Abstract PD3-1: Evaluation and clinical impact of intra-tumor heterogeneity (ITH) in primary HER2-overexpressing breast cancers (HER2+BC) treated with adjuvant trastuzumab and chemotherapy (CT)

Background: Despite the success of trastuzumab, when added to CT, for the treatment of women with primary HER2+ BC, diversity in clinical responses and survival are still observed. ITH or the presence of subclonal populations is theorized to be a cause of drug resistance. In this study, we investigated if ITH that could be estimated from a single sample taken at primary surgery from patients with newly-diagnosed HER2+ disease and if ITH was associated with poorer clinical outcomes despite adjuvant trastuzumab-based treatment.

Methods: Fifty-two frozen tumor and matched germline samples were taken from patients diagnosed with primary HER2+BC and treated with adjuvant trastuzumab and CT with a median follow-up of 6.3yrs (range 1.5-13). There were 10 (19%) invasive relapses, 7 (13%) distant relapses and 5 (9.6%) deaths. We performed tumor and germline whole exome sequencing (WES), tumor and germline copy number (CN) data profiling (Affymetrix SNP6.0), tumor gene expression (Affymetrix U133 2.0Plus). Variants were called with MuTect, CNs were called using GISTIC. We developed a novel bioinformatics method that integrated WES variant allele fractions, purity estimates and SNP data to delineate the presence of single or multiple genetically distinct subclones. We confirmed our estimated tumor ploidy using flow cytometry on 9 samples. We investigated the association between the presence of ITH and survival using multivariate Cox regression analyses.

Results: We observed in HER2+ BCs the presence of substantial chromosomal instability, numerous CN alterations and aneuploidy. With regards to their genomic architecture, 76.9% (40/52) displayed the presence of at least one aneuploid subclone, where the median ploidy was 3.3 (range:1.7-6.3) copies. Multiple distinct subclones or the presence of ITH could be clearly detected in 35/52 (67.3%) samples, 8/52 (15.4%) had evidence of only a single clone, whilst in 9/52 (17.3%) samples their genomic structure could not be definitively determined. The existence of ITH was significantly associated with invasive relapse after adjustment (HR:4.38;95%CI:1.61-7.14;p=0.002) with estrogen receptor and nodal status also remaining significant in the Cox model–in contrast, the absence of ITH was associated with excellent outcomes (no distant relapses). Other surrogates of genomic instability (gene expression signature [CIN70] and SNP signature [Genomic Instability Index]) were not significantly associated with survival in this dataset.

As exploratory analyses, potential genetic drivers of ITH were investigated. PIK3CA (n=13,p=0.008), MED1 (n=3,p=0.03) and IKZF1 (n=3,p=0.03) mutations, amplifications in 8q22.2 (n=7,p=0.008) as well as deletion in 1q24.2 (n=5, p=0.006) were associated with the presence of a single clone, whereas we did not find any genetic drivers with significant associations with ITH.

Conclusions: We show for the first time that the presence of ITH in primary HER2+ tumors is associated with worse outcomes despite adjuvant trastuzumab and CT. These findings should be evaluated in larger cohorts.

Citation Format: Sherene Loi, Peter Savas, Ingrid Lonnstedt, Debora Fumagalli, Franco Caramia, Jason Li, Roberto Salgado, Andrew Rowan, Fabrice Andre, Carsten Denkert, Patrick Neven, Sibylle Loibl, Christos Sotiriou, Charles Swanton, Terence P Speed. Evaluation and clinical impact of intra-tumor heterogeneity (ITH) in primary HER2-overexpressing breast cancers (HER2+BC) treated with adjuvant trastuzumab and chemotherapy (CT) [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr PD3-1.

Statistical methods for handling unwanted variation in metabolomics data

Metabolomics experiments are inevitably subject to a component of unwanted variation, due to factors such as batch effects, long runs of samples, and confounding biological variation. Although the removal of this unwanted variation is a vital step in the analysis of metabolomics data, it is considered a gray area in which there is a recognized need to develop a better understanding of the procedures and statistical methods required to achieve statistically relevant optimal biological outcomes. In this paper, we discuss the causes of unwanted variation in metabolomics experiments, review commonly used metabolomics approaches for handling this unwanted variation, and present a statistical approach for the removal of unwanted variation to obtain normalized metabolomics data. The advantages and performance of the approach relative to several widely used metabolomics normalization approaches are illustrated through two metabolomics studies, and recommendations are provided for choosing and assessing the most suitable normalization method for a given metabolomics experiment. Software for the approach is made freely available.

Deciphering clonality in aneuploid breast tumors using SNP array and sequencing data

Intra-tumor heterogeneity concerns the existence of genetically different subclones within the same tumor. Single sample quantification of heterogeneity relies on precise determination of chromosomal copy numbers throughout the genome, and an assessment of whether identified mutation variant allele fractions match clonal or subclonal copy numbers. We discuss these issues using data from SNP arrays, whole exome sequencing and pathologist purity estimates on several breast cancers characterized by ERBB2 amplification. We show that chromosomal copy numbers can only be estimated from SNP array signals or sequencing depths for subclonal tumor samples with simple subclonal architectures under certain assumptions.

Combining calls from multiple somatic mutation-callers

Background

Accurate somatic mutation-calling is essential for insightful mutation analyses in cancer studies. Several mutation-callers are publicly available and more are likely to appear. Nonetheless, mutation-calling is still challenging and there is unlikely to be one established caller that systematically outperforms all others. Therefore, fully utilizing multiple callers can be a powerful way to construct a list of final calls for one’s research.

Results

Using a set of mutations from multiple callers that are impartially validated, we present a statistical approach for building a combined caller, which can be applied to combine calls in a wider dataset generated using a similar protocol. Using the mutation outputs and the validation data from The Cancer Genome Atlas endometrial study (6,746 sites), we demonstrate how to build a statistical model that predicts the probability of each call being a somatic mutation, based on the detection status of multiple callers and a few associated features.

Conclusion

The approach allows us to build a combined caller across the full range of stringency levels, which outperforms all of the individual callers.

Silencing of odorant receptor genes by G protein βγ signaling ensures the expression of one odorant receptor per olfactory sensory neuron

Olfactory sensory neurons express just one out of a possible ∼ 1,000 odorant receptor genes, reflecting an exquisite mode of gene regulation. In one model, once an odorant receptor is chosen for expression, other receptor genes are suppressed by a negative feedback mechanism, ensuring a stable functional identity of the sensory neuron for the lifetime of the cell. The signal transduction mechanism subserving odorant receptor gene silencing remains obscure, however. Here, we demonstrate in the zebrafish that odorant receptor gene silencing is dependent on receptor activity. Moreover, we show that signaling through G protein βγ subunits is both necessary and sufficient to suppress the expression of odorant receptor genes and likely acts through histone methylation to maintain the silenced odorant receptor genes in transcriptionally inactive heterochromatin. These results link receptor activity with the epigenetic mechanisms responsible for ensuring the expression of one odorant receptor per olfactory sensory neuron.

A component of the mir-17-92 polycistronic oncomir promotes oncogene-dependent apoptosis

mir-17-92, a potent polycistronic oncomir, encodes six mature miRNAs with complex modes of interactions. In the Eμ-myc Burkitt’s lymphoma model, mir-17-92 exhibits potent oncogenic activity by repressing c-Myc-induced apoptosis, primarily through its miR-19 components. Surprisingly, mir-17-92 also encodes the miR-92 component that negatively regulates its oncogenic cooperation with c-Myc. This miR-92 effect is, at least in part, mediated by its direct repression of Fbw7, which promotes the proteosomal degradation of c-Myc. Thus, overexpressing miR-92 leads to aberrant c-Myc increase, imposing a strong coupling between excessive proliferation and p53-dependent apoptosis. Interestingly, miR-92 antagonizes the oncogenic miR-19 miRNAs; and such functional interaction coordinates proliferation and apoptosis during c-Myc-induced oncogenesis. This miR-19:miR-92 antagonism is disrupted in B-lymphoma cells that favor a greater increase of miR-19 over miR-92. Altogether, we suggest a new paradigm whereby the unique gene structure of a polycistronic oncomir confers an intricate balance between oncogene and tumor suppressor crosstalk.

DOI:http://dx.doi.org/10.7554/eLife.00822.001

The role of genes, in very simple terms, is to be transcribed into messenger RNA molecules, which are then translated into strings of amino acids that fold into proteins. Each of these steps is extremely complex, and a wide range of other molecules can speed up, slow down, stop or otherwise disrupt the expression of genes as protein products. Genes can also code for nucleic acids that are not translated into proteins, such as microRNAs. These are small RNA molecules that can reduce the production of proteins by repressing the translation step and/or by partially degrading the messenger RNA molecules.

mir-17-92 is a gene that exemplifies much of this complexity. It codes for six different microRNAs in a single primary transcript, and has been implicated in a number of cancers, including lung cancer, Burkitt’s lymphoma and other forms of lymphomas and leukemia. One of six microRNAs has a longer evolutionary history than the remaining five: mir-92 is found in vertebrates, chordates and invertebrates, whereas the other five are only found in vertebrates. However, it is not known how or why the mir-17-92 gene evolved to code for multiple different microRNAs.

Olive et al. have studied how these mir-17-92 microRNAs functionally interact in mice with Burkitt’s lymphoma, a form of cancer that is associated with a gene called c-Myc being over-activated. Mutations in this gene promote the proliferation of cells, and in cooperation with other genetic lesions, this ultimately leads to cancer. mir-17-92 is implicated in this cancer because it represses the process of programmed cell death (which is induced by the protein c-Myc) that the body employs to stop tumors growing.

Olive et al. found that deleting one of the six microRNAs, miR-92, increased the tendency of the mir-17-92 gene to promote Burkitt’s lymphoma. By repressing an enzyme called Fbw7, miR-92 causes high levels of c-Myc to be produced. While this leads to the uncontrolled proliferation of cells that promotes cancer, it also increases programmed cell death, at least in part, by activating the p53 pathway, a well-known tumor suppression pathway. The experiments also revealed that the action of miR-92 and that of one of the other microRNAs, miR-19, were often opposed to each other. These findings have revealed an unexpected interaction among different components within a single microRNA gene, which acts to maintain an intricate balance between pathways that promote and suppress cancer.

DOI:http://dx.doi.org/10.7554/eLife.00822.002

A high force of plasmodium vivax blood-stage infection drives the rapid acquisition of immunity in papua new guinean children

BACKGROUND

When both parasite species are co-endemic, Plasmodium vivax incidence peaks in younger children compared to P. falciparum. To identify differences in the number of blood stage infections of these species and its potential link to acquisition of immunity, we have estimated the molecular force of blood-stage infection of P. vivax ((mol)FOB, i.e. the number of genetically distinct blood-stage infections over time), and compared it to previously reported values for P. falciparum.

METHODS

P. vivax (mol)FOB was estimated by high resolution genotyping parasites in samples collected over 16 months in a cohort of 264 Papua New Guinean children living in an area highly endemic for P. falciparum and P. vivax. In this cohort, P. vivax episodes decreased three-fold over the age range of 1-4.5 years.

RESULTS

On average, children acquired 14.0 new P. vivax blood-stage clones/child/year-at-risk. While the incidence of clinical P. vivax illness was strongly associated with mol FOB (incidence rate ratio (IRR) = 1.99, 95% confidence interval (CI95) [1.80, 2.19]), (mol)FOB did not change with age. The incidence of P. vivax showed a faster decrease with age in children with high (IRR = 0.49, CI95 [0.38, 0.64] p<0.001) compared to those with low exposure (IRR = 0.63, CI95[0.43, 0.93] p = 0.02).

CONCLUSION

P. vivax (mol)FOB is considerably higher than P. falciparum (mol)FOB (5.5 clones/child/year-at-risk). The high number of P. vivax clones that infect children in early childhood contribute to the rapid acquisition of immunity against clinical P. vivax malaria.

Comparing somatic mutation-callers: beyond Venn diagrams

BACKGROUND

Somatic mutation-calling based on DNA from matched tumor-normal patient samples is one of the key tasks carried by many cancer genome projects. One such large-scale project is The Cancer Genome Atlas (TCGA), which is now routinely compiling catalogs of somatic mutations from hundreds of paired tumor-normal DNA exome-sequence data. Nonetheless, mutation calling is still very challenging. TCGA benchmark studies revealed that even relatively recent mutation callers from major centers showed substantial discrepancies. Evaluation of the mutation callers or understanding the sources of discrepancies is not straightforward, since for most tumor studies, validation data based on independent whole-exome DNA sequencing is not available, only partial validation data for a selected (ascertained) subset of sites.

RESULTS

To provide guidelines to comparing outputs from multiple callers, we have analyzed two sets of mutation-calling data from the TCGA benchmark studies and their partial validation data. Various aspects of the mutation-calling outputs were explored to characterize the discrepancies in detail. To assess the performances of multiple callers, we introduce four approaches utilizing the external sequence data to varying degrees, ranging from having independent DNA-seq pairs, RNA-seq for tumor samples only, the original exome-seq pairs only, or none of those.

CONCLUSIONS

Our analyses provide guidelines to visualizing and understanding the discrepancies among the outputs from multiple callers. Furthermore, applying the four evaluation approaches to the whole exome data, we illustrate the challenges and highlight the various circumstances that require extra caution in assessing the performances of multiple callers.

Id2-mediated inhibition of E2A represses memory CD8+ T cell differentiation

The transcription factor inhibitor of DNA binding (Id)2 modulates T cell fate decisions, but the molecular mechanism underpinning this regulation is unclear. In this study we show that loss of Id2 cripples effector differentiation and instead programs CD8(+) T cells to adopt a memory fate with increased Eomesodermin and Tcf7 expression. We demonstrate that Id2 restrains CD8(+) T cell memory differentiation by inhibiting E2A-mediated direct activation of Tcf7 and that Id2 expression level mirrors T cell memory recall capacity. As a result of the defective effector differentiation, Id2-deficient CD8(+) T cells fail to induce sufficient Tbx21 expression to generate short-lived effector CD8(+) T cells. Our findings reveal that the Id2/E2A axis orchestrates T cell differentiation through the induction or repression of downstream transcription factors essential for effector and memory T cell differentiation.

Statistical analysis of metabolomics data

Statistical matters form an integral part of a metabolomics experiment. In this chapter we describe several important aspects in the analysis of metabolomics data such as the removal of unwanted variation and the identification of differentially abundant metabolites, along with a number of other essential statistical considerations.

Copy-number-aware differential analysis of quantitative DNA sequencing data

Developments in microarray and high-throughput sequencing (HTS) technologies have resulted in a rapid expansion of research into epigenomic changes that occur in normal development and in the progression of disease, such as cancer. Not surprisingly, copy number variation (CNV) has a direct effect on HTS read densities and can therefore bias differential detection results. We have developed a flexible approach called ABCD-DNA (affinity-based copy-number-aware differential quantitative DNA sequencing analyses) that integrates CNV and other systematic factors directly into the differential enrichment engine.

Normalizing and integrating metabolomics data

Metabolomics research often requires the use of multiple analytical platforms, batches of samples, and laboratories, any of which can introduce a component of unwanted variation. In addition, every experiment is subject to within-platform and other experimental variation, which often includes unwanted biological variation. Such variation must be removed in order to focus on the biological information of interest. We present a broadly applicable method for the removal of unwanted variation arising from various sources for the identification of differentially abundant metabolites and, hence, for the systematic integration of data on the same quantities from different sources. We illustrate the versatility and the performance of the approach in four applications, and we show that it has several advantages over the existing normalization methods.

Bayesian inference of signaling network topology in a cancer cell line

MOTIVATION

Protein signaling networks play a key role in cellular function, and their dysregulation is central to many diseases, including cancer. To shed light on signaling network topology in specific contexts, such as cancer, requires interrogation of multiple proteins through time and statistical approaches to make inferences regarding network structure.

RESULTS

In this study, we use dynamic Bayesian networks to make inferences regarding network structure and thereby generate testable hypotheses. We incorporate existing biology using informative network priors, weighted objectively by an empirical Bayes approach, and exploit a connection between variable selection and network inference to enable exact calculation of posterior probabilities of interest. The approach is computationally efficient and essentially free of user-set tuning parameters. Results on data where the true, underlying network is known place the approach favorably relative to existing approaches. We apply these methods to reverse-phase protein array time-course data from a breast cancer cell line (MDA-MB-468) to predict signaling links that we independently validate using targeted inhibition. The methods proposed offer a general approach by which to elucidate molecular networks specific to biological context, including, but not limited to, human cancers.

AVAILABILITY

http://mukherjeelab.nki.nl/DBN (code and data).

Effect of vascular endothelial growth factor upregulation on retinal gene expression in the Kimba mouse

BACKGROUND

  The Kimba mouse carries a human vascular endothelial growth factor transgene causing retinal neovascularisation similar to that seen in diabetic retinopathy. Here, we examine the relationship between differential gene expression induced by vascular endothelial growth factor overexpression and the architectural changes that occur in the retinae of these mice.

METHODS

  Retinal gene expression changes in juvenile and adult Kimba mice were assayed by microarray and compared with age-matched wild-type littermates. Transcription of selected genes was validated by quantitative real-time polymerase chain reaction. Protein translation was determined using immunohistochemistry and enzyme-linked immunosorbent assay.

RESULTS

  Semaphorin 3C was upregulated, and nuclear receptor subfamily 2, group 3, member 3 (Nr2e3) was downregulated in juvenile Kimba mice. Betacellulin and endothelin 2 were upregulated in adults. Semaphorin 3C colocalized with glial fibrillary acidic protein in Müller cells of Kimba retinae at greater signal intensities than in wild type. Endothelin 2 colocalised to Müller cell end feet and extended into the outer limiting membrane. Endothelin receptor type B staining was most pronounced in the inner nuclear layer, the region containing Müller cell somata.

CONCLUSIONS

  An early spike in vascular endothelial growth factor induced significant long-term retinal neovascularisation associated with changes to the retinal ganglion, photoreceptor and Müller cells. Overexpression of vascular endothelial growth factor led to dysregulation of photoreceptor metabolism through differential expression of Nr2e3, endothelin 2, betacellulin and semaphorin 3C. Alterations in the expression of these genes may therefore play key roles in the pathological mechanisms that result from retinal neovascularisation.

Subcompartmentalisation of proteins in the rhoptries correlates with ordered events of erythrocyte invasion by the blood stage malaria parasite

Host cell infection by apicomplexan parasites plays an essential role in lifecycle progression for these obligate intracellular pathogens. For most species, including the etiological agents of malaria and toxoplasmosis, infection requires active host-cell invasion dependent on formation of a tight junction – the organising interface between parasite and host cell during entry. Formation of this structure is not, however, shared across all Apicomplexa or indeed all parasite lifecycle stages. Here, using an in silico integrative genomic search and endogenous gene-tagging strategy, we sought to characterise proteins that function specifically during junction-dependent invasion, a class of proteins we term invasins to distinguish them from adhesins that function in species specific host-cell recognition. High-definition imaging of tagged Plasmodium falciparum invasins localised proteins to multiple cellular compartments of the blood stage merozoite. This includes several that localise to distinct subcompartments within the rhoptries. While originating from the same organelle, however, each has very different dynamics during invasion. Apical Sushi Protein and Rhoptry Neck protein 2 release early, following the junction, whilst a novel rhoptry protein PFF0645c releases only after invasion is complete. This supports the idea that organisation of proteins within a secretory organelle determines the order and destination of protein secretion and provides a localisation-based classification strategy for predicting invasin function during apicomplexan parasite invasion.

A bioinformatic strategy for the detection, classification and analysis of bacterial autotransporters

Autotransporters are secreted proteins that are assembled into the outer membrane of bacterial cells. The passenger domains of autotransporters are crucial for bacterial pathogenesis, with some remaining attached to the bacterial surface while others are released by proteolysis. An enigma remains as to whether autotransporters should be considered a class of secretion system, or simply a class of substrate with peculiar requirements for their secretion. We sought to establish a sensitive search protocol that could identify and characterize diverse autotransporters from bacterial genome sequence data. The new sequence analysis pipeline identified more than 1500 autotransporter sequences from diverse bacteria, including numerous species of Chlamydiales and Fusobacteria as well as all classes of Proteobacteria. Interrogation of the proteins revealed that there are numerous classes of passenger domains beyond the known proteases, adhesins and esterases. In addition the barrel-domain-a characteristic feature of autotransporters-was found to be composed from seven conserved sequence segments that can be arranged in multiple ways in the tertiary structure of the assembled autotransporter. One of these conserved motifs overlays the targeting information required for autotransporters to reach the outer membrane. Another conserved and diagnostic motif maps to the linker region between the passenger domain and barrel-domain, indicating it as an important feature in the assembly of autotransporters.

The N-terminal domains of SOCS proteins: a conserved region in the disordered N-termini of SOCS4 and 5

Suppressors of cytokine signaling (SOCS) proteins function as negative regulators of cytokine signaling and are involved in fine tuning the immune response. The structure and role of the SH2 domains and C-terminal SOCS box motifs of the SOCS proteins are well characterized, but the long N-terminal domains of SOCS4-7 remain poorly understood. Here, we present bioinformatic analyses of the N-terminal domains of the mammalian SOCS proteins, which indicate that these domains of SOCS4, 5, 6, and 7 are largely disordered. We have also identified a conserved region of about 70 residues in the N-terminal domains of SOCS4 and 5 that is predicted to be more ordered than the surrounding sequence. The conservation of this region can be traced as far back as lower vertebrates. As conserved regions with increased structural propensity that are located within long disordered regions often contain molecular recognition motifs, we expressed the N-terminal conserved region of mouse SOCS4 for further analysis. This region, mSOCS4₈₆₋₁₅₅, has been characterized by circular dichroism and nuclear magnetic resonance spectroscopy, both of which indicate that it is predominantly unstructured in aqueous solution, although it becomes helical in the presence of trifluoroethanol. The high degree of sequence conservation of this region across different species and between SOCS4 and SOCS5 nonetheless implies that it has an important functional role, and presumably this region adopts a more ordered conformation in complex with its partners. The recombinant protein will be a valuable tool in identifying these partners and defining the structures of these complexes.

SRMA: an R package for resequencing array data analysis

Sequencing by hybridization to oligonucleotides has evolved into an inexpensive, reliable and fast technology for targeted sequencing. Hundreds of human genes can now be sequenced within a day using a single hybridization to a resequencing microarray. However, several issues inherent to these arrays (e.g. cross-hybridization, variable probe/target affinity) cause sequencing errors and have prevented more widespread applications. We developed an R package for resequencing microarray data analysis that integrates a novel statistical algorithm, sequence robust multi-array analysis (SRMA), for rare variant detection with high sensitivity (false negative rate, FNR 5%) and accuracy (false positive rate, FPR 1×10⁻⁵). The SRMA package consists of five modules for quality control, data normalization, single array analysis, multi-array analysis and output analysis. The entire workflow is efficient and identifies rare DNA single nucleotide variations and structural changes such as gene deletions with high accuracy and sensitivity.

AVAILABILITY

http://cran.r-project.org/, http://odin.mdacc.tmc.edu/~wwang7/SRMAIndex.html

A DNA resequencing array for genes involved in Parkinson's disease

Parkinson's disease (PD) is aetiologically complex with both familial and sporadic forms. Familial PD results from rare, highly penetrant pathogenic mutations whereas multiple variants of low penetrance may contribute to the risk of sporadic PD. Common variants implicated in PD risk appear to explain only a minor proportion of the familial clustering observed in sporadic PD. It is therefore plausible that combinations of rare and/or common variants in genes already implicated in disease pathogenesis may help to explain the genetic basis of PD. We have developed a CustomSeq Affymetrix resequencing array to enable high-throughput sequencing of 13 genes (44 kb) implicated in the pathogenesis of PD. Using the array we sequenced 269 individuals, including 186 PD patients and 75 controls, achieving an overall call rate of 96.5% and 93.6%, for two respective versions of the array, and >99.9% accuracy for five samples sequenced by capillary sequencing in parallel. We identified modest associations with common variants in SNCA and LRRK2 and a trend suggestive of an overrepresentation of rare variants in cases compared to controls for several genes. We propose that this technology offers a robust and cost-effective alternative to targeted sequencing using traditional sequencing methods, and here we demonstrate the potential of this approach for either routine clinical investigation or for research studies aimed at understanding the genetic aetiology of PD.

Protocol matters: which methylome are you actually studying?

The field of epigenetics is now capitalizing on the vast number of emerging technologies, largely based on second-generation sequencing, which interrogate DNA methylation status and histone modifications genome-wide. However, getting an exhaustive and unbiased view of a methylome at a reasonable cost is proving to be a significant challenge. In this article, we take a closer look at the impact of the DNA sequence and bias effects introduced to datasets by genome-wide DNA methylation technologies and where possible, explore the bioinformatics tools that deconvolve them. There remains much to be learned about the performance of genome-wide technologies, the data we mine from these assays and how it reflects the actual biology. While there are several methods to interrogate the DNA methylation status genome-wide, our opinion is that no single technique suitably covers the minimum criteria of high coverage and, high resolution at a reasonable cost. In fact, the fraction of the methylome that is studied currently depends entirely on the inherent biases of the protocol employed. There is promise for this to change, as the third generation of sequencing technologies is expected to again 'revolutionize' the way that we study genomes and epigenomes.

Summarizing and correcting the GC content bias in high-throughput sequencing

GC content bias describes the dependence between fragment count (read coverage) and GC content found in Illumina sequencing data. This bias can dominate the signal of interest for analyses that focus on measuring fragment abundance within a genome, such as copy number estimation (DNA-seq). The bias is not consistent between samples; and there is no consensus as to the best methods to remove it in a single sample. We analyze regularities in the GC bias patterns, and find a compact description for this unimodal curve family. It is the GC content of the full DNA fragment, not only the sequenced read, that most influences fragment count. This GC effect is unimodal: both GC-rich fragments and AT-rich fragments are underrepresented in the sequencing results. This empirical evidence strengthens the hypothesis that PCR is the most important cause of the GC bias. We propose a model that produces predictions at the base pair level, allowing strand-specific GC-effect correction regardless of the downstream smoothing or binning. These GC modeling considerations can inform other high-throughput sequencing analyses such as ChIP-seq and RNA-seq.

Tissue-specific regulation of genes by estrogen receptors

Estrogens are frequently used in reproductive medicine. The Women's Health Initiative trial found that the risks of menopausal hormone therapy (MHT) exceed the benefits. The estrogens in MHT, however, were introduced prior to our understanding of the mechanism of action of estrogens. Estrogen signaling is highly complex, involving various DNA regulatory elements to which estrogen receptors bind. Numerous transcription factors and co-regulatory proteins modify chromatin structure to further regulate gene transcription. With a greater understanding of estrogen action, the major problem with the current estrogens in MHT appears to be that they are nonselective. This produces beneficial effects in bone, brain, and adipose tissue but increases the risk of breast and endometrial cancer and thromboembolism. Resurrecting MHT for long-term therapy will require the development of more selective estrogens, such as estrogen receptor (ER)β-selective estrogens and tissue-selective ERα agonists. These compounds will offer the best prospects to expand the indications of MHT and thus prevent the chronic conditions associated with menopause.

Estrogenic plant extracts reverse weight gain and fat accumulation without causing mammary gland or uterine proliferation

Long-term estrogen deficiency increases the risk of obesity, diabetes and metabolic syndrome in postmenopausal women. Menopausal hormone therapy containing estrogens might prevent these conditions, but its prolonged use increases the risk of breast cancer, as wells as endometrial cancer if used without progestins. Animal studies indicate that beneficial effects of estrogens in adipose tissue and adverse effects on mammary gland and uterus are mediated by estrogen receptor alpha (ERα). One strategy to improve the safety of estrogens to prevent/treat obesity, diabetes and metabolic syndrome is to develop estrogens that act as agonists in adipose tissue, but not in mammary gland and uterus. We considered plant extracts, which have been the source of many pharmaceuticals, as a source of tissue selective estrogens. Extracts from two plants, Glycyrrhiza uralensis (RG) and Pueraria montana var. lobata (RP) bound to ERα, activated ERα responsive reporters, and reversed weight gain and fat accumulation comparable to estradiol in ovariectomized obese mice maintained on a high fat diet. Unlike estradiol, RG and RP did not induce proliferative effects on mammary gland and uterus. Gene expression profiling demonstrated that RG and RP induced estradiol-like regulation of genes in abdominal fat, but not in mammary gland and uterus. The compounds in extracts from RG and RP might constitute a new class of tissue selective estrogens to reverse weight gain, fat accumulation and metabolic syndrome in postmenopausal women.