haplotype of their fetus, without endangering the pregnancy.

Agency
National Institute of Health (NIH)
Institute
Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
Type
Small Business Innovation Research Grants (SBIR) - Phase I (R43)
Project #
1R43HD087113-01A1
Application #
9139622
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Parisi, Melissa
Project Start
2016-05-15
Project End
2017-04-30
Budget Start
2016-05-15
Budget End
2017-04-30
Support Year
1
Fiscal Year
2016
Total Cost
Indirect Cost
Name
Arima Genomics, LLC
Department
Type
DUNS #
079163557
City
San Diego
State
CA
Country
United States
Zip Code
92122