Population bias in somatic measurement of microsatellite instability status.

Microsatellite instability (MSI) is a key secondary effect of a defective DNA mismatch repair mechanism resulting in incorrectly replicated microsatellites in many malignant tumors. Historically, MSI detection has been performed by fragment analysis (FA) on a panel of representative genomic markers. More recently, using next-generation sequencing (NGS) to analyze thousands of microsatellites has been shown to improve the robustness and sensitivity of MSI detection. However, NGS-based MSI tests can be prone to population biases if NGS results are aligned to a reference genome instead of patient-matched normal tissue. We observed an increased rate of false positives in patients of African ancestry with an NGS-based diagnostic for MSI status utilizing 7317 microsatellite loci. We then minimized this bias by training a modified calling model that utilized 2011 microsatellite loci. With these adjustments 100% (95% CI: 89.1% to 100%) of African ancestry patients in an independent validation test were called correctly using the updated model. This poses not only a significant technical improvement but also has an important clinical impact on directing immune checkpoint inhibitor therapy.

Establishing guidelines to harmonize tumor mutational burden (TMB): in silico assessment of variation in TMB quantification across diagnostic platforms: phase I of the Friends of Cancer Research TMB Harmonization Project.

BACKGROUND: Tumor mutational burden (TMB), defined as the number of somatic mutations per megabase of interrogated genomic sequence, demonstrates predictive biomarker potential for the identification of patients with cancer most likely to respond to immune checkpoint inhibitors. TMB is optimally calculated by whole exome sequencing (WES), but next-generation sequencing targeted panels provide TMB estimates in a time-effective and cost-effective manner. However, differences in panel size and gene coverage, in addition to the underlying bioinformatics pipelines, are known drivers of variability in TMB estimates across laboratories. By directly comparing panel-based TMB estimates from participating laboratories, this study aims to characterize the theoretical variability of panel-based TMB estimates, and provides guidelines on TMB reporting, analytic validation requirements and reference standard alignment in order to maintain consistency of TMB estimation across platforms. METHODS: Eleven laboratories used WES data from The Cancer Genome Atlas Multi-Center Mutation calling in Multiple Cancers (MC3) samples and calculated TMB from the subset of the exome restricted to the genes covered by their targeted panel using their own bioinformatics pipeline (panel TMB). A reference TMB value was calculated from the entire exome using a uniform bioinformatics pipeline all members agreed on (WES TMB). Linear regression analyses were performed to investigate the relationship between WES and panel TMB for all 32 cancer types combined and separately. Variability in panel TMB values at various WES TMB values was also quantified using 95% prediction limits. RESULTS: Study results demonstrated that variability within and between panel TMB values increases as the WES TMB values increase. For each panel, prediction limits based on linear regression analyses that modeled panel TMB as a function of WES TMB were calculated and found to approximately capture the intended 95% of observed panel TMB values. Certain cancer types, such as uterine, bladder and colon cancers exhibited greater variability in panel TMB values, compared with lung and head and neck cancers. CONCLUSIONS: Increasing uptake of TMB as a predictive biomarker in the clinic creates an urgent need to bring stakeholders together to agree on the harmonization of key aspects of panel-based TMB estimation, such as the standardization of TMB reporting, standardization of analytical validation studies and the alignment of panel-based TMB values with a reference standard. These harmonization efforts should improve consistency and reliability of panel TMB estimates and aid in clinical decision-making.

Tumor Mutational Burden Is Site Specific in Non-Small-Cell Lung Cancer and Is Highest in Lung Adenocarcinoma Brain Metastases.

PURPOSE: Tumor mutational burden (TMB) is a developing biomarker in non-small-cell lung cancer (NSCLC). Little is known regarding differences between TMB and sample location, histology, or other biomarkers. METHODS: A total of 3,424 unmatched NSCLC samples, including 2,351 lung adenocarcinomas (LUADs) and 1,073 lung squamous cell carcinomas (LUSCs), underwent profiling, including next-generation sequencing of 592 cancer-related genes, programmed death ligand 1 immunohistochemistry, and TMB. The rate TMB of 10 mutations per megabase (Mb) or greater was compared between primary and metastatic LUAD and LUSC. Molecular alteration frequency was compared at a cutoff of 10 mutations/Mb. RESULTS: LUAD metastases were more likely to have a TMB of 10 mutations/Mb or greater compared with primary LUADs (38% v 25%; P < .001), and this difference was most pronounced with brain metastases (61% v 35% for other metastases; P < .001). The median TMB for LUAD brain metastases was 13 mutations/Mb compared with six mutations/Mb for primary LUADs. Variability existed for other LUAD metastasis sites, with adrenal metastases most likely to meet the cutoff of 10 mutations/Mb (51%) and bone metastases least likely to meet the cutoff (19%). TMB was more commonly 10 mutations/Mb or greater for LUSC primary tumors than for LUAD primary tumors (35% v 25%, respectively; P < .001). LUSC metastases were more likely to have a TMB of 10 mutations/Mb or greater than LUSC primary tumors. Poorly differentiated disease was more likely have a TMB of 10 mutations/Mb or greater when stratified by histology and primary tumor or metastasis. Site-specific molecular differences existed at this TMB cutoff including programmed death ligand 1 positivity and STK11 and KRAS mutation rate. CONCLUSION: TMB is a site-specific biomarker in NSCLC with important spatial and histologic differences. TMB is more frequently 10 mutations/Mb or greater in LUAD and LUSC metastases and highest in LUAD brain metastases. Along this TMB cutoff, clinically informative distinctions exist in other tumor profiling characteristics. Further investigation is needed to expand on these findings.

Genomic leftovers: identifying novel microsatellites, over-represented motifs and functional elements in the human genome.

The human genome is 99% complete. This study contributes to filling the 1% gap by enriching previously unknown repeat regions called microsatellites (MST). We devised a Global MST Enrichment (GME) kit to enrich and nextgen sequence 2 colorectal cell lines and 16 normal human samples to illustrate its utility in identifying contigs from reads that do not map to the genome reference. The analysis of these samples yielded 790 novel extra-referential concordant contigs that are observed in more than one sample. We searched for evidence of functional elements in the concordant contigs in two ways: (1) BLAST-ing each contig against normal RNA-Seq samples, (2) Checking for predicted functional elements using GlimmerHMM. Of the 790 concordant contigs, 37 had an exact match to at least one RNA-Seq read; 15 aligned to more than 100 RNA-Seq reads. Of the 249 concordant contigs predicted by GlimmerHMM to have functional elements, 6 had at least one exact RNA-Seq match. BLAST-ing these novel contigs against all publically available sequences confirmed that they were found in human and chimpanzee BAC and FOSMID clones sequenced as part of the original human genome project. These extra-referential contigs predominantly contained pentameric repeats, especially two motifs: AATGG and GTGGA.

Genomic Signatures of Speciation in Sympatric and Allopatric Hawaiian Picture-Winged Drosophila.

The Hawaiian archipelago provides a natural arena for understanding adaptive radiation and speciation. The Hawaiian Drosophila are one of the most diverse endemic groups in Hawaiì with up to 1,000 species. We sequenced and analyzed entire genomes of recently diverged species of Hawaiian picture-winged Drosophila, Drosophila silvestris and Drosophila heteroneura from Hawaiì Island, in comparison with Drosophila planitibia, their sister species from Maui, a neighboring island where a common ancestor of all three had likely occurred. Genome-wide single nucleotide polymorphism patterns suggest the more recent origin of D. silvestris and D. heteroneura, as well as a pervasive influence of positive selection on divergence of the three species, with the signatures of positive selection more prominent in sympatry than allopatry. Positively selected genes were significantly enriched for functional terms related to sensory detection and mating, suggesting that sexual selection played an important role in speciation of these species. In particular, sequence variation in Olfactory receptor and Gustatory receptor genes seems to play a major role in adaptive radiation in Hawaiian pictured-winged Drosophila.

Exome-wide somatic microsatellite variation is altered in cells with DNA repair deficiencies.

Microsatellites (MST), tandem repeats of 1-6 nucleotide motifs, are mutational hot-spots with a bias for insertions and deletions (INDELs) rather than single nucleotide polymorphisms (SNPs). The majority of MST instability studies are limited to a small number of loci, the Bethesda markers, which are only informative for a subset of colorectal cancers. In this paper we evaluate non-haplotype alleles present within next-gen sequencing data to evaluate somatic MST variation (SMV) within DNA repair proficient and DNA repair defective cell lines. We confirm that alleles present within next-gen data that do not contribute to the haplotype can be reliably quantified and utilized to evaluate the SMV without requiring comparisons of matched samples. We observed that SMV patterns found in DNA repair proficient cell lines without DNA repair defects, MCF10A, HEK293 and PD20 RV:D2, had consistent patterns among samples. Further, we were able to confirm that changes in SMV patterns in cell lines lacking functional BRCA2, FANCD2 and mismatch repair were consistent with the different pathways perturbed. Using this new exome sequencing analysis approach we show that DNA instability can be identified in a sample and that patterns of instability vary depending on the impaired DNA repair mechanism, and that genes harboring minor alleles are strongly associated with cancer pathways. The MST Minor Allele Caller used for this study is available at https://github.com/zalmanv/MST_minor_allele_caller.

Large scale comparison of non-human sequences in human sequencing data.

Several studies have demonstrated that unmapped reads in next generation sequencing data could be used to identify infectious agents or structural variants, but there has been no intensive effort to analyze and classify all non-human sequences found in individual large data sets. To identify commonality in non-human sequences by infectious agents and putative contamination events, we analyzed non-human sequences in 150 genomic sequencing data files from the 1000 Genomes Project and observed that 0.13% of reads on average showed similarities to non-human genomes. We compared results among different sample groups divided based on ethnicities, sequencing centers and enrichment methods (whole genome sequencing vs. exome sequencing) and found that sequencing centers had specific signatures of contaminating genomes as 'time stamps'. We also observed many unmapped reads that falsely indicated contamination because of the high similarity of human sequences to sequences in non-human genome assemblies such as mouse and Nicotiana.

The dynamic exome: acquired variants as individuals age.

A singular genome used for inference into population-based studies is a standard method in genomics. Recent studies show that spontaneous genomic variants can propagate into new generations and these changes can contribute to individual cell aging with environmental and evolutionary elements contributing to cumulative genomic variation. However, the contribution of aging to genomic changes in tissue samples remains uncharacterized. Here, we report the impact of aging on individual human exomes and their implications. We found the human genome to be dynamic, acquiring a varying number of mutations with age (5,000 to 50,000 in 9 to 16 years). This equates to a variation rate of 9.6x10(-7) to 8.4x10(-6) bp(-1) year(-1) for nonsynonymous single nucleotide variants and 2.0x10(-4) to 1.0x10(-3) locus(-1) year(-1) for microsatellite loci in these individuals. These mutations span across 3,000 to 13,000 genes, which commonly showed association with Wnt signaling and Gonadotropin releasing hormone receptor pathways, and indicated for individuals a specific and significant enrichment for increased risk for diabetes, kidney failure, cancer, Rheumatoid arthritis, and Alzheimer's disease--conditions usually associated with aging. The results suggest that "age" is an important variable while analyzing an individual human genome to extract individual-specific clinically significant information necessary for personalized genomics.

Nicotine and oxidative stress induced exomic variations are concordant and overrepresented in cancer-associated genes.

Although the connection between cancer and cigarette smoke is well established, nicotine is not characterized as a carcinogen. Here, we used exome sequencing to identify nicotine and oxidative stress-induced somatic mutations in normal human epithelial cells and its correlation with cancer. We identified over 6,400 SNVs, indels and microsatellites in each of the stress exposed cells relative to the control, of which, 2,159 were consistently observed at all nicotine doses. These included 429 nsSNVs including 158 novel and 79 cancer-associated. Over 80% of consistently nicotine induced variants overlap with variations detected in oxidative stressed cells, indicating that nicotine induced genomic alterations could be mediated through oxidative stress. Nicotine induced mutations were distributed across 1,585 genes, of which 49% were associated with cancer. MUC family genes were among the top mutated genes. Analysis of 591 lung carcinoma tumor exomes from The Cancer Genome Atlas (TCGA) revealed that 20% of non-small-cell lung cancer tumors in smokers have mutations in at least one of the MUC4, MUC6 or MUC12 genes in contrast to only 6% in non-smokers. These results indicate that nicotine induces genomic variations, promotes instability potentially mediated by oxidative stress, implicating nicotine in carcinogenesis, and establishes MUC genes as potential targets.

Discretized Gaussian mixture for genotyping of microsatellite loci containing homopolymer runs.

MOTIVATION: Inferring lengths of inherited microsatellite alleles with single base pair resolution from short sequence reads is challenging due to several sources of noise caused by the repetitive nature of microsatellites and the technologies used to generate raw sequence data. RESULTS: We have developed a program, GenoTan, using a discretized Gaussian mixture model combined with a rules-based approach to identify inherited variation of microsatellite loci from short sequence reads without paired-end information. It effectively distinguishes length variants from noise including insertion/deletion errors in homopolymer runs by addressing the bidirectional aspect of insertion and deletion errors in sequence reads. Here we first introduce a homopolymer decomposition method which estimates error bias toward insertion or deletion in homopolymer sequence runs. Combining these approaches, GenoTan was able to genotype 94.9% of microsatellite loci accurately from simulated data with 40x sequence coverage quickly while the other programs showed <90% correct calls for the same data and required 5∼30× more computational time than GenoTan. It also showed the highest true-positive rate for real data using mixed sequence data of two Drosophila inbred lines, which was a novel validation approach for genotyping. AVAILABILITY: GenoTan is open-source software available at http://genotan.sourceforge.net.

Characterizing the Genetic Basis for Nicotine Induced Cancer Development: A Transcriptome Sequencing Study.

Nicotine is a known risk factor for cancer development and has been shown to alter gene expression in cells and tissue upon exposure. We used Illumina® Next Generation Sequencing (NGS) technology to gain unbiased biological insight into the transcriptome of normal epithelial cells (MCF-10A) to nicotine exposure. We generated expression data from 54,699 transcripts using triplicates of control and nicotine stressed cells. As a result, we identified 138 differentially expressed transcripts, including 39 uncharacterized genes. Additionally, 173 transcripts that are primarily associated with DNA replication, recombination, and repair showed evidence for alternative splicing. We discovered the greatest nicotine stress response by HPCAL4 (up-regulated by 4.71 fold) and NPAS3 (down-regulated by -2.73 fold); both are genes that have not been previously implicated in nicotine exposure but are linked to cancer. We also discovered significant down-regulation (-2.3 fold) and alternative splicing of NEAT1 (lncRNA) that may have an important, yet undiscovered regulatory role. Gene ontology analysis revealed nicotine exposure influenced genes involved in cellular and metabolic processes. This study reveals previously unknown consequences of nicotine stress on the transcriptome of normal breast epithelial cells and provides insight into the underlying biological influence of nicotine on normal cells, marking the foundation for future studies.

ReviSTER: an automated pipeline to revise misaligned reads to simple tandem repeats.

MOTIVATION: Simple tandem repeats are highly variable genetic elements and widespread in genomes of many organisms. Next-generation sequencing technologies have enabled a robust comparison of large numbers of simple tandem repeat loci; however, analysis of their variation using traditional sequence analysis approaches still remains limiting and problematic due to variants occurring in repeat sequences confusing alignment programs into mapping sequence reads to incorrect loci when the sequence reads are significantly different from the reference sequence. RESULTS: We have developed a program, ReviSTER, which is an automated pipeline using a 'local mapping reference reconstruction method' to revise mismapped or partially misaligned reads at simple tandem repeat loci. RevisSTER estimates alleles of repeat loci using a local alignment method and creates temporary local mapping reference sequences, and finally remaps reads to the local mapping references. Using this approach, ReviSTER was able to successfully revise reads misaligned to repeat loci from both simulated data and real data. AVAILABILITY: ReviSTER is open-source software available at http://revister.sourceforge.net. CONTACT: garner@vbi.vt.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Improved variation calling via an iterative backbone remapping and local assembly method for bacterial genomes.

Sequencing data analysis remains limiting and problematic, especially for low complexity repeat sequences and transposon elements due to inherent sequencing errors and short sequence read lengths. We have developed a program, ReviSeq, which uses a hybrid method composed of iterative remapping and local assembly upon a bacterial sequence backbone. Application of this method to six Brucella suis field isolates compared to the newly revised B. suis 1330 reference genome identified on average 13, 15, 19 and 9 more variants per sample than STAMPY/SAMtools, BWA/SAMtools, iCORN and BWA/PINDEL pipelines, and excluded on average 4, 2, 3 and 19 variants per sample, respectively. In total, using this iterative approach, we identified on average 87 variants including SNVs, short INDELs and long INDELs per strain when compared to the reference. Our program outperforms other methods especially for long INDEL calling. The program is available at http://reviseq.sourceforge.net.

ESTclean: a cleaning tool for next-gen transcriptome shotgun sequencing.

BACKGROUND: With the advent of next-generation sequencing (NGS) technologies, full cDNA shotgun sequencing has become a major approach in the study of transcriptomes, and several different protocols in 454 sequencing have been invented. As each protocol uses its own short DNA tags or adapters attached to the ends of cDNA fragments for labeling or sequencing, different contaminants may lead to mis-assembly and inaccurate sequence products. RESULTS: We have designed and implemented a new program for raw sequence cleaning in a graphical user interface and a batch script. The cleaning process consists of several modules including barcode trimming, sequencing adapter trimming, amplification primer trimming, poly-A tail trimming, vector screening and low quality region trimming. These modules can be combined based on various sequencing applications. CONCLUSIONS: ESTclean is a software package not only for cleaning cDNA sequences, but also for helping to develop sequencing protocols by providing summary tables and figures for sequencing quality control in a graphical user interface. It outperforms in cleaning read sequences from complicated sequencing protocols which use barcodes and multiple amplification primers.

Comparison of genome diversity of Brucella spp. field isolates using Universal Bio-signature Detection Array and whole genome sequencing reveals limitations of current diagnostic methods.

The detection and identification of bio-threat agents and the study of host-pathogen interactions require a high-resolution detection platform capable of discerning closely related species. Diverse analysis methods are used to identify pathogens, specifically Brucella species or biovars. In this study, we compared four diagnostic approaches including serology-based biochemical test, PCR assay, microarray analysis using a Universal Bio-signature Detection Array (UBDA) and whole genome "deep" sequencing for Brucella organisms including a number of field isolates. We found that although there was frequent agreement among the different tests, some tests gave compound/contradictory results that were a consequence of species diversity due to mixed infections or minor contaminants as measured by UBDA and validated from whole genome sequence. By comparing these analysis techniques, we demonstrate that standard diagnostics used in the field are limited in their ability to identify genomic DNA contaminants in field isolates while UBDA and sequencing analysis are highly sensitive in tracing genomic differences among the isolates.

Genome-wide DNA methylation analysis reveals novel epigenetic changes in chronic lymphocytic leukemia.

We conducted a genome-wide DNA methylation analysis in CD19 (+) B-cells from chronic lymphocytic leukemia (CLL) patients and normal control samples using reduced representation bisulfite sequencing (RRBS). The methylation status of 1.8-2.3 million CpGs in the CLL genome was determined; about 45% of these CpGs were located in more than 23,000 CpG islands (CGIs). While global CpG methylation was similar between CLL and normal B-cells, 1764 gene promoters were identified as being differentially methylated in at least one CLL sample when compared with normal B-cell samples. Nineteen percent of the differentially methylated genes were involved in transcriptional regulation. Aberrant hypermethylation was found in all HOX gene clusters and a significant number of WNT signaling pathway genes. Hypomethylation occurred more frequently in the gene body including introns, exons, and 3'-UTRs in CLL. The NFATc1 P2 promoter and first intron was found to be hypomethylated and correlated with upregulation of both NFATc1 RNA and protein expression levels in CLL suggesting that an epigenetic mechanism is involved in the constitutive activation of NFAT activity in CLL cells. This comprehensive DNA methylation analysis will further our understanding of the epigenetic contribution to cellular dysfunction in CLL.

Identification of early zygotic genes in the yellow fever mosquito Aedes aegypti and discovery of a motif involved in early zygotic genome activation.

During early embryogenesis the zygotic genome is transcriptionally silent and all mRNAs present are of maternal origin. The maternal-zygotic transition marks the time over which embryogenesis changes its dependence from maternal RNAs to zygotically transcribed RNAs. Here we present the first systematic investigation of early zygotic genes (EZGs) in a mosquito species and focus on genes involved in the onset of transcription during 2-4 hr. We used transcriptome sequencing to identify the "pure" (without maternal expression) EZGs by analyzing transcripts from four embryonic time ranges of 0-2, 2-4, 4-8, and 8-12 hr, which includes the time of cellular blastoderm formation and up to the start of gastrulation. Blast of 16,789 annotated transcripts vs. the transcriptome reads revealed evidence for 63 (P<0.001) and 143 (P<0.05) nonmaternally derived transcripts having a significant increase in expression at 2-4 hr. One third of the 63 EZG transcripts do not have predicted introns compared to 10% of all Ae. aegypti genes. We have confirmed by RT-PCR that zygotic transcription starts as early as 2-3 hours. A degenerate motif VBRGGTA was found to be overrepresented in the upstream sequences of the identified EZGs using a motif identification software called SCOPE. We find evidence for homology between this motif and the TAGteam motif found in Drosophila that has been implicated in EZG activation. A 38 bp sequence in the proximal upstream sequence of a kinesin light chain EZG (KLC2.1) contains two copies of the mosquito motif. This sequence was shown to support EZG transcription by luciferase reporter assays performed on injected early embryos, and confers early zygotic activity to a heterologous promoter from a divergent mosquito species. The results of these studies are consistent with the model of early zygotic genome activation via transcriptional activators, similar to what has been found recently in Drosophila.

Draft genome sequence and genetic transformation of the oleaginous alga Nannochloropis gaditana.

The potential use of algae in biofuels applications is receiving significant attention. However, none of the current algal model species are competitive production strains. Here we present a draft genome sequence and a genetic transformation method for the marine microalga Nannochloropsis gaditana CCMP526. We show that N. gaditana has highly favourable lipid yields, and is a promising production organism. The genome assembly includes nuclear (~29 Mb) and organellar genomes, and contains 9,052 gene models. We define the genes required for glycerolipid biogenesis and detail the differential regulation of genes during nitrogen-limited lipid biosynthesis. Phylogenomic analysis identifies genetic attributes of this organism, including unique stramenopile photosynthesis genes and gene expansions that may explain the distinguishing photoautotrophic phenotypes observed. The availability of a genome sequence and transformation methods will facilitate investigations into N. gaditana lipid biosynthesis and permit genetic engineering strategies to further improve this naturally productive alga.

Complete genome sequence of Brucella suis VBI22, isolated from bovine milk.

Brucella suis is the causative agent of swine brucellosis and is known to be able to infect several different hosts, including cattle, dogs, and horses, without causing disease symptoms. Here we report the complete genome sequence of Brucella suis VBI22, which was isolated from raw milk from an infected cow.