Statistical method to compare massive parallel sequencing pipelines

Breed-specific reference sequence optimized mapping accuracy of NGS analyses for pigs

Background

Reference sequences play a vital role in next-generation sequencing (NGS), impacting mapping quality during genome analyses. However, reference genomes usually do not represent the full range of genetic diversity of a species as a result of geographical divergence and independent demographic events of different populations. For the mitochondrial genome (mitogenome), which occurs in high copy numbers in cells and is strictly maternally inherited, an optimal reference sequence has the potential to make mitogenome alignment both more accurate and more efficient. In this study, we used three different types of reference sequences for mitogenome mapping, i.e., the commonly used reference sequence (CU-ref), the breed-specific reference sequence (BS-ref) and the sample-specific reference sequence (SS-ref), respectively, and compared the accuracy of mitogenome alignment and SNP calling among them, for the purpose of proposing the optimal reference sequence for mitochondrial DNA (mtDNA) analyses of specific populations

Results

Four pigs, representing three different breeds, were high-throughput sequenced, subsequently mapping reads to the reference sequences mentioned above, resulting in a largest mapping ratio and a deepest coverage without increased running time when aligning reads to a BS-ref. Next, single nucleotide polymorphism (SNP) calling was carried out by 18 detection strategies with the three tools SAMtools, VarScan and GATK with different parameters, using the bam results mapping to BS-ref. The results showed that all eighteen strategies achieved the same high specificity and sensitivity, which suggested a high accuracy of mitogenome alignment by the BS-ref because of a low requirement for SNP calling tools and parameter choices.

Conclusions

This study showed that different reference sequences representing different genetic relationships to sample reads influenced mitogenome alignment, with the breed-specific reference sequences being optimal for mitogenome analyses, which provides a refined processing perspective for NGS data.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-08030-1.

Mitochondrial DNA enrichment reduced NUMT contamination in porcine NGS analyses

Genetic associations between mitochondrial DNA (mtDNA) and economic traits have been widely reported for pigs, which indicate the importance of mtDNA. However, studies on mtDNA heteroplasmy in pigs are rare. Next generation sequencing (NGS) methodologies have emerged as a promising genomic approach for detection of mitochondrial heteroplasmy. Due to the short reads, flexible bioinformatic analyses and the contamination of nuclear mitochondrial sequences (NUMTs), NGS was expected to increase false-positive detection of heteroplasmy. In this study, Sanger sequencing was performed as a gold standard to detect heteroplasmy with a detection sensitivity of 5% in pigs and then one whole-genome sequencing method (WGS) and two mtDNA enrichment sequencing methods (Capture and LongPCR) were carried out. The aim of this study was to determine whether mitochondrial heteroplasmy identification from NGS data was affected by NUMTs. We find that WGS generated more false intra-individual polymorphisms and less mapping specificity than the two enrichment sequencing methods, suggesting NUMTs indeed led to false-positive mitochondrial heteroplasmies from NGS data. In addition, to accurately detect mitochondrial diversity, three commonly used tools-SAMtools, VarScan and GATK-with different parameter values were compared. VarScan achieved the best specificity and sensitivity when considering the base alignment quality re-computation and the minimum variant frequency of 0.25. It also suggested bioinformatic workflow interfere in the identification of mtDNA SNPs. In conclusion, intra-individual polymorphism in pig mitochondria from NGS data was confused with NUMTs, and mtDNA-specific enrichment is essential before high-throughput sequencing in the detection of mitochondrial genome sequences.

Next-generation sequencing for the clinical management of hepatitis C virus infections: does one test fits all purposes?

While the prospect of viral cure is higher than ever for individuals infected with the hepatitis C virus (HCV) due to ground-breaking progress in antiviral treatment, success rates are still negatively influenced by HCV's high genetic variability. This genetic diversity is represented in the circulation of various genotypes and subtypes, mixed infections, recombinant forms and the presence of numerous drug resistant variants among infected individuals. Common misclassifications by commercial genotyping assays in combination with the limitations of currently used targeted population sequencing approaches have encouraged researchers to exploit alternative methods for the clinical management of HCV infections. Next-generation sequencing (NGS), a revolutionary and powerful tool with a variety of applications in clinical virology, can characterize viral diversity and depict viral dynamics in an ultra-wide and ultra-deep manner. The level of detail it provides makes it the method of choice for the diagnosis and clinical assessment of HCV infections. The sequence library provided by NGS is of a higher magnitude and sensitivity than data generated by conventional methods. Therefore, these technologies are helpful to guide clinical practice and at the same time highly valuable for epidemiological studies. The decreasing costs of NGS to determine genotypes, mixed infections, recombinant strains and drug resistant variants will soon make it feasible to employ NGS in clinical laboratories, to assist in the daily care of patients with HCV.

Next Generation Sequencing Methods for Diagnosis of Epilepsy Syndromes

Epilepsy is a neurological disorder characterized by an increased predisposition for seizures. Although this definition suggests that it is a single disorder, epilepsy encompasses a group of disorders with diverse aetiologies and outcomes. A genetic basis for epilepsy syndromes has been postulated for several decades, with several mutations in specific genes identified that have increased our understanding of the genetic influence on epilepsies. With 70-80% of epilepsy cases identified to have a genetic cause, there are now hundreds of genes identified to be associated with epilepsy syndromes which can be analyzed using next generation sequencing (NGS) techniques such as targeted gene panels, whole exome sequencing (WES) and whole genome sequencing (WGS). For effective use of these methodologies, diagnostic laboratories and clinicians require information on the relevant workflows including analysis and sequencing depth to understand the specific clinical application and diagnostic capabilities of these gene sequencing techniques. As epilepsy is a complex disorder, the differences associated with each technique influence the ability to form a diagnosis along with an accurate detection of the genetic etiology of the disorder. In addition, for diagnostic testing, an important parameter is the cost-effectiveness and the specific diagnostic outcome of each technique. Here, we review these commonly used NGS techniques to determine their suitability for application to epilepsy genetic diagnostic testing.