Lel Eory

Contributions of Protein-Coding and Regulatory Change to Adaptive Molecular Evolution in Murid Rodents

The contribution of regulatory versus protein change to adaptive evolution has long been controversial. In principle, the rate and strength of adaptation within functional genetic elements can be quantified on the basis of an excess of nucleotide substitutions between species compared to the neutral expectation or from effects of recent substitutions on nucleotide diversity at linked sites. Here, we infer the nature of selective forces acting in proteins, their UTRs and conserved noncoding elements (CNEs) using genome-wide patterns of diversity in wild house mice and divergence to related species. By applying an extension of the McDonald-Kreitman test, we infer that adaptive substitutions are widespread in protein-coding genes, UTRs and CNEs, and we estimate that there are at least four times as many adaptive substitutions in CNEs and UTRs as in proteins. We observe pronounced reductions in mean diversity around nonsynonymous sites (whether or not they have experienced a recent substitution). This can be explained by selection on multiple, linked CNEs and exons. We also observe substantial dips in mean diversity (after controlling for divergence) around protein-coding exons and CNEs, which can also be explained by the combined effects of many linked exons and CNEs. A model of background selection (BGS) can adequately explain the reduction in mean diversity observed around CNEs. However, BGS fails to explain the wide reductions in mean diversity surrounding exons (encompassing ∼100 Kb, on average), implying that there is a substantial role for adaptation within exons or closely linked sites. The wide dips in diversity around exons, which are hard to explain by BGS, suggest that the fitness effects of adaptive amino acid substitutions could be substantially larger than substitutions in CNEs. We conclude that although there appear to be many more adaptive noncoding changes, substitutions in proteins may dominate phenotypic evolution.

Carbonic Anhydrase 9 Expression Increases with Vascular Endothelial Growth Factor–Targeted Therapy and Is Predictive of Outcome in Metastatic Clear Cell Renal Cancer

Background There is a lack of biomarkers to predict outcome with targeted therapy in metastatic clear cell renal cancer (mccRCC). This may be because dynamic molecular changes occur with therapy. Objective To explore if dynamic, targeted-therapy-driven molecular changes correlate with mccRCC outcome. Design, setting, and participants Multiple frozen samples from primary tumours were taken from sunitinib-naïve (n = 22) and sunitinib-treated mccRCC patients (n = 23) for protein analysis. A cohort (n = 86) of paired, untreated and sunitinib/pazopanib-treated mccRCC samples was used for validation. Array comparative genomic hybridisation (CGH) analysis and RNA interference (RNAi) was used to support the findings. Intervention Three cycles of sunitinib 50 mg (4 wk on, 2 wk off). Outcome measurements and statistical analysis Reverse phase protein arrays (training set) and immunofluorescence automated quantitative analysis (validation set) assessed protein expression. Results and limitations Differential expression between sunitinib-naïve and treated samples was seen in 30 of 55 proteins (p < 0.05 for each). The proteins B-cell CLL/lymphoma 2 (BCL2), mutL homolog 1 (MLH1), carbonic anhydrase 9 (CA9), and mechanistic target of rapamycin (mTOR) (serine/threonine kinase) had both increased intratumoural variance and significant differential expression with therapy. The validation cohort confirmed increased CA9 expression with therapy. Multivariate analysis showed high CA9 expression after treatment was associated with longer survival (hazard ratio: 0.48; 95% confidence interval, 0.26–0.87; p = 0.02). Array CGH profiles revealed sunitinib was associated with significant CA9 region loss. RNAi CA9 silencing in two cell lines inhibited the antiproliferative effects of sunitinib. Shortcomings of the study include selection of a specific protein for analysis, and the specific time points at which the treated tissue was analysed. Conclusions CA9 levels increase with targeted therapy in mccRCC. Lower CA9 levels are associated with a poor prognosis and possible resistance, as indicated by the validation cohort. Patient summary Drug treatment of advanced kidney cancer alters molecular markers of treatment resistance. Measuring carbonic anhydrase 9 levels may be helpful in determining which patients benefit from therapy.

Sunitinib treatment exacerbates intratumoral heterogeneity in metastatic renal cancer

Purpose: The aim of this study was to investigate the effect of VEGF-targeted therapy (sunitinib) on molecular intratumoral heterogeneity (ITH) in metastatic clear cell renal cancer (mccRCC). Experimental Design: Multiple tumor samples (n = 187 samples) were taken from the primary renal tumors of patients with mccRCC who were sunitinib treated (n = 23, SuMR clinical trial) or untreated (n = 23, SCOTRRCC study). ITH of pathologic grade, DNA (aCGH), mRNA (Illumina Beadarray) and candidate proteins (reverse phase protein array) were evaluated using unsupervised and supervised analyses (driver mutations, hypoxia, and stromal-related genes). ITH was analyzed using intratumoral protein variance distributions and distribution of individual patient aCGH and gene-expression clustering. Results: Tumor grade heterogeneity was greater in treated compared with untreated tumors (P = 0.002). In unsupervised analysis, sunitinib therapy was not associated with increased ITH in DNA or mRNA. However, there was an increase in ITH for the driver mutation gene signature (DNA and mRNA) as well as increasing variability of protein expression with treatment (P < 0.05). Despite this variability, significant chromosomal and transcript changes to key targets of sunitinib, such as VHL, PBRM1, and CAIX, occurred in the treated samples. Conclusions: These findings suggest that sunitinib treatment has significant effects on the expression and ITH of key tumor and treatment specific genes/proteins in mccRCC. The results, based on primary tumor analysis, do not support the hypothesis that resistant clones are selected and predominate following targeted therapy. Clin Cancer Res; 21(18); 4212–23. ©2015 AACR.

Avianbase: a community resource for bird genomics.

Giving access to sequence and annotation data for genome assemblies is important because, while facilitating research, it places both assembly and annotation quality under scrutiny, resulting in improvements to both. Therefore we announce Avianbase, a resource for bird genomics, which provides access to data released by the Avian Phylogenomics Consortium.

Functional classification of 15 million SNPs detected from diverse chicken populations

Next-generation sequencing has prompted a surge of discovery of millions of genetic variants from vertebrate genomes. Besides applications in genetic association and linkage studies, a fraction of these variants will have functional consequences. This study describes detection and characterization of 15 million SNPs from chicken genome with the goal to predict variants with potential functional implications (pfVars) from both coding and non-coding regions. The study reports: 183K amino acid-altering SNPs of which 48% predicted as evolutionary intolerant, 13K splicing variants, 51K likely to alter RNA secondary structures, 500K within most conserved elements and 3K from non-coding RNAs. Regions of local fixation within commercial broiler and layer lines were investigated as potential selective sweeps using genome-wide SNP data. Relationships with phenotypes, if any, of the pfVars were explored by overlaying the sweep regions with known QTLs. Based on this, the candidate genes and/or causal mutations for a number of important traits are discussed. Although the fixed variants within sweep regions were enriched with non-coding SNPs, some non-synonymous-intolerant mutations reached fixation, suggesting their possible adaptive advantage. The results presented in this study are expected to have important implications for future genomic research to identify candidate causal mutations and in poultry breeding.

Inference of Mutation Parameters and Selective Constraint in Mammalian Coding Sequences by Approximate Bayesian Computation

We develop an inference method that uses approximate Bayesian computation (ABC) to simultaneously estimate mutational parameters and selective constraint on the basis of nucleotide divergence for protein-coding genes between pairs of species. Our simulations explicitly model CpG hypermutability and transition vs. transversion mutational biases along with negative and positive selection operating on synonymous and nonsynonymous sites. We evaluate the method by simulations in which true mean parameter values are known and show that it produces reasonably unbiased parameter estimates as long as sequences are not too short and sequence divergence is not too low. We show that the use of quadratic regression within ABC offers an improvement over linear regression, but that weighted regression has little impact on the efficiency of the procedure. We apply the method to estimate mutational and selective constraint parameters in data sets of protein-coding genes extracted from the genome sequences of primates, murids, and carnivores. Estimates of CpG hypermutability are substantially higher in primates than murids and carnivores. Nonsynonymous site selective constraint is substantially higher in murids and carnivores than primates, and autosomal nonsynonymous constraint is higher than X-chromsome constraint in all taxa. We detect significant selective constraint at synonymous sites in primates, carnivores, and murid rodents. Synonymous site selective constraint is weakest in murids, a surprising result, considering that murid effective population sizes are likely to be considerably higher than the other two taxa.

The use of reverse phase protein arrays (RPPA) to explore protein expression variation within individual renal cell cancers.

Currently there is no curative treatment for metastatic clear cell renal cell cancer, the commonest variant of the disease. A key factor in this treatment resistance is thought to be the molecular complexity of the disease. Targeted therapy such as the tyrosine kinase inhibitor (TKI)-sunitinib have been utilized, but only 40% of patients will respond, with the overwhelming majority of these patients relapsing within 1 year. As such the question of intrinsic and acquired resistance in renal cell cancer patients is highly relevant. In order to study resistance to TKIs, with the ultimate goal of developing effective, personalized treatments, sequential tissue after a specific period of targeted therapy is required, an approach which had proved successful in chronic myeloid leukaemia. However the application of such a strategy in renal cell carcinoma is complicated by the high level of both inter- and intratumoral heterogeneity, which is a feature of renal cell carcinoma as well as other solid tumors. Intertumoral heterogeneity due to transcriptomic and genetic differences is well established even in patients with similar presentation, stage and grade of tumor. In addition it is clear that there is great morphological (intratumoral) heterogeneity in RCC, which is likely to represent even greater molecular heterogeneity. Detailed mapping and categorization of RCC tumors by combined morphological analysis and Fuhrman grading allows the selection of representative areas for proteomic analysis. Protein based analysis of RCC is attractive due to its widespread availability in pathology laboratories; however, its application can be problematic due to the limited availability of specific antibodies. Due to the dot blot nature of the Reverse Phase Protein Arrays (RPPA), antibody specificity must be pre-validated; as such strict quality control of antibodies used is of paramount importance. Despite this limitation the dot blot format does allow assay miniaturization, allowing for the printing of hundreds of samples onto a single nitrocellulose slide. Printed slides can then be analyzed in a similar fashion to Western analysis with the use of target specific primary antibodies and fluorescently labelled secondary antibodies, allowing for multiplexing. Differential protein expression across all the samples on a slide can then be analyzed simultaneously by comparing the relative level of fluorescence in a more cost-effective and high-throughput manner.

Proteomic analysis of pre- and post-sunitinib treated renal cancer tissue to assess tumor heterogeneity and differential protein expression.

388 Background: To investigate acquired resistance of clear cell renal cell cancer (ccRCC) patients to sunitinib and develop personalised treatment strategies, sequential tissue after a specific period of targeted therapy is required. This approach has proven successful with targeted therapy in chronic myeloid leukaemia; however, we are concerned that extensive tumour heterogeneity occurs in ccRCC. In this study we evaluated heterogeneity and differential protein expression in sunitinib treated and untreated ccRCC samples using high-throughput proteomics. METHODS Fresh frozen tissue was obtained from 27 sunitinib naïve ccRCC specimens and 27 nephrectomy samples from patients treated with neoadjuvant sunitinib (18 weeks) as part of the SuMR trial. From each tumour frozen sections were performed and up to 5 protein lysates obtained from each morphologically differing region of each tumour as well as matched normal kidney. Reverse phase protein arrays (RPPA) were performed to assess the levels of multiple proteins relevant to ccRCC pathogenesis and sunitinib activity. Appropriate statistical tests were used to examine protein heterogeneity and differential expression, including false discovery rate (FDR) correction. Kaplan-Meier method was used to correlate changes in protein expression with outcome. RESULTS Expression of 20 proteins has been examined to date. The range of expression in tumours normalised by matched normal renal tissue had >2-fold differences in untreated (n=8 proteins) and treated samples (n=4 proteins). Four markers displayed significantly increased inter-tumoural variance in sunitinib treated tumours compared with untreated tissue (e.g. VEGFR1, FDR P<0.05). Despite this heterogeneity, sunitinib was associated with significant expression changes for several key proteins (e.g. VEGFR2, CyclinD2; FDR P<0.05). CONCLUSIONS Protein expression in ccRCC is heterogenous and key proteins showed significantly increased variance of expression with sunitinib therapy. Despite heterogeneity, significant changes in protein expression can be identified with sunitinib treatment and have been correlated with outcome.