Xuchao Li

Noninvasive prenatal diagnosis of common fetal chromosomal aneuploidies by maternal plasma DNA sequencing

Objective: To develop a new bioinformatic method in the noninvasive prenatal identification of common fetal aneuploidies using massively parallel sequencing on maternal plasma. Methods: Massively parallel sequencing was performed on plasma DNA samples from 108 pregnant women (median gestation: 12+5 week) immediately before chorionic villus sampling (CVS) or amniocentesis. Data were analysed using a novel z-score method with internal reference chromosome. The diagnostic accuracies of the fetal karyotyping status were compared against two previously reported z-score methods – one without adjustment and the other with GC correction. Results: A total of 32 cases with fetal aneuploidy were confirmed by conventional karyotyping, including 11 cases of Trisomy 21, 10 cases of Trisomy 18, 2 cases of Trisomy 13, 8 cases of Turner syndrome (45, XO) and one case of Klinefelter syndrome (47, XXY). Using the z-score method without reference adjustment, the detection rate for Trisomy 21, Trisomy 18, Trisomy 13, Turner syndrome, and Klinefelter’s syndrome is 100%, 40%, 0%, 88% and 0% respectively. Using the z-score method with GC correction, the detection rate increased to 100% for Trisomy 21, 90% for Trisomy 18, 100% for Trisomy 13. By using the z-score method with internal reference, the detection rate increased to 100% for all aneuploidies. The false positive rate was 0% for all three methods. Conclusion: This massively parallel sequencing-based approach, combined with the improved z-score test methodology, enables the prenatal diagnosis of most common aneuploidies with a high degree of accuracy, even in the first trimester of pregnancy.

Massively Parallel Sequencing for Chromosomal Abnormality Testing in Trophectoderm Cells of Human Blastocysts

ABSTRACT Preimplantation genetic diagnosis and screening are widely accepted for chromosomal abnormality identification to avoid transferring embryos with genetic defects. Massively parallel sequencing (MPS) is a rapidly developing approach for genome analysis with increasing application in clinical practice. The purpose of this study was to use MPS for identification of aneuploidies and unbalanced chromosomal rearrangements after blastocyst biopsy. Trophectoderm (TE) samples of 38 blastocysts from 16 in vitro fertilization cycles were subjected to analysis. Low-coverage whole genome sequencing was performed using the Illumina HiSeq2000 platform with a novel algorithm purposely created for chromosomal analysis. The efficiency of this MPS approach was estimated by comparing results obtained by an Affymetrix single-nucleotide polymorphism (SNP) array. Whole genome amplification (WGA) products of TE cells were detected by MPS, with an average of 0.07× depth and 5.5% coverage of the human genome. Twenty-six embryos (68.4%) were detected as euploid, while six embryos (15.8%) contained uniform aneuploidies. Four of these (10.5%) were with solely unbalanced chromosomal rearrangements, whereas the remaining two embryos (5.3%) showed both aneuploidies and unbalanced rearrangements. Almost all these results were confirmed by the SNP array, with the exception of one sample, where different sizes of unbalanced rearrangements were detected, possibly due to chromosomal GC bias in array analysis. Our study demonstrated MPS could be applied to accurately detect embryonic chromosomal abnormality with a flexible and cost-effective strategy and higher potential accuracy.

A method for noninvasive detection of fetal large deletions/ duplications by low coverage massively parallel sequencing

To report the feasibility of fetal chromosomal deletion/duplication detection using a novel bioinformatic method of low coverage whole genome sequencing of maternal plasma.

A single cell level based method for copy number variation analysis by low coverage massively parallel sequencing.

Copy number variations (CNVs), a common genomic mutation associated with various diseases, are important in research and clinical applications. Whole genome amplification (WGA) and massively parallel sequencing have been applied to single cell CNVs analysis, which provides new insight for the fields of biology and medicine. However, the WGA-induced bias significantly limits sensitivity and specificity for CNVs detection. Addressing these limitations, we developed a practical bioinformatic methodology for CNVs detection at the single cell level using low coverage massively parallel sequencing. This method consists of GC correction for WGA-induced bias removal, binary segmentation algorithm for locating CNVs breakpoints, and dynamic threshold determination for final signals filtering. Afterwards, we evaluated our method with seven test samples using low coverage sequencing (4∼9.5%). Four single-cell samples from peripheral blood, whose karyotypes were confirmed by whole genome sequencing analysis, were acquired. Three other test samples derived from blastocysts whose karyotypes were confirmed by SNP-array analysis were also recruited. The detection results for CNVs of larger than 1 Mb were highly consistent with confirmed results reaching 99.63% sensitivity and 97.71% specificity at base-pair level. Our study demonstrates the potential to overcome WGA-bias and to detect CNVs (>1 Mb) at the single cell level through low coverage massively parallel sequencing. It highlights the potential for CNVs research on single cells or limited DNA samples and may prove as a promising tool for research and clinical applications, such as pre-implantation genetic diagnosis/screening, fetal nucleated red blood cells research and cancer heterogeneity analysis.

Noninvasive prenatal testing of trisomies 21 and 18 by massively parallel sequencing of maternal plasma DNA in twin pregnancies.

The objective of this study is to assess the performance of noninvasive prenatal testing for trisomies 21 and 18 on the basis of massively parallel sequencing of cell‐free DNA from maternal plasma in twin pregnancies.

Haplotype-assisted accurate non-invasive fetal whole genome recovery through maternal plasma sequencing

BackgroundThe 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.MethodsHere, 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.ResultsUsing 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.ConclusionsOur method provides a useful strategy for non-invasive whole fetal genome recovery.

Performance Comparison between Rapid Sequencing Platforms for Ultra-Low Coverage Sequencing Strategy

Ultra-low coverage sequencing (ULCS) is one of the most promising strategies for sequencing based clinical application. These clinical applications, especially prenatal diagnosis, have a strict requirement of turn-around-time; therefore, the application of ULCS is restricted by current high throughput sequencing platforms. Recently, the emergence of rapid sequencing platforms, such as MiSeq and Ion Proton, brings ULCS strategy into a new era. The comparison of their performance could shed lights on their potential application in large-scale clinic trials. In this study, we performed ULCS (<0.1X coverage) on both MiSeq and Ion Proton platforms for 18 spontaneous abortion fetuses carrying aneuploidy and compared their performance on different levels. Overall basic data and GC bias showed no significant difference between these two platforms. We also found the sex and aneuploidy detection indicated 100% sensitivity and 100% specificity on both platforms. Our study generated essential data from these two rapid sequencing platforms, which provides useful reference for later research and potentially accelerates the clinical applications of ULCS.

Noninvasive prenatal testing for autosomal recessive conditions by maternal plasma sequencing in a case of congenital deafness

Purpose:The goals of our study were to develop a noninvasive prenatal test for autosomal recessive monogenic conditions and to prove its overall feasibility and potential for clinical integration.Methods:We recruited a pregnant woman and her spouse, who had a proband child suffering from congenital deafness, and obtained the target-region sequencing data from a semicustom array that used genomic and maternal plasma DNA from three generations of this family. A haplotype-assisted strategy was developed to detect whether the fetus inherited the pathogenic mutations in the causative gene, GJB2. The parental haplotype was constructed using a trio strategy through two different processes, namely, the grandparent-assisted haplotype phasing process and the proband-assisted haplotype phasing process. The fetal haplotype was deduced afterward based on both the maternal plasma sequencing data and the parental haplotype.Results:The accuracy levels of paternal and maternal haplotypes obtained by grandparent-assisted haplotype phasing were 99.01 and 97.36%, respectively, and the proband-assisted haplotype phasing process yielded slightly lower accuracies of 98.73 and 96.79%, respectively. Fetal inheritance of the pathogenic gene was deduced correctly in both processes.Conclusion:Our study indicates that the strategy of haplotype-based noninvasive prenatal testing for monogenic conditions has potential applications in clinical practice.Genet Med 16 12, 972–976.

Prenatal detection of aneuploidy and imbalanced chromosomal arrangements by massively parallel sequencing.

Fetal chromosomal abnormalities are the most common reasons for invasive prenatal testing. Currently, G-band karyotyping and several molecular genetic methods have been established for diagnosis of chromosomal abnormalities. Although these testing methods are highly reliable, the major limitation remains restricted resolutions or can only achieve limited coverage on the human genome at one time. The massively parallel sequencing (MPS) technologies which can reach single base pair resolution allows detection of genome-wide intragenic deletions and duplication challenging karyotyping and microarrays as the tool for prenatal diagnosis. Here we reported a novel and robust MPS-based method to detect aneuploidy and imbalanced chromosomal arrangements in amniotic fluid (AF) samples. We sequenced 62 AF samples on Illumina GAIIx platform and with averagely 0.01× whole genome sequencing data we detected 13 samples with numerical chromosomal abnormalities by z-test. With up to 2× whole genome sequencing data we were able to detect microdeletion/microduplication (ranged from 1.4 Mb to 37.3 Mb of 5 samples from chorionic villus sampling (CVS) using SeqSeq algorithm. Our work demonstrated MPS is a robust and accurate approach to detect aneuploidy and imbalanced chromosomal arrangements in prenatal samples.

Haplotype-based approach for noninvasive prenatal tests of Duchenne muscular dystrophy using cell-free fetal DNA in maternal plasma

Purpose:This study demonstrates noninvasive prenatal testing (NIPT) for Duchenne muscular dystrophy (DMD) using a newly developed haplotype-based approach.Methods:Eight families at risk for DMD were recruited for this study. Parental haplotypes were constructed using target-region sequencing data from the parents and the probands. Fetal haplotypes were constructed using a hidden Markov model through maternal plasma DNA sequencing. The presence of haplotypes linked to the maternal mutant alleles in males indicated affected fetuses. This method was further validated by comparing the inferred single-nucleotide polymorphism (SNP) genotypes to the direct sequencing results of fetal genomic DNA. Prenatal diagnosis was confirmed with amniocentesis, and those results were interpreted in a blinded fashion.Results:The results showed an average accuracy of 99.98% for the total inferred maternal SNPs. With a mean depth of 30× achieved in the 10-Mb target region of each sample, the noninvasive results were consistent with those of the invasive procedure.Conclusion:This is the first report of NIPT for DMD and the first application of a haplotype-based approach in NIPT for X-linked diseases. With further improvements in accuracy, this haplotype-based strategy could be feasible for NIPT for DMD and even other X-linked single-gene disorders.Genet Med 17 11, 889–896.