Three-stage quality control strategies for DNA re-sequencing data

Biostatistical Aspects of Whole Genome Sequencing Studies: Preprocessing and Quality Control

Rapid advances in high-throughput DNA sequencing technologies have enabled large-scale whole genome sequencing (WGS) studies. Before performing association analysis between phenotypes and genotypes, preprocessing and quality control (QC) of the raw sequence data need to be performed. Because many biostatisticians have not been working with WGS data so far, we first sketch Illumina's short-read sequencing technology. Second, we explain the general preprocessing pipeline for WGS studies. Third, we provide an overview of important QC metrics, which are applied to WGS data: on the raw data, after mapping and alignment, after variant calling, and after multisample variant calling. Fourth, we illustrate the QC with the data from the GENEtic SequencIng Study Hamburg-Davos (GENESIS-HD), a study involving more than 9000 human whole genomes. All samples were sequenced on an Illumina NovaSeq 6000 with an average coverage of 35× using a PCR-free protocol. For QC, one genome in a bottle (GIAB) trio was sequenced in four replicates, and one GIAB sample was successfully sequenced 70 times in different runs. Fifth, we provide empirical data on the compression of raw data using the DRAGEN original read archive (ORA). The most important quality metrics in the application were genetic similarity, sample cross-contamination, deviations from the expected Het/Hom ratio, relatedness, and coverage. The compression ratio of the raw files using DRAGEN ORA was 5.6:1, and compression time was linear by genome coverage. In summary, the preprocessing, joint calling, and QC of large WGS studies are feasible within a reasonable time, and efficient QC procedures are readily available.

Whole genome sequences of 70 indigenous Ethiopian cattle

Indigenous animal genetic resources play a crucial role in preserving global genetic diversity and supporting the livelihoods of millions of people. In Ethiopia, the majority of the cattle population consists of indigenous breeds. Understanding the genetic architecture of these cattle breeds is essential for effective management and conservation efforts. In this study, we sequenced DNA samples from 70 animals from seven indigenous cattle breeds, generating about two terabytes of pair-end reads with an average coverage of 14X. The sequencing data were pre-processed and mapped to the cattle reference genome (ARS-UCD1.2) with an alignment rate of 99.2%. Finally, the variant calling process produced approximately 35 million high-quality SNPs. These data provide a deeper understanding of the genetic landscape, facilitate the identification of causal mutations, and enable the exploration of evolutionary patterns to assist cattle improvement and sustainable utilization, particularly in the face of unpredictable climate changes.

Comparing the performances of SSR and SNP markers for population analysis in Theobroma cacao L., as alternative approach to validate a new ddRADseq protocol for cacao genotyping

Proper cacao (Theobroma cacao L.) plant genotyping is mandatory for the conservation and use of the species genetic resources. A set of 15 international standard SSR markers was assumed as universal cacao genotyping system. Recently, different SNPs and SNP genotyping techniques have been exploited in cacao. However, a consensus on which to use has not been reached yet, driving the search for new approaches. To validate a new ddRADseq protocol for cacao genotyping, we compared the performances for population analysis of a dataset with 7,880 SNPs obtained from ddRADseq and the genotypic data from the aforementioned SSR set, using 158 cacao plants from productive farms and gene bank. Four genetic groups were identified with STRUCTURE and ADMIXTURE softwares using SSR and SNP data, respectively. Similarities of cacao ancestries among these groups allowed the identification of analogous pairs of groups of individuals, referred to as: G1SSR/G1SNP, G2SSR/G2SNP, G3SSR/G3SNP, G4SSR/G4SNP, whether SSRs or SNPs were used. Both marker systems identified Amelonado and Criollo as the most abundant cacao ancestries among all samples. Genetic distance matrices from both data types were significantly similar to each other according to Mantel test (p < 0.0001). PCoA and UPGMA clustering mostly confirmed the identified genetic groups. AMOVA and FST pairwise comparison revealed a moderate to very large genetic differentiation among identified groups from SSR and SNP data. Genetic diversity parameters from SSR (Hobs = 0.616, Hexp = 0.524 and PIC = 0.544) were higher than that from SNP data (0.288, 0.264, 0.230). In both cases, genetic groups carrying the highest Amelonado proportion (G1SSR and G1SNP) had the lowest genetic diversity parameters among the identified groups. The high congruence among population analysis results using both systems validated the ddRADseq protocol employed for cacao SNP genotyping. These results could provide new ways for developing a universal SNP-based genotyping system very much needed for cacao genetic studies.

A comparative study of structural variant calling in WGS from Alzheimer's disease families

Detecting structural variants (SVs) in whole-genome sequencing poses significant challenges. We present a protocol for variant calling, merging, genotyping, sensitivity analysis, and laboratory validation for generating a high-quality SV call set in whole-genome sequencing from the Alzheimer's Disease Sequencing Project comprising 578 individuals from 111 families. Employing two complementary pipelines, Scalpel and Parliament, for SV/indel calling, we assessed sensitivity through sample replicates (N = 9) with in silico variant spike-ins. We developed a novel metric, D-score, to evaluate caller specificity for deletions. The accuracy of deletions was evaluated by Sanger sequencing. We generated a high-quality call set of 152,301 deletions of diverse sizes. Sanger sequencing validated 114 of 146 detected deletions (78.1%). Scalpel excelled in accuracy for deletions ≤100 bp, whereas Parliament was optimal for deletions >900 bp. Overall, 83.0% and 72.5% of calls by Scalpel and Parliament were validated, respectively, including all 11 deletions called by both Parliament and Scalpel between 101 and 900 bp. Our flexible protocol successfully generated a high-quality deletion call set and a truth set of Sanger sequencing-validated deletions with precise breakpoints spanning 1-17,000 bp.

Using ddRADseq to assess the genetic diversity of in-farm and gene bank cacao resources in the Baracoa region, eastern Cuba, for use and conservation purposes

The Baracoa region, eastern Cuba, hosts around 80 % of the country cacao (Theobroma cacao L.) plantations. Cacao plants in farms are diverse in origin and propagation, with grafted and hybrid plants being the more common ones. Less frequent are plants from cuttings, TSH progeny, and traditional Cuban cacao. A national cacao gene bank is also present in Baracoa, with 282 accessions either prospected in Cuba or introduced from other countries. A breeding program associated with the gene bank started in the 1990s based on agro-morphological descriptors. The genetic diversity of cacao resources in Baracoa has been poorly described, except for traditional Cuban cacao, affecting the proper development of the breeding program and the cacao planting policies in the region. To assess the population structure and genetic diversity of cacao resources in Baracoa region, we genotyped plants from both cacao gene bank (CG) and cacao farms (CF) applying a new ddRADseq protocol for cacao. After data processing, two SNPs datasets containing 11,425 and 6,481 high-quality SNPs were generated with 238 CG and 135 CF plants, respectively. SNPs were unevenly distributed along the 10 cacao chromosomes and laid mainly in noncoding regions of the genome. Population structure analysis with these SNP datasets identified seven and four genetic groups in CG and CF samples, respectively. Clustering using UPGMA and principal component analysis mostly agree with population structure results. Amelonado was the predominant cacao ancestry, accounting for 49.22 % (CG) and 57.73 % (CF) of the total. Criollo, Contamana, Iquitos, and Nanay ancestries were detected in both CG and CF samples, while Nacional and Marañon backgrounds were only identified in CG. Genetic differentiation among CG (FST ranging from 0.071 to 0.407) was higher than among CF genetic groups (FST: 0.093-0.282). Genetic diversity parameters showed similar values for CG and CF samples. The CG and CF genetic groups with the lowest genetic diversity parameters had the highest proportion of Amelonado ancestry. These results should contribute to reinforcing the ongoing breeding program and updating the planting policies on cacao farms, with an impact on the social and economic life of the region.

A Comprehensive Analysis of 3 Moroccan Genomes Revealed Contributions From Both African and European Ancestries

Genetic variations in the human genome represent the differences in DNA sequence within individuals. This highlights the important role of whole human genome sequencing which has become the keystone for precision medicine and disease prediction. Morocco is an important hub for studying human population migration and mixing history. This study presents the analysis of 3 Moroccan genomes; the variant analysis revealed 6 379 606 single nucleotide variants (SNVs) and 1 050 577 small InDels. Of those identified SNVs, 219 152 were novel, with 1233 occurring in coding regions, and 5580 non-synonymous single nucleotide variants (nsSNP) variants were predicted to affect protein functions. The InDels produced 1055 coding variants and 454 non-3n length variants, and their size ranged from -49 and 49 bp. We further analysed the gene pathways of 8 novel coding variants found in the 3 genomes and revealed 5 genes involved in various diseases and biological pathways. We found that the Moroccan genomes share 92.78% of African ancestry, and 92.86% of Non-Finnish European ancestry, according to the gnomAD database. Then, population structure inference, by admixture analysis and network-based approach, revealed that the studied genomes form a mixed population structure, highlighting the increased genetic diversity in Morocco.

Whole-genome resource sequences of 57 indigenous Ethiopian goats

Domestic goats are distributed worldwide, with approximately 35% of the one billion world goat population occurring in Africa. Ethiopia has 52.5 million goats, ~99.9% of which are considered indigenous landraces deriving from animals introduced to the Horn of Africa in the distant past by nomadic herders. They have continued to be managed by smallholder farmers and semi-mobile pastoralists throughout the region. We report here 57 goat genomes from 12 Ethiopian goat populations sampled from different agro-climates. The data were generated through sequencing DNA samples on the Illumina NovaSeq 6000 platform at a mean depth of 9.71x and 150 bp pair-end reads. In total, ~2 terabytes of raw data were generated, and 99.8% of the clean reads mapped successfully against the goat reference genome assembly at a coverage of 99.6%. About 24.76 million SNPs were generated. These SNPs can be used to study the population structure and genome dynamics of goats at the country, regional, and global levels to shed light on the species' evolutionary trajectory.

Bioinformatics of germline variant discovery for rare disease diagnostics: current approaches and remaining challenges

Next-generation sequencing (NGS) has revolutionized the field of rare disease diagnostics. Whole exome and whole genome sequencing are now routinely used for diagnostic purposes; however, the overall diagnosis rate remains lower than expected. In this work, we review current approaches used for calling and interpretation of germline genetic variants in the human genome, and discuss the most important challenges that persist in the bioinformatic analysis of NGS data in medical genetics. We describe and attempt to quantitatively assess the remaining problems, such as the quality of the reference genome sequence, reproducible coverage biases, or variant calling accuracy in complex regions of the genome. We also discuss the prospects of switching to the complete human genome assembly or the human pan-genome and important caveats associated with such a switch. We touch on arguably the hardest problem of NGS data analysis for medical genomics, namely, the annotation of genetic variants and their subsequent interpretation. We highlight the most challenging aspects of annotation and prioritization of both coding and non-coding variants. Finally, we demonstrate the persistent prevalence of pathogenic variants in the coding genome, and outline research directions that may enhance the efficiency of NGS-based disease diagnostics.

Whole‑exome sequencing reveals Lewis lung carcinoma is a hypermutated Kras/Nras-mutant cancer with extensive regional mutation clusters in its genome

Lewis lung carcinoma (LLC), as a widely used preclinical cancer model, has still not been genetically and genomically characterized. Here, we performed a whole-exome sequencing analysis on the LLC cell line to elucidate its molecular characteristics and etiologies. Our data showed that LLC originated from a male mouse belonging to C57BL/6L (a transitional strain between C57BL/6J and C57BL/6N) and contains substantial somatic SNV and InDel mutations (> 20,000). Extensive regional mutation clusters are present in its genome, which were caused mainly by the mutational processes underlying the SBS1, SBS5, SBS15, SBS17a, and SBS21 signatures during frequent structural rearrangements. Thirty three deleterious mutations are present in 30 cancer genes including Kras, Nras, Trp53, Dcc, and Cacna1d. Cdkn2a and Cdkn2b are biallelically deleted from the genome. Five pathways (RTK/RAS, p53, cell cycle, TGFB, and Hippo) are oncogenically deregulated or affected. The major mutational processes in LLC include chromosomal instability, exposure to metabolic mutagens, spontaneous 5-methylcytosine deamination, defective DNA mismatch repair, and reactive oxygen species. Our data also suggest that LLC is a lung cancer similar to human lung adenocarcinoma. This study lays a molecular basis for the more targeted application of LLC in preclinical research.

Increased heterozygosity in low-pass sequencing data allows identification of blood chimeras in cattle

In about 90% of multiple pregnancies in cattle, shared blood circulation between fetuses leads to genetic chimerism in peripheral blood and can reduce reproductive performance in heterosexual co-twins. However, the early detection of heterosexual chimeras requires specialized tests. Here, we used low-pass sequencing data with a median coverage of 0.64× generated from blood samples of 322 F1 crosses between beef and dairy cattle and identified 20 putative blood chimeras through increased levels of genome-wide heterozygosity. In contrast, for 77 samples with routine SNP microarray data generated from hair bulbs of the same F1s, we found no evidence of chimerism, simultaneously observing high levels of genotype discordance with sequencing data. Fifteen out of 18 reported twins showed signs of blood chimerism, in line with previous reports, whereas the presence of five alleged singletons with strong signs of chimerism suggests that the in-utero death rate of co-twins is at the upper limit of former estimates. Together, our results show that low-pass sequencing data allow reliable screening for blood chimeras. They further affirm that blood is not recommended as a source of DNA for the detection of germline variants.

Standardized Polyalthia longifolia leaf extract induces the apoptotic HeLa cells death via microRNA regulation: identification, validation, and therapeutic potential

Polyalthia longifolia var. angustifolia Thw. (Annonaceae), is a famous traditional medicinal plant in Asia. Ample data specifies that the medicinal plant P. longifolia has anticancer activity; however, the detailed mechanisms of action still need to be well studied. Recent studies have revealed the cytotoxicity potential of P. longifolia leaf against HeLa cells. Therefore, the current study was conducted to examine the regulation of miRNAs in HeLa cancer cells treated with the standardized P. longifolia methanolic leaf extract (PLME). The regulation of miRNAs in HeLa cancer cells treated with the standardized PLME extract was studied through Illumina, Hi-Seq. 2000 platform of Next-Generation Sequencing (NGS) and various in silico bioinformatics tools. The PLME treatment regulated a subset of miRNAs in HeLa cells. Interestingly, the PLME treatment against HeLa cancer cells identified 10 upregulated and 43 downregulated (p < 0.05) miRNAs associated with apoptosis induction. Gene ontology (GO) term analysis indicated that PLME induces cell death in HeLa cells by inducing the pro-apoptotic genes. Moreover, the downregulated oncomiRs modulated by PLME treatment in HeLa cells were identified, targeting apoptosis-related genes through gene ontology and pathway analysis. The LC-ESI-MS/MS analysis identified the presence of Vidarabine and Anandamide compounds that were previously reported to exhibit anticancer activity. The findings of this study obviously linked the cell cytotoxicity effect of PLME treatment against the HeLa cells with regulating various miRNAs expression related to apoptosis induction in the HeLa cells. PLME treatment induced apoptotic HeLa cell death mechanism by regulating multiple miRNAs. The identified miRNAs regulated by PLME may provide further insight into the mechanisms that play a critical role in cervical cancer, as well as novel ideas regarding gene therapeutic strategies.

In-silico identification and comparison of transcription factor binding sites cluster in anterior-posterior patterning genes in Drosophila melanogaster and Tribolium castaneum

The cis-regulatory data that help in transcriptional regulation is arranged into modular pieces of a few hundred base pairs called CRMs (cis-regulatory modules) and numerous binding sites for multiple transcription factors are prominent characteristics of these cis-regulatory modules. The present study was designed to localize transcription factor binding site (TFBS) clusters on twelve Anterior-posterior (A-P) genes in Tribolium castaneum and compare them to their orthologous gene enhancers in Drosophila melanogaster. Out of the twelve A-P patterning genes, six were gap genes (Kruppel, Knirps, Tailless, Hunchback, Giant, and Caudal) and six were pair rule genes (Hairy, Runt, Even-skipped, Fushi-tarazu, Paired, and Odd-skipped). The genes along with 20 kb upstream and downstream regions were scanned for TFBS clusters using the Motif Cluster Alignment Search Tool (MCAST), a bioinformatics tool that looks for set of nucleotide sequences for statistically significant clusters of non-overlapping occurrence of a given set of motifs. The motifs used in the current study were Hunchback, Caudal, Giant, Kruppel, Knirps, and Even-skipped. The results of the MCAST analysis revealed the maximum number of TFBS for Hunchback, Knirps, Caudal, and Kruppel in both D. melanogaster and T. castaneum, while Bicoid TFBS clusters were found only in D. melanogaster. The size of all the predicted TFBS clusters was less than 1kb in both insect species. These sequences revealed more transversional sites (Tv) than transitional sites (Ti) and the average Ti/Tv ratio was 0.75.

Mapinsights: deep exploration of quality issues and error profiles in high-throughput sequence data

High-throughput sequencing (HTS) has revolutionized science by enabling super-fast detection of genomic variants at base-pair resolution. Consequently, it poses the challenging problem of identification of technical artifacts, i.e. hidden non-random error patterns. Understanding the properties of sequencing artifacts holds the key in separating true variants from false positives. Here, we develop Mapinsights, a toolkit that performs quality control (QC) analysis of sequence alignment files, capable of detecting outliers based on sequencing artifacts of HTS data at a deeper resolution compared with existing methods. Mapinsights performs a cluster analysis based on novel and existing QC features derived from the sequence alignment for outlier detection. We applied Mapinsights on community standard open-source datasets and identified various quality issues including technical errors related to sequencing cycles, sequencing chemistry, sequencing libraries and across various orthogonal sequencing platforms. Mapinsights also enables identification of anomalies related to sequencing depth. A logistic regression-based model built on the features of Mapinsights shows high accuracy in detecting 'low-confidence' variant sites. Quantitative estimates and probabilistic arguments provided by Mapinsights can be utilized in identifying errors, bias and outlier samples, and also aid in improving the authenticity of variant calls.

Impaired Reorganization of Centrosome Structure Underlies Human Infantile Dilated Cardiomyopathy

BACKGROUND

During cardiomyocyte maturation, the centrosome, which functions as a microtubule organizing center in cardiomyocytes, undergoes dramatic structural reorganization where its components reorganize from being localized at the centriole to the nuclear envelope. This developmentally programmed process, referred to as centrosome reduction, has been previously associated with cell cycle exit. However, understanding of how this process influences cardiomyocyte cell biology, and whether its disruption results in human cardiac disease, remains unknown. We studied this phenomenon in an infant with a rare case of infantile dilated cardiomyopathy (iDCM) who presented with left ventricular ejection fraction of 18% and disrupted sarcomere and mitochondria structure.

METHODS

We performed an analysis beginning with an infant who presented with a rare case of iDCM. We derived induced pluripotent stem cells from the patient to model iDCM in vitro. We performed whole exome sequencing on the patient and his parents for causal gene analysis. CRISPR/Cas9-mediated gene knockout and correction in vitro were used to confirm whole exome sequencing results. Zebrafish and Drosophila models were used for in vivo validation of the causal gene. Matrigel mattress technology and single-cell RNA sequencing were used to characterize iDCM cardiomyocytes further.

RESULTS

Whole exome sequencing and CRISPR/Cas9 gene knockout/correction identified RTTN, the gene encoding the centrosomal protein RTTN (rotatin), as the causal gene underlying the patient's condition, representing the first time a centrosome defect has been implicated in a nonsyndromic dilated cardiomyopathy. Genetic knockdowns in zebrafish and Drosophila confirmed an evolutionarily conserved requirement of RTTN for cardiac structure and function. Single-cell RNA sequencing of iDCM cardiomyocytes showed impaired maturation of iDCM cardiomyocytes, which underlie the observed cardiomyocyte structural and functional deficits. We also observed persistent localization of the centrosome at the centriole, contrasting with expected programmed perinuclear reorganization, which led to subsequent global microtubule network defects. In addition, we identified a small molecule that restored centrosome reorganization and improved the structure and contractility of iDCM cardiomyocytes.

CONCLUSIONS

This study is the first to demonstrate a case of human disease caused by a defect in centrosome reduction. We also uncovered a novel role for RTTN in perinatal cardiac development and identified a potential therapeutic strategy for centrosome-related iDCM. Future study aimed at identifying variants in centrosome components may uncover additional contributors to human cardiac disease.

Genomic resources for population analyses of an invasive insect pest Oryctes rhinoceros

Over the last few years, various types of NGS data have been accumulating for the coconut rhinoceros beetle (CRB, Oryctes rhinoceros), reflecting the growing interest in curtailing this invasive pest of palm trees. Whilst reference-free analyses of RNA-seq and RAD-seq datasets have been done for different CRB collections, recent availability of the CRB's genome assembly provides an opportunity to collate diverse data and create a reference-based population dataset. Here, I release such a dataset containing 6,725,935 SNPs and genotypes called across 393 individual samples from 16 populations, using the previously published raw sequences generated in 9 different experiments (RAD-Seq, RNA-Seq, WGS). I also provide reference-based datasets for the CRB's mitochondrial variants and for variants of its viral biocontrol agent Oryctes rhinoceros nudivirus. SNP data provide high resolution for determining the geographic origin of invasive CRB. With these genomic resources, new data can be analysed without re-processing the published samples and then integrated to expand the reference datasets.

Performance comparisons between clustering models for reconstructing NGS results from technical replicates

To improve the performance of individual DNA sequencing results, researchers often use replicates from the same individual and various statistical clustering models to reconstruct a high-performance callset. Here, three technical replicates of genome NA12878 were considered and five model types were compared (consensus, latent class, Gaussian mixture, Kamila–adapted k-means, and random forest) regarding four performance indicators: sensitivity, precision, accuracy, and F1-score. In comparison with no use of a combination model, i) the consensus model improved precision by 0.1%; ii) the latent class model brought 1% precision improvement (97%–98%) without compromising sensitivity (= 98.9%); iii) the Gaussian mixture model and random forest provided callsets with higher precisions (both &gt;99%) but lower sensitivities; iv) Kamila increased precision (&gt;99%) and kept a high sensitivity (98.8%); it showed the best overall performance. According to precision and F1-score indicators, the compared non-supervised clustering models that combine multiple callsets are able to improve sequencing performance vs. previously used supervised models. Among the models compared, the Gaussian mixture model and Kamila offered non-negligible precision and F1-score improvements. These models may be thus recommended for callset reconstruction (from either biological or technical replicates) for diagnostic or precision medicine purposes.

Genetic diversity and within-breed variation in three indigenous Ethiopian sheep based on whole-genome analysis

The objective of this work was to study genetic diversity by comparing whole genome sequence data of Rutana, Gumuz and Washera sheep found in Amhara and Benishanguel gumuz regional states of Ethiopia. We employed variant calling format tools version 0.1.15 to calculate some genetic diversity indices such as observed heterozygosity, expected heterozygosity, inbreeding coefficient, and nucleotide diversity. The results revealed that, observed heterozygosity ranged from 0.33 in Gumuz to 0.34 in Rutana and Washera sheep. Expected heterozygosity ranged from 0.37 in Rutana to 0.38 in Gumuz and Washera sheep. Expected heterozygosity was found to be higher than observed heterozygosity. Higher inbreeding coefficient (0.12) was recorded for Gumuz sheep compared to 0.09 of Rutana and Washera sheep. Mean nucleotide diversity values were 0.0029, 0.0030 and 0.0028 for Gumuz, Rutana and Washera sheep, respectively. Higher values of nucleotide diversity were recorded. Population structure analysis using principal component analysis revealed no clear separation between Gumuz, Rutana and Washera sheep populations with possibility of gene flow attributed to geographical location proximity. The smaller population size, closed breeding system, genetic drift and uncontrolled (non-random) mating might lead to higher rate of inbreeding in Gumuz, Rutana and Washera sheep, requiring timely intervention. This intervention helps to prevent inbreeding depression and extinction of these valuable breeds of sheep, which helps in sustaining the livelihood of sheep keepers in lowlands and highlands. Nevertheless, the whole-genome analysis revealed high within-breed variation. Uncovered areas of studies like mapping quantitative trait loci, identifying genes underpinning productivity traits such as carcass quantity and meat quality could be carried out on diversified sheep resources identified by the current study. Identifying the genomic regions and biological pathways that contribute to explaining variability in these traits is of great importance for selection purposes. Designing conservation-based within-breed sheep selective breeding programs are recommended considering economically important traits into account.

Heterosubtypic immune pressure accelerates emergence of influenza A virus escape phenotypes in mice

Rapid antigenic evolution of the influenza A virus surface antigen hemagglutinin undermines protection conferred by seasonal vaccines. Protective correlates targeted by universal vaccines such as cytotoxic T cells or HA stem directed broadly neutralizing antibodies have been shown to select for immune escape mutants during infection. We developed an in vivo serial passage mouse model for viral adaptation and used next generation sequencing to evaluate full genome viral evolution in the context of broadly protective immunity. Heterosubtypic immune pressure increased the incidence of genome-wide single nucleotide variants, though mutations found in early adapted populations were predominantly stochastic in nature. Prolonged adaptation under heterosubtypic immune selection resulted in the manifestation of highly virulent phenotypes that ablated vaccine mediated protection from mortality. High frequency mutations unique to escape phenotypes were identified within the polymerase encoding segments. These findings suggest that a suboptimial usage of population-wide universal influenza vaccine may drive formation of escape variants attributed to polygenic changes.

Challenges Related to the Use of Next-Generation Sequencing for the Optimization of Drug Therapy

Over the last decade, next-generation sequencing (NGS) methods have become increasingly used in various areas of human genomics. In routine clinical care, their use is already implemented in oncology to profile the mutational landscape of a tumor, as well as in rare disease diagnostics. However, its utilization in pharmacogenomics is largely lacking behind. Recent population-scale genome data has revealed that human pharmacogenes carry a plethora of rare genetic variations that are not interrogated by conventional array-based profiling methods and it is estimated that these variants could explain around 30% of the genetically encoded functional pharmacogenetic variability.To interpret the impact of such variants on drug response a multitude of computational tools have been developed, but, while there have been major advancements, it remains to be shown whether their accuracy is sufficient to improve personalized pharmacogenetic recommendations in robust trials. In addition, conventional short-read sequencing methods face difficulties in the interrogation of complex pharmacogenes and high NGS test costs require stringent evaluations of cost-effectiveness to decide about reimbursement by national healthcare programs. Here, we illustrate current challenges and discuss future directions toward the clinical implementation of NGS to inform genotype-guided decision-making.

Polymorphism of prolactin (PRL) gene exon 5 and its association with egg production in IPB-D1 chickens

The prolactin (PRL) gene regulates the egg production and incubation in laying chickens. Local chickens' reproductive systems will disrupt as a result of the incubation period activity, and they will lay fewer eggs. This study aimed to determine the prolactin gene polymorphism in IPB-D1 hens and its relationship to egg production. The polymorphism of the exon 5 prolactin gene was examined on 112 samples of the IPB-D1 chicken DNA collection from the Division of Animal Genetics and Breeding, Faculty of Animal Sciences, IPB University. By performing the phenol-chloroform method, the genomic DNA was obtained. A polymerase chain reaction (PCR) product with a size of 557 bp was produced as a result of the DNA amplification. Three single-nucleotide sequences were discovered. Three single-nucleotide polymorphisms (SNPs), g.7835A  >  G, g.7886A  >  T, and g.8052T  >  C, were found in exon 5 of the PRL gene. Each mutation was polymorphic and in Hardy-Weinberg equilibrium. The point mutation g.8052T  >  C significantly impacted the egg production of IPB-D1 chickens, according to the SNP association analysis on egg production, and may serve as a marker to enhance the selection for the features of egg production in IPB-D1 chickens.

Genetic structure and historic demography of endangered unarmoured threespine stickleback at southern latitudes signals a potential new management approach

Habitat loss, flood control infrastructure, and drought have left most of southern California and northern Baja California's native freshwater fish near extinction, including the endangered unarmoured threespine stickleback (Gasterosteus aculeatus williamsoni). This subspecies, an unusual morph lacking the typical lateral bony plates of the G. aculeatus complex, occurs at arid southern latitudes in the eastern Pacific Ocean and survives in only three inland locations. Managers have lacked molecular data to answer basic questions about the ancestry and genetic distinctiveness of unarmoured populations. These data could be used to prioritize conservation efforts. We sampled G. aculeatus from 36 localities and used microsatellites and whole genome data to place unarmoured populations within the broader evolutionary context of G. aculeatus across southern California/northern Baja California. We identified three genetic groups with none consisting solely of unarmoured populations. Unlike G. aculeatus at northern latitudes, where Pleistocene glaciation has produced similar historical demographic profiles across populations, we found markedly different demographics depending on sampling location, with inland unarmoured populations showing steeper population declines and lower heterozygosity compared to low armoured populations in coastal lagoons. One exception involved the only high elevation population in the region, where the demography and alleles of unarmoured fish were similar to low armoured populations near the coast, exposing one of several cases of artificial translocation. Our results suggest that the current "management-by-phenotype" approach, based on lateral plates, is incidentally protecting the most imperilled populations; however, redirecting efforts toward evolutionary units, regardless of phenotype, may more effectively preserve adaptive potential.

Merfin: improved variant filtering, assembly evaluation and polishing via k-mer validation

Variant calling has been widely used for genotyping and for improving the consensus accuracy of long-read assemblies. Variant calls are commonly hard-filtered with user-defined cutoffs. However, it is impossible to define a single set of optimal cutoffs, as the calls heavily depend on the quality of the reads, the variant caller of choice and the quality of the unpolished assembly. Here, we introduce Merfin, a k-mer based variant-filtering algorithm for improved accuracy in genotyping and genome assembly polishing. Merfin evaluates each variant based on the expected k-mer multiplicity in the reads, independently of the quality of the read alignment and variant caller's internal score. Merfin increased the precision of genotyped calls in several benchmarks, improved consensus accuracy and reduced frameshift errors when applied to human and nonhuman assemblies built from Pacific Biosciences HiFi and continuous long reads or Oxford Nanopore reads, including the first complete human genome. Moreover, we introduce assembly quality and completeness metrics that account for the expected genomic copy numbers.

Pangenome-based genome inference allows efficient and accurate genotyping across a wide spectrum of variant classes

Typical genotyping workflows map reads to a reference genome before identifying genetic variants. Generating such alignments introduces reference biases and comes with substantial computational burden. Furthermore, short-read lengths limit the ability to characterize repetitive genomic regions, which are particularly challenging for fast k-mer-based genotypers. In the present study, we propose a new algorithm, PanGenie, that leverages a haplotype-resolved pangenome reference together with k-mer counts from short-read sequencing data to genotype a wide spectrum of genetic variation-a process we refer to as genome inference. Compared with mapping-based approaches, PanGenie is more than 4 times faster at 30-fold coverage and achieves better genotype concordances for almost all variant types and coverages tested. Improvements are especially pronounced for large insertions (≥50 bp) and variants in repetitive regions, enabling the inclusion of these classes of variants in genome-wide association studies. PanGenie efficiently leverages the increasing amount of haplotype-resolved assemblies to unravel the functional impact of previously inaccessible variants while being faster compared with alignment-based workflows.

Clinical exome sequencing - mistakes and caveats

Massive parallel sequencing technology has become the predominant technique for genetic diagnostics and research. Many genetic laboratories have wrestled with the challenges of setting up genetic testing workflows based on a completely new technology. The learning curve we went through as a laboratory was accompanied by growing pains while we gained new knowledge and expertise. Here we discuss some important mistakes that have been made in our laboratory through 10 years of clinical exome sequencing but that have given us important new insights on how to adapt our working methods. We provide these examples and the lessons that we learned to help other laboratories avoid to make the same mistakes.

GTQC: Automated Genotyping Array Quality Control and Report

Genotyping array is the most economical approach for conducting large-scale genome-wide genetic association studies. Thorough quality control is key to generating high integrity genotyping data and robust results. Quality control of genotyping array is generally a complicated process, as it requires intensive manual labor in implementing the established protocols and curating a comprehensive quality report. There is an urgent need to reduce manual intervention via an automated quality control process. Based on previously established protocols and strategies, we developed an R package GTQC (GenoTyping Quality Control) to automate a majority of the quality control steps for general array genotyping data. GTQC covers a comprehensive spectrum of genotype data quality metrics and produces a detailed HTML report comprising tables and figures. Here, we describe the concepts underpinning GTQC and demonstrate its effectiveness using a real genotyping dataset. R package GTQC streamlines a majority of the quality control steps and produces a detailed HTML report on a plethora of quality control metrics, thus enabling a swift and rigorous data quality inspection prior to downstream GWAS and related analyses. By significantly cutting down on the time on genotyping quality control procedures, GTQC ensures maximum utilization of available resources and minimizes waste and inefficient allocation of manual efforts. GTQC tool can be accessed at https://github.com/slzhao/GTQC.

Haplotype distribution in a forensic full mtDNA genome database of admixed Southern Brazilians and its association with self-declared ancestry and pigmentation traits

BACKGROUND

The advent of massively parallel sequencing (MPS) applications focused on the generation of forensic-quality full mitochondrial genome sequences led to a popularization of the technique on a global scale. However, the lack of forensic-graded population databases has refrained a wider adoption of full genome sequences as the industry standard, despite its better discrimination capacity of individual maternal lineages.

PURPOSE

This work describes a forensic-oriented full mtDNA genome database comprised of 480 samples from a Southern Brazilian population.

METHODS

A collection of mitochondrial sequences were obtained from low-pass, full genome DNA sequencing results. The complete sample set was evaluated regarding haplotype composition and distribution. Summary statistics and forensic parameters were calculated and are presented for the database, with detailed information concerning the impact of removing genetic information in the form of specific variants or increasingly larger genomic regions. Interpopulational analysis comparing haplotypical diversity in Brazilian and 26 worldwide populations was also performed. The association between mitochondrial genetic variability and phenotypic diversity was also evaluated in populations, with self-declared ancestry and three distinct phenotypic pigmentation traits (eyes, skin and hair colors) as parameters.

RESULTS

The presented database can be used to evaluate mitochondrial-related genetic evidence, providing LR values of up to 20,465 for unobserved haplotypes. Haplotype distribution in Southern Brazil seems to be different than the remaining of the country, with a larger contribution of maternal lines with European origin. Despite association can be found between lighter and darker phenotypes or self-declared ancestry and haplotype distribution, prediction models cannot be reliably proposed due to the admixed nature of the Brazilian population.

CONCLUSIONS

The proposed database provides a basis for statistical calculation and frequency estimation of full mitochondrial genomes, and can be part of an integrated, representative, national database comprising most of the genetic diversity of maternal lineages in the country.

The pink salmon genome: Uncovering the genomic consequences of a two-year life cycle

Pink salmon (Oncorhynchus gorbuscha) adults are the smallest of the five Pacific salmon native to the western Pacific Ocean. Pink salmon are also the most abundant of these species and account for a large proportion of the commercial value of the salmon fishery worldwide. A two-year life history of pink salmon generates temporally isolated populations that spawn either in even-years or odd-years. To uncover the influence of this genetic isolation, reference genome assemblies were generated for each year-class and whole genome re-sequencing data was collected from salmon of both year-classes. The salmon were sampled from six Canadian rivers and one Japanese river. At multiple centromeres we identified peaks of Fst between year-classes that were millions of base-pairs long. The largest Fst peak was also associated with a million base-pair chromosomal polymorphism found in the odd-year genome near a centromere. These Fst peaks may be the result of a centromere drive or a combination of reduced recombination and genetic drift, and they could influence speciation. Other regions of the genome influenced by odd-year and even-year temporal isolation and tentatively under selection were mostly associated with genes related to immune function, organ development/maintenance, and behaviour.

Genetic Variation and the Distribution of Variant Types in the Horse

Genetic variation is a key contributor to health and disease. Understanding the link between an individual's genotype and the corresponding phenotype is a major goal of medical genetics. Whole genome sequencing (WGS) within and across populations enables highly efficient variant discovery and elucidation of the molecular nature of virtually all genetic variation. Here, we report the largest catalog of genetic variation for the horse, a species of importance as a model for human athletic and performance related traits, using WGS of 534 horses. We show the extent of agreement between two commonly used variant callers. In data from ten target breeds that represent major breed clusters in the domestic horse, we demonstrate the distribution of variants, their allele frequencies across breeds, and identify variants that are unique to a single breed. We investigate variants with no homozygotes that may be potential embryonic lethal variants, as well as variants present in all individuals that likely represent regions of the genome with errors, poor annotation or where the reference genome carries a variant. Finally, we show regions of the genome that have higher or lower levels of genetic variation compared to the genome average. This catalog can be used for variant prioritization for important equine diseases and traits, and to provide key information about regions of the genome where the assembly and/or annotation need to be improved.

MhcVizPipe: A Quality Control Software for Rapid Assessment of Small- to Large-Scale Immunopeptidome Data Sets

Mass spectrometry (MS)-based immunopeptidomics is maturing into an automatized, high-throughput technology, producing small- to large-scale datasets of clinically relevant MHC class I- and II-associated peptides. Consequently, the development of quality control (QC) and quality assurance (QA) systems capable of detecting sample and/or measurement issues is important for instrument operators and scientists in charge of downstream data interpretation. Here, we created MhcVizPipe (MVP), a semi-automated QC software tool that enables rapid and simultaneous assessment of multiple MHC class I and II immunopeptidomic datasets generated by MS, including datasets generated from large sample cohorts. In essence, MVP provides a rapid and consolidated view of sample quality, composition and MHC-specificity to greatly accelerate the 'pass-fail' QC decision-making process toward data interpretation. MVP parallelizes the use of well-established immunopeptidomic algorithms (NetMHCpan, NetMHCIIpan and GibbsCluster) and rapidly generates organized and easy-to-understand reports in HTML format. The reports are fully portable and can be viewed on any computer with a modern web browser. MVP is intuitive to use and will find utility in any specialized immunopeptidomic laboratory and proteomics core facility that provides immunopeptidomic services to the community.

Detecting SARS-CoV-2 and its variant strains with a full genome tiling array

Coronavirus disease 2019 pandemic is the most damaging pandemic in recent human history. Rapid detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and variant strains is paramount for recovery from this pandemic. Conventional SARS-CoV-2 tests interrogate only limited regions of the whole SARS-CoV-2 genome, which are subjected to low specificity and miss the opportunity of detecting variant strains. In this work, we developed the first SARS-CoV-2 tiling array that captures the entire SARS-CoV-2 genome at single nucleotide resolution and offers the opportunity to detect point mutations. A thorough bioinformatics protocol of two base calling methods has been developed to accompany this array. To demonstrate the effectiveness of the tiling array, we genotyped all genomic positions of eight SARS-CoV-2 samples. Using high-throughput sequencing as the benchmark, we show that the tiling array had a genome-wide accuracy of at least 99.5%. From the tiling array analysis results, we identified the D614G mutation in the spike protein in four of the eight samples, suggesting the widespread distribution of this variant at the early stage of the outbreak in the United States. Two additional nonsynonymous mutations were identified in one sample in the nucleocapsid protein (P13L and S197L), which may complicate future vaccine development. With around $5 per array, supreme accuracy, and an ultrafast bioinformatics protocol, the SARS-CoV-2 tiling array makes an invaluable toolkit for combating current and future pandemics. Our SARS-CoV-2 tilting array is currently utilized by Molecular Vision, a CLIA-certified lab for SARS-CoV-2 diagnosis.

Statistical guidelines for quality control of next-generation sequencing techniques

More and more next-generation sequencing (NGS) data are made available every day. However, the quality of this data is not always guaranteed. Available quality control tools require profound knowledge to correctly interpret the multiplicity of quality features. Moreover, it is usually difficult to know if quality features are relevant in all experimental conditions. Therefore, the NGS community would highly benefit from condition-specific data-driven guidelines derived from many publicly available experiments, which reflect routinely generated NGS data. In this work, we have characterized well-known quality guidelines and related features in big datasets and concluded that they are too limited for assessing the quality of a given NGS file accurately. Therefore, we present new data-driven guidelines derived from the statistical analysis of many public datasets using quality features calculated by common bioinformatics tools. Thanks to this approach, we confirm the high relevance of genome mapping statistics to assess the quality of the data, and we demonstrate the limited scope of some quality features that are not relevant in all conditions. Our guidelines are available at https://cbdm.uni-mainz.de/ngs-guidelines.

Possible Protective Effect of LOXL1 Variant in the Cohort of Chernobyl Catastrophe Clean-Up Workers

Ionising radiation (IR) is an environmental factor known to alter genomes and therefore challenge organisms to adapt. Lithuanian clean-up workers of the Chernobyl nuclear disaster (LCWC) experienced high doses of IR, leading to different consequences. This study aims to characterise a unique protective genomic variation in a relatively healthy LCWC group. This variation influenced their individual reaction to IR and potentially protects against certain diseases such as exfoliation syndrome and glaucoma. Clinical and IR dosage data were collected using a questionnaire to characterise the cohort of 93 LCWC. Genome-wide genotyping using Illumina beadchip technology was performed. The control group included 466 unrelated, self-reported healthy individuals of Lithuanian descent. Genotypes were filtered out from the microarray dataset using a catalogue of SNPs. The data were used to perform association, linkage disequilibrium, and epistasis analysis. Phenotype data analysis showed the distribution of the most common disease groups among the LCWC. A genomic variant of statistical significance (Fishers' exact test, p = 0.019), rs3825942, was identified in LOXL1 (NM_005576.4:c.458G>A). Linkage disequilibrium and epistasis analysis for this variant identified the genes LHFPL3, GALNT6, PIH1D1, ANKS1B, and METRNL as potentially involved in the etiopathogenesis of exfoliation syndrome and glaucoma, which were not previously associated with the disease. The LOXL1 variant is mostly considered a risk factor in the development of exfoliation syndrome and glaucoma. The influence of recent positive selection, the phenomenon of allele-flipping, and the fact that only individuals with the homozygous reference allele have glaucoma in the cohort of the LCWC suggest otherwise. The identification of rs3825942 and other potentially protective genomic variants may be useful for further analysis of the genetic architecture and etiopathogenetic mechanisms of other multifactorial diseases.

Targeted resequencing showing novel common and rare genetic variants increases the risk of asthma in the Chinese Han population

BACKGROUND

Although studies have identified hundreds of genetic variants associated with asthma risk, a large fraction of heritability remains unexplained, especially in Chinese individuals.

METHODS

To identify genetic risk factors for asthma in a Han Chinese population, 211 asthma-related genes were first selected based on database searches. The genes were then sequenced for subjects in a Discovery Cohort (284 asthma patients and 205 older healthy controls) using targeted next-generation sequencing. Bioinformatics analysis and statistical association analyses were performed to reveal the associations between rare/common variants and asthma, respectively. The identified common risk variants underwent a validation analysis using a Replication Cohort (664 patients and 650 controls).

RESULTS

First, we identified 18 potentially functional rare loss-of-function (LOF) variants in 21/284 (7.4%) of the asthma cases. Second, using burden tests, we found that the asthma group had nominally significant (p < 0.05) burdens of rare nonsynonymous variants in 10 genes. Third, 23 common single-nucleotide polymorphisms were associated with the risk of asthma, 7/23 (30.4%) and 9/23 (39.1%) of which were modestly significant (p < 9.1 × 10^-4 ) in the Replication Cohort and Combined Cohort, respectively. According to our cumulative risk model involving the modestly associated alleles, middle- and high-risk subjects had a 2.0-fold (95% CI: 1.621-2.423, p = 2.624 × 10^-11 ) and 6.0-fold (95% CI: 3.623-10.156, p = 7.086 × 10^-12 ) increased risk of asthma, respectively, compared with low-risk subjects.

CONCLUSION

This study revealed novel rare and common genetic risk factors for asthma, and provided a cumulative risk model for asthma risk prediction and stratification in Han Chinese individuals.

A rapid competitive method for bacteriophage genomic DNA extraction

The bacteriophage (phage) DNA extraction methods for genomics analysis is a critical and time-consuming process. Hence, a rapid and cost-effective method for DNA extraction of phages is favorable for phage biologists. In the present study, a cost-effective, simple and rapid procedure for phage genome extraction in less than 10 min is introduced. Highly concentrated phage lysates were prepared using acetone precipitation followed by extraction using various methods such as commercial kits, TES lysis buffer, potassium iodide, and sodium iodide. The quality of the extracted DNA was analyzed by agarose gel electrophoresis and UV absorbance of DNA at 260 and 280 nm. Finally, the extracted DNA was subjected to restriction digestion and next-generation sequencing to approve the efficiency of the method. Based on the time, cost, and quality of obtained DNA, the acetone precipitation of phages and extraction by potassium iodide or sodium iodide method was determined to be the best method for phage DNA extraction tested in this study. Moreover, the extracted genomic DNA using this method is suitable for phage genomic analysis such as restriction enzyme studies, preparation of DNA library, and also next-generation sequencing.

Next-generation sequencing for the diagnosis of hepatitis B: current status and future prospects

INTRODUCTION

Hepatitis B virus (HBV) causes a complex and persistent infection with a major impact on patients health. Viral-genome sequencing can provide valuable information for characterizing virus genotype, infection dynamics and drug and vaccine resistance.

AREAS COVERED

This article reviews the current literature to describe the next-generation sequencing progress that facilitated a more comprehensive study of HBV quasispecies in diagnosis and clinical monitoring.

EXPERT OPINION

HBV variability plays a key role in liver disease progression and treatment efficacy. Second-generation sequencing improved the sensitivity for detecting and quantifying mutations, mixed genotypes and viral recombination. Third-generation sequencing enables the analysis of the entire HBV genome, although the high error rate limits its use in clinical practice.

A streamlined solution for processing, elucidating and quality control of cyclobutane pyrimidine dimer sequencing data

UV radiation may lead to melanoma and nonmelanoma skin cancers by causing helix-distorting DNA damage such as cyclobutane pyrimidine dimers (CPDs). These DNA lesions, if located in important genes and not repaired promptly, are mutagenic and may eventually result in carcinogenesis. Examining CPD formation and repair processes across the genome can shed light on the mutagenesis mechanisms associated with UV damage in relevant cancers. We recently developed CPD-Seq, a high-throughput and single-nucleotide resolution sequencing technique that can specifically capture UV-induced CPD lesions across the genome. This novel technique has been increasingly used in studies of UV damage and can be adapted to sequence other clinically relevant DNA lesions. Although the library preparation protocol has been established, a systematic protocol to analyze CPD-Seq data has not been described yet. To streamline the various general or specific analysis steps, we developed a protocol named CPDSeqer to assist researchers with CPD-Seq data processing. CPDSeqer can accommodate both a single- and multiple-sample experimental design, and it allows both genome-wide analyses and regional scrutiny (such as of suspected UV damage hotspots). The runtime of CPDSeqer scales with raw data size and takes roughly 4 h per sample with the possibility of acceleration by parallel computing. Various guiding graphics are generated to help diagnose the performance of the experiment and inform regional enrichment of CPD formation. UV damage comparison analyses are set forth in three analysis scenarios, and the resulting HTML pages report damage directional trends and statistical significance. CPDSeqer can be accessed at https://github.com/shengqh/cpdseqer .

Whole-genome sequencing data of Kazakh individuals

Objectives

Kazakhstan is a Central Asian crossroad of European and Asian populations situated along the way of the Great Silk Way. The territory of Kazakhstan has historically been inhabited by nomadic tribes and today is the multi-ethnic country with the dominant Kazakh ethnic group. We sequenced and analyzed the whole-genomes of five ethnic healthy Kazakh individuals with high coverage using next-generation sequencing platform. This whole-genome sequence data of healthy Kazakh individuals can be a valuable reference for biomedical studies investigating disease associations and population-wide genomic studies of ethnically diverse Central Asian region.

Data description

Blood samples have been collected from five ethnic healthy Kazakh individuals living in Kazakhstan. The genomic DNA was extracted from blood and sequenced. Sequencing was performed on Illumina HiSeq2000 next-generation sequencing platform. We sequenced and analyzed the whole-genomes of ethnic Kazakh individuals with the coverage ranging from 26 to 32X. Ranging from 98.85 to 99.58% base pairs were totally mapped and aligned on the human reference genome GRCh37 hg19. Het/Hom and Ts/Tv ratios for each whole genome ranged from 1.35 to 1.49 and from 2.07 to 2.08, respectively. Sequencing data are available in the National Center for Biotechnology Information SRA database under the accession number PRJNA374772.

Global Autozygosity Is Associated with Cancer Risk, Mutational Signature and Prognosis

Simple Summary

Global autozygosity in the form of runs of homozygosity is associated with various diseases. Heterozygosity ratio, an alternative measure of global autozygosity, is used to assess cancer risk in this study. Our analysis shows strong and consistent associations between heterozygosity ratios and various cancer types. Further analysis reveals the heterozygosity ratio’s potential connections to mutational signatures and cancer prognosis.

Abstract

Global autozygosity quantifies the genome-wide levels of homozygous and heterozygous variants. It is the signature of non-random reproduction, though it can also be driven by other factors, and has been used to assess risk in various diseases. However, the association between global autozygosity and cancer risk has not been studied. From 4057 cancer subjects and 1668 healthy controls, we found strong associations between global autozygosity and risk in ten different cancer types. For example, the heterozygosity ratio was found to be significantly associated with breast invasive carcinoma in Blacks and with male skin cutaneous melanoma in Caucasians. We also discovered eleven associations between global autozygosity and mutational signatures which can explain a portion of the etiology. Furthermore, four significant associations for heterozygosity ratio were revealed in disease-specific survival analyses. This study demonstrates that global autozygosity is effective for cancer risk assessment.

A new method for long-read sequencing of animal mitochondrial genomes: application to the identification of equine mitochondrial DNA variants

BACKGROUND

Mitochondrial DNA is remarkably polymorphic. This is why animal geneticists survey mitochondrial genomes variations for fundamental and applied purposes. We present here an approach to sequence whole mitochondrial genomes using nanopore long-read sequencing. Our method relies on the selective elimination of nuclear DNA using an exonuclease treatment and on the amplification of circular mitochondrial DNA using a multiple displacement amplification step.

RESULTS

We optimized each preparative step to obtain a 100 million-fold enrichment of horse mitochondrial DNA relative to nuclear DNA. We sequenced these amplified mitochondrial DNA using nanopore sequencing technology and obtained mitochondrial DNA reads that represented up to half of the sequencing output. The sequence reads were 2.3 kb of mean length and provided an even coverage of the mitochondrial genome. Long-reads spanning half or more of the whole mtDNA provided a coverage that varied between 118X and 488X. We evaluated SNPs identified using these long-reads by Sanger sequencing as ground truth and found a precision of 100.0%; a recall of 93.1% and a F1-score of 0.964 using the Twilight horse mtDNA reference. The choice of the mtDNA reference impacted variant calling efficiency with F1-scores varying between 0.947 and 0.964.

CONCLUSIONS

Our method to amplify mtDNA and to sequence it using the nanopore technology is usable for mitochondrial DNA variant analysis. With minor modifications, this approach could easily be applied to other large circular DNA molecules.

Alternative Applications of Genotyping Array Data Using Multivariant Methods

One of the forerunners that pioneered the revolution of high-throughput genomic technologies is the genotyping microarray technology, which can genotype millions of single-nucleotide variants simultaneously. Owing to apparent benefits, such as high speed, low cost, and high throughput, the genotyping array has gained lasting applications in genome-wide association studies (GWAS) and thus accumulated an enormous amount of data. Empowered by continuous manufactural upgrades and analytical innovation, unconventional applications of genotyping array data have emerged to address more diverse genetic problems, holding promise of boosting genetic research into human diseases through the re-mining of the rich accumulated data. Here, we review several unconventional genotyping array analysis techniques that have been built on the idea of large-scale multivariant analysis and provide empirical application examples. These unconventional outcomes of genotyping arrays include polygenic score, runs of homozygosity (ROH)/heterozygosity ratio, distant pedigree computation, and mitochondrial DNA (mtDNA) copy number inference.

The sockeye salmon genome, transcriptome, and analyses identifying population defining regions of the genome

Sockeye salmon (Oncorhynchus nerka) is a commercially and culturally important species to the people that live along the northern Pacific Ocean coast. There are two main sockeye salmon ecotypes—the ocean-going (anadromous) ecotype and the fresh-water ecotype known as kokanee. The goal of this study was to better understand the population structure of sockeye salmon and identify possible genomic differences among populations and between the two ecotypes. In pursuit of this goal, we generated the first reference sockeye salmon genome assembly and an RNA-seq transcriptome data set to better annotate features of the assembly. Resequenced whole-genomes of 140 sockeye salmon and kokanee were analyzed to understand population structure and identify genomic differences between ecotypes. Three distinct geographic and genetic groups were identified from analyses of the resequencing data. Nucleotide variants in an immunoglobulin heavy chain variable gene cluster on chromosome 26 were found to differentiate the northwestern group from the southern and upper Columbia River groups. Several candidate genes were found to be associated with the kokanee ecotype. Many of these genes were related to ammonia tolerance or vision. Finally, the sex chromosomes of this species were better characterized, and an alternative sex-determination mechanism was identified in a subset of upper Columbia River kokanee.

Raw transcriptomics data to gene specific SSRs: a validated free bioinformatics workflow for biologists

Recent advances in next-generation sequencing technologies have paved the path for a considerable amount of sequencing data at a relatively low cost. This has revolutionized the genomics and transcriptomics studies. However, different challenges are now created in handling such data with available bioinformatics platforms both in assembly and downstream analysis performed in order to infer correct biological meaning. Though there are a handful of commercial software and tools for some of the procedures, cost of such tools has made them prohibitive for most research laboratories. While individual open-source or free software tools are available for most of the bioinformatics applications, those components usually operate standalone and are not combined for a user-friendly workflow. Therefore, beginners in bioinformatics might find analysis procedures starting from raw sequence data too complicated and time-consuming with the associated learning-curve. Here, we outline a procedure for de novo transcriptome assembly and Simple Sequence Repeats (SSR) primer design solely based on tools that are available online for free use. For validation of the developed workflow, we used Illumina HiSeq reads of different tissue samples of Santalum album (sandalwood), generated from a previous transcriptomics project. A portion of the designed primers were tested in the lab with relevant samples and all of them successfully amplified the targeted regions. The presented bioinformatics workflow can accurately assemble quality transcriptomes and develop gene specific SSRs. Beginner biologists and researchers in bioinformatics can easily utilize this workflow for research purposes.

Development and Verification of an Economical Method of Custom Target Library Construction

Although technological advances have greatly reduced the cost of DNA sequencing, sample preparation time and reagent costs remain the limiting factors for many studies. Based on low-cost targeted amplification, we developed an economical method for custom target library construction based on DNA nanoball (DNB) technology and two-step polymerase chain reaction (PCR). Here, we refer to this method as the two-step PCR, which was compared to traditional multiplex PCR methods in three aspects, data quality, efficiency, and specificity to humans. The results confirmed that two-step PCR reduces to finishing 128 sequencing libraries in only 2 h 24 min 59 s of the total PCR time and at a data utilization rate of 0.44 at a cost of approximately $1.70 per sample for targeted sequencing via the two-step PCR. The replacement of traditional multiplex PCR methods with this strategy makes the sample preparation process before sequencing relatively more cost-effective and further reduces the cost of next-generation sequencing (NGS). This method may also be free from the interference of other species and the limitations of sample type and DNA content. These findings reveal possibilities for broad applications of this approach in forensic research.

Comprehensive fundamental somatic variant calling and quality management strategies for human cancer genomes

Next-generation sequencing (NGS) technology has revolutionised human cancer research, particularly via detection of genomic variants with its ultra-high-throughput sequencing and increasing affordability. However, the inundation of rich cancer genomics data has resulted in significant challenges in its exploration and translation into biological insights. One of the difficulties in cancer genome sequencing is software selection. Currently, multiple tools are widely used to process NGS data in four stages: raw sequence data pre-processing and quality control (QC), sequence alignment, variant calling and annotation and visualisation. However, the differences between these NGS tools, including their installation, merits, drawbacks and application, have not been fully appreciated. Therefore, a systematic review of the functionality and performance of NGS tools is required to provide cancer researchers with guidance on software and strategy selection. Another challenge is the multidimensional QC of sequencing data because QC can not only report varied sequence data characteristics but also reveal deviations in diverse features and is essential for a meaningful and successful study. However, monitoring of QC metrics in specific steps including alignment and variant calling is neglected in certain pipelines such as the 'Best Practices Workflows' in GATK. In this review, we investigated the most widely used software for the fundamental analysis and QC of cancer genome sequencing data and provided instructions for selecting the most appropriate software and pipelines to ensure precise and efficient conclusions. We further discussed the prospects and new research directions for cancer genomics.

High throughput sequencing of in vitro selections of mRNA-displayed peptides: data analysis and applications

In vitro selection using mRNA display is currently a widely used method to isolate functional peptides with desired properties. The analysis of high throughput sequencing (HTS) data from in vitro evolution experiments has proven to be a powerful technique but only recently has it been applied to mRNA display selections. In this Perspective, we introduce aspects of mRNA display and HTS that may be of interest to physical chemists. We highlight the potential of HTS to analyze in vitro selections of peptides and review recent advances in the application of HTS analysis to mRNA display experiments. We discuss some possible issues involved with HTS analysis and summarize some strategies to alleviate them. Finally, the potential for future impact of advancing HTS analysis on mRNA display experiments is discussed.

Exploring the Molecular Aetiology of Preeclampsia by Massive Parallel Sequencing of DNA

PURPOSE OF REVIEW

This manuscript aims to review (for the first time) studies describing NGS sequencing of preeclampsia (PE) women's DNA.

RECENT FINDINGS

Describing markers for the early detection of PE is an essential task because, although associated molecular dysfunction begins early on during pregnancy, the disease's clinical signs usually appear late in pregnancy. Although several biochemical biomarkers have been proposed, their use in clinical environments is still limited, thereby encouraging research into PE's genetic origin. Hundreds of genes involved in numerous implantation- and placentation-related biological processes may be coherent candidates for PE aetiology. Next-generation sequencing (NGS) offers new technical possibilities for PE studying, as it enables large genomic regions to be analysed at affordable cost. This technique has facilitated the description of genes contributing to the molecular origin of a significant amount of monogenic and complex diseases. Regarding PE, NGS of DNA has been used in familial and isolated cases, thereby enabling new genes potentially related to the phenotype to be proposed. For a better understanding of NGS, technical aspects, applications and limitations are presented initially. Thereafter, NGS studies of DNA in familial and non-familial cases are described, including pitfalls and positive findings. The information given here should enable scientists and clinicians to analyse and design new studies permitting the identification of novel clinically useful molecular PE markers.

Bioinformatics Workflows With NoSQL Database in Cloud Computing

Scientific workflows can be understood as arrangements of managed activities executed by different processing entities. It is a regular Bioinformatics approach applying workflows to solve problems in Molecular Biology, notably those related to sequence analyses. Due to the nature of the raw data and the in silico environment of Molecular Biology experiments, apart from the research subject, 2 practical and closely related problems have been studied: reproducibility and computational environment. When aiming to enhance the reproducibility of Bioinformatics experiments, various aspects should be considered. The reproducibility requirements comprise the data provenance, which enables the acquisition of knowledge about the trajectory of data over a defined workflow, the settings of the programs, and the entire computational environment. Cloud computing is a booming alternative that can provide this computational environment, hiding technical details, and delivering a more affordable, accessible, and configurable on-demand environment for researchers. Considering this specific scenario, we proposed a solution to improve the reproducibility of Bioinformatics workflows in a cloud computing environment using both Infrastructure as a Service (IaaS) and Not only SQL (NoSQL) database systems. To meet the goal, we have built 3 typical Bioinformatics workflows and ran them on 1 private and 2 public clouds, using different types of NoSQL database systems to persist the provenance data according to the Provenance Data Model (PROV-DM). We present here the results and a guide for the deployment of a cloud environment for Bioinformatics exploring the characteristics of various NoSQL database systems to persist provenance data.