title: Effective noninvasive zygosity determination by maternal plasma target region sequencing.
abstract: BACKGROUND
  Currently very few noninvasive molecular genetic approaches are available to determine zygosity for twin pregnancies in clinical laboratories. This study aimed to develop a novel method to determine zygosity by using maternal plasma target region sequencing.
  
  
  METHODS
  We constructed a statistic model to calculate the possibility of each zygosity type using likelihood ratios ( Li ) and empirical dynamic thresholds targeting at 4,524 single nucleotide polymorphisms (SNPs) loci on 22 autosomes. Then two dizygotic (DZ) twin pregnancies,two monozygotic (MZ) twin pregnancies and two singletons were recruited to evaluate the performance of our novel method. Finally we estimated the sensitivity and specificity of the model in silico under different cell-free fetal DNA (cff-DNA) concentration and sequence depth.
  
  
  CONCLUSIONS
  We obtained 8.90 Gbp sequencing data on average for six clinical samples. Two samples were classified as DZ with L values of 1.891 and 1.554, higher than the dynamic DZ cut-off values of 1.162 and 1.172, respectively. Another two samples were judged as MZ with 0.763 and 0.784 of L values, lower than the MZ cut-off values of 0.903 and 0.918. And the rest two singleton samples were regarded as MZ twins, with L values of 0.639 and 0.757, lower than the MZ cut-off values of 0.921 and 0.799. In silico, the estimated sensitivity of our noninvasive zygosity determination was 99.90% under 10% total cff-DNA concentration with 2 Gbp sequence data. As the cff-DNA concentration increased to 15%, the specificity was as high as 97% with 3.50 Gbp sequence data, much higher than 80% with 10% cff-DNA concentration.
  
  
  CONCLUSIONS
  This study presents the feasibility to noninvasively determine zygosity of twin pregnancy using target region sequencing, and illustrates the sensitivity and specificity under various detecting condition. Our method can act as an alternative approach for zygosity determination of twin pregnancies in clinical practice.
authors.affiliation: Science and Technology, BGI-Shenzhen, Shenzhen, China.
authors.forename: Jing
authors.initials: J
authors.lastname: Zheng
authors.forename: Chenming
authors.initials: C
authors.lastname: Xu
authors.forename: Jing
authors.initials: J
authors.lastname: Guo
authors.forename: Yuan
authors.initials: Y
authors.lastname: Wei
authors.forename: Huijuan
authors.initials: H
authors.lastname: Ge
authors.forename: Xuchao
authors.initials: X
authors.lastname: Li
authors.forename: Chunlei
authors.initials: C
authors.lastname: Zhang
authors.forename: Haojun
authors.initials: H
authors.lastname: Jiang
authors.forename: Ling
authors.initials: L
authors.lastname: Pan
authors.forename: Weiping
authors.initials: W
authors.lastname: Tang
authors.forename: Weiwei
authors.initials: W
authors.lastname: Xie
authors.forename: Hongyun
authors.initials: H
authors.lastname: Zhang
authors.forename: Yangyu
authors.initials: Y
authors.lastname: Zhao
authors.forename: Fuman
authors.initials: F
authors.lastname: Jiang
authors.forename: Shengpei
authors.initials: S
authors.lastname: Chen
authors.forename: Wei
authors.initials: W
authors.lastname: Wang
authors.forename: Xun
authors.initials: X
authors.lastname: Xu
authors.forename: Fang
authors.initials: F
authors.lastname: Chen
authors.forename: Hefeng
authors.initials: H
authors.lastname: Huang
authors.forename: Hui
authors.initials: H
authors.lastname: Jiang
mesh_terms: D003198:Computer Simulation; D004247:DNA / Q000097:blood / Q000235:genetics*; D005260:Female; D006801:Humans; D008297:Male; D062145:Maternal Serum Screening Tests; D008962:Models, Theoretical; D011247:Pregnancy; D011272:Pregnancy, Multiple / Q000235:genetics*; D059285:Pregnancy, Twin; D011296:Prenatal Diagnosis / Q000379:methods*; D060888:Real-Time Polymerase Chain Reaction; D012680:Sensitivity and Specificity; D014429:Twins, Dizygotic / Q000235:genetics*; D014430:Twins, Monozygotic / Q000235:genetics*
chemical_list: D004247:DNA