title: Haplotype-assisted accurate non-invasive fetal whole genome recovery through maternal plasma sequencing.
abstract: BACKGROUND
  The applications of massively parallel sequencing technology to fetal cell-free DNA (cff-DNA) have brought new insight to non-invasive prenatal diagnosis. However, most previous research based on maternal plasma sequencing has been restricted to fetal aneuploidies. To detect specific parentally inherited mutations, invasive approaches to obtain fetal DNA are the current standard in the clinic because of the experimental complexity and resource consumption of previously reported non-invasive approaches.
  
  
  METHODS
  Here, we present a simple and effective non-invasive method for accurate fetal genome recovery-assisted with parental haplotypes. The parental haplotype were firstly inferred using a combination strategy of trio and unrelated individuals. Assisted with the parental haplotype, we then employed a hidden Markov model to non-invasively recover the fetal genome through maternal plasma sequencing.
  
  
  RESULTS
  Using a sequence depth of approximately 44X against a an approximate 5.69% cff-DNA concentration, we non-invasively inferred fetal genotype and haplotype under different situations of parental heterozygosity. Our data show that 98.57%, 95.37%, and 98.45% of paternal autosome alleles, maternal autosome alleles, and maternal chromosome X in the fetal haplotypes, respectively, were recovered accurately. Additionally, we obtained efficient coverage or strong linkage of 96.65% of reported Mendelian-disorder genes and 98.90% of complex disease-associated markers.
  
  
  CONCLUSIONS
  Our method provides a useful strategy for non-invasive whole fetal genome recovery.
authors: BGI-Shenzhen, Shenzhen 518083, China ; State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China.
authors: Shengpei
authors: S
authors: Chen
authors: BGI-Shenzhen, Shenzhen 518083, China.
authors: Huijuan
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authors: Ge
authors: BGI-Shenzhen, Shenzhen 518083, China.
authors: Xuebin
authors: X
authors: Wang
authors: BGI-Shenzhen, Shenzhen 518083, China ; School of Bioscience and Bioengineering, South China University of Technology, Guangzhou 510000, China.
authors: Xiaoyu
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authors: BGI-Shenzhen, Shenzhen 518083, China.
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authors: BGI-Shenzhen, Shenzhen 518083, China.
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authors: BGI-Shenzhen, Shenzhen 518083, China.
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authors: BGI-Shenzhen, Shenzhen 518083, China.
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authors: BGI-Shenzhen, Shenzhen 518083, China.
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authors: BGI-Shenzhen, Shenzhen 518083, China.
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authors: BGI-Shenzhen, Shenzhen 518083, China.
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authors: BGI-Shenzhen, Shenzhen 518083, China.
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authors: BGI-Shenzhen, Shenzhen 518083, China.
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authors: BGI-Shenzhen, Shenzhen 518083, China.
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authors: BGI-Shenzhen, Shenzhen 518083, China.
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authors: BGI-Shenzhen, Shenzhen 518083, China.
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authors: BGI-Shenzhen, Shenzhen 518083, China.
authors: Xiuqing
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authors: Zhang