Genome sequencing reveals loci under artificial selection that underlie disease phenotypes in the laboratory rat.

Large numbers of inbred laboratory rat strains have been developed for a range of complex disease phenotypes. To gain insights into the evolutionary pressures underlying selection for these phenotypes, we sequenced the genomes of 27 rat strains, including 11 models of hypertension, diabetes, and insulin resistance, along with their respective control strains. Altogether, we identified more than 13 million single-nucleotide variants, indels, and structural variants across these rat strains. Analysis of strain-specific selective sweeps and gene clusters implicated genes and pathways involved in cation transport, angiotensin production, and regulators of oxidative stress in the development of cardiovascular disease phenotypes in rats. Many of the rat loci that we identified overlap with previously mapped loci for related traits in humans, indicating the presence of shared pathways underlying these phenotypes in rats and humans. These data represent a step change in resources available for evolutionary analysis of complex traits in disease models.

Clinical heterogeneity of mitochondrial NAD kinase deficiency caused by a NADK2 start loss variant.

Mitochondrial NAD kinase deficiency (NADK2D, OMIM #615787) is a rare autosomal recessive disorder of NADPH biosynthesis that can cause hyperlysinemia and dienoyl-CoA reductase deficiency (DECRD, OMIM #616034). NADK2 deficiency has been reported in only three unrelated patients. Two had severe, unremitting disease; one died at 4 months and the other at 5 years of age. The third was a 10 year old female with CNS anomalies, ataxia, and incoordination. In two cases mutations in NADK2 have been demonstrated. Here, we report the fourth known case, a 15 year old female with normal intelligence and a mild clinical and biochemical phenotype presumably without DECRD. Her clinical symptoms, which are now stable, became evident at the age of 9 with the onset of decreased visual acuity, bilateral optic atrophy, nystagmus, episodic lower extremity weakness, peripheral neuropathy, and gait abnormalities. Plasma amino acid levels were within normal limits except for mean lysine and proline levels that were 3.7 and 2.5 times the upper limits of normal. Whole exome sequencing (WES) revealed homozygosity for a g.36241900 A>G p. Met1Val start loss mutation in the primary NADK2 transcript (NM_001085411.1) encoding the 442 amino acid isoform. This presumed hypomorphic mutation has not been previously reported and is absent from the v1000GP, EVS, and ExAC databases. Our patient's normal intelligence and stable disease expands the clinical heterogeneity and the prognosis associated with NADK2 deficiency. Our findings also clarify the mechanism underlying NADK2 deficiency and suggest that this disease should be ruled out in cases of hyperlysinemia, especially those with visual loss, and neurological phenotypes.

Prostate cancer risk locus at 8q24 as a regulatory hub by physical interactions with multiple genomic loci across the genome.

Chromosome 8q24 locus contains regulatory variants that modulate genetic risk to various cancers including prostate cancer (PC). However, the biological mechanism underlying this regulation is not well understood. Here, we developed a chromosome conformation capture (3C)-based multi-target sequencing technology and systematically examined three PC risk regions at the 8q24 locus and their potential regulatory targets across human genome in six cell lines. We observed frequent physical contacts of this risk locus with multiple genomic regions, in particular, inter-chromosomal interaction with CD96 at 3q13 and intra-chromosomal interaction with MYC at 8q24. We identified at least five interaction hot spots within the predicted functional regulatory elements at the 8q24 risk locus. We also found intra-chromosomal interaction genes PVT1, FAM84B and GSDMC and inter-chromosomal interaction gene CXorf36 in most of the six cell lines. Other gene regions appeared to be cell line-specific, such as RRP12 in LNCaP, USP14 in DU-145 and SMIN3 in lymphoblastoid cell line. We further found that the 8q24 functional domains more likely interacted with genomic regions containing genes enriched in critical pathways such as Wnt signaling and promoter motifs such as E2F1 and TCF3. This result suggests that the risk locus may function as a regulatory hub by physical interactions with multiple genes important for prostate carcinogenesis. Further understanding genetic effect and biological mechanism of these chromatin interactions will shed light on the newly discovered regulatory role of the risk locus in PC etiology and progression.

Changes in Daily Apparent Diffusion Coefficient on Fully Quantitative Magnetic Resonance Imaging Correlate With Established Genomic Pathways of Radiation Sensitivity and Reveal Novel Biologic Associations.

PURPOSE: Changes in quantitative magnetic resonance imaging (qMRI) are frequently observed during chemotherapy or radiation therapy (RT). It is hypothesized that qMRI features are reflective of underlying tissue responses. It's unknown what underlying genomic characteristics underly qMRI changes. We hypothesized that qMRI changes may correlate with DNA damage response (DDR) capacity within human tumors. Therefore, we designed the current study to correlate qMRI changes from daily RT treatment with underlying tumor transcriptomic profiles. METHODS AND MATERIALS: Study participants were prospectively enrolled (National Clinical Trial 03500081). RNA expression levels for 757 genes from pretreatment biopsies were obtained using a custom panel that included signatures of radiation sensitivity and DDR. Daily qMRI data were obtained from a 1.5 Tesla MR linear accelerator. Using these images, d-slow, d-star, perfusion, and apparent diffusion coefficient-mean values in tumors were plotted per-fraction, over time, and associated with genomic pathways. RESULTS: A total of 1022 qMRIs were obtained from 39 patients and both genomic data and qMRI data from 27 total patients. For 20 of those patients, we also generated normal tissue transcriptomic data. Radio sensitivity index values most closely associated with tissue of origin. Multiple genomic pathways including DNA repair, peroxisome, late estrogen receptor responses, KRAS signaling, and UV response were significantly associated with qMRI feature changes (P < .001). CONCLUSIONS: Genomic pathway associations across metabolic, RT sensitivity, and DDR pathways indicate common tumor biology that may correlate with qMRI changes during a course of treatment. Such data provide hypothesis-generating novel mechanistic insight into the biologic meaning of qMRI changes during treatment and enable optimal selection of imaging biomarkers for biologically MR-guided RT.

Characterization of human plasma-derived exosomal RNAs by deep sequencing.

BACKGROUND: Exosomes, endosome-derived membrane microvesicles, contain specific RNA transcripts that are thought to be involved in cell-cell communication. These RNA transcripts have great potential as disease biomarkers. To characterize exosomal RNA profiles systemically, we performed RNA sequencing analysis using three human plasma samples and evaluated the efficacies of small RNA library preparation protocols from three manufacturers. In all we evaluated 14 libraries (7 replicates). RESULTS: From the 14 size-selected sequencing libraries, we obtained a total of 101.8 million raw single-end reads, an average of about 7.27 million reads per library. Sequence analysis showed that there was a diverse collection of the exosomal RNA species among which microRNAs (miRNAs) were the most abundant, making up over 42.32% of all raw reads and 76.20% of all mappable reads. At the current read depth, 593 miRNAs were detectable. The five most common miRNAs (miR-99a-5p, miR-128, miR-124-3p, miR-22-3p, and miR-99b-5p) collectively accounted for 48.99% of all mappable miRNA sequences. MiRNA target gene enrichment analysis suggested that the highly abundant miRNAs may play an important role in biological functions such as protein phosphorylation, RNA splicing, chromosomal abnormality, and angiogenesis. From the unknown RNA sequences, we predicted 185 potential miRNA candidates. Furthermore, we detected significant fractions of other RNA species including ribosomal RNA (9.16% of all mappable counts), long non-coding RNA (3.36%), piwi-interacting RNA (1.31%), transfer RNA (1.24%), small nuclear RNA (0.18%), and small nucleolar RNA (0.01%); fragments of coding sequence (1.36%), 5' untranslated region (0.21%), and 3' untranslated region (0.54%) were also present. In addition to the RNA composition of the libraries, we found that the three tested commercial kits generated a sufficient number of DNA fragments for sequencing but each had significant bias toward capturing specific RNAs. CONCLUSIONS: This study demonstrated that a wide variety of RNA species are embedded in the circulating vesicles. To our knowledge, this is the first report that applied deep sequencing to discover and characterize profiles of plasma-derived exosomal RNAs. Further characterization of these extracellular RNAs in diverse human populations will provide reference profiles and open new doors for the development of blood-based biomarkers for human diseases.

IreB, a Ser/Thr kinase substrate, influences antimicrobial resistance in Enterococcus faecalis.

Enterococcus faecalis is a Gram-positive bacterium that is a major cause of hospital-acquired infections, in part due to its intrinsic resistance to cephalosporins. The mechanism that confers intrinsic cephalosporin resistance in enterococci remains incompletely defined. Previously, we have shown that the Ser/Thr protein kinase and phosphatase pair IreK and IreP act antagonistically to regulate cephalosporin resistance in E. faecalis. We hypothesize that IreK senses antibiotic-induced cell wall damage and activates a signaling pathway leading to antibiotic resistance. However, the factors downstream of IreK have not yet been identified. To discover such factors, suppressor mutations that restored resistance to a ΔireK kinase mutant were identified. Mutations were found in IreB, a highly conserved gene of unknown function that is widespread among low-GC Gram-positive bacteria. We show that IreB plays a negative regulatory role in cephalosporin resistance and is an endogenous substrate of both IreK and IreP. IreB is phosphorylated on conserved threonine residues, and mutations at these sites impair cephalosporin resistance. Our results are consistent with a model in which the activity of IreB is modulated by IreK-dependent phosphorylation in a signaling pathway required for cephalosporin resistance and begin to shed light on the function of this previously uncharacterized protein.

Genetic Mapping of Multiple Traits Identifies Novel Genes for Adiposity, Lipids, and Insulin Secretory Capacity in Outbred Rats.

Despite the successes of human genome-wide association studies, the causal genes underlying most metabolic traits remain unclear. We used outbred heterogeneous stock (HS) rats, coupled with expression data and mediation analysis, to identify quantitative trait loci (QTLs) and candidate gene mediators for adiposity, glucose tolerance, serum lipids, and other metabolic traits. Physiological traits were measured in 1,519 male HS rats, with liver and adipose transcriptomes measured in >410 rats. Genotypes were imputed from low-coverage whole-genome sequencing. Linear mixed models were used to detect physiological and expression QTLs (pQTLs and eQTLs, respectively), using both single nucleotide polymorphism (SNP)- and haplotype-based models for pQTL mapping. Genes with cis-eQTLs that overlapped pQTLs were assessed as causal candidates through mediation analysis. We identified 14 SNP-based pQTLs and 19 haplotype-based pQTLs, of which 10 were in common. Using mediation, we identified the following genes as candidate mediators of pQTLs: Grk5 for fat pad weight and serum triglyceride pQTLs on Chr1, Krtcap3 for fat pad weight and serum triglyceride pQTLs on Chr6, Ilrun for a fat pad weight pQTL on Chr20, and Rfx6 for a whole pancreatic insulin content pQTL on Chr20. Furthermore, we verified Grk5 and Ktrcap3 using gene knockdown/out models, thereby shedding light on novel regulators of obesity.

Identification of somatic mutations in non-small cell lung carcinomas using whole-exome sequencing.

Lung cancer is the leading cause of cancer-related death, with non-small cell lung cancer (NSCLC) being the predominant form of the disease. Most lung cancer is caused by the accumulation of genomic alterations due to tobacco exposure. To uncover its mutational landscape, we performed whole-exome sequencing in 31 NSCLCs and their matched normal tissue samples. We identified both common and unique mutation spectra and pathway activation in lung adenocarcinomas and squamous cell carcinomas, two major histologies in NSCLC. In addition to identifying previously known lung cancer genes (TP53, KRAS, EGFR, CDKN2A and RB1), the analysis revealed many genes not previously implicated in this malignancy. Notably, a novel gene CSMD3 was identified as the second most frequently mutated gene (next to TP53) in lung cancer. We further demonstrated that loss of CSMD3 results in increased proliferation of airway epithelial cells. The study provides unprecedented insights into mutational processes, cellular pathways and gene networks associated with lung cancer. Of potential immediate clinical relevance, several highly mutated genes identified in our study are promising druggable targets in cancer therapy including ALK, CTNNA3, DCC, MLL3, PCDHIIX, PIK3C2B, PIK3CG and ROCK2.

Making a definitive diagnosis: successful clinical application of whole exome sequencing in a child with intractable inflammatory bowel disease.

PURPOSE: We report a male child who presented at 15 months with perianal abscesses and proctitis, progressing to transmural pancolitis with colocutaneous fistulae, consistent with a Crohn disease-like illness. The age and severity of the presentation suggested an underlying immune defect; however, despite comprehensive clinical evaluation, we were unable to arrive at a definitive diagnosis, thereby restricting clinical management. METHODS: We sought to identify the causative mutation(s) through exome sequencing to provide the necessary additional information required for clinical management. RESULTS: After sequencing, we identified 16,124 variants. Subsequent analysis identified a novel, hemizygous missense mutation in the X-linked inhibitor of apoptosis gene, substituting a tyrosine for a highly conserved and functionally important cysteine. X-linked inhibitor of apoptosis was not previously associated with Crohn disease but has a central role in the proinflammatory response and bacterial sensing through the NOD signaling pathway. The mutation was confirmed by Sanger sequencing in a licensed clinical laboratory. Functional assays demonstrated an increased susceptibility to activation-induced cell death and defective responsiveness to NOD2 ligands, consistent with loss of normal X-linked inhibitor of apoptosis protein function in apoptosis and NOD2 signaling. CONCLUSIONS: Based on this medical history, genetic and functional data, the child was diagnosed as having an X-linked inhibitor of apoptosis deficiency. Based on this finding, an allogeneic hematopoietic progenitor cell transplant was performed to prevent the development of life-threatening hemophagocytic lymphohistiocytosis, in concordance with the recommended treatment for X-linked inhibitor of apoptosis deficiency. At >42 days posttransplant, the child was able to eat and drink, and there has been no recurrence of gastrointestinal disease, suggesting this mutation also drove the gastrointestinal disease. This report describes the identification of a novel cause of inflammatory bowel disease. Equally importantly, it demonstrates the power of exome sequencing to render a molecular diagnosis in an individual patient in the setting of a novel disease, after all standard diagnoses were exhausted, and illustrates how this technology can be used in a clinical setting.

Interpreting Sequence Variation in PDAC-Predisposing Genes Using a Multi-Tier Annotation Approach Performed at the Gene, Patient, and Cohort Level.

We investigated germline variation in pancreatic ductal adenocarcinoma (PDAC) predisposition genes in 535 patients, using a custom-built panel and a new complementary bioinformatic approach. Our panel assessed genes belonging to DNA repair, cell cycle checkpoints, migration, and preneoplastic pancreatic conditions. Our bioinformatics approach integrated annotations of variants by using data derived from both germline and somatic references. This integrated approach with expanded evidence enabled us to consider patterns even among private mutations, supporting a functional role for certain alleles, which we believe enhances individualized medicine beyond classic gene-centric approaches. Concurrent evaluation of three levels of evidence, at the gene, sample, and cohort level, has not been previously done. Overall, we identified in PDAC patient germline samples, 12% with mutations previously observed in pancreatic cancers, 23% with mutations previously discovered by sequencing other human tumors, and 46% with mutations with germline associations to cancer. Non-polymorphic protein-coding pathogenic variants were found in 18.4% of patient samples. Moreover, among patients with metastatic PDAC, 16% carried at least one pathogenic variant, and this subgroup was found to have an improved overall survival (22.0 months versus 9.8; p=0.008) despite a higher pre-treatment CA19-9 level (p=0.02). Genetic alterations in DNA damage repair genes were associated with longer overall survival among patients who underwent resection surgery (92 months vs. 46; p=0.06). ATM alterations were associated with more frequent metastatic stage (p = 0.04) while patients with BRCA1 or BRCA2 alterations had improved overall survival (79 months vs. 39; p=0.05). We found that mutations in genes associated with chronic pancreatitis were more common in non-white patients (p<0.001) and associated with longer overall survival (52 months vs. 26; p=0.004), indicating the need for greater study of the relationship among these factors. More than 90% of patients were found to have variants of uncertain significance, which is higher than previously reported. Furthermore, we generated 3D models for selected mutant proteins, which suggested distinct mechanisms underlying their dysfunction, likely caused by genetic alterations. Notably, this type of information is not predictable from sequence alone, underscoring the value of structural bioinformatics to improve genomic interpretation. In conclusion, the variation in PDAC predisposition genes appears to be more extensive than anticipated. This information adds to the growing body of literature on the genomic landscape of PDAC and brings us closer to a more widespread use of precision medicine for this challenging disease.

Fine-mapping a locus for glucose tolerance using heterogeneous stock rats.

Heterogeneous stock (HS) animals provide the ability to map quantitative trait loci at high resolution [<5 Megabase (Mb)] in a relatively short time period. In the current study, we hypothesized that the HS rat colony would be useful for fine-mapping a region on rat chromosome 1 that has previously been implicated in glucose regulation. We administered a glucose tolerance test to 515 HS rats and genotyped these animals with 69 microsatellite markers, spaced an average distance of <1 Mb apart, on a 67 Mb region of rat chromosome 1. Using regression modeling of inferred haplotypes based on a hidden Markov model reconstruction and mixed model analysis in which we accounted for the complex family structure of the HS, we identified one sharp peak within this region. Using positional bootstrapping, we determined the most likely location of this locus is from 205.04 to 207.48 Mb. This work demonstrates the utility of HS rats for fine-mapping complex traits and emphasizes the importance of taking into account family structure when using highly recombinant populations.

Genetically hypertensive Brown Norway congenic rat strains suggest intermediate traits underlying genetic hypertension.

AIM: To determine the independent and combined effects of three quantitative trait loci (QTL) for blood pressure in the Genetically Hypertensive (GH/Omr) rat by generating and characterizing single and combined congenic strains that have QTL on rat chromosomes (RNO) 2, 6, and 18 from the GH rat introduced into a hypertension resistant Brown Norway (BN) background. METHODS: Linkage analysis and QTL identification (genome wide QTL scan) were performed with MapMaker/EXP to build the genetic maps and MapMaker/QTL for linking the phenotypes to the genetic map. The congenic strains were derived using marker-assisted selection strategy from a single male F1 offspring of an intercross between the male GH/Omr and female BN/Elh, followed by 10 generations of selective backcrossing to the female BN progenitor strain. Single congenic strains generated were BN.GH-(D2Rat22-D2Mgh11)/Mcwi (BN.GH2); BN.GH-(D6Mit12-D6Rat15)/Mcwi (BN.GH6); and BN.GH-(D18Rat41-D18Mgh4)/Mcwi (BN.GH18). Blood pressure measurements were obtained either via a catheter placed in the femoral artery or by radiotelemetry. Responses to angiotensin II (ANGII), norepinephrine (NE), and baroreceptor sensitivity were measured in the single congenics. RESULTS: Transferring one or more QTL from the hypertensive GH into normotensive BN strain was not sufficient to cause hypertension in any of the developed congenic strains. There were no differences between the parental and congenic strains in their response to NE. However, BN.GH18 rats revealed significantly lower baroreceptor sensitivity (beta=-1.25-/+0.17), whereas BN.GH2 (beta=0.66-/+0.09) and BN.GH18 (beta=0.71-/+0.07) had significantly decreased responses to ANGII from those observed in the BN (beta=0.88-/+0.08). CONCLUSION: The failure to alter blood pressure levels by introducing the hypertensive QTL from the GH into the hypertension resistant BN background suggests that the QTL effects are genome background-dependent in the GH rat. BN.GH2 and BN.GH18 rats reveal significant differences in response to ANGII and impaired baroreflex sensitivity, suggesting that we may have captured a locus responsible for the genetic control of baroreceptor sensitivity, which would be considered an intermediate phenotype of blood pressure.

De novo repeat interruptions are associated with reduced somatic instability and mild or absent clinical features in myotonic dystrophy type 1.

Myotonic dystrophy type 1 (DM1) is a multisystem disorder, caused by expansion of a CTG trinucleotide repeat in the 3'-untranslated region of the DMPK gene. The repeat expansion is somatically unstable and tends to increase in length with time, contributing to disease progression. In some individuals, the repeat array is interrupted by variant repeats such as CCG and CGG, stabilising the expansion and often leading to milder symptoms. We have characterised three families, each including one person with variant repeats that had arisen de novo on paternal transmission of the repeat expansion. Two individuals were identified for screening due to an unusual result in the laboratory diagnostic test, and the third due to exceptionally mild symptoms. The presence of variant repeats in all three expanded alleles was confirmed by restriction digestion of small pool PCR products, and allele structures were determined by PacBio sequencing. Each was different, but all contained CCG repeats close to the 3'-end of the repeat expansion. All other family members had inherited pure CTG repeats. The variant repeat-containing alleles were more stable in the blood than pure alleles of similar length, which may in part account for the mild symptoms observed in all three individuals. This emphasises the importance of somatic instability as a disease mechanism in DM1. Further, since patients with variant repeats may have unusually mild symptoms, identification of these individuals has important implications for genetic counselling and for patient stratification in DM1 clinical trials.

Genetic Fine-Mapping and Identification of Candidate Genes and Variants for Adiposity Traits in Outbred Rats.

OBJECTIVE: Obesity is a major risk factor for multiple diseases and is in part heritable, yet the majority of causative genetic variants that drive excessive adiposity remain unknown. Here, outbred heterogeneous stock (HS) rats were used in controlled environmental conditions to fine-map novel genetic modifiers of adiposity. METHODS: Body weight and visceral fat pad weights were measured in male HS rats that were also genotyped genome-wide. Quantitative trait loci (QTL) were identified by genome-wide association of imputed single-nucleotide polymorphism (SNP) genotypes using a linear mixed effect model that accounts for unequal relatedness between the HS rats. Candidate genes were assessed by protein modeling and mediation analysis of expression for coding and noncoding variants, respectively. RESULTS: HS rats exhibited large variation in adiposity traits, which were highly heritable and correlated with metabolic health. Fine-mapping of fat pad weight and body weight revealed three QTL and prioritized five candidate genes. Fat pad weight was associated with missense SNPs in Adcy3 and Prlhr and altered expression of Krtcap3 and Slc30a3, whereas Grid2 was identified as a candidate within the body weight locus. CONCLUSIONS: These data demonstrate the power of HS rats for identification of known and novel heritable mediators of obesity traits.

Plasma exosomal miRNAs-based prognosis in metastatic kidney cancer.

Plasma exosomal miRNAs were evaluated for prognosis in an initial set of 44 metastatic renal cell cancer (mRCC) patients by RNA sequencing. Among ∼3.49 million mappable reads per patient, miRNAs accounted for 93.1% of the mapped RNAs. 227 miRNAs with high abundance were selected for survival analysis. Cox regression analysis identified association of 6 miRNAs with overall survival (OS) (P<0.01, False discovery rate (FDR) < 0.3). Five of the associated miRNAs were quantified in an independent follow-up cohort of 65 mRCC patients by TaqMan-based miRNA assays. Kaplan-Meier analysis confirmed the significant OS association of three miRs; miR-let-7i-5p (P=0.018, HR=0.49, 95% CI=0.21-0.84), miR-26a-1-3p (P=0.025, HR=0.43, 95% CI=0.10-0.84) and miR-615-3p (P=0.0007, HR=0.36, 95% CI=0.11-0.54). A multivariate analysis of miR-let-7i-5p with the clinical factor-based Memorial Sloan-Kettering Cancer Center (MSKCC) score improved survival prediction from an area under the curve (AUC) of 0.58 for MSKCC score to an average AUC of 0.64 across 48-month follow-up time. The multivariate model was able to define a high-risk group with median survival of 14 months and low risk group of 39 months (P=0.0002, HR=3.43, 95%CI, 2.73-24.15). Further validation of miRNA-based prognostic biomarkers are needed to improve current clinic-pathologic based prognostic models in patients with mRCC.

Regression forest-based automatic estimation of the articular margin plane for shoulder prosthesis planning.

In shoulder arthroplasty, the proximal humeral head is resected by sawing along the cartilage-bone transition and replaced by a prosthetic implant. The resection plane, called articular margin plane (AMP), defines the orientation, position and size of the prosthetic humeral head in relation to the humeral shaft. Therefore, the correct definition of the AMP is crucial for the computer-assisted preoperative planning of shoulder arthroplasty. We present a fully automated method for estimating the AMP relying only on computed tomography (CT) images of the upper arm. It consists of two consecutive steps, each of which uses random regression forests (RFs) to establish a direct mapping from the CT image to the AMP parameters. In the first step, image intensities serve as features to compute a coarse estimate of the AMP. The second step builds upon this estimate, calculating a refined AMP using novel feature types that combine a bone enhancing sheetness measure with ray features. The proposed method was evaluated on a dataset consisting of 72 CT images of upper arm cadavers. A mean localization error of 2.40mm and a mean angular error of 6.51° was measured compared to manually annotated ground truth.

Plasma genetic and genomic abnormalities predict treatment response and clinical outcome in advanced prostate cancer.

Liquid biopsies, examinations of tumor components in body fluids, have shown promise for predicting clinical outcomes. To evaluate tumor-associated genomic and genetic variations in plasma cell-free DNA (cfDNA) and their associations with treatment response and overall survival, we applied whole genome and targeted sequencing to examine the plasma cfDNAs derived from 20 patients with advanced prostate cancer. Sequencing-based genomic abnormality analysis revealed locus-specific gains or losses that were common in prostate cancer, such as 8q gains, AR amplifications, PTEN losses and TMPRSS2-ERG fusions. To estimate tumor burden in cfDNA, we developed a Plasma Genomic Abnormality (PGA) score by summing the most significant copy number variations. Cox regression analysis showed that PGA scores were significantly associated with overall survival (p < 0.04). After androgen deprivation therapy or chemotherapy, targeted sequencing showed significant mutational profile changes in genes involved in androgen biosynthesis, AR activation, DNA repair, and chemotherapy resistance. These changes may reflect the dynamic evolution of heterozygous tumor populations in response to these treatments. These results strongly support the feasibility of using non-invasive liquid biopsies as potential tools to study biological mechanisms underlying therapy-specific resistance and to predict disease progression in advanced prostate cancer.

Utilization of a labeled tracking oligonucleotide for visualization and quality control of spotted 70-mer arrays.

BACKGROUND: Spotted 70-mer oligonucleotide arrays offer potentially greater specificity and an alternative to expensive cDNA library maintenance and amplification. Since microarray fabrication is a considerable source of data variance, we previously directly tagged cDNA probes with a third fluorophore for prehybridization quality control. Fluorescently modifying oligonucleotide sets is cost prohibitive, therefore, a co-spotted Staphylococcus aureus-specific fluorescein-labeled "tracking" oligonucleotide is described to monitor fabrication variables of a Mycobacterium tuberculosis oligonucleotide microarray. RESULTS: Significantly (p < 0.01) improved DNA retention was achieved printing in 15% DMSO/1.5 M betaine compared to the vendor recommended buffers. Introduction of tracking oligonucleotide did not effect hybridization efficiency or introduce ratio measurement bias in hybridizations between M. tuberculosis H37Rv and M. tuberculosis mprA. Linearity between the mean log Cy3/Cy5 ratios of genes differentially expressed from arrays either possessing or lacking the tracking oligonucleotide was observed (R2 = 0.90, p < 0.05) and there were no significant differences in Pearson's correlation coefficients of ratio data between replicates possessing (0.72 +/- 0.07), replicates lacking (0.74 +/- 0.10), or replicates with and without (0.70 +/- 0.04) the tracking oligonucleotide. ANOVA analysis confirmed the tracking oligonucleotide introduced no bias. Titrating target-specific oligonucleotide (40 microM to 0.78 microM) in the presence of 0.5 microM tracking oligonucleotide, revealed a fluorescein fluorescence inversely related to target-specific oligonucleotide molarity, making tracking oligonucleotide signal useful for quality control measurements and differentiating false negatives (synthesis failures and mechanical misses) from true negatives (no gene expression). CONCLUSIONS: This novel approach enables prehybridization array visualization for spotted oligonucleotide arrays and sets the stage for more sophisticated slide qualification and data filtering applications.

Identification of a novel gene for diabetic traits in rats, mice, and humans.

The genetic basis of type 2 diabetes remains incompletely defined despite the use of multiple genetic strategies. Multiparental populations such as heterogeneous stocks (HS) facilitate gene discovery by allowing fine mapping to only a few megabases, significantly decreasing the number of potential candidate genes compared to traditional mapping strategies. In the present work, we employed expression and sequence analysis in HS rats (Rattus norvegicus) to identify Tpcn2 as a likely causal gene underlying a 3.1-Mb locus for glucose and insulin levels. Global gene expression analysis on liver identified Tpcn2 as the only gene in the region that is differentially expressed between HS rats with glucose intolerance and those with normal glucose regulation. Tpcn2 also maps as a cis-regulating expression QTL and is negatively correlated with fasting glucose levels. We used founder sequence to identify variants within this region and assessed association between 18 variants and diabetic traits by conducting a mixed-model analysis, accounting for the complex family structure of the HS. We found that two variants were significantly associated with fasting glucose levels, including a nonsynonymous coding variant within Tpcn2. Studies in Tpcn2 knockout mice demonstrated a significant decrease in fasting glucose levels and insulin response to a glucose challenge relative to those in wild-type mice. Finally, we identified variants within Tpcn2 that are associated with fasting insulin in humans. These studies indicate that Tpcn2 is a likely causal gene that may play a role in human diabetes and demonstrate the utility of multiparental populations for positionally cloning genes within complex loci.

A learning-based approach for fast and robust vessel tracking in long ultrasound sequences.

We propose a learning-based method for robust tracking in long ultrasound sequences for image guidance applications. The framework is based on a scale-adaptive block-matching and temporal realignment driven by the image appearance learned from an initial training phase. The latter is introduced to avoid error accumulation over long sequences. The vessel tracking performance is assessed on long 2D ultrasound sequences of the liver of 9 volunteers under free breathing. We achieve a mean tracking accuracy of 0.96 mm. Without learning, the error increases significantly (2.19 mm, p<0.001).