Whole-genome sequencing based on formalin-fixed paraffin-embedded endomyocardial biopsies for genetic studies on outcomes after heart transplantation

Successful application of ancient DNA extraction and library construction protocols to museum wet collection specimens

Millions of scientific specimens are housed in museum collections, a large part of which are fluid preserved. The use of formaldehyde as fixative and subsequent storage in ethanol is especially common in ichthyology and herpetology. This type of preservation damages DNA and reduces the chance of successful retrieval of genetic data. We applied ancient DNA extraction and single stranded library construction protocols to a variety of vertebrate samples obtained from wet collections and of different ages. Our results show that almost all samples tested yielded endogenous DNA. Archival DNA extraction was successful across different tissue types as well as using small amounts of tissue. Conversion of archival DNA fragments into single-stranded libraries resulted in usable data even for samples with initially undetectable DNA amounts. Subsequent target capture approaches for mitochondrial DNA using homemade baits on a subset of 30 samples resulted in almost complete mitochondrial genome sequences in several instances. Thus, application of ancient DNA methodology makes wet collection specimens, including type material as well as rare, old or extinct species, accessible for genetic and genomic analyses. Our results, accompanied by detailed step-by-step protocols, are a large step forward to open the DNA archive of museum wet collections for scientific studies.

Big Data Approaches in Heart Failure Research

PURPOSE OF REVIEW

The goal of this review is to summarize the state of big data analyses in the study of heart failure (HF). We discuss the use of big data in the HF space, focusing on "omics" and clinical data. We address some limitations of this data, as well as their future potential.

RECENT FINDINGS

Omics are providing insight into plasmal and myocardial molecular profiles in HF patients. The introduction of single cell and spatial technologies is a major advance that will reshape our understanding of cell heterogeneity and function as well as tissue architecture. Clinical data analysis focuses on HF phenotyping and prognostic modeling. Big data approaches are increasingly common in HF research. The use of methods designed for big data, such as machine learning, may help elucidate the biology underlying HF. However, important challenges remain in the translation of this knowledge into improvements in clinical care.