Recent advances in whole genome sequencing have brought the vision of personal genomics and genomic medicine closer to reality. However, current methods lack clinical accuracy and the ability to describe the context (haplotypes) in which genome variants co-occur in a cost-effective manner. Here we describe a low-cost DNA sequencing and haplotyping process, Long Fragment Read (LFR) technology, similar to sequencing long single DNA molecules without cloning or separation of metaphase chromosomes. In this study, ten LFR libraries were made using only ~100 pg of human DNA per sample. Up to 97% of the heterozygous single nucleotide variants (SNVs) were assembled into long haplotype contigs. Removal of false positive SNVs not phased by multiple LFR haplotypes resulted in a final genome error rate of 1 in 10 Mb. Cost-effective and accurate genome sequencing and haplotyping from 10-20 human cells, as demonstrated here, will enable comprehensive genetic studies and diverse clinical applications.

Mudskippers are amphibious fishes that have developed morphological and physiological adaptations to match their unique lifestyles. Here we perform whole-genome sequencing of four representative mudskippers to elucidate the molecular mechanisms underlying these adaptations. We discover an expansion of innate immune system genes in the mudskippers that may provide defence against terrestrial pathogens. Several genes of the ammonia excretion pathway in the gills have experienced positive selection, suggesting their important roles in mudskippers’ tolerance to environmental ammonia. Some vision-related genes are differentially lost or mutated, illustrating genomic changes associated with aerial vision. Transcriptomic analyses of mudskippers exposed to air highlight regulatory pathways that are up- or down-regulated in response to hypoxia. The present study provides a valuable resource for understanding the molecular mechanisms underlying water-to-land transition of vertebrates.

Preimplantation genetic testing for aneuploidy (PGT-A) with trophectoderm (TE) biopsy is widely applied in in vitro fertilization (IVF) to identify aneuploid embryos. However, potential safety concerns regarding biopsy and restrictions to only those embryos suitable for biopsy pose limitations. In addition, embryo mosaicism gives rise to false positives and false negatives in PGT-A because the inner cell mass (ICM) cells, which give rise to the fetus, are not tested. Here, we report a critical examination of the efficacy of noninvasive preimplantation genetic testing for aneuploidy (niPGT-A) in the spent culture media of human blastocysts by analyzing the cell-free DNA, which reflects ploidy of both the TE and ICM. Fifty-two frozen donated blastocysts with TE biopsy results were thawed; each of their spent culture medium was collected after 24-h culture and analyzed by next-generation sequencing (NGS). niPGT-A and TE-biopsy PGT-A results were compared with the sequencing results of the corresponding embryos, which were taken as true results for aneuploidy reporting. With removal of all corona-cumulus cells, the false-negative rate (FNR) for niPGT-A was found to be zero. By applying an appropriate threshold for mosaicism, both the positive predictive value (PPV) and specificity for niPGT-A were much higher than TE-biopsy PGT-A. Furthermore, the concordance rates for both embryo ploidy and chromosome copy numbers were higher for niPGT-A than TE-biopsy PGT-A. These results suggest that niPGT-A is less prone to errors associated with embryo mosaicism and is more reliable than TE-biopsy PGT-A.

In vitro fertilization (IVF), preimplantation genetic diagnosis (PGD), and preimplantation genetic screening (PGS) help patients to select embryos free of monogenic diseases and aneuploidy (chromosome abnormality). Next-generation sequencing (NGS) methods, while experiencing a rapid cost reduction, have improved the precision of PGD/PGS. However, the precision of PGD has been limited by the false-positive and false-negative single-nucleotide variations (SNVs), which are not acceptable in IVF and can be circumvented by linkage analyses, such as short tandem repeats or karyomapping. It is noteworthy that existing methods of detecting SNV/copy number variation (CNV) and linkage analysis often require separate procedures for the same embryo. Here we report an NGS-based PGD/PGS procedure that can simultaneously detect a single-gene disorder and aneuploidy and is capable of linkage analysis in a cost-effective way. This method, called “mutated allele revealed by sequencing with aneuploidy and linkage analyses” (MARSALA), involves multiple annealing and looping-based amplification cycles (MALBAC) for single-cell whole-genome amplification. Aneuploidy is determined by CNVs, whereas SNVs associated with the monogenic diseases are detected by PCR amplification of the MALBAC product. The false-positive and -negative SNVs are avoided by an NGS-based linkage analysis. Two healthy babies, free of the monogenic diseases of their parents, were born after such embryo selection. The monogenic diseases originated from a single base mutation on the autosome and the X-chromosome of the disease-carrying father and mother, respectively.

Currently, the methods available for preimplantation genetic diagnosis (PGD) of in vitro fertilized (IVF) embryos do not detect de novo single-nucleotide and short indel mutations, which have been shown to cause a large fraction of genetic diseases. Detection of all these types of mutations requires whole-genome sequencing (WGS). In this study, advanced massively parallel WGS was performed on three 5-to 10-cell biopsies from two blastocyst-stage embryos. Both parents and paternal grandparents were also analyzed to allow for accurate measurements of false-positive and false-negative error rates. Overall, >95% of each genome was called. In the embryos, experimentally derived haplotypes and barcoded read data were used to detect and phase up to 82% of de novo single base mutations with a false-positive rate of about one error per Gb, resulting in fewer than 10 such errors per embryo. This represents a~100-fold lower error rate than previously published from 10 cells, and it is the first demonstration that advanced WGS can be used to accurately identify these de novo mutations in spite of the thousands of false-positive errors introduced by the extensive DNA amplification required for deep sequencing. Using haplotype information, we also demonstrate how small de novo deletions could be detected. These results suggest that phased WGS using barcoded DNA could be used in the future as part of the PGD process to maximize comprehensiveness in detecting disease-causing mutations and to reduce the incidence of genetic diseases.

BackgroundWhole exome sequencing (WES) has been widely used in human genetics research. BGISEQ-500 is a recently established next-generation sequencing platform. However, the performance of BGISEQ-500 on WES is not well studied. In this study, we evaluated the performance of BGISEQ-500 on WES by side-to-side comparison with Hiseq4000, on well-characterized human sample NA12878.ResultsBGISEQ demonstrated similarly high reproducibility as Hiseq for variation detection. Also, the SNVs from BGISEQ data is highly consistent with Hiseq results (concordance 96.5%~ 97%). Variation detection accuracy was subsequently evaluated with data from the genome in a bottle project as the benchmark. Both platforms showed similar sensitivity and precision in SNV detection. While in indel detection, BGISEQ showed slightly higher sensitivity and lower precision. The impact of sequence depth and read length on variation detection accuracy was further analyzed, and showed that variation detection sensitivity still increasing when the sequence depth is larger than 100x, and the impact of read length is minor when using 100x data.ConclusionsThis study suggested that BGISEQ-500 is a qualified sequencing platform for WES.

Because the new Proton platform from Life Technologies produced markedly different data from those of the Illumina platform, the conventional Illumina data analysis pipeline could not be used directly. We developed an optimized SNP calling method using TMAP and GATK (OTG-snpcaller). This method combined our own optimized processes, Remove Duplicates According to AS Tag (RDAST) and Alignment Optimize Structure (AOS), together with TMAP and GATK, to call SNPs from Proton data. We sequenced four sets of exomes captured by Agilent SureSelect and NimbleGen SeqCap EZ Kit, using Life Technology’s Ion Proton sequencer. Then we applied OTG-snpcaller and compared our results with the results from Torrent Variants Caller. The results indicated that OTG-snpcaller can reduce both false positive and false negative rates. Moreover, we compared our results with Illumina results generated by GATK best practices, and we found that the results of these two platforms were comparable. The good performance in variant calling using GATK best practices can be primarily attributed to the high quality of the Illumina sequences.

Copy-number variations (CNV), loss of heterozygosity (LOH), and uniparental disomy (UPD) are large genomic aberrations leading to many common inherited diseases, cancers, and other complex diseases. An integrated tool to identify these aberrations is essential in understanding diseases and in designing clinical interventions. Previous discovery methods based on whole-genome sequencing (WGS) require very high depth of coverage on the whole genome scale, and are cost-wise inefficient. Another approach, whole exome genome sequencing (WEGS), is limited to discovering variations within exons. Thus, we are lacking efficient methods to detect genomic aberrations on the whole genome scale using next-generation sequencing technology. Here we present a method to identify genome-wide CNV, LOH and UPD for the human genome via selectively sequencing a small portion of genome termed Selected Target Regions (SeTRs). In our experiments, the SeTRs are covered by 99.73%~99.95% with sufficient depth. Our developed bioinformatics pipeline calls genome-wide CNVs with high confidence, revealing 8 credible events of LOH and 3 UPD events larger than 5M from 15 individual samples. We demonstrate that genome-wide CNV, LOH and UPD can be detected using a cost-effective SeTRs sequencing approach, and that LOH and UPD can be identified using just a sample grouping technique, without using a matched sample or familial information.