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

Discovery of Functional SNPs via Genome-Wide Exploration of Malaysian Pigmented Rice Varieties

Recently, rice breeding program has shown increased interests on the pigmented rice varieties due to their benefits to human health. However, the genetic variation of pigmented rice varieties is still scarce and remains unexplored. Hence, we performed genome-wide SNP analysis from the genome resequencing of four Malaysian pigmented rice varieties, representing two black and two red rice varieties. The genome of four pigmented varieties was mapped against Nipponbare reference genome sequences, and 1.9 million SNPs were discovered. Of these, 622 SNPs with polymorphic sites were identified in 258 protein-coding genes related to metabolism, stress response, and transporter. Comparative analysis of 622 SNPs with polymorphic sites against six rice SNP datasets from the Ensembl Plants variation database was performed, and 70 SNPs were identified as novel SNPs. Analysis of SNPs in the flavonoid biosynthetic genes revealed 40 nonsynonymous SNPs, which has potential as molecular markers for rice seed colour identification. The highlighted SNPs in this study show effort in producing valuable genomic resources for application in the rice breeding program, towards the genetic improvement of new and improved pigmented rice varieties.

Empirical design of a variant quality control pipeline for whole genome sequencing data using replicate discordance

The success of next-generation sequencing depends on the accuracy of variant calls. Few objective protocols exist for QC following variant calling from whole genome sequencing (WGS) data. After applying QC filtering based on Genome Analysis Tool Kit (GATK) best practices, we used genotype discordance of eight samples that were sequenced twice each to evaluate the proportion of potentially inaccurate variant calls. We designed a QC pipeline involving hard filters to improve replicate genotype concordance, which indicates improved accuracy of genotype calls. Our pipeline analyzes the efficacy of each filtering step. We initially applied this strategy to well-characterized variants from the ClinVar database, and subsequently to the full WGS dataset. The genome-wide biallelic pipeline removed 82.11% of discordant and 14.89% of concordant genotypes, and improved the concordance rate from 98.53% to 99.69%. The variant-level read depth filter most improved the genome-wide biallelic concordance rate. We also adapted this pipeline for triallelic sites, given the increasing proportion of multiallelic sites as sample sizes increase. For triallelic sites containing only SNVs, the concordance rate improved from 97.68% to 99.80%. Our QC pipeline removes many potentially false positive calls that pass in GATK, and may inform future WGS studies prior to variant effect analysis.

Introducing the first whole genomes of nationals from the United Arab Emirates

Whole Genome Sequencing (WGS) provides an in depth description of genome variation. In the era of large-scale population genome projects, the assembly of ethnic-specific genomes combined with mapping human reference genomes of underrepresented populations has improved the understanding of human diversity and disease associations. In this study, for the first time, whole genome sequences of two nationals of the United Arab Emirates (UAE) at >27X coverage are reported. The two Emirati individuals were predominantly of Central/South Asian ancestry. An in-house customized pipeline using BWA, Picard followed by the GATK tools to map the raw data from whole genome sequences of both individuals was used. A total of 3,994,521 variants (3,350,574 Single Nucleotide Polymorphisms (SNPs) and 643,947 indels) were identified for the first individual, the UAE S001 sample. A similar number of variants, 4,031,580 (3,373,501 SNPs and 658,079 indels), were identified for UAE S002. Variants that are associated with diabetes, hypertension, increased cholesterol levels, and obesity were also identified in these individuals. These Whole Genome Sequences has provided a starting point for constructing a UAE reference panel which will lead to improvements in the delivery of precision medicine, quality of life for affected individuals and a reduction in healthcare costs. The information compiled will likely lead to the identification of target genes that could potentially lead to the development of novel therapeutic modalities.

Regulatory variants: from detection to predicting impact

Variants within non-coding genomic regions can greatly affect disease. In recent years, increasing focus has been given to these variants, and how they can alter regulatory elements, such as enhancers, transcription factor binding sites and DNA methylation regions. Such variants can be considered regulatory variants. Concurrently, much effort has been put into establishing international consortia to undertake large projects aimed at discovering regulatory elements in different tissues, cell lines and organisms, and probing the effects of genetic variants on regulation by measuring gene expression. Here, we describe methods and techniques for discovering disease-associated non-coding variants using sequencing technologies. We then explain the computational procedures that can be used for annotating these variants using the information from the aforementioned projects, and prediction of their putative effects, including potential pathogenicity, based on rule-based and machine learning approaches. We provide the details of techniques to validate these predictions, by mapping chromatin-chromatin and chromatin-protein interactions, and introduce Clustered Regularly Interspaced Short Palindromic Repeats-Associated Protein 9 (CRISPR-Cas9) technology, which has already been used in this field and is likely to have a big impact on its future evolution. We also give examples of regulatory variants associated with multiple complex diseases. This review is aimed at bioinformaticians interested in the characterization of regulatory variants, molecular biologists and geneticists interested in understanding more about the nature and potential role of such variants from a functional point of views, and clinicians who may wish to learn about variants in non-coding genomic regions associated with a given disease and find out what to do next to uncover how they impact on the underlying mechanisms.

Mutations in SURF1 are important genetic causes of Leigh syndrome in Slovak patients

OBJECTIVES

Leigh syndrome is a progressive early onset neurodegenerative disease typically presenting with psychomotor regression, signs of brainstem and/or basal ganglia disease, lactic acidosis, and characteristic magnetic resonance imaging findings. At molecular level, deficiency of respiratory complexes and/or pyruvate dehydrogenase complex is usually observed. Nuclear gene SURF1 encodes an assembly factor for cytochrome c-oxidase complex of the respiratory chain and autosomal recessive mutations in SURF1 are one of the most frequent causes of cytochrome c-oxidase-related Leigh syndrome cases. Here, we aimed to elucidate the genetic basis of Leigh syndrome in three Slovak families.

METHODS AND RESULTS

Three probands presenting with Leigh syndrome were selected for DNA analysis. The first proband, presenting with atypical LS onset without abnormal basal ganglia magnetic resonance imaging findings, was analyzed with whole exome sequencing. In the two remaining probands, SURF1 was screened by Sanger sequencing. Four different heterozygous mutations were identified in SURF1: c.312_321delinsAT:p.(Pro104Profs*1), c.588+1G>A, c.823_833+7del:p. (?) and c.845_846del:p.(Ser282Cysfs*9). All the mutations are predicted to have a loss-of-function effect.

CONCLUSIONS

We identified disease-causing mutations in all three probands, which points to the important role of SURF1 gene in etiology of Leigh syndrome in Slovakia. Our data showed that patients with atypical Leigh syndrome phenotype without lesions in basal ganglia may benefit from the whole exome sequencing method. In the case of probands presenting the typical phenotype, Sanger sequencing of the SURF1 gene seems to be an effective method of DNA analysis.

Using QC-Blind for Quality Control and Contamination Screening of Bacteria DNA Sequencing Data Without Reference Genome

Quality control for next generation sequencing (NGS) has become increasingly important with the ever increasing importance of sequencing data for omics studies. Tools have been developed for filtering possible contaminants from species with known reference genome. Unfortunately, reference genomes for all the species involved, including the contaminants, are required for these tools to work. This precludes many real-life samples that have no information about the complete genome of the target species, and are contaminated with unknown microbial species. In this work we proposed QC-Blind, a novel quality control pipeline for removing contaminants without any use of reference genomes. The pipeline merely requires the information about a few marker genes of the target species. The entire pipeline consists of unsupervised read assembly, contig binning, read clustering, and marker gene assignment. When evaluated on in silico, ab initio and in vivo datasets, QC-Blind proved effective in removing unknown contaminants with high specificity and accuracy, while preserving most of the genomic information of the target bacterial species. Therefore, QC-Blind could serve well in situations where limited information is available for both target and contamination species.

Quality control and integration of genotypes from two calling pipelines for whole genome sequence data in the Alzheimer's disease sequencing project

The Alzheimer's Disease Sequencing Project (ADSP) performed whole genome sequencing (WGS) of 584 subjects from 111 multiplex families at three sequencing centers. Genotype calling of single nucleotide variants (SNVs) and insertion-deletion variants (indels) was performed centrally using GATK-HaplotypeCaller and Atlas V2. The ADSP Quality Control (QC) Working Group applied QC protocols to project-level variant call format files (VCFs) from each pipeline, and developed and implemented a novel protocol, termed "consensus calling," to combine genotype calls from both pipelines into a single high-quality set. QC was applied to autosomal bi-allelic SNVs and indels, and included pipeline-recommended QC filters, variant-level QC, and sample-level QC. Low-quality variants or genotypes were excluded, and sample outliers were noted. Quality was assessed by examining Mendelian inconsistencies (MIs) among 67 parent-offspring pairs, and MIs were used to establish additional genotype-specific filters for GATK calls. After QC, 578 subjects remained. Pipeline-specific QC excluded ~12.0% of GATK and 14.5% of Atlas SNVs. Between pipelines, ~91% of SNV genotypes across all QCed variants were concordant; 4.23% and 4.56% of genotypes were exclusive to Atlas or GATK, respectively; the remaining ~0.01% of discordant genotypes were excluded. For indels, variant-level QC excluded ~36.8% of GATK and 35.3% of Atlas indels. Between pipelines, ~55.6% of indel genotypes were concordant; while 10.3% and 28.3% were exclusive to Atlas or GATK, respectively; and ~0.29% of discordant genotypes were. The final WGS consensus dataset contains 27,896,774 SNVs and 3,133,926 indels and is publicly available.

Targeted next generation sequencing as a tool for precision medicine

BACKGROUND

Targeted next-generation sequencing (NGS) enables rapid identification of common and rare genetic variation. The detection of variants contributing to therapeutic drug response or adverse effects is essential for implementation of individualized pharmacotherapy. Successful application of short-read based NGS to pharmacogenes with high sequence homology, nearby pseudogenes and complex structure has been previously shown despite anticipated technical challenges. However, little is known regarding the utility of such panels to detect copy number variation (CNV) in the highly polymorphic cytochrome P450 (CYP) 2D6 gene, or to identify the promoter (TA)₇ TAA repeat polymorphism UDP glucuronosyltransferase (UGT) 1A1*28. Here we developed and validated PGxSeq, a targeted exome panel for pharmacogenes pertinent to drug disposition and/or response.

METHODS

A panel of capture probes was generated to assess 422 kb of total coding region in 100 pharmacogenes. NGS was carried out in 235 subjects, and sequencing performance and accuracy of variant discovery validated in clinically relevant pharmacogenes. CYP2D6 CNV was determined using the bioinformatics tool CNV caller (VarSeq). Identified SNVs were assessed in terms of population allele frequency and predicted functional effects through in silico algorithms.

RESULTS

Adequate performance of the PGxSeq panel was demonstrated with a depth-of-coverage (DOC) ≥ 20× for at least 94% of the target sequence. We showed accurate detection of 39 clinically relevant gene variants compared to standard genotyping techniques (99.9% concordance), including CYP2D6 CNV and UGT1A1*28. Allele frequency of rare or novel variants and predicted function in 235 subjects mirrored findings from large genomic datasets. A large proportion of patients (78%, 183 out of 235) were identified as homozygous carriers of at least one variant necessitating altered pharmacotherapy.

CONCLUSIONS

PGxSeq can serve as a comprehensive, rapid, and reliable approach for the detection of common and novel SNVs in pharmacogenes benefiting the emerging field of precision medicine.

Novel EYA4 variant in Slovak family with late onset autosomal dominant hearing loss: a case report

Background

Progressive bilateral sensorineural deafness in postlingual period may be linked to many different etiologies including genetic factors. Identification of the exact deafness cause may, therefore, be quite challenging. Here we present a family with late-onset hearing loss as an autosomal dominant trait caused by a novel EYA4 mutation.

Case presentation

Forty-four years old female proband clinically investigated for progressive hearing loss and occasional dizziness with positive family history for deafness was subject to molecular-genetic testing. Patient’s DNA sample was analyzed by whole exome sequencing. We identified a novel missense variant c.804G > C located at the last base pair of exon 10 in EYA4. Candidate variant was confirmed by Sanger sequencing in the proband and her family members. In silico prediction tools and co-segregation analysis were used to indicate pathogenicity of the identified variant. To confirm our hypothesis, we performed minigene assay to demonstrate if the transcript of exon 10 in EYA4 is present. We provide evidence that this mutation in vitro compromises donor site functionality and causes exon 10 skipping and frameshift that most likely results in nonsense-mediated mRNA decay. The onset of moderate to severe hearing loss in the family ranged from 10 to 40 years. The normal cardiac phenotype was confirmed by ECG and echocardiography.

Conclusions

We identified a novel EYA4 mutation associated with adult-onset autosomal dominant sensorineural hearing loss. This report extends the knowledge of spectrum of EYA4 mutations and demonstrates the pathogenicity of a variant affecting specific position in the gene. A comprehensive review of known EYA4 mutations is also given and their impact on cardiac phenotype is discussed. Our findings highlight the importance of genetic testing and complex clinical assessment in patients with familial progressive hearing loss.

Accurate sequence variant genotyping in cattle using variation-aware genome graphs

BACKGROUND

Genotyping of sequence variants typically involves, as a first step, the alignment of sequencing reads to a linear reference genome. Because a linear reference genome represents only a small fraction of all the DNA sequence variation within a species, reference allele bias may occur at highly polymorphic or divergent regions of the genome. Graph-based methods facilitate the comparison of sequencing reads to a variation-aware genome graph, which incorporates a collection of non-redundant DNA sequences that segregate within a species. We compared the accuracy and sensitivity of graph-based sequence variant genotyping using the Graphtyper software to two widely-used methods, i.e., GATK and SAMtools, which rely on linear reference genomes using whole-genome sequencing data from 49 Original Braunvieh cattle.

RESULTS

We discovered 21,140,196, 20,262,913, and 20,668,459 polymorphic sites using GATK, Graphtyper, and SAMtools, respectively. Comparisons between sequence variant genotypes and microarray-derived genotypes showed that Graphtyper outperformed both GATK and SAMtools in terms of genotype concordance, non-reference sensitivity, and non-reference discrepancy. The sequence variant genotypes that were obtained using Graphtyper had the smallest number of Mendelian inconsistencies between sequence-derived single nucleotide polymorphisms and indels in nine sire-son pairs. Genotype phasing and imputation using the Beagle software improved the quality of the sequence variant genotypes for all the tools evaluated, particularly for animals that were sequenced at low coverage. Following imputation, the concordance between sequence- and microarray-derived genotypes was almost identical for the three methods evaluated, i.e., 99.32, 99.46, and 99.24% for GATK, Graphtyper, and SAMtools, respectively. Variant filtration based on commonly used criteria improved genotype concordance slightly but it also decreased sensitivity. Graphtyper required considerably more computing resources than SAMtools but less than GATK.

CONCLUSIONS

Sequence variant genotyping using Graphtyper is accurate, sensitive and computationally feasible in cattle. Graph-based methods enable sequence variant genotyping from variation-aware reference genomes that may incorporate cohort-specific sequence variants, which is not possible with the current implementation of state-of-the-art methods that rely on linear reference genomes.

Strategies for processing and quality control of Illumina genotyping arrays

Illumina genotyping arrays have powered thousands of large-scale genome-wide association studies over the past decade. Yet, because of the tremendous volume and complicated genetic assumptions of Illumina genotyping data, processing and quality control (QC) of these data remain a challenge. Thorough QC ensures the accurate identification of single-nucleotide polymorphisms and is required for the correct interpretation of genetic association results. By processing genotyping data on > 100 000 subjects from >10 major Illumina genotyping arrays, we have accumulated extensive experience in handling some of the most peculiar scenarios related to the processing and QC of Illumina genotyping data. Here, we describe strategies for processing Illumina genotyping data from the raw data to an analysis ready format, and we elaborate on the necessary QC procedures required at each processing step. High-quality Illumina genotyping data sets can be obtained by following our detailed QC strategies.

Single-nucleotide variants in human RNA: RNA editing and beyond

Through analysis of paired high-throughput DNA-Seq and RNA-Seq data, researchers quickly recognized that RNA-Seq can be used for more than just gene expression quantification. The alternative applications of RNA-Seq data are abundant, and we are particularly interested in its usefulness for detecting single-nucleotide variants, which arise from RNA editing, genomic variants and other RNA modifications. A stunning discovery made from RNA-Seq analyses is the unexpectedly high prevalence of RNA-editing events, many of which cannot be explained by known RNA-editing mechanisms. Over the past 6-7 years, substantial efforts have been made to maximize the potential of RNA-Seq data. In this review we describe the controversial history of mining RNA-editing events from RNA-Seq data and the corresponding development of methodologies to identify, predict, assess the quality of and catalog RNA-editing events as well as genomic variants.

Blacklisting variants common in private cohorts but not in public databases optimizes human exome analysis

Computational analyses of human patient exomes aim to filter out as many nonpathogenic genetic variants (NPVs) as possible, without removing the true disease-causing mutations. This involves comparing the patient's exome with public databases to remove reported variants inconsistent with disease prevalence, mode of inheritance, or clinical penetrance. However, variants frequent in a given exome cohort, but absent or rare in public databases, have also been reported and treated as NPVs, without rigorous exploration. We report the generation of a blacklist of variants frequent within an in-house cohort of 3,104 exomes. This blacklist did not remove known pathogenic mutations from the exomes of 129 patients and decreased the number of NPVs remaining in the 3,104 individual exomes by a median of 62%. We validated this approach by testing three other independent cohorts of 400, 902, and 3,869 exomes. The blacklist generated from any given cohort removed a substantial proportion of NPVs (11-65%). We analyzed the blacklisted variants computationally and experimentally. Most of the blacklisted variants corresponded to false signals generated by incomplete reference genome assembly, location in low-complexity regions, bioinformatic misprocessing, or limitations inherent to cohort-specific private alleles (e.g., due to sequencing kits, and genetic ancestries). Finally, we provide our precalculated blacklists, together with ReFiNE, a program for generating customized blacklists from any medium-sized or large in-house cohort of exome (or other next-generation sequencing) data via a user-friendly public web server. This work demonstrates the power of extracting variant blacklists from private databases as a specific in-house but broadly applicable tool for optimizing exome analysis.

SOAPnuke: a MapReduce acceleration-supported software for integrated quality control and preprocessing of high-throughput sequencing data

Quality control (QC) and preprocessing are essential steps for sequencing data analysis to ensure the accuracy of results. However, existing tools cannot provide a satisfying solution with integrated comprehensive functions, proper architectures, and highly scalable acceleration. In this article, we demonstrate SOAPnuke as a tool with abundant functions for a “QC-Preprocess-QC” workflow and MapReduce acceleration framework. Four modules with different preprocessing functions are designed for processing datasets from genomic, small RNA, Digital Gene Expression, and metagenomic experiments, respectively. As a workflow-like tool, SOAPnuke centralizes processing functions into 1 executable and predefines their order to avoid the necessity of reformatting different files when switching tools. Furthermore, the MapReduce framework enables large scalability to distribute all the processing works to an entire compute cluster.

We conducted a benchmarking where SOAPnuke and other tools are used to preprocess a ∼30× NA12878 dataset published by GIAB. The standalone operation of SOAPnuke struck a balance between resource occupancy and performance. When accelerated on 16 working nodes with MapReduce, SOAPnuke achieved ∼5.7 times the fastest speed of other tools.

Single nucleotide variant counts computed from RNA sequencing and cellular traffic into human kidney allografts

Advances in bioinformatics allow identification of single nucleotide polymorphisms (variants) from RNA sequence data. In an allograft biopsy, 2 genomes contribute to the RNA pool, 1 from the donor organ and the other from the infiltrating recipient's cells. We hypothesize that imbalances in genetic variants of RNA sequence data of kidney allograft biopsies provide an objective measure of cellular infiltration of the allograft. We performed mRNA sequencing of 40 kidney allograft biopsies, selected to represent a comprehensive range of diagnostic categories. We analyzed the sequencing reads of these biopsies and of 462 lymphoblastoid cell lines from the 1000 Genomes Project, for RNA variants. The ratio of heterozygous to nonreference genome homozygous variants (Het/Hom ratio) on all autosomes was determined for each sample, and the estimation of stromal and immune cells in malignant tumors using expression data (ESTIMATE) score was computed as a complementary estimate of the degree of cellular infiltration into biopsies. The Het/Hom ratios (P = .02) and the ESTIMATE scores (P < .001) were associated with the biopsy diagnosis. Both measures correlated significantly (r = .67, P < .0001), even though the Het/Hom ratio is based on mRNA sequence variation, while the ESTIMATE score uses mRNA expression. Het/Hom ratio and the ESTIMATE score may offer unbiased and quantitative parameters for characterizing cellular traffic into human kidney allografts.

Challenges of Identifying Clinically Actionable Genetic Variants for Precision Medicine

Advances in genomic medicine have the potential to change the way we treat human disease, but translating these advances into reality for improving healthcare outcomes depends essentially on our ability to discover disease- and/or drug-associated clinically actionable genetic mutations. Integration and manipulation of diverse genomic data and comprehensive electronic health records (EHRs) on a big data infrastructure can provide an efficient and effective way to identify clinically actionable genetic variants for personalized treatments and reduce healthcare costs. We review bioinformatics processing of next-generation sequencing (NGS) data, bioinformatics infrastructures for implementing precision medicine, and bioinformatics approaches for identifying clinically actionable genetic variants using high-throughput NGS data and EHRs.

Functional metagenomics: a tool to gain knowledge for agronomic and veterinary sciences

The increased global demand for food production has motivated agroindustries to increase their own levels of production. Scientific efforts have contributed to improving these production systems, aiding to solve problems and establishing novel conceptual views and sustainable alternatives to cope with the increasing demand. Although microorganisms are key players in biological systems and may drive certain desired responses toward food production, little is known about the microbial communities that constitute the microbiomes associated with agricultural and veterinary activities. Understanding the diversity, structure and in situ interactions of microbes, together with how these interactions occur within microbial communities and with respect to their environments (including hosts), constitutes a major challenge with an enormous relevance for agriculture and biotechnology. The emergence of high-throughput sequencing technologies, together with novel and more accessible bioinformatics tools, has allowed researchers to learn more about the functional potential and functional activity of these microbial communities. These tools constitute a relevant approach for understanding the metabolic processes that can occur or are currently occurring in a given system and for implementing novel strategies focused on solving production problems or improving sustainability. Several 'omics' sciences and their applications in agriculture are discussed in this review, and the usage of functional metagenomics is proposed to achieve substantial advances for food agroindustries and veterinary sciences.

Isolation, characterization and molecular identification of a novel aquareovirus that infects endangered fountain darter Etheostoma fonticola

The fountain darter Etheostoma fonticola (FOD) is a federally endangered fish listed under the US Endangered Species Act. Here, we identified and characterized a novel aquareovirus isolated from wild fountain darters inhabiting the San Marcos River. This virus was propagated in Chinook salmon embryo (CHSE)-214, rainbow trout gonad-2 and fathead minnow cells at 15°C. The epithelioma papulosum cyprini cell line was refractory at all temperatures evaluated. High throughput sequencing technologies facilitated the complete genome sequencing of this virus utilizing ribosomal RNA-depleted RNA extracted from infected CHSE-214 cells. Conventional PCR primer sets were developed for the detection and confirmation of this virus to assist diagnostic screening methods. Phylogenetic analysis suggests this virus belongs to the Aquareovirus A genus. This research provides requisite initial data critical to support hatchery and refugia biosecurity measures for this endangered species.

Applications of next-generation sequencing analysis for the detection of hepatocellular carcinoma-associated hepatitis B virus mutations

BACKGROUND

Next-generation sequencing (NGS) is a powerful and high-throughput method for the detection of viral mutations. This article provides a brief overview about optimization of NGS analysis for hepatocellular carcinoma (HCC)-associated hepatitis B virus (HBV) mutations, and hepatocarcinogenesis of relevant mutations.

MAIN BODY

For the application of NGS analysis in the genome of HBV, four noteworthy steps were discovered in testing. First, a sample-specific reference sequence was the most effective mapping reference for NGS. Second, elongating the end of reference sequence improved mapping performance at the end of the genome. Third, resetting the origin of mapping reference sequence could probed deletion mutations and variants at a certain location with common mutations. Fourth, using a platform-specific cut-off value to distinguish authentic minority variants from technical artifacts was found to be highly effective. One hundred and sixty-seven HBV single nucleotide variants (SNVs) were found to be studied previously through a systematic literature review, and 12 SNVs were determined to be associated with HCC by meta-analysis. From comprehensive research using a HBV genome-wide NGS analysis, 60 NGS-defined HCC-associated SNVs with their pathogenic frequencies were identified, with 19 reported previously. All the 12 HCC-associated SNVs proved by meta-analysis were confirmed by NGS analysis, except for C1766T and T1768A which were mainly expressed in genotypes A and D, but including the subgroup analysis of A1762T. In the 41 novel NGS-defined HCC-associated SNVs, 31.7% (13/41) had cut-off values of SNV frequency lower than 20%. This showed that NGS could be used to detect HCC-associated SNVs with low SNV frequency. Most SNV II (the minor strains in the majority of non-HCC patients) had either low (< 20%) or high (> 80%) SNV frequencies in HCC patients, a characteristic U-shaped distribution pattern. The cut-off values of SNV frequency for HCC-associated SNVs represent their pathogenic frequencies. The pathogenic frequencies of HCC-associated SNV II also showed a U-shaped distribution. Hepatocarcinogenesis induced by HBV mutated proteins through cellular pathways was reviewed.

CONCLUSION

NGS analysis is useful to discover novel HCC-associated HBV SNVs, especially those with low SNV frequency. The hepatocarcinogenetic mechanisms of novel HCC-associated HBV SNVs defined by NGS analysis deserve further investigation.

Frequent BRAF mutations suggest a novel oncogenic driver in colonic neuroendocrine carcinoma

BACKGROUND AND OBJECTIVES

The World Health Organization (WHO) 2010 has classified GI neuroendocrine neoplasms into neuroendocrine tumor (NET) and high-grade neuroendocrine carcinoma (NEC). The genetic underpinnings of NEC are poorly understood. The aim of the study was to perform genomic profiling of NEC to better characterize this aggressive disease.

METHODS

We identified nine patients with colonic NEC between January 1, 2005 and June 30, 2013. Whole exome sequencing (WES) was performed on tumor DNA from two patients with ≥80% tumor cellularity and matched normal tissue available. Focused BRAF mutational analysis was performed on an additional seven patients via sanger sequencing of BRAF exons 11 and 15.

RESULTS

We identified BRAF exon 15 mutations (c.A1781G: p.D594G and c.T1799A: p.V600E) by WES in two patients. Upon additional screening of seven colonic NECs for BRAF exon 11 and 15 mutations, we identified BRAF V600E mutations in two of seven specimens (29%). Overall, BRAF exon 15 mutations were present in four of nine colonic NECs.

CONCLUSION

Colonic NEC is a rare but aggressive tumor with high frequency (44%) of BRAF mutations. Further investigation is warranted to ascertain the incidence of BRAF mutations in a larger population as BRAF inhibition may be a potential avenue of targeted treatment for these patients.

BET bromodomain inhibitors suppress EWS-FLI1-dependent transcription and the IGF1 autocrine mechanism in Ewing sarcoma

Ewing sarcoma is driven by characteristic chromosomal translocations between the EWSR1 gene with genes encoding ETS family transcription factors (EWS-ETS), most commonly FLI1. However, direct pharmacological inhibition of transcription factors like EWS-FLI1 remains largely unsuccessful. Active gene transcription requires orchestrated actions of many epigenetic regulators, such as the bromodomain and extra-terminal domain (BET) family proteins. Emerging BET bromodomain inhibitors have exhibited promising antineoplastic activities via suppression of oncogenic transcription factors in various cancers. We reasoned that EWS-FLI1-mediated transcription activation might be susceptible to BET inhibition. In this study, we demonstrated that small molecule BET bromodomain inhibitors repressed EWS-FLI1-driven gene signatures and downregulated important target genes. However, expression of EWS-FLI1 was not significantly affected. Repression of autocrine IGF1 by BET inhibitors led to significant inhibition of the IGF1R/AKT pathway critical to Ewing sarcoma cell proliferation and survival. Consistently, BET inhibitors impaired viability and clonogenic survival of Ewing sarcoma cell lines and blocked EWS-FLI1-induced transformation of mouse NIH3T3 fibroblast cells. Selective depletion of individual BET genes partially phenocopied the actions of BET inhibitors. Finally, the prototypical BET inhibitor, JQ1, significantly repressed Ewing sarcoma xenograft tumor growth. These findings suggest therapeutic potential of BET inhibitors in Ewing sarcoma and highlight an emerging paradigm of using epigenetic agents to treat cancers driven by fusion transcription factors.

Targeted sequencing of established and candidate colorectal cancer genes in the Colon Cancer Family Registry Cohort

The underlying genetic cause of colorectal cancer (CRC) can be identified for 5-10% of all cases, while at least 20% of CRC cases are thought to be due to inherited genetic factors. Screening for highly penetrant mutations in genes associated with Mendelian cancer syndromes using next-generation sequencing (NGS) can be prohibitively expensive for studies requiring large samples sizes. The aim of the study was to identify rare single nucleotide variants and small indels in 40 established or candidate CRC susceptibility genes in 1,046 familial CRC cases (including both MSS and MSI-H tumor subtypes) and 1,006 unrelated controls from the Colon Cancer Family Registry Cohort using a robust and cost-effective DNA pooling NGS strategy. We identified 264 variants in 38 genes that were observed only in cases, comprising either very rare (minor allele frequency <0.001) or not previously reported (n=90, 34%) in reference databases, including six stop-gain, three frameshift, and 255 non-synonymous variants predicted to be damaging. We found novel germline mutations in established CRC genes MLH1, APC, and POLE, and likely pathogenic variants in cancer susceptibility genes BAP1, CDH1, CHEK2, ENG, and MSH3. For the candidate CRC genes, we identified likely pathogenic variants in the helicase domain of POLQ and in the LRIG1, SH2B3, and NOS1 genes and present their clinicopathological characteristics. Using a DNA pooling NGS strategy, we identified novel germline mutations in established CRC susceptibility genes in familial CRC cases. Further studies are required to support the role of POLQ, LRIG1, SH2B3 and NOS1 as CRC susceptibility genes.

The discrepancy among single nucleotide variants detected by DNA and RNA high throughput sequencing data

BACKGROUND

High throughput sequencing technology enables the both the human genome and transcriptome to be screened at the single nucleotide resolution. Tools have been developed to infer single nucleotide variants (SNVs) from both DNA and RNA sequencing data. To evaluate how much difference can be expected between DNA and RNA sequencing data, and among tissue sources, we designed a study to examine the single nucleotide difference among five sources of high throughput sequencing data generated from the same individual, including exome sequencing from blood, tumor and adjacent normal tissue, and RNAseq from tumor and adjacent normal tissue.

RESULTS

Through careful quality control and analysis of the SNVs, we found little difference between DNA-DNA pairs (1%-2%). However, between DNA-RNA pairs, SNV differences ranged anywhere from 10% to 20%.

CONCLUSIONS

Only a small portion of these differences can be explained by RNA editing. Instead, the majority of the DNA-RNA differences should be attributed to technical errors from sequencing and post-processing of RNAseq data. Our analysis results suggest that SNV detection using RNAseq is subject to high false positive rates.

Synthetic Circulating Cell-free DNA as Quality Control Materials for Somatic Mutation Detection in Liquid Biopsy for Cancer

BACKGROUND

Detection of somatic genomic alterations in tumor-derived cell-free DNA (cfDNA) in the plasma is challenging owing to the low concentrations of cfDNA, variable detection methods, and complex workflows. Moreover, no proper quality control materials are available currently.

METHODS

We developed a set of synthetic cfDNA quality control materials (SCQCMs) containing spike-in cfDNA on the basis of micrococcal nuclease digestion carrying somatic mutations as simulated cfDNA and matched genomic DNA as genetic background to emulate paired tumor-normal samples in real clinical tests. Site-directed mutagenesis DNA that contained 1500–2000 bases with single-nucleotide variants or indels and genomic DNA from CRISPR/Cas9 edited cells with EML4-ALK rearrangements was fragmented, quantified, and added into micrococcal nuclease-digested DNA derived from HEK293T cells. To prove their suitability, the SCQCMs were compared with patient-derived plasma samples and validated in a collaborative study that encompassed 11 laboratories.

RESULTS

The results of SCQCM analysis by next-generation sequencing showed strong agreement with those of patient-derived plasma samples, including the size profile of cfDNA and the quality control metrics of the sequencing data. More than 95% of laboratories correctly detected the SCQCMs with EGFR T790M, L858R, KRAS G12D, and a deletion in exon 19, as well as with EML4-ALK variant 2.

CONCLUSIONS

The SCQCMs were successfully applied in a broad range of settings, methodologies, and informatics techniques. We conclude that SCQCMs can be used as optimal quality controls in test performance assessments for circulating tumor DNA somatic mutation detection.

Hypoplastic Left Heart Syndrome Sequencing Reveals a Novel NOTCH1 Mutation in a Family with Single Ventricle Defects

Hypoplastic left heart syndrome (HLHS) has been associated with germline mutations in 12 candidate genes and a recurrent somatic mutation in HAND1 gene. Using targeted and whole exome sequencing (WES) of heart tissue samples from HLHS patients, we sought to estimate the prevalence of somatic and germline mutations associated with HLHS. We performed Sanger sequencing of the HAND1 gene on 14 ventricular (9 LV and 5 RV) samples obtained from HLHS patients, and WES of 4 LV, 2 aortic, and 4 matched PBMC samples, analyzing for sequence discrepancy. We also screened for mutations in the 12 candidate genes implicated in HLHS. We found no somatic mutations in our HLHS cohort. However, we detected a novel germline frameshift/stop-gain mutation in NOTCH1 in a HLHS patient with a family history of both HLHS and hypoplastic right heart syndrome (HRHS). Our study, involving one of the first familial cases of single ventricle defects linked to a specific mutation, strengthens the association of NOTCH1 mutations with HLHS and suggests that the two morphologically distinct single ventricle conditions, HLHS and HRHS, may share a common molecular and cellular etiology. Finally, somatic mutations in the LV are an unlikely contributor to HLHS.

A Method to Evaluate the Quality of Clinical Gene-Panel Sequencing Data for Single-Nucleotide Variant Detection

Customized gene-panel tests, based on next-generation sequencing, have demonstrated their usefulness in a plethora of clinical settings. As with other clinical diagnostic techniques, gene-panel sequencing for clinical purposes requires precise quality control (QC) measures to ensure its reliability. Only detected variants are currently recorded in clinical reports; however, identifying whether a nondetected variant is a true or false negative is regarded essential in a clinical setting and, thus, a comprehensive QC measure is in demand. Conventional QC metrics, such as mean coverage and uniformity, are considered inadequate for such an evaluation. As such, a more specific measure focused on clinically important variants is herein proposed. In this study, we suggest a new scoring method for assessing the quality of clinical gene-panel sequencing data, specifically for the detection of a set of single-nucleotide variants. The performance of the method was analyzed using 2295 clinical samples (1012 formalin-fixed, paraffin-embedded and 1283 fresh-frozen tissues), and was shown to provide additional information that conventional methods do not show, such as mean depth and uniformity. Customized sequencing protocols, which include QC criteria, have been optimized by each genomic laboratory. The pass rate scoring method proposed in this study provides an appropriate QC response variable for the customized panel, which strengthens the reliability of calls on clinically relevant variants implicated in clinical reports.

Profiles of Long Noncoding RNAs in Human Naive and Memory T Cells

We employed whole-genome RNA-sequencing to profile mRNAs and both annotated and novel long noncoding RNAs (lncRNAs) in human naive, central memory, and effector memory CD4+ T cells. Loci transcribing both lineage-specific annotated and novel lncRNA are adjacent to lineage-specific protein-coding genes in the genome. Lineage-specific novel lncRNA loci are transcribed from lineage-specific typical- and supertranscriptional enhancers and are not multiexonic, thus are more similar to enhancer RNAs. Novel enhancer-associated lncRNAs transcribed from the IFNG locus bind the transcription factor NF-κB and enhance binding of NF-κB to the IFNG genomic locus. Depletion of the annotated lncRNA, IFNG-AS1, or one IFNG enhancer-associated lncRNA abrogates IFNG expression by memory T cells, indicating these lncRNAs have biologic function.

Expression of long non-coding RNAs in autoimmunity and linkage to enhancer function and autoimmune disease risk genetic variants

Genome-wide association studies have identified numerous genetic variants conferring autoimmune disease risk. Most of these genetic variants lie outside protein-coding genes hampering mechanistic explorations. Numerous mRNAs are also differentially expressed in autoimmune disease but their regulation is also unclear. The majority of the human genome is transcribed yet its biologic significance is incompletely understood. We performed whole genome RNA-sequencing [RNA-seq] to categorize expression of mRNAs, known and novel long non-coding RNAs [lncRNAs] in leukocytes from subjects with autoimmune disease and identified annotated and novel lncRNAs differentially expressed across multiple disorders. We found that loci transcribing novel lncRNAs were not randomly distributed across the genome but co-localized with leukocyte transcriptional enhancers, especially super-enhancers, and near genetic variants associated with autoimmune disease risk. We propose that alterations in enhancer function, including lncRNA expression, produced by genetics and environment, change cellular phenotypes contributing to disease risk and pathogenesis and represent attractive therapeutic targets.

Improvements and impacts of GRCh38 human reference on high throughput sequencing data analysis

Analyses of high throughput sequencing data starts with alignment against a reference genome, which is the foundation for all re-sequencing data analyses. Each new release of the human reference genome has been augmented with improved accuracy and completeness. It is presumed that the latest release of human reference genome, GRCh38 will contribute more to high throughput sequencing data analysis by providing more accuracy. But the amount of improvement has not yet been quantified. We conducted a study to compare the genomic analysis results between the GRCh38 reference and its predecessor GRCh37. Through analyses of alignment, single nucleotide polymorphisms, small insertion/deletions, copy number and structural variants, we show that GRCh38 offers overall more accurate analysis of human sequencing data. More importantly, GRCh38 produced fewer false positive structural variants. In conclusion, GRCh38 is an improvement over GRCh37 not only from the genome assembly aspect, but also yields more reliable genomic analysis results.

A Transcriptional Signature Identifies LKB1 Functional Status as a Novel Determinant of MEK Sensitivity in Lung Adenocarcinoma

LKB1 is a commonly mutated tumor suppressor in non-small cell lung cancer that exerts complex effects on signal transduction and transcriptional regulation. To better understand the downstream impact of loss of functional LKB1, we developed a transcriptional fingerprint assay representing this phenotype. This assay was predictive of LKB1 functional loss in cell lines and clinical specimens, even those without detected sequence alterations in the gene. In silico screening of drug sensitivity data identified putative LKB1-selective drug candidates, revealing novel associations not apparent from analysis of LKB1 mutations alone. Among the candidates, MEK inhibitors showed robust association with signature expression in both training and testing datasets independent of RAS/RAF mutations. This susceptibility phenotype is directly altered by RNA interference-mediated LKB1 knockdown or by LKB1 re-expression into mutant cell lines and is readily observed in vivo using a xenograft model. MEK sensitivity is dependent on LKB1-induced changes in AKT and FOXO3 activation, consistent with genomic and proteomic analyses of LKB1-deficient lung adenocarcinomas. Our findings implicate the MEK pathway as a potential therapeutic target for LKB1-deficient cancers and define a practical NanoString biomarker to identify functional LKB1 loss. Cancer Res; 77(1); 153-63. ©2016 AACR.

Alternate-locus aware variant calling in whole genome sequencing

Background

The last two human genome assemblies have extended the previous linear golden-path paradigm of the human genome to a graph-like model to better represent regions with a high degree of structural variability. The new model offers opportunities to improve the technical validity of variant calling in whole-genome sequencing (WGS).

Methods

We developed an algorithm that analyzes the patterns of variant calls in the 178 structurally variable regions of the GRCh38 genome assembly, and infers whether a given sample is most likely to contain sequences from the primary assembly, an alternate locus, or their heterozygous combination at each of these 178 regions. We investigate 121 in-house WGS datasets that have been aligned to the GRCh37 and GRCh38 assemblies.

Results

We show that stretches of sequences that are largely but not entirely identical between the primary assembly and an alternate locus can result in multiple variant calls against regions of the primary assembly. In WGS analysis, this results in characteristic and recognizable patterns of variant calls at positions that we term alignable scaffold-discrepant positions (ASDPs). In 121 in-house genomes, on average 51.8±3.8 of the 178 regions were found to correspond best to an alternate locus rather than the primary assembly sequence, and filtering these genomes with our algorithm led to the identification of 7863 variant calls per genome that colocalized with ASDPs. Additionally, we found that 437 of 791 genome-wide association study hits located within one of the regions corresponded to ASDPs.

Conclusions

Our algorithm uses the information contained in the 178 structurally variable regions of the GRCh38 genome assembly to avoid spurious variant calls in cases where samples contain an alternate locus rather than the corresponding segment of the primary assembly. These results suggest the great potential of fully incorporating the resources of graph-like genome assemblies into variant calling, but also underscore the importance of developing computational resources that will allow a full reconstruction of the genotype in personal genomes. Our algorithm is freely available at https://github.com/charite/asdpex.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-016-0383-z) contains supplementary material, which is available to authorized users.

De novo transcriptome sequencing in Monsonia burkeana revealed putative genes for key metabolic pathways involved in tea quality and medicinal value

Monsonia (Monsonia burkeana Planch. ex Harv) is one of the most valuable tea and traditional medicinal plants used in Southern Africa. In spite of this, there is no sequence information regarding this plant in literature. To provide understanding of the naturally occurring tea and drug-specific products and the key pathways for the biosynthesis of these molecules, we sequenced the leaf transcriptome using Illumina MiSeq platform and generated 2,590,652 paired-end reads that were assembled de novo into 45,450 high-quality transcripts. Annotation of these transcripts revealed best hits for homology to discover more than 17,800 functional genes and conserved domains. A total of 93 KEGG pathways and associated genes encoded by more than 90% of the coding transcripts are responsible for the biosynthesis of these life-saving metabolites. We validated and enriched the genes by GO annotation and linked this to enzyme-powered pathways through interactive network map. Caffeine metabolism, flavonoid, phenylpropanoid and terpenoids biosynthesis and xenobiotics degradation were typical in tea quality and drug therapy. The relatedness of more than 80 gene families encoding key enzymes was shown using unrooted phylogenetic tree. In conclusion, the M. burkeana leaf transcriptome gives insight into tea and drug-specific products, therefore representing basis in further investigation of the plant.

lncRNA expression in the auditory forebrain during postnatal development

The biological processes governing brain development and maturation depend on complex patterns of gene and protein expression, which can be influenced by many factors. One of the most overlooked is the long noncoding class of RNAs (lncRNAs), which are known to play important regulatory roles in an array of biological processes. Little is known about the distribution of lncRNAs in the sensory systems of the brain, and how lncRNAs interact with other mechanisms to guide the development of these systems. In this study, we profiled lncRNA expression in the mouse auditory forebrain during postnatal development at time points before and after the onset of hearing (P7, P14, P21, adult). First, we generated lncRNA profiles of the primary auditory cortex (A1) and medial geniculate body (MG) at each age. Then, we determined the differential patterns of expression by brain region and age. These analyses revealed that the lncRNA expression profile was distinct between both brain regions and between each postnatal age, indicating spatial and temporal specificity during maturation of the auditory forebrain. Next, we explored potential interactions between functionally-related lncRNAs, protein coding RNAs (pcRNAs), and associated proteins. The maturational trajectories (P7 to adult) of many lncRNA - pcRNA pairs were highly correlated, and predictive analyses revealed that lncRNA-protein interactions tended to be strong. A user-friendly database was constructed to facilitate inspection of the expression levels and maturational trajectories for any lncRNA or pcRNA in the database. Overall, this study provides an in-depth summary of lncRNA expression in the developing auditory forebrain and a broad-based foundation for future exploration of lncRNA function during brain development.

Determining the cause of recurrent Clostridium difficile infection using whole genome sequencing

Understanding the contribution of relapse and reinfection to recurrent Clostridium difficile infection (CDI) has implications for therapy and infection prevention, respectively. We used whole genome sequencing to determine the relation of C. difficile strains isolated from patients with recurrent CDI at an academic medical center in the United States. Thirty-five toxigenic C. difficile isolates from 16 patients with 19 recurrent CDI episodes with median time of 53.5days (range, 13-362) between episodes were whole genome sequenced on the Illumina MiSeq platform. In 84% (16) of recurrences, the cause of recurrence was relapse with prior strain of C. difficile. In 16% (3) of recurrent episodes, reinfection with a new strain of C. difficile was the cause. In conclusion, the majority of CDI recurrences at our institution were due to infection with the same strain rather than infection with a new strain.

RNA Sequencing of Formalin-Fixed, Paraffin-Embedded Specimens for Gene Expression Quantification and Data Mining

Background. Proper rRNA depletion is crucial for the successful utilization of FFPE specimens when studying gene expression. We performed a study to evaluate two major rRNA depletion methods: Ribo-Zero and RNase H. RNAs extracted from 4 samples were treated with the two rRNA depletion methods in duplicate and sequenced (N = 16). We evaluated their reducibility, ability to detect RNA, and ability to molecularly subtype these triple negative breast cancer specimens. Results. Both rRNA depletion methods produced consistent data between the technical replicates. We found that the RNase H method produced higher quality RNAseq data as compared to the Ribo-Zero method. In addition, we evaluated the RNAseq data generated from the FFPE tissue samples for noncoding RNA, including lncRNA, enhancer/super enhancer RNA, and single nucleotide variation (SNV). We found that the RNase H is more suitable for detecting high-quality, noncoding RNAs as compared to the Ribo-Zero and provided more consistent molecular subtype identification between replicates. Unfortunately, neither method produced reliable SNV data. Conclusions. In conclusion, for FFPE specimens, the RNase H rRNA depletion method performed better than the Ribo-Zero. Neither method generates data sufficient for SNV detection.

The MAPK Pathway Regulates Intrinsic Resistance to BET Inhibitors in Colorectal Cancer

Purpose: The bromodomain and extra-terminal domain (BET) family proteins are epigenetic readers for acetylated histone marks. Emerging BET bromodomain inhibitors have exhibited antineoplastic activities in a wide range of human cancers through suppression of oncogenic transcription factors, including MYC. However, the preclinical activities of BET inhibitors in advanced solid cancers are moderate at best. To improve BET-targeted therapy, we interrogated mechanisms mediating resistance to BET inhibitors in colorectal cancer.Experimental Design: Using a panel of molecularly defined colorectal cancer cell lines, we examined the impact of BET inhibition on cellular proliferation and survival as well as MYC activity. We further tested the ability of inhibitors targeting the RAF/MEK/ERK (MAPK) pathway to enhance MYC suppression and circumvent intrinsic resistance to BET inhibitors. Key findings were validated using genetic approaches.Results: BET inhibitors as monotherapy moderately reduced colorectal cancer cell proliferation and MYC expression. Blockade of the MAPK pathway synergistically sensitized colorectal cancer cells to BET inhibitors, leading to potent apoptosis and MYC downregulation in vitro and in vivo A combination of JQ1 and trametinib, but neither agent alone, induced significant regression of subcutaneous colorectal cancer xenografts.Conclusions: Our findings suggest that the MAPK pathway confers intrinsic resistance to BET inhibitors in colorectal cancer and propose an effective combination strategy for the treatment of colorectal cancer. Clin Cancer Res; 23(8); 2027-37. ©2016 AACR.

Practicability of mitochondrial heteroplasmy detection through an Illumina genotyping array

MOTIVATION

High-throughput genomic data often contain unexpected information that can be mined for alternative applications. Despite the rise of high-throughput sequencing, Illumina genotyping arrays remain a driving force in large scale genetic and epidemiology studies. By processing and analyzing genotyping data of over 100,000 samples genotyped on Illumina genotyping arrays, we discovered evidence that indicates that mitochondrial heteroplasmy can be estimated from the fluorescence intensity data of the array. To verify our hypothesis, we conducted a sequencing validation study.

RESULT

Mitochondrial DNA targeted sequencing was performed on three samples that had been genotyped using the Illumina exome genotyping array. In each sample chosen, one heteroplasmy target was identified from the genotyping array, and sequencing data verified all three putative heteroplasmic sites. The estimated heteroplasmy level difference between that estimated from the genotyping fluorescence intensity and that directly measured from sequencing was 3.2% on average. Our analysis showed that an Illumina genotyping array can accurately and reliably estimate high-level heteroplasmy (>40%); however, intensity data from a genotyping array is not suitable for estimating low level heteroplasmy (<25%).

Heterozygosity Ratio, a Robust Global Genomic Measure of Autozygosity and Its Association with Height and Disease Risk

Greater genetic variability in an individual is protective against recessive disease. However, existing quantifications of autozygosity, such as runs of homozygosity (ROH), have proved highly sensitive to genotyping density and have yielded inconclusive results about the relationship of diversity and disease risk. Using genotyping data from three data sets with >43,000 subjects, we demonstrated that an alternative approach to quantifying genetic variability, the heterozygosity ratio, is a robust measure of diversity and is positively associated with the nondisease trait height and several disease phenotypes in subjects of European ancestry. The heterozygosity ratio is the number of heterozygous sites in an individual divided by the number of nonreference homozygous sites and is strongly affected by the degree of genetic admixture of the population and varies across human populations. Unlike quantifications of ROH, the heterozygosity ratio is not sensitive to the density of genotyping performed. Our results establish the heterozygosity ratio as a powerful new statistic for exploring the patterns and phenotypic effects of different levels of genetic variation in populations.

The Role of Quality Control in Targeted Next-generation Sequencing Library Preparation

Next-generation sequencing (NGS) is getting routinely used in the diagnosis of hereditary diseases, such as human cardiomyopathies. Hence, it is of utter importance to secure high quality sequencing data, enabling the identification of disease-relevant mutations or the conclusion of negative test results. During the process of sample preparation, each protocol for target enrichment library preparation has its own requirements for quality control (QC); however, there is little evidence on the actual impact of these guidelines on resulting data quality. In this study, we analyzed the impact of QC during the diverse library preparation steps of Agilent SureSelect XT target enrichment and Illumina sequencing. We quantified the parameters for a cohort of around 600 samples, which include starting amount of DNA, amount of sheared DNA, smallest and largest fragment size of the starting DNA; amount of DNA after the pre-PCR, and smallest and largest fragment size of the resulting DNA; as well as the amount of the final library, the corresponding smallest and largest fragment size, and the number of detected variants. Intriguingly, there is a high tolerance for variations in all QC steps, meaning that within the boundaries proposed in the current study, a considerable variance at each step of QC can be well tolerated without compromising NGS quality.

Concordance between whole-exome sequencing and clinical Sanger sequencing: implications for patient care

The clinical translation of next‐generation sequencing has created a paradigm shift in the diagnostic assessment of individuals with suspected rare genetic diseases. Whole‐exome sequencing (WES) simultaneously examines the majority of the coding portion of the genome and is rapidly becoming accepted as an efficient alternative to clinical Sanger sequencing for diagnosing genetically heterogeneous disorders. Among reports of the clinical and diagnostic utility of WES, few studies to date have directly compared its concordance to Sanger sequencing, which is considered the clinical “gold standard”. We performed a direct comparison of 391 coding and noncoding polymorphisms and variants of unknown significance identified by clinical Sanger sequencing to the WES results of 26 patients. Of the 150 well‐covered coding variants identified by Sanger sequencing, 146 (97.3%) were also reported by WES. Nine genes were excluded from the comparison due to consistently low coverage in WES, which might be attributed to the use of older exome capture kits. We performed confirmatory Sanger sequencing of discordant variants; including five variants with discordant bases and four with discordant zygosity. Confirmatory Sanger sequencing supported the original Sanger report for three of the five discordant bases, one was shown to be a false positive supporting the WES data, and one result differed from both the Sanger and WES data. Two of the discordant zygosity results supported Sanger and the other two supported WES data. We report high concordance for well‐covered coding variants, supporting the use of WES as a screening tool for heterogeneous disorders, and recommend the use of supplementary Sanger sequencing for poorly‐covered genes when the clinical suspicion is high. Importantly, despite remaining difficulties with achieving complete coverage of the whole exome, 10 (38.5%) of the 26 compared patients were diagnosed through WES.

Kinesin-5 inhibitor resistance is driven by kinesin-12

The kinesin-5 Eg5 is essential for mitotic progression, and the lethal effects of Eg5 inhibitors make these inhibitors attractive candidates for chemotherapy drugs. Sturgill et al. show that kinesin-12 and a nonmotile Eg5 mutant form an alternative spindle assembly pathway that provides resistance to Eg5 inhibitors.

The microtubule (MT) cytoskeleton bipolarizes at the onset of mitosis to form the spindle. In animal cells, the kinesin-5 Eg5 primarily drives this reorganization by actively sliding MTs apart. Its primacy during spindle assembly renders Eg5 essential for mitotic progression, demonstrated by the lethal effects of kinesin-5/Eg5 inhibitors (K5Is) administered in cell culture. However, cultured cells can acquire resistance to K5Is, indicative of alternative spindle assembly mechanisms and/or pharmacological failure. Through characterization of novel K5I-resistant cell lines, we unveil an Eg5 motility-independent spindle assembly pathway that involves both an Eg5 rigor mutant and the kinesin-12 Kif15. This pathway centers on spindle MT bundling instead of Kif15 overexpression, distinguishing it from those previously described. We further show that large populations (∼10⁷ cells) of HeLa cells require Kif15 to survive K5I treatment. Overall, this study provides insight into the functional plasticity of mitotic kinesins during spindle assembly and has important implications for the development of antimitotic regimens that target this process.

Practicability of detecting somatic point mutation from RNA high throughput sequencing data

Traditionally, somatic mutations are detected by examining DNA sequence. The maturity of sequencing technology has allowed researchers to screen for somatic mutations in the whole genome. Increasingly, researchers have become interested in identifying somatic mutations through RNAseq data. With this motivation, we evaluated the practicability of detecting somatic mutations from RNAseq data. Current somatic mutation calling tools were designed for DNA sequencing data. To increase performance on RNAseq data, we developed a somatic mutation caller GLMVC based on bias reduced generalized linear model for both DNA and RNA sequencing data. Through comparison with MuTect and Varscan we showed that GLMVC performed better for somatic mutation detection using exome sequencing or RNAseq data. GLMVC is freely available for download at the following website: https://github.com/shengqh/GLMVC/wiki.

Standards for Clinical Grade Genomic Databases

CONTEXT

Next-generation sequencing performed in a clinical environment must meet clinical standards, which requires reproducibility of all aspects of the testing. Clinical-grade genomic databases (CGGDs) are required to classify a variant and to assist in the professional interpretation of clinical next-generation sequencing. Applying quality laboratory standards to the reference databases used for sequence-variant interpretation presents a new challenge for validation and curation.

OBJECTIVES

To define CGGD and the categories of information contained in CGGDs and to frame recommendations for the structure and use of these databases in clinical patient care.

DESIGN

Members of the College of American Pathologists Personalized Health Care Committee reviewed the literature and existing state of genomic databases and developed a framework for guiding CGGD development in the future.

RESULTS

Clinical-grade genomic databases may provide different types of information. This work group defined 3 layers of information in CGGDs: clinical genomic variant repositories, genomic medical data repositories, and genomic medicine evidence databases. The layers are differentiated by the types of genomic and medical information contained and the utility in assisting with clinical interpretation of genomic variants. Clinical-grade genomic databases must meet specific standards regarding submission, curation, and retrieval of data, as well as the maintenance of privacy and security.

CONCLUSION

These organizing principles for CGGDs should serve as a foundation for future development of specific standards that support the use of such databases for patient care.

Mitochondria single nucleotide variation across six blood cell types

It has been shown that heteroplasmic mitochondrial DNA variants can be tissue specific. However, whether mitochondrial DNA variants are specific by blood cell types has not been investigated. Motivated by this question and using mitochondria sequences extracted from RNAseq data from six distinct blood cell types (neutrophil, monocyte, myeloid dendritic, natural killer, T and B), we thoroughly compared SNPs and heteroplasmies among these cell types. Each cell type from each subject was sequenced at four time points used as biological replicates. We found that mitochondria content is low in neutrophil compared to the other five blood cell types. Subsequent analysis on the other five blood cell types showed that at the SNP level, there was no discrepancy. At the heteroplasmy level, we observed good concordances among all blood cell types. However, the allele frequencies of the heteroplasmy differed between blood cell types for certain heteroplasmic sites. Furthermore, we identified five tri-allelic sites (1610, 2617, 8303, 12146, 13710) that are likely caused by RNA editing. Three out of these five sites are located at the ninth position of tRNA genes, and are likely resulting from post-transcriptional methylation.

Mitochondria sequence mapping strategies and practicability of mitochondria variant detection from exome and RNA sequencing data

The rapid progress in high-throughput sequencing has significantly enriched our capacity for studying the mitochondrial DNA (mtDNA). In addition to performing specific mitochondrial targeted sequencing, an increasingly popular alternative approach is using the off-target reads from exome sequencing to infer mtDNA variants, including single nucleotide polymorphisms (SNPs) and heteroplasmy. However, the effectiveness and practicality of this approach have not been tested. Recently, RNAseq data have also been suggested as a good source for alternative data mining, but whether mitochondrial variants can be detected from RNAseq data has not been validated. We designed a study to evaluate the practicability of mtDNA variant detection using exome and RNA sequencing data. Five breast cancer cell lines were sequenced through mitochondrial targeted, exome, and RNA sequencing. Mitochondrial targeted sequencing was used as the gold standard to compute the validation and false discovery rates of SNP and heteroplasmy detection in exome and RNAseq data. We found that exome and RNA sequencing can accurately detect mitochondrial SNPs. However, the lower false discovery rate makes exome sequencing a better choice for heteroplasmy detection than RNAseq. Furthermore, we examined three alignment strategies and found that aligning reads directly to the mitochondrial reference genome or aligning reads to the nuclear and mitochondrial references genomes simultaneously produced the best results, and that aligning to the nuclear genome first and afterwards to the mitochondrial genome performed poorly. In conclusion, our study provides important guidelines for future studies that intend to use either exome sequencing or RNAseq data to infer mitochondrial SNPs and heteroplasmy.

A Distributed Network for Social Cognition Enriched for Oxytocin Receptors

Oxytocin is a neuropeptide important for social behaviors such as maternal care and parent-infant bonding. It is believed that oxytocin receptor signaling in the brain is critical for these behaviors, but it is unknown precisely when and where oxytocin receptors are expressed or which neural circuits are directly sensitive to oxytocin. To overcome this challenge, we generated specific antibodies to the mouse oxytocin receptor and examined receptor expression throughout the brain. We identified a distributed network of female mouse brain regions for maternal behaviors that are especially enriched for oxytocin receptors, including the piriform cortex, the left auditory cortex, and CA2 of the hippocampus. Electron microscopic analysis of the cerebral cortex revealed that oxytocin receptors were mainly expressed at synapses, as well as on axons and glial processes. Functionally, oxytocin transiently reduced synaptic inhibition in multiple brain regions and enabled long-term synaptic plasticity in the auditory cortex. Thus modulation of inhibition may be a general mechanism by which oxytocin can act throughout the brain to regulate parental behaviors and social cognition.

Antagonistic roles for the ubiquitin ligase Asr1 and the ubiquitin-specific protease Ubp3 in subtelomeric gene silencing

Ubiquitin, and components of the ubiquitin-proteasome system, feature extensively in the regulation of gene transcription. Although there are many examples of how ubiquitin controls the activity of transcriptional regulators and coregulators, there are few examples of core components of the transcriptional machinery that are directly controlled by ubiquitin-dependent processes. The budding yeast protein Asr1 is the prototypical member of the RPC (RING, PHD, CBD) family of ubiquitin-ligases, characterized by the presence of amino-terminal RING (really interesting new gene) and PHD (plant homeo domain) fingers and a carboxyl-terminal domain that directly binds the largest subunit of RNA polymerase II (pol II), Rpb1, in response to phosphorylation events tied to the initiation of transcription. Asr1-mediated oligo-ubiquitylation of pol II leads to ejection of two core subunits of the enzyme and is associated with inhibition of polymerase function. Here, we present evidence that Asr1-mediated ubiquitylation of pol II is required for silencing of subtelomeric gene transcription. We show that Asr1 associates with telomere-proximal chromatin and that disruption of the ubiquitin-ligase activity of Asr1--or mutation of ubiquitylation sites within Rpb1--induces transcription of silenced gene sequences. In addition, we report that Asr1 associates with the Ubp3 deubiquitylase and that Asr1 and Ubp3 play antagonistic roles in setting transcription levels from silenced genes. We suggest that control of pol II by nonproteolytic ubiquitylation provides a mechanism to enforce silencing by transient and reversible inhibition of pol II activity at subtelomeric chromatin.

Long non-coding RNAs in innate and adaptive immunity

Long noncoding RNAs (lncRNAs) represent a newly discovered class of regulatory molecules that impact a variety of biological processes in cells and organ systems. In humans, it is estimated that there may be more than twice as many lncRNA genes than protein-coding genes. However, only a handful of lncRNAs have been analyzed in detail. In this review, we describe expression and functions of lncRNAs that have been demonstrated to impact innate and adaptive immunity. These emerging paradigms illustrate remarkably diverse mechanisms that lncRNAs utilize to impact the transcriptional programs of immune cells required to fight against pathogens and maintain normal health and homeostasis.