Current Protocols in Human Genetics最新文献

Our understanding of genetic disease(s) has increased exponentially since the completion of human genome sequencing and the development of numerous techniques to detect genetic variants. These techniques have not only allowed us to diagnose genetic disease, but in so doing, also provide increased understanding of the pathogenesis of these diseases to aid in developing appropriate therapeutic options. Additionally, the advent of next-generation or massively parallel sequencing (NGS/MPS) is increasingly being used in the clinical setting, as it can detect a number of abnormalities from point mutations to chromosomal rearrangements as well as aberrations within the transcriptome. In this article, we will discuss the use of multiple techniques that are used in genetic diagnosis. © 2020 by John Wiley & Sons, Inc.

In order to comply with regulations set by established local, state, and federal agencies and other regulatory organizations, such as the College of American Pathologists and the International Organization for Standardization, a clinical laboratory needs to develop procedures for the processes of validating laboratory-developed tests (LDTs) and establishing performance specifications for these assays prior to use in clinical testing. This is applicable to all fluorescence in situ hybridization (FISH) assays. Even Food and Drug Administration–approved FISH assays must undergo some form of verification before implementation in the clinical laboratory. The process of validating an assay as an LDT must include a plan, a procedure, and a report. The validation studies described here include metaphase and interphase FISH methodology for identification of the LSI EGR1/D5S23, D5S721 dual-color probe, which labels distinct biomarkers consistent with myeloid hematologic disorders, including myelodysplasias and acute myeloid leukemia. © 2020 by John Wiley & Sons, Inc.

Basic Protocol 1: Validation plan for fluorescence in situ hybridization (FISH) probes for chromosome 5 monosomy and deletion

Support Protocol: Normal cut-off calculation

Basic Protocol 2: Validation procedure for FISH probes for chromosome 5 monosomy and deletion

Basic Protocol 3: Validation report for FISH probes for chromosome 5 monosomy and deletion

Cover: In Igo et al. (http://doi.org/10.1002/cphg.95), the image shows (A) Raw output from the ––logistic function in PLINK. The column OR contains the odds ratio per copy of allele A1. (B) Corresponding PLINK myprofile.raw file with marker name, reference allele (A1), and ln (OR) from the test of additive effects (lines labeled ADD under TEST).

Genome-wide variation data with millions of genetic markers have become commonplace. However, the potential for interpretation and application of these data for clinical assessment of outcomes of interest, and prediction of disease risk, is currently not fully realized. Many common complex diseases now have numerous, well-established risk loci and likely harbor many genetic determinants with effects too small to be detected at genome-wide levels of statistical significance. A simple and intuitive approach for converting genetic data to a predictive measure of disease susceptibility is to aggregate the effects of these loci into a single measure, the genetic risk score. Here, we describe some common methods and software packages for calculating genetic risk scores and polygenic risk scores, with focus on studies of common complex diseases. We review the basic information needed, as well as important considerations for constructing genetic risk scores, including specific requirements for phenotypic and genetic data, and limitations in their application. © 2019 by John Wiley & Sons, Inc.

Traditional approaches for interrogating the mitochondrial genome often involve laborious extraction and enrichment protocols followed by Sanger sequencing. Although preparation techniques are still demanding, the advent of next-generation or massively parallel sequencing has made it possible to routinely obtain nucleotide-level data with relative ease. These short-read sequencing platforms offer deep coverage with unparalleled read accuracy in high-complexity genomic regions but encounter numerous difficulties in the low-complexity homopolymeric sequences characteristic of the mitochondrial genome. The inability to discern identical units within monomeric repeats and resolve copy-number variations for heteroplasmy detection results in suboptimal genome assemblies that ultimately complicate downstream data analysis and interpretation of biological significance. Oxford Nanopore Technologies offers the ability to generate long-read sequencing data on a pocket-sized device known as the MinION. Nanopore-based sequencing is scalable, portable, and theoretically capable of sequencing the entire mitochondrial genome in a single contig. Furthermore, the recent development of a nanopore protein with dual reader heads allows for clear identification of nucleotides within homopolymeric stretches, significantly increasing resolution throughout these regions. The unrestricted read lengths, superior homopolymeric resolution, and affordability of the MinION device make it an attractive alternative to the labor-intensive, time-consuming, and costly mainstay deep-sequencing platforms. This article describes three approaches to extract, prepare, and sequence mitochondrial DNA on the Oxford Nanopore MinION device. Two of the workflows include enrichment of mitochondrial DNA prior to sequencing, whereas the other relies on direct sequencing of native genomic DNA to allow for simultaneous assessment of the nuclear and mitochondrial genomes. © 2019 by John Wiley & Sons, Inc.

Basic Protocol: Enrichment-free mitochondrial DNA sequencing

Alternate Protocol 1: Mitochondrial DNA sequencing following enrichment with polymerase chain reaction (PCR)

Alternate Protocol 2: Mitochondrial DNA sequencing following enrichment with PCR-free hybridization capture

Support Protocol 1: DNA quantification and quality assessment using the Agilent 4200 TapeStation System

Support Protocol 2: AMPure XP bead clean-up

Support Protocol 3: Suggested data analysis pipeline

Cover: In Köhler et al. (https://doi.org/10.1002/cphg.92), the image shows how to use PatientArchive to explore the top three candidate disorders associated with the patient phenotype profile.

The 2015 ACMG/AMP guidelines established a classification system for sequence variants; however, the broad scope of these guidelines necessitates specification of evidence types for specific genes or diseases of interest. Since publication of the guidelines, both general use and disease-focused specifications have emerged to aid in accurate application of ACMG/AMP evidence types. This article summarizes the approaches to, and rationale for, specifying three evidence categories (population frequency data, variant type and location, and case-level data), including available resources and a quantitative framework that can inform the specification process. © 2019 by John Wiley & Sons, Inc.

The Human Phenotype Ontology (HPO) is a standardized set of phenotypic terms that are organized in a hierarchical fashion. It is a widely used resource for capturing human disease phenotypes for computational analysis to support differential diagnostics. The HPO is frequently used to create a set of terms that accurately describe the observed clinical abnormalities of an individual being evaluated for suspected rare genetic disease. This profile is compared with computational disease profiles in the HPO database with the aim of identifying genetic diseases with comparable phenotypic profiles. The computational analysis can be coupled with the analysis of whole-exome or whole-genome sequencing data through applications such as Exomiser. This article explains how to choose an optimal set of HPO terms for these cases and enter them with software, such as PhenoTips and PatientArchive, and demonstrates how to use Phenomizer and Exomiser to generate a computational differential diagnosis. © 2019 by John Wiley & Sons, Inc.

In this unit, we describe a set of protocols and recommendations for Illumina library preparation. We review best practices in template quantitation methods; template fragmentation methodologies; solid-phase reverse-immobilization cleanup, including buffer exchange and size selection; end repair, A-tailing, and adapter ligation; indexing strategies; considerations regarding whether to use polymerase chain reaction; final library quantification methodologies; and normalization and pooling strategies. These workflows are applicable to both high-throughput and low-throughput Illumina library preparation and should help reduce bias, increase cost effectiveness, and produce high library yields. This is an extensive update of the previous version of this unit. © 2019 by John Wiley & Sons, Inc.

Carnitine is an essential molecule for mitochondrial beta-oxidation of long-chain fatty acids and other cellular functions. Several rare, inherited disorders of carnitine metabolism occur in humans, and secondary carnitine deficiency is an important feature in a variety of clinical settings. Many of these conditions can be detected via quantitative analysis of free and esterified carnitine in plasma or urine, which thus offers an effective means for assessing the transport and initial processing of fatty acids. Here, we describe some of the methods most commonly employed for quantification of plasma carnitine and consider some of the advantages and disadvantages of these approaches. © 2019 by John Wiley & Sons, Inc.