To review the registration and technical data for prenatal diagnosis of chromosome aneuploidy by next generation sequencing technology. On the basis of introducing declarations of the reagents, analysis registration dossier common problems. And analysis the requirement of performance evaluation, reference intervals and clinical evaluation study.
Aneuploidy ; Female ; High-Throughput Nucleotide Sequencing ; Humans ; Pregnancy ; Prenatal Diagnosis ; standards

Characterized reference materials (RMs) are needed for clinical laboratory test development and validation, quality control procedures, and proficiency testing to assure their quality. In this article, we review the development and characterization of RMs for clinical molecular genetic tests. We describe various types of RMs and how to access and utilize them, especially focusing on the Genetic Testing Reference Materials Coordination Program (Get-RM) and the Genome in a Bottle (GIAB) Consortium. This review also reinforces the need for collaborative efforts in the clinical genetic testing community to develop additional RMs.
Genetic Testing/*standards ; High-Throughput Nucleotide Sequencing/standards ; Humans ; Public Relations ; Quality Control ; Reference Values ; Sequence Analysis, DNA/standards

The rapid development of high-throughput sequencing technologies has led to a dramatic decrease in the money and time required for de novo genome sequencing or genome resequencing projects, with new genome sequences constantly released every week. Among such projects, the plethora of updated genome assemblies induces the requirement of version-dependent annotation files and other compatible public dataset for downstream analysis. To handle these tasks in an efficient manner, we developed the reference-based genome assembly and annotation tool (RGAAT), a flexible toolkit for resequencing-based consensus building and annotation update. RGAAT can detect sequence variants with comparable precision, specificity, and sensitivity to GATK and with higher precision and specificity than Freebayes and SAMtools on four DNA-seq datasets tested in this study. RGAAT can also identify sequence variants based on cross-cultivar or cross-version genomic alignments. Unlike GATK and SAMtools/BCFtools, RGAAT builds the consensus sequence by taking into account the true allele frequency. Finally, RGAAT generates a coordinate conversion file between the reference and query genomes using sequence variants and supports annotation file transfer. Compared to the rapid annotation transfer tool (RATT), RGAAT displays better performance characteristics for annotation transfer between different genome assemblies, strains, and species. In addition, RGAAT can be used for genome modification, genome comparison, and coordinate conversion. RGAAT is available at https://sourceforge.net/projects/rgaat/ and https://github.com/wushyer/RGAAT_v2 at no cost.
Genome ; Genomics ; High-Throughput Nucleotide Sequencing ; methods ; standards ; Humans ; Reference Standards ; Sequence Analysis, DNA ; methods ; standards ; Software

As next-generation sequencing (NGS) technology has become widely used to identify genetic causal variants for various diseases and traits, a number of packages for checking NGS data quality have sprung up in public domains. In addition to the quality of sequencing data, sample quality issues, such as gender mismatch, abnormal inbreeding coefficient, cryptic relatedness, and population outliers, can also have fundamental impact on downstream analysis. However, there is a lack of tools specialized in identifying problematic samples from NGS data, often due to the limitation of sample size and variant counts. We developed SeqSQC, a Bioconductor package, to automate and accelerate sample cleaning in NGS data of any scale. SeqSQC is designed for efficient data storage and access, and equipped with interactive plots for intuitive data visualization to expedite the identification of problematic samples. SeqSQC is available at http://bioconductor.org/packages/SeqSQC.
Breast Neoplasms ; genetics ; Cohort Studies ; Continental Population Groups ; genetics ; Female ; Genome, Human ; High-Throughput Nucleotide Sequencing ; methods ; standards ; Humans ; Software ; Whole Exome Sequencing

Gastric cancer(GC) is a highly heterogeneous malignancy. The present widely used histopathological classifications have gradually failed to meet the needs of individualized diagnosis and treatment. Development of technologies such as microarray and next-generation sequencing (NGS) has allowed GC to be studied at the molecular level. Mechanisms about tumorigenesis and progression of GC can be elucidated in the aspects of gene mutations, chromosomal alterations, transcriptional and epigenetic changes, on the basis of which GC can be divided into several subtypes. The classifications of Tan's, Lei's, TCGA and ACRG are relatively comprehensive. Especially the TCGA and ACRG classifications have large sample size and abundant molecular profiling data, thus, the genomic characteristics of GC can be depicted more accurately. However, significant differences between both classifications still exist so that they cannot be substituted for each other. So far there is no widely accepted molecular classification of GC. Compared with TCGA classification, ACRG system may have more clinical significance in Chinese GC patients since the samples are mostly from Asian population and show better association with prognosis. The molecular classification of GC may provide the theoretical and experimental basis for early diagnosis, therapeutic efficacy prediction and treatment stratification while their clinical application is still limited. Future work should involve the application of molecular classifications in the clinical settings for improving the medical management of GC.
Asian Continental Ancestry Group ; Carcinogenesis ; genetics ; Disease Progression ; Early Detection of Cancer ; Epigenesis, Genetic ; physiology ; High-Throughput Nucleotide Sequencing ; Humans ; Microarray Analysis ; Molecular Epidemiology ; standards ; Mutation ; physiology ; Prognosis ; Stomach Neoplasms ; classification ; genetics

Fructus Arctii is a traditional Chinese medicine. The main counterfeit species are the seeds of Arctium tomentosum, Onopordum acanthium, Silybum marianum, Saussurea costus, Amorpha fruticosa. Traditional identification methods or molecular barcoding techniques can identify Fructus Arctii and its counterfeit species. However, the identification of the mixture of it and its spurious species is rarely reported. In this paper, we sequenced the ITS2 sequences of Fructus Arctii and 5 kinds of spurious species mix powder by high-throughput sequencing to identify the mixed powder species and providing new ideas for the identification of Fructus Arctii mix powder. The total DNA in mixed powder was extracted, and the ITS2 sequences in total DNA was amplified. Paired-end sequencing was performed on the DNA fragment of the community using the Illumina MiSeq platform. The sequence was analyzed by the software FLASH, QIIME and GraPhlAn etc. The results showed that the high quality ITS2 sequences of 39910 mix samples were obtained from the mixed samples, of which the total ITS2 sequence of the samples genus was 34 935. Phylogenetic analysis showed that the samples contained Fructus Arctii, A. tomentosum, O. acanthium, S. marianum, S. costus and A. fruticosa. Using ITS2 sequences as DNA barcodes, high-throughput sequencing technology can be used to detect the Fructus Arctii and its spurious specie in mixed powder, which can provide reference for the quality control, safe use of medicinal materials of Fructus Arctii and the identification of mixed powder of traditional Chinese medicine.
Arctium ; chemistry ; classification ; DNA Barcoding, Taxonomic ; DNA, Plant ; genetics ; DNA, Ribosomal Spacer ; genetics ; Drug Contamination ; Drugs, Chinese Herbal ; standards ; Fabaceae ; Fruit ; High-Throughput Nucleotide Sequencing ; Milk Thistle ; Onopordum ; Phylogeny ; Saussurea

DNA methylation is an important epigenetic mark that plays a vital role in gene expression and cell differentiation. The average DNA methylation level among a group of cells has been extensively documented. However, the cell-to-cell heterogeneity in DNA methylation, which reflects the differentiation of epigenetic status among cells, remains less investigated. Here we established a gold standard of the cell-to-cell heterogeneity in DNA methylation based on single-cell bisulfite sequencing (BS-seq) data. With that, we optimized a computational pipeline for estimating the heterogeneity in DNA methylation from bulk BS-seq data. We further built HeteroMeth, a database for searching, browsing, visualizing, and downloading the data for heterogeneity in DNA methylation for a total of 141 samples in humans, mice, Arabidopsis, and rice. Three genes are used as examples to illustrate the power of HeteroMeth in the identification of unique features in DNA methylation. The optimization of the computational strategy and the construction of the database in this study complement the recent experimental attempts on single-cell DNA methylomes and will facilitate the understanding of epigenetic mechanisms underlying cell differentiation and embryonic development. HeteroMeth is publicly available at http://qianlab.genetics.ac.cn/HeteroMeth.
Animals ; Arabidopsis ; genetics ; Cell Line ; Computer Simulation ; DNA Methylation ; genetics ; Databases, Genetic ; Entropy ; Genetic Heterogeneity ; Genome ; High-Throughput Nucleotide Sequencing ; Humans ; Mice ; Oryza ; genetics ; Reference Standards ; Reproducibility of Results ; Sequence Analysis, DNA ; Single-Cell Analysis ; User-Computer Interface