Kocher, Jean‐Pierre

Abstract Background: Given the high technical reproducibility and orders of magnitude greater resolution than microarrays, next-generation sequencing of mRNA (RNA-Seq) is quickly becoming the de facto standard for measuring levels of gene expression in biological experiments. Two important questions must be taken into consideration when designing a particular experiment, namely, 1) how deep does one need to sequence? and, 2) how many biological replicates are necessary to observe a significant change in expression? Results: Based on the gene expression distributions from 127 RNA-Seq experiments, we find evidence that 91% ± 4% of all annotated genes are sequenced at a frequency of 0.1 times per million bases mapped, regardless of sample source. Based on this observation, and combining this information with other parameters such as biological variation and technical variation that we empirically estimate from our large datasets, we developed a model to estimate the statistical power needed to identify differentially expressed genes from RNA-Seq experiments. Conclusions: Our results provide a needed reference for ensuring RNA-Seq gene expression studies are conducted with the optimally sample size, power, and sequencing depth. We also make available both R code and an Excel worksheet for investigators to calculate for their own experiments.

Abstract Motivation: Batch effects are due to probe-specific systematic variation between groups of samples (batches) resulting from experimental features that are not of biological interest. Principal component analysis (PCA) is commonly used as a visual tool to determine whether batch effects exist after applying a global normalization method. However, PCA yields linear combinations of the variables that contribute maximum variance and thus will not necessarily detect batch effects if they are not the largest source of variability in the data. Results: We present an extension of PCA to quantify the existence of batch effects, called guided PCA (gPCA). We describe a test statistic that uses gPCA to test whether a batch effect exists. We apply our proposed test statistic derived using gPCA to simulated data and to two copy number variation case studies: the first study consisted of 614 samples from a breast cancer family study using Illumina Human 660 bead-chip arrays, whereas the second case study consisted of 703 samples from a family blood pressure study that used Affymetrix SNP Array 6.0. We demonstrate that our statistic has good statistical properties and is able to identify significant batch effects in two copy number variation case studies. Conclusion: We developed a new statistic that uses gPCA to identify whether batch effects exist in high-throughput genomic data. Although our examples pertain to copy number data, gPCA is general and can be used on other data types as well. Availability and implementation: The gPCA R package (Available via CRAN) provides functionality and data to perform the methods in this article. Contact: reesese@vcu.edu or eckel@mayo.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Abstract Zebrafish ( Danio rerio ) is a popular vertebrate model organism largely deployed using outbred laboratory animals. The nonisogenic nature of the zebrafish as a model system offers the opportunity to understand natural variations and their effect in modulating phenotype. In an effort to better characterize the range of natural variation in this model system and to complement the zebrafish reference genome project, the whole genome sequence of a wild zebrafish at 39-fold genome coverage was determined. Comparative analysis with the zebrafish reference genome revealed approximately 5.2 million single nucleotide variations and over 1.6 million insertion–deletion variations. This dataset thus represents a new catalog of genetic variations in the zebrafish genome. Further analysis revealed selective enrichment for variations in genes involved in immune function and response to the environment, suggesting genome-level adaptations to environmental niches. We also show that human disease gene orthologs in the sequenced wild zebrafish genome show a lower ratio of nonsynonymous to synonymous single nucleotide variations.

Abstract Motivation: KRAS is commonly mutated in a variety of cancers including lung cancer. The KRAS gene is frequently mutated at codons 12 and 13 in lung adenocarcinomas in patients with a history of smoking. Tumors harboring an activating KRAS mutation are aggressive and are often resistant to available therapies. In the present study, we set out to identify pathways that are specifically altered in lung cancer patients whose tumors harbor a KRAS mutation using next generation sequencing technology. Methods: We performed 50nt paired-end RNA-sequencing in 15 lung adenocarcinoma samples (8 and 7 samples with and without KRAS mutation). Reads were aligned to genome and exon junctions using Illumina's alignment tool ELAND_RNA. CASAVA and Genome Studio data analysis software were used to obtain read counts for genes, exons and exon junctions. We applied a variety of computational methods (Casper R package, Bowtie, TopHat) and softwares (Partek, R statistical software, JMP, Ingenuity Pathway Anlaysis, DAVID) to carry out our analyses. Results: Differential gene expression and splicing analysis were performed between the two groups. We identified 115 genes that were differentially expressed and 112 genes that consist of splicing variants with at least 2 fold changes and p-value < 0.01. We randomly selected 6/15 samples and performed real-time qRT-PCR for 6 differentially expressed genes. Significant correlations were observed ranging from 0.44 to 0.83, when qRT-PCR results were compared with RNA-sequencing expression data. Pathway analysis with 115 differentially expressed genes and 112 splicing variants revealed that the most significant pathway is composed entirely of NFκB focus genes, suggesting that there is a direct connection between oncogenic KRAS and activation of the NFκB signaling pathway. Conclusions: NFκB has been implicated in KRas-mediated formation of early stage lung adenomas in the LSL-Kas mouse model. Our data indicate that this connection also occurs in human lung cancer and establish NFκB activation as a key manifestation of KRAS mutation in human lung cancer. Hence drugs targeting NFκB and NFκB related genes may potentially be helpful for the treatment of patients with oncogenic KRAS mutations. (Supported in part by grants from the 26.2 with Donna Foundation and the Florida Department of Health Bankhead/Coley program.) Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4975. doi:10.1158/1538-7445.AM2011-4975

Abstract The role of fusion gene transcripts such as BRC-ABL1 has been long appreciated in hematopoietic malignancies. Recent evidence from next generation sequencing projects has suggested that gene fusion events and the resultant chimaeric transcripts may be expressed in solid tumors. We have developed a novel bioinformatics analytical pipeline to detect fusion gene transcripts from paired-end mRNA-seq data. The bioinformatics tool used for fusion transcript discovery employs multiple steps of false positive filtering and nominates the fusion transcript candidates with high confidence (approaching 100%). The screening and validation of the fusion candidates were quickly carried out using the recommended primer design regions as one of the outputs of the SnowShoes-FD pipeline. This pipeline was used to analyze the transcriptome of 22 breast cancer cell lines and 9 non-transformed breast cell populations. Fifty-four fusion candidates were nominated, all of which were validated using reverse transcription PCR and Sanger sequencing. Five fusion products were predicted to have a second fusion junction point between two fusion partners. These 54 fusion transcripts consist of 103 partner genes that are involved in cell cycle and/or nuclear receptor signaling. No fusion transcripts were identified from the non-transformed breast cell lines. We subsequently analyzed a panel of primary breast tumors, 8 each HER2+, triple negative, and ER+. Fifteen novel fusion transcript candidates have been nominated. Validation and functional analysis of these candidates is in progress. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr LB-276. doi:10.1158/1538-7445.AM2011-LB-276

Abstract Summary: Reduced representation bisulfite sequencing (RRBS) is a cost-effective approach for genome-wide methylation pattern profiling. Analyzing RRBS sequencing data is challenging and specialized alignment/mapping programs are needed. Although such programs have been developed, a comprehensive solution that provides researchers with good quality and analyzable data is still lacking. To address this need, we have developed a Streamlined Analysis and Annotation Pipeline for RRBS data (SAAP-RRBS) that integrates read quality assessment/clean-up, alignment, methylation data extraction, annotation, reporting and visualization. This package facilitates a rapid transition from sequencing reads to a fully annotated CpG methylation report to biological interpretation. Availability and implementation: SAAP-RRBS is freely available to non-commercial users at the web site http://ndc.mayo.edu/mayo/research/biostat/stand-alone-packages.cfm. Contact: baheti.saurabh@mayo.edu or sun.zhifu@mayo.edu Supplementary Information: Supplementary data are available at Bioinformatics online.

Insulin regulates many cellular processes, but the full impact of insulin deficiency on cellular functions remains to be defined. Applying a mass spectrometry–based nontargeted metabolomics approach, we report here alterations of 330 plasma metabolites representing 33 metabolic pathways during an 8-h insulin deprivation in type 1 diabetic individuals. These pathways included those known to be affected by insulin such as glucose, amino acid and lipid metabolism, Krebs cycle, and immune responses and those hitherto unknown to be altered including prostaglandin, arachidonic acid, leukotrienes, neurotransmitters, nucleotides, and anti-inflammatory responses. A significant concordance of metabolome and skeletal muscle transcriptome–based pathways supports an assumption that plasma metabolites are chemical fingerprints of cellular events. Although insulin treatment normalized plasma glucose and many other metabolites, there were 71 metabolites and 24 pathways that differed between nondiabetes and insulin-treated type 1 diabetes. Confirmation of many known pathways altered by insulin using a single blood test offers confidence in the current approach. Future research needs to be focused on newly discovered pathways affected by insulin deficiency and systemic insulin treatment to determine whether they contribute to the high morbidity and mortality in T1D despite insulin treatment.

We conducted a genome-wide association study to identify novel genes influencing diastolic blood pressure (BP) response to hydrochlorothiazide, a commonly prescribed thiazide diuretic preferred for the treatment of high BP. Affymetrix GeneChip Human Mapping 100K Arrays were used to measure single nucleotide polymorphisms across the 22 autosomes in 194 non-Hispanic black subjects and 195 non-Hispanic white subjects with essential hypertension selected from opposite tertiles of the race- and sex-specific distributions of age-adjusted diastolic BP response to hydrochlorothiazide (25 mg daily, PO, for 4 weeks). The black sample consisted of 97 “good” responders (diastolic BP response [mean±SD]=−18.3±4.2 mm Hg; age=47.1±6.1 years; 51.5% women) and 97 “poor” responders (diastolic BP response=−0.18±4.3; age=47.4±6.5 years; 51.5% women). Haplotype trend regression identified a region of chromosome 12q15 in which haplotypes constructed from 3 successive single nucleotide polymorphisms (rs317689, rs315135, and rs7297610) in proximity to lysozyme ( LYZ ), YEATS domain containing 4 ( YEATS4 ), and fibroblast growth receptor substrate 2 ( FRS2 ) were significantly associated with diastolic BP response (nominal P =2.39×10 −7 ; Bonferroni corrected P =0.024; simulated experiment-wise P =0.040). Genotyping of 35 additional single nucleotide polymorphisms selected to “tag” linkage disequilibrium blocks in these genes provided corroboration that variation in LYZ and YEATS4 was associated with diastolic BP response in a statistically independent data set of 291 black subjects and in the sample of 294 white subjects. These results support the use of genome-wide association analyses to identify novel genes influencing antihypertensive drug responses.