A critical spotlight on the paradigms of FFPE-DNA sequencing.

In the late 19th century, formalin fixation with paraffin-embedding (FFPE) of tissues was developed as a fixation and conservation method and is still used to this day in routine clinical and pathological practice. The implementation of state-of-the-art nucleic acid sequencing technologies has sparked much interest for using historical FFPE samples stored in biobanks as they hold promise in extracting new information from these valuable samples. However, formalin fixation chemically modifies DNA, which potentially leads to incorrect sequences or misinterpretations in downstream processing and data analysis. Many publications have concentrated on one type of DNA damage, but few have addressed the complete spectrum of FFPE-DNA damage. Here, we review mitigation strategies in (I) pre-analytical sample quality control, (II) DNA repair treatments, (III) analytical sample preparation and (IV) bioinformatic analysis of FFPE-DNA. We then provide recommendations that are tested and illustrated with DNA from 13-year-old liver specimens, one FFPE preserved and one fresh frozen, applying target-enriched sequencing. Thus, we show how DNA damage can be compensated, even when using low quantities (50 ng) of fragmented FFPE-DNA (DNA integrity number 2.0) that cannot be amplified well (Q129 bp/Q41 bp = 5%). Finally, we provide a checklist called 'ERROR-FFPE-DNA' that summarises recommendations for the minimal information in publications required for assessing fitness-for-purpose and inter-study comparison when using FFPE samples.

The RD-Connect Genome-Phenome Analysis Platform: Accelerating diagnosis, research, and gene discovery for rare diseases.

Rare disease patients are more likely to receive a rapid molecular diagnosis nowadays thanks to the wide adoption of next-generation sequencing. However, many cases remain undiagnosed even after exome or genome analysis, because the methods used missed the molecular cause in a known gene, or a novel causative gene could not be identified and/or confirmed. To address these challenges, the RD-Connect Genome-Phenome Analysis Platform (GPAP) facilitates the collation, discovery, sharing, and analysis of standardized genome-phenome data within a collaborative environment. Authorized clinicians and researchers submit pseudonymised phenotypic profiles encoded using the Human Phenotype Ontology, and raw genomic data which is processed through a standardized pipeline. After an optional embargo period, the data are shared with other platform users, with the objective that similar cases in the system and queries from peers may help diagnose the case. Additionally, the platform enables bidirectional discovery of similar cases in other databases from the Matchmaker Exchange network. To facilitate genome-phenome analysis and interpretation by clinical researchers, the RD-Connect GPAP provides a powerful user-friendly interface and leverages tens of information sources. As a result, the resource has already helped diagnose hundreds of rare disease patients and discover new disease causing genes.

Genetic lesions in MYC and STAT3 drive oncogenic transcription factor overexpression in plasmablastic lymphoma.

Plasmablastic lymphoma mutational profile is undescribed. Here we performed a targeted exonic NGS analysis of 30 plasmablastic lymphoma cases with a B cell lymphoma dedicated panel and FISH for the detection of MYC rearrangements. A complete phenotyping of the neoplastic and microenvironment cell populations was also performed. We have identified an enrichment in recurrent genetic events in MYC (69% with MYC translocation or amplification and 3 cases with missense point mutations), PRDM1/Blimp1 and STAT3 mutations. These gene mutations were more frequent in EBV positive disease. Other genetic events included mutations in BRAF, EP300, BCR (CD79A and CD79B), NOTCH pathway (NOTCH2, NOTCH1 and SGK1) and MYD88pL265P. Immunohistochemical analysis showed consistent MYC expression, higher in cases with MYC rearrangements together with phospho-STAT3 (Tyr705) overexpression in cases with STAT3 SH2 domain mutations. Microenvironment populations were heterogeneous and unrelated with EBV, with an enrichment of Tumor Associated Macrophages (TAM) and PD1 positive T cells. PD-L1 was expressed in all cases in the TAM population but only in 5 cases in the neoplastic cells (4 out of 14 EBV positive cases). HLA expression was absent in the majority of PBL cases. In summary, Plasmablastic lymphoma mutational profile is heterogeneous and related with EBV infection. Genetic events in MYC, STAT3 and PRDM1/Blimp1 are more frequent in EBV positive disease. An enrichment in TAM and PD1 reactive T lymphocytes is found in the microenvironment of PBL cases, that express PD-L1 in the neoplastic cells in a fraction of cases.

Variability in porcine microRNA genes and its association with mRNA expression and lipid phenotypes.

BACKGROUND: Mature microRNAs (miRNAs) play an important role in repressing the expression of a wide range of mRNAs. The presence of polymorphic sites in miRNA genes and their corresponding 3'UTR binding sites can disrupt canonical conserved miRNA-mRNA pairings, and thus modify gene expression patterns. However, to date such polymorphic sites in miRNA genes and their association with gene expression phenotypes and complex traits are poorly characterized in pigs. RESULTS: By analyzing whole-genome sequences from 120 pigs and wild boars from Europe and Asia, we identified 285 single nucleotide polymorphisms (SNPs) that map to miRNA loci, and 109,724 SNPs that are located in predicted 7mer-m8 miRNA binding sites within porcine 3'UTR. In porcine miRNA genes, SNP density is reduced compared with their flanking non-miRNA regions. By sequencing the genomes of five Duroc boars, we identified 12 miRNA SNPs that were subsequently genotyped in their offspring (N = 345, Lipgen population). Association analyses of miRNA SNPs with 38 lipid-related traits and hepatic and muscle microarray expression phenotypes recorded in the Lipgen population were performed. The most relevant detected association was between the genotype of the rs319154814 (G/A) SNP located in the apical loop of the ssc-miR-326 hairpin precursor and PPP1CC mRNA levels in the liver (q-value = 0.058). This result was subsequently confirmed by qPCR (P-value = 0.027). The rs319154814 (G/A) genotype was also associated with several fatty acid composition traits. CONCLUSIONS: Our findings show a reduced variability of porcine miRNA genes, which is consistent with strong purifying selection, particularly in the seed region that plays a critical role in miRNA binding. Although it is generally assumed that SNPs mapping to the seed region are those with the most pronounced consequences on mRNA expression, we show that a SNP mapping to the apical region of ssc-miR-326 is significantly associated with hepatic mRNA levels of the PPP1CC gene, one of its predicted targets. Although experimental confirmation of such an interaction is reported in humans but not in pigs, this result highlights the need to further investigate the functional effects of miRNA polymorphisms that are located outside the seed region on gene expression in pigs.

Runs of homozygosity reveal signatures of positive selection for reproduction traits in breed and non-breed horses.

BACKGROUND: Modern horses represent heterogeneous populations specifically selected for appearance and performance. Genomic regions under high selective pressure show characteristic runs of homozygosity (ROH) which represent a low genetic diversity. This study aims at detecting the number and functional distribution of ROHs in different horse populations using next generation sequencing data. METHODS: Next generation sequencing was performed for two Sorraia, one Dülmen Horse, one Arabian, one Saxon-Thuringian Heavy Warmblood, one Thoroughbred and four Hanoverian. After quality control reads were mapped to the reference genome EquCab2.70. ROH detection was performed using PLINK, version 1.07 for a trimmed dataset with 11,325,777 SNPs and a mean read depth of 12. Stretches with homozygous genotypes of >40 kb as well as >400 kb were defined as ROHs. SNPs within consensus ROHs were tested for neutrality. Functional classification was done for genes annotated within ROHs using PANTHER gene list analysis and functional variants were tested for their distribution among breed or non-breed groups. RESULTS: ROH detection was performed using whole genome sequences of ten horses of six populations representing various breed types and non-breed horses. In total, an average number of 3492 ROHs were detected in windows of a minimum of 50 consecutive homozygous SNPs and an average number of 292 ROHs in windows of 500 consecutive homozygous SNPs. Functional analyses of private ROHs in each horse revealed a high frequency of genes affecting cellular, metabolic, developmental, immune system and reproduction processes. In non-breed horses, 198 ROHs in 50-SNP windows and seven ROHs in 500-SNP windows showed an enrichment of genes involved in reproduction, embryonic development, energy metabolism, muscle and cardiac development whereas all seven breed horses revealed only three common ROHs in 50-SNP windows harboring the fertility-related gene YES1. In the Hanoverian, a total of 18 private ROHs could be shown to be located in the region of genes potentially involved in neurologic control, signaling, glycogen balance and reproduction. Comparative analysis of homozygous stretches common in all ten horses displayed three ROHs which were all located in the region of KITLG, the ligand of KIT known to be involved in melanogenesis, haematopoiesis and gametogenesis. CONCLUSIONS: The results of this study give a comprehensive insight into the frequency and number of ROHs in various horses and their potential influence on population diversity and selection pressures. Comparisons of breed and non-breed horses suggest a significant artificial as well as natural selection pressure on reproduction performance in all types of horse populations.

Next generation sequencing gives an insight into the characteristics of highly selected breeds versus non-breed horses in the course of domestication.

BACKGROUND: Domestication has shaped the horse and lead to a group of many different types. Some have been under strong human selection while others developed in close relationship with nature. The aim of our study was to perform next generation sequencing of breed and non-breed horses to provide an insight into genetic influences on selective forces. RESULTS: Whole genome sequencing of five horses of four different populations revealed 10,193,421 single nucleotide polymorphisms (SNPs) and 1,361,948 insertion/deletion polymorphisms (indels). In comparison to horse variant databases and previous reports, we were able to identify 3,394,883 novel SNPs and 868,525 novel indels. We analyzed the distribution of individual variants and found significant enrichment of private mutations in coding regions of genes involved in primary metabolic processes, anatomical structures, morphogenesis and cellular components in non-breed horses and in contrast to that private mutations in genes affecting cell communication, lipid metabolic process, neurological system process, muscle contraction, ion transport, developmental processes of the nervous system and ectoderm in breed horses. CONCLUSIONS: Our next generation sequencing data constitute an important first step for the characterization of non-breed in comparison to breed horses and provide a large number of novel variants for future analyses. Functional annotations suggest specific variants that could play a role for the characterization of breed or non-breed horses.

Quantification of rare somatic single nucleotide variants by droplet digital PCR using SuperSelective primers.

Somatic single-nucleotide variants (SNVs) occur every time a cell divides, appearing even in healthy tissues at low frequencies. These mutations may accumulate as neutral variants during aging, or eventually, promote the development of neoplasia. Here, we present the SP-ddPCR, a droplet digital PCR (ddPCR) based approach that utilizes customized SuperSelective primers aiming at quantifying the proportion of rare SNVs. For that purpose, we selected five potentially pathogenic variants identified by whole-exome sequencing (WES) occurring at low variant allele frequency (VAF) in at-risk colon healthy mucosa of patients diagnosed with colorectal cancer or advanced adenoma. Additionally, two APC SNVs detected in two cancer lesions were added to the study for WES-VAF validation. SuperSelective primers were designed to quantify SNVs at low VAFs both in silico and in clinical samples. In addition to the two APC SNVs in colonic lesions, SP-ddPCR confirmed the presence of three out of five selected SNVs in the normal colonic mucosa with allelic frequencies ≤ 5%. Moreover, SP-ddPCR showed the presence of two potentially pathogenic variants in the distal normal mucosa of patients with colorectal carcinoma. In summary, SP-ddPCR offers a rapid and feasible methodology to validate next-generation sequencing data and accurately quantify rare SNVs, thus providing a potential tool for diagnosis and stratification of at-risk patients based on their mutational profiling.

Germ line variants in patients with acute myeloid leukemia without a suspicion of hereditary hematologic malignancy syndrome.

Germ line predisposition in acute myeloid leukemia (AML) has gained attention in recent years because of a nonnegligible frequency and an impact on management of patients and their relatives. Risk alleles for AML development may be present in patients without a clinical suspicion of hereditary hematologic malignancy syndrome. In this study we investigated the presence of germ line variants (GVs) in 288 genes related to cancer predisposition in 47 patients with available paired, tumor-normal material, namely bone marrow stroma cells (n = 29), postremission bone marrow (n = 17), and saliva (n = 1). These patients correspond to 2 broad AML categories with heterogeneous genetic background (AML myelodysplasia related and AML defined by differentiation) and none of them had phenotypic abnormalities, previous history of cytopenia, or strong cancer aggregation. We found 11 pathogenic or likely pathogenic variants, 6 affecting genes related to autosomal dominant cancer predisposition syndromes (ATM, DDX41, and CHEK2) and 5 related to autosomal recessive bone marrow failure syndromes (FANCA, FANCM, SBDS, DNAJC21, and CSF3R). We did not find differences in clinical characteristics nor outcome between carriers of GVs vs noncarriers. Further studies in unselected AML cohorts are needed to determine GV incidence and penetrance and, in particular, to clarify the role of ATM nonsense mutations in AML predisposition.

Systematic Collaborative Reanalysis of Genomic Data Improves Diagnostic Yield in Neurologic Rare Diseases.

Many patients experiencing a rare disease remain undiagnosed even after genomic testing. Reanalysis of existing genomic data has shown to increase diagnostic yield, although there are few systematic and comprehensive reanalysis efforts that enable collaborative interpretation and future reinterpretation. The Undiagnosed Rare Disease Program of Catalonia project collated previously inconclusive good quality genomic data (panels, exomes, and genomes) and standardized phenotypic profiles from 323 families (543 individuals) with a neurologic rare disease. The data were reanalyzed systematically to identify relatedness, runs of homozygosity, consanguinity, single-nucleotide variants, insertions and deletions, and copy number variants. Data were shared and collaboratively interpreted within the consortium through a customized Genome-Phenome Analysis Platform, which also enables future data reinterpretation. Reanalysis of existing genomic data provided a diagnosis for 20.7% of the patients, including 1.8% diagnosed after the generation of additional genomic data to identify a second pathogenic heterozygous variant. Diagnostic rate was significantly higher for family-based exome/genome reanalysis compared with singleton panels. Most new diagnoses were attributable to recent gene-disease associations (50.8%), additional or improved bioinformatic analysis (19.7%), and standardized phenotyping data integrated within the Undiagnosed Rare Disease Program of Catalonia Genome-Phenome Analysis Platform functionalities (18%).

PrecisionFDA Truth Challenge V2: Calling variants from short and long reads in difficult-to-map regions.

The precisionFDA Truth Challenge V2 aimed to assess the state of the art of variant calling in challenging genomic regions. Starting with FASTQs, 20 challenge participants applied their variant-calling pipelines and submitted 64 variant call sets for one or more sequencing technologies (Illumina, PacBio HiFi, and Oxford Nanopore Technologies). Submissions were evaluated following best practices for benchmarking small variants with updated Genome in a Bottle benchmark sets and genome stratifications. Challenge submissions included numerous innovative methods, with graph-based and machine learning methods scoring best for short-read and long-read datasets, respectively. With machine learning approaches, combining multiple sequencing technologies performed particularly well. Recent developments in sequencing and variant calling have enabled benchmarking variants in challenging genomic regions, paving the way for the identification of previously unknown clinically relevant variants.