Large scale analysis of positional effects of single-base mismatches on microarray gene expression data

Notch signaling drives intestinal graft-versus-host disease in mice and nonhuman primates

Notch signaling promotes T cell pathogenicity and graft-versus-host disease (GVHD) after allogeneic hematopoietic cell transplantation (allo-HCT) in mice, with a dominant role for the Delta-like Notch ligand DLL4. To assess whether Notch's effects are evolutionarily conserved and to identify the mechanisms of Notch signaling inhibition, we studied antibody-mediated DLL4 blockade in a nonhuman primate (NHP) model similar to human allo-HCT. Short-term DLL4 blockade improved posttransplant survival with durable protection from gastrointestinal GVHD in particular. Unlike prior immunosuppressive strategies tested in the NHP GVHD model, anti-DLL4 interfered with a T cell transcriptional program associated with intestinal infiltration. In cross-species investigations, Notch inhibition decreased surface abundance of the gut-homing integrin α4β7 in conventional T cells while preserving α4β7 in regulatory T cells, with findings suggesting increased β1 competition for α4 binding in conventional T cells. Secondary lymphoid organ fibroblastic reticular cells emerged as the critical cellular source of Delta-like Notch ligands for Notch-mediated up-regulation of α4β7 integrin in T cells after allo-HCT. Together, DLL4-Notch blockade decreased effector T cell infiltration into the gut, with increased regulatory to conventional T cell ratios early after allo-HCT. Our results identify a conserved, biologically unique, and targetable role of DLL4-Notch signaling in intestinal GVHD.

Identification of Rhythmically Expressed LncRNAs in the Zebrafish Pineal Gland and Testis

Noncoding RNAs have been known to contribute to a variety of fundamental life processes, such as development, metabolism, and circadian rhythms. However, much remains unrevealed in the huge noncoding RNA datasets, which require further bioinformatic analysis and experimental investigation-and in particular, the coding potential of lncRNAs and the functions of lncRNA-encoded peptides have not been comprehensively studied to date. Through integrating the time-course experimentation with state-of-the-art computational techniques, we studied tens of thousands of zebrafish lncRNAs from our own experiments and from a published study including time-series transcriptome analyses of the testis and the pineal gland. Rhythmicity analysis of these data revealed approximately 700 rhythmically expressed lncRNAs from the pineal gland and the testis, and their GO, COG, and KEGG pathway functions were analyzed. Comparative and conservative analyses determined 14 rhythmically expressed lncRNAs shared between both the pineal gland and the testis, and 15 pineal gland lncRNAs as well as 3 testis lncRNAs conserved among zebrafish, mice, and humans. Further, we computationally analyzed the conserved lncRNA-encoded peptides, and revealed three pineal gland and one testis lncRNA-encoded peptides conserved among these three species, which were further investigated for their three-dimensional (3D) structures and potential functions. Our computational findings provided novel annotations and regulatory mechanisms for hundreds of rhythmically expressed pineal gland and testis lncRNAs in zebrafish, and set the stage for their experimental studies in the near future.

One-step colorimetric genotyping of single nucleotide polymorphism using probe-enhanced loop-mediated isothermal amplification (PE-LAMP)

Single nucleotide polymorphism (SNP) is the most abundant molecular marker associated with many physiologic and pathologic phenotypes. An isothermal, accurate and cost-effective SNP detection could make a great difference in point-of-care testing (POCT) or on-site diagnosis. However, there are two challenges, the expensive instrument and labor-intensive process, faced by the development of on-site SNP detection. We reported a novel SNP typing method based on the probe-enhanced loop-mediated isothermal amplification (PE-LAMP), which combines the oligonucleotide probe with a conventional LAMP to realize the SNP discrimination by analyzing the great discrepancy in amplification efficiency.

Methods: We firstly constructed the genotyping method by combining the hybridization of the specific probe with the powerful amplification of LAMP. Then we validated the method by genotyping the SNP rs3741219 and we sought to realize one-step visualized typing. Finally, we applied the method to pharmacogenomic testing by genotyping CYP2C19*2 and MDR1 C3435T.

Results: The PE-LAMP was successfully constructed to detect SNP and the sensitivity of our method is as low as 1000 copies of target DNA, which is sufficient to routine diagnosis. The high specificity in detecting mutant in the presence of excess wild-type allele could be achieved. It has shown good performance in helping predict the individual response of antiplatelet drug Clopidogrel through typing simply treated saliva samples.

Conclusions: The proposed method is one-step, colorimetric, specific and sensitive enough to detect crudely treated samples, showing great potential in the pharmacogenomic study and POCT use.

Sequence characteristics define trade-offs between on-target and genome-wide off-target hybridization of oligoprobes

Off-target oligoprobe's interaction with partially complementary nucleotide sequences represents a problem for many bio-techniques. The goal of the study was to identify oligoprobe sequence characteristics that control the ratio between on-target and off-target hybridization. To understand the complex interplay between specific and genome-wide off-target (cross-hybridization) signals, we analyzed a database derived from genomic comparison hybridization experiments performed with an Affymetrix tiling array. The database included two types of probes with signals derived from (i) a combination of specific signal and cross-hybridization and (ii) genomic cross-hybridization only. All probes from the database were grouped into bins according to their sequence characteristics, where both hybridization signals were averaged separately. For selection of specific probes, we analyzed the following sequence characteristics: vulnerability to self-folding, nucleotide composition bias, numbers of G nucleotides and GGG-blocks, and occurrence of probe's k-mers in the human genome. Increases in bin ranges for these characteristics are simultaneously accompanied by a decrease in hybridization specificity-the ratio between specific and cross-hybridization signals. However, both averaged hybridization signals exhibit growing trends along with an increase of probes' binding energy, where the hybridization specific signal increases significantly faster in comparison to the cross-hybridization. The same trend is evident for the S function, which serves as a combined evaluation of probe binding energy and occurrence of probe's k-mers in the genome. Application of S allows extracting a larger number of specific probes, as compared to using only binding energy. Thus, we showed that high values of specific and cross-hybridization signals are not mutually exclusive for probes with high values of binding energy and S. In this study, the application of a new set of sequence characteristics allows detection of probes that are highly specific to their targets for array design and other bio-techniques that require selection of specific probes.

Combined OX40L and mTOR blockade controls effector T cell activation while preserving Treg reconstitution after transplant

A critical question facing the field of transplantation is how to control effector T cell (T_eff) activation while preserving regulatory T cell (T_reg) function. Standard calcineurin inhibitor-based strategies can partially control T_effs, but breakthrough activation still occurs, and these agents are antagonistic to T_reg function. Conversely, mechanistic target of rapamycin (mTOR) inhibition with sirolimus is more T_reg-compatible but is inadequate to fully control T_eff activation. In contrast, blockade of OX40L signaling has the capacity to partially control T_eff activation despite maintaining T_reg function. We used the nonhuman primate graft-versus-host disease (GVHD) model to probe the efficacy of combinatorial immunomodulation with sirolimus and the OX40L-blocking antibody KY1005. Our results demonstrate significant biologic activity of KY1005 alone (prolonging median GVHD-free survival from 8 to 19.5 days), as well as marked, synergistic control of GVHD with KY1005 + sirolimus (median survival time, >100 days; P < 0.01 compared to all other regimens), which was associated with potent control of both T_H/T_C1 (T helper cell 1/cytotoxic T cell 1) and T_H/T_C17 activation. Combined administration also maintained T_reg reconstitution [resulting in an enhanced T_reg/T_eff ratio (40% over baseline) in the KY1005/sirolimus cohort compared to a 2.9-fold decrease in the unprophylaxed GVHD cohort]. This unique immunologic signature resulted in transplant recipients that were able to control GVHD for the length of analysis and to down-regulate donor/recipient alloreactivity despite maintaining anti-third-party responses. These data indicate that combined OX40L blockade and sirolimus represents a promising strategy to induce immune balance after transplant and is an important candidate regimen for clinical translation.

Transcriptome analysis of GVHD reveals aurora kinase A as a targetable pathway for disease prevention

Graft-versus-host disease (GVHD) is the most common complication of hematopoietic stem cell transplant (HCT). However, our understanding of the molecular pathways that cause this disease remains incomplete, leading to inadequate treatment strategies. To address this, we measured the gene expression profile of nonhuman primate (NHP) T cells during acute GVHD. Utilizing microarray technology, we measured the expression profiles of CD3(+) T cells from five cohorts: allogeneic transplant recipients receiving (i) no immunoprophylaxis (No Rx), (ii) sirolimus monotherapy (Siro), (iii) tacrolimus-methotrexate (Tac-Mtx), as well as (iv) autologous transplant recipients (Auto) and (v) healthy controls (HC). This comparison allowed us to identify transcriptomic signatures specific for alloreactive T cells and determine the impact of both mTOR (mechanistic target of rapamycin) and calcineurin inhibition on GVHD. We found that the transcriptional profile of unprophylaxed GVHD was characterized by significant perturbation of pathways regulating T cell proliferation, effector function, and cytokine synthesis. Within these pathways, we discovered potentially druggable targets not previously implicated in GVHD, prominently including aurora kinase A (AURKA). Utilizing a murine GVHD model, we demonstrated that pharmacologic inhibition of AURKA could improve survival. Moreover, we found enrichment of AURKA transcripts both in allo-proliferating T cells and in sorted T cells from patients with clinical GVHD. These data provide a comprehensive elucidation of the T cell transcriptome in primate acute GVHD and suggest that AURKA should be considered a target for preventing GVHD, which, given the many available AURKA inhibitors in clinical development, could be quickly deployed for the prevention of GVHD.

Predicting the functions of long noncoding RNAs using RNA-seq based on Bayesian network

Long noncoding RNAs (lncRNAs) have been shown to play key roles in various biological processes. However, functions of most lncRNAs are poorly characterized. Here, we represent a framework to predict functions of lncRNAs through construction of a regulatory network between lncRNAs and protein-coding genes. Using RNA-seq data, the transcript profiles of lncRNAs and protein-coding genes are constructed. Using the Bayesian network method, a regulatory network, which implies dependency relations between lncRNAs and protein-coding genes, was built. In combining protein interaction network, highly connected coding genes linked by a given lncRNA were subsequently used to predict functions of the lncRNA through functional enrichment. Application of our method to prostate RNA-seq data showed that 762 lncRNAs in the constructed regulatory network were assigned functions. We found that lncRNAs are involved in diverse biological processes, such as tissue development or embryo development (e.g., nervous system development and mesoderm development). By comparison with functions inferred using the neighboring gene-based method and functions determined using lncRNA knockdown experiments, our method can provide comparable predicted functions of lncRNAs. Overall, our method can be applied to emerging RNA-seq data, which will help researchers identify complex relations between lncRNAs and coding genes and reveal important functions of lncRNAs.

Introduction to sequencing the brain transcriptome

High-throughput next-generation sequencing is now entering its second decade. However, it was not until 2008 that the first report of sequencing the brain transcriptome appeared (Mortazavi, Williams, Mccue, Schaeffer, & Wold, 2008). These authors compared short-read RNA-Seq data for mouse whole brain with microarray results for the same sample and noted both the advantages and disadvantages of the RNA-Seq approach. While RNA-Seq provided exon level resolution, the majority of the reads were provided by a small proportion of highly expressed genes and the data analysis was exceedingly complex. Over the past 6 years, there have been substantial improvements in both RNA-Seq technology and data analysis. This volume contains 11 chapters that detail various aspects of sequencing the brain transcriptome. Some of the chapters are very methods driven, while others focus on the use of RNA-Seq to study such diverse areas as development, schizophrenia, and drug abuse. This chapter briefly reviews the transition from microarrays to RNA-Seq as the preferred method for analyzing the brain transcriptome. Compared with microarrays, RNA-Seq has a greater dynamic range, detects both coding and noncoding RNAs, is superior for gene network construction, detects alternative spliced transcripts, and can be used to extract genotype information, e.g., nonsynonymous coding single nucleotide polymorphisms. RNA-Seq embraces the complexity of the brain transcriptome and provides a mechanism to understand the underlying regulatory code; the potential to inform the brain-behavior-disease relationships is substantial.

Selective nucleic acid capture with shielded covalent probes

Nucleic acid probes are used for diverse applications in vitro, in situ, and in vivo. In any setting, their power is limited by imperfect selectivity (binding of undesired targets) and incomplete affinity (binding is reversible, and not all desired targets bound). These difficulties are fundamental, stemming from reliance on base pairing to provide both selectivity and affinity. Shielded covalent (SC) probes eliminate the longstanding trade-off between selectivity and durable target capture, achieving selectivity via programmable base pairing and molecular conformation change, and durable target capture via activatable covalent cross-linking. In pure and mixed samples, SC probes covalently capture complementary DNA or RNA oligo targets and reject two-nucleotide mismatched targets with near-quantitative yields at room temperature, achieving discrimination ratios of 2-3 orders of magnitude. Semiquantitative studies with full-length mRNA targets demonstrate selective covalent capture comparable to that for RNA oligo targets. Single-nucleotide DNA or RNA mismatches, including nearly isoenergetic RNA wobble pairs, can be efficiently rejected with discrimination ratios of 1-2 orders of magnitude. Covalent capture yields appear consistent with the thermodynamics of probe/target hybridization, facilitating rational probe design. If desired, cross-links can be reversed to release the target after capture. In contrast to existing probe chemistries, SC probes achieve the high sequence selectivity of a structured probe, yet durably retain their targets even under denaturing conditions. This previously incompatible combination of properties suggests diverse applications based on selective and stable binding of nucleic acid targets under conditions where base-pairing is disrupted (e.g., by stringent washes in vitro or in situ, or by enzymes in vivo).

Genes, behavior and next-generation RNA sequencing

Advances in next-generation sequencing suggest that RNA-Seq is poised to supplant microarray-based approaches for transcriptome analysis. This article briefly reviews the use of microarrays in the brain-behavior context and then illustrates why RNA-Seq is a superior strategy. Compared with microarrays, RNA-Seq has a greater dynamic range, detects both coding and noncoding RNAs, is superior for gene network construction, detects alternative spliced transcripts, detects allele specific expression and can be used to extract genotype information, e.g. nonsynonymous coding single nucleotide polymorphisms. Examples of where RNA-Seq has been used to assess brain gene expression are provided. Despite the advantages of RNA-Seq, some disadvantages remain. These include the high cost of RNA-Seq and the computational complexities associated with data analysis. RNA-Seq embraces the complexity of the transcriptome and provides a mechanism to understand the underlying regulatory code; the potential to inform the brain-behavior relationship is substantial.

A model of binding on DNA microarrays: understanding the combined effect of probe synthesis failure, cross-hybridization, DNA fragmentation and other experimental details of affymetrix arrays

BACKGROUND

DNA microarrays are used both for research and for diagnostics. In research, Affymetrix arrays are commonly used for genome wide association studies, resequencing, and for gene expression analysis. These arrays provide large amounts of data. This data is analyzed using statistical methods that quite often discard a large portion of the information. Most of the information that is lost comes from probes that systematically fail across chips and from batch effects. The aim of this study was to develop a comprehensive model for hybridization that predicts probe intensities for Affymetrix arrays and that could provide a basis for improved microarray analysis and probe development. The first part of the model calculates probe binding affinities to all the possible targets in the hybridization solution using the Langmuir isotherm. In the second part of the model we integrate details that are specific to each experiment and contribute to the differences between hybridization in solution and on the microarray. These details include fragmentation, wash stringency, temperature, salt concentration, and scanner settings. Furthermore, the model fits probe synthesis efficiency and target concentration parameters directly to the data. All the parameters used in the model have a well-established physical origin.

RESULTS

For the 302 chips that were analyzed the mean correlation between expected and observed probe intensities was 0.701 with a range of 0.88 to 0.55. All available chips were included in the analysis regardless of the data quality. Our results show that batch effects arise from differences in probe synthesis, scanner settings, wash strength, and target fragmentation. We also show that probe synthesis efficiencies for different nucleotides are not uniform.

CONCLUSIONS

To date this is the most complete model for binding on microarrays. This is the first model that includes both probe synthesis efficiency and hybridization kinetics/cross-hybridization. These two factors are sequence dependent and have a large impact on probe intensity. The results presented here provide novel insight into the effect of probe synthesis errors on Affymetrix microarrays; furthermore, the algorithms developed in this work provide useful tools for the analysis of cross-hybridization, probe synthesis efficiency, fragmentation, wash stringency, temperature, and salt concentration on microarray intensities.

Global transcriptional analysis of oocyte-based and factor-based nuclear reprogramming in the nonhuman primate

The mechanisms of nuclear reprogramming following somatic cell nuclear transfer (SCNT) to enucleated oocytes or factor-based reprogramming are poorly understood. In this study global transcriptional analysis was performed on a number of different rhesus monkey (Macaca mulatta) cell and tissue samples, including rhesus-induced pluripotent stem cells (IPSCs) and rhesus SCNT-derived embryonic stem cells (SCNT-ESCs). Global transcriptional cluster analysis and stem cell-specific gene expression analysis both suggested that the oocyte-reprogrammed SCNT-ESCs were transcriptionally closer to the control fertilized ESCs than IPSCs. These results, combined with previous epigenetic analysis studies in the mouse, reinforce the hypothesis that oocyte-reprogrammed cell nuclei are more completely reprogrammed to an ESC state than IPSCs. Transcriptional analysis of rhesus oocytes detected over 500 ESC-specific genes, including OCT3/4, NR5A2, and DNMT3B. These results, combined with previously published reprogramming research, were used as the basis for a general model to explain the mechanisms of nuclear reprogramming.