Current Protocols in Human Genetics最新文献

Endothelial cells (ECs) line the interior surface of blood and lymphatic vessels, and play a key role in a variety of physiological or pathological processes such as thrombosis, inflammation, or vascular wall remodeling. Human-induced pluripotent stem cell (iPSCs)-derived ECs provide a new opportunity for vascular regeneration and serve as a model to study the mechanism and to screen for novel therapies. We use developmental cues in a monolayer differentiation approach to efficiently generate mesoderm cells from iPSCs via small-molecule activation of WNT signaling in chemically defined medium for 4 days, and subsequent EC specification using vascular endothelial growth factor and fibroblast growth factor for another 4 days. After 8 days of differentiation, mature ECs are further purified using magnetic-activated cell sorting for the EC surface marker CD144. These ECs exhibit molecular and cellular characteristics consistent with native ECs, such as expression of specific surface markers, formation of tube-like structures and acetylated low-density lipoprotein uptake. © 2018 by John Wiley & Sons, Inc.

Copy Number Variants (CNVs) are structural rearrangements contributing to phenotypic variation but also associated with many disease states. In recent years, the identification of CNVs from high-throughput sequencing experiments has become a common practice for both research and clinical purposes. Several computational methods have been developed so far. In this unit, we describe and give instructions on how to run two read count–based tools, XCAVATOR and EXCAVATOR2, which are tailored for the detection of both germline and somatic CNVs from different sequencing experiments (whole-genome, whole-exome, and targeted) in various disease contexts and population genetic studies. © 2018 by John Wiley & Sons, Inc.

Amniotic fluid obtained via amniocentesis provides a source of fetal material used in prenatal diagnosis. The fluid may be used directly for biochemical analyses, fluorescence in situ hybridization (FISH), and isolation of DNA for molecular studies, including chromosomal microarray analysis (CMA). The fluid is typically cultured as a source of metaphase cells for chromosome analysis and to provide additional material for biochemical and DNA-based testing. This unit describes an in situ method for the preparation, culture, and harvest of amniotic fluid samples for metaphase chromosome analysis. Cells are grown, harvested for metaphase spreads, and analyzed on glass coverslips. The unit also describes methods to obtain cells for additional studies (such as molecular genetic analyses) by growing cells in flasks either following passaging of cells from a glass coverslip culture or by directly establishing a flask culture from the amniotic fluid specimen. When cells are grown in flasks, they must be removed from the flask with trypsin before they can be used in studies. Lastly, this unit describes a method for isolating DNA for CMA from uncultured amniotic fluid and cultured cells. © 2018 by John Wiley & Sons, Inc.

Genetic data analysis of large numbers of single nucleotide variants (SNVs), including genome-wide association studies (GWAS), exome chips, and whole exome (WES) or whole-genome (WGS) sequencing data, requires well defined processing steps. As a result, several freely available analytic toolkits have been developed to streamline these processes. Among these, PLINK is the most comprehensive in terms of its quality control and analytic modules, although its focus remains on SNVs. PLINK fulfills two analytic needs-aiding the process of performing quality control (QC) on large data sets and providing basic statistical tools to analyze the variants in genetic models. The current version of PLINK (v1.90b) has incorporated several sophisticated statistical modeling features, such as those that were introduced by GCTA (genome-wide complex trait analysis), including mixed-model association analysis and cluster-based algorithms. Although PLINK is diverse in its applicability to data management and analysis, in some instances, other available tools offer more optimal options. Here we provide a practical overview of major PLINK features with respect to QC, data management, and association mapping, along with learned shortcuts and limitations to be considered. In cases where PLINK features are limited, we provide alternative approaches using additional freely available pipelines. © 2018 by John Wiley & Sons, Inc.

Balanced and apparently balanced chromosome abnormalities (BCAs) have long been known to generate disease through position effects, either by altering local networks of gene regulation or positioning genes in architecturally different chromosome domains. Despite these observations, identification of distally affected genes by BCAs is oftentimes neglected, especially when predicted gene disruptions are found elsewhere in the genome. In this unit, we provide detailed instructions on how to run a computational pipeline that identifies relevant candidates of non-coding BCA position effects. This methodology facilitates quick identification of genes potentially involved in disease by non-coding BCAs and other types of rearrangements, and expands on the importance of considering the long-range consequences of genomic lesions.

Identification of sequence variants that create or eliminate splice sites has proven to be a significant challenge and represents one of many roadblocks in the clinical interpretation of rare genetic variation. Current methods of identifying splice altering sequence variants exist, however, these are limited by an imperfect understanding of splice signals and cumbersome functional assays. We have recently developed a computational tool that prioritizes putative splice-altering sequence variants, and a moderate-throughput minigene assay that confirms the variants which alter splicing. This bioinformatic strategy represents a substantial increase in accuracy and efficiency of historical in vitro splicing assays. In this unit we give detailed instructions on how to organize, run, and interpret various features of this protocol. We expect that splice-altering variants revealed through this protocol can be reliably carried forward for further clinical and biological analyses.

DNA structural variants can be analyzed by droplet digital PCR (ddPCR), a water-oil microfluidics and fluorescence technology to quantify target nucleic acids with extreme precision and sensitivity. Traditional ddPCR uses expensive fluorescent oligonucleotide probes that require extensive optimization. Here we describe a variation of ddPCR using a DNA-binding dye (EvaGreen), whose properties allow target products to be effectively quantified at a significantly lower cost. © 2018 by John Wiley & Sons, Inc.

In this article, we discuss strategies for selection of families and family members for genetic studies. We will evaluate strategies to sample large families with multiply affected members, sibships, and nuclear families. In addition, we have added a section to discuss sub-sampling within pedigrees for large sequencing studies, particularly when genome-wide SNP chips are available on all members of a pedigree. The type of family sampled for a study will determine the statistical analyses and power of discovery of genetic findings. We will evaluate study designs that maximize power and allow for linkage and association analyses to identify genetic loci predisposing to phenotype. © 2018 by John Wiley & Sons, Inc.

This unit is devoted to safety issues that must be considered when generating and working with the most common vectors under development for human gene therapy today. © 2018 by John Wiley & Sons, Inc.

High-density SNP genotyping technology provides a low-cost, effective tool for conducting Genome Wide Association (GWA) studies. The wide adoption of GWA studies has indeed led to discoveries of disease- or trait-associated SNPs, some of which were subsequently shown to be causal. However, the nearly universal shortcoming of many GWA studies—missing heritability—has prompted great interest in searching for other types of genetic variation, such as copy number variation (CNV). Certain CNVs have been reported to alter disease susceptibility. Algorithms and tools have been developed to identify CNVs using SNP array hybridization intensity data. Such an approach provides an additional source of data with almost no extra cost. In this unit, we demonstrate the steps for calling CNVs from Illumina SNP array data using PennCNV and performing association analysis using R and PLINK. Curr. Protoc. Hum. Genet. 79:1.27.1-1.27.15. © 2013 by John Wiley & Sons, Inc.