Katharina E. Hayer

CircaDB: a database of mammalian circadian gene expression profiles

CircaDB (http://circadb.org) is a new database of circadian transcriptional profiles from time course expression experiments from mice and humans. Each transcript’s expression was evaluated by three separate algorithms, JTK_Cycle, Lomb Scargle and DeLichtenberg. Users can query the gene annotations using simple and powerful full text search terms, restrict results to specific data sets and provide probability thresholds for each algorithm. Visualizations of the data are intuitive charts that convey profile information more effectively than a table of probabilities. The CircaDB web application is open source and available at http://github.com/itmat/circadb.

IVT-seq reveals extreme bias in RNA sequencing

BackgroundRNA-seq is a powerful technique for identifying and quantifying transcription and splicing events, both known and novel. However, given its recent development and the proliferation of library construction methods, understanding the bias it introduces is incomplete but critical to realizing its value.ResultsWe present a method, in vitro transcription sequencing (IVT-seq), for identifying and assessing the technical biases in RNA-seq library generation and sequencing at scale. We created a pool of over 1,000 in vitro transcribed RNAs from a full-length human cDNA library and sequenced them with polyA and total RNA-seq, the most common protocols. Because each cDNA is full length, and we show in vitro transcription is incredibly processive, each base in each transcript should be equivalently represented. However, with common RNA-seq applications and platforms, we find 50% of transcripts have more than two-fold and 10% have more than 10-fold differences in within-transcript sequence coverage. We also find greater than 6% of transcripts have regions of dramatically unpredictable sequencing coverage between samples, confounding accurate determination of their expression. We use a combination of experimental and computational approaches to show rRNA depletion is responsible for the most significant variability in coverage, and several sequence determinants also strongly influence representation.ConclusionsThese results show the utility of IVT-seq for promoting better understanding of bias introduced by RNA-seq. We find rRNA depletion is responsible for substantial, unappreciated biases in coverage introduced during library preparation. These biases suggest exon-level expression analysis may be inadvisable, and we recommend caution when interpreting RNA-seq results.

Simulation-based comprehensive benchmarking of RNA-seq aligners

Alignment is the first step in most RNA-seq analysis pipelines, and the accuracy of downstream analyses depends heavily on it. Unlike most steps in the pipeline, alignment is particularly amenable to benchmarking with simulated data. We performed a comprehensive benchmarking of 14 common splice-aware aligners for base, read, and exon junction-level accuracy and compared default with optimized parameters. We found that performance varied by genome complexity, and accuracy and popularity were poorly correlated. The most widely cited tool underperforms for most metrics, particularly when using default settings.

Benchmark analysis of algorithms for determining and quantifying full-length mRNA splice forms from RNA-seq data

Motivation: Because of the advantages of RNA sequencing (RNA-Seq) over microarrays, it is gaining widespread popularity for highly parallel gene expression analysis. For example, RNA-Seq is expected to be able to provide accurate identification and quantification of full-length splice forms. A number of informatics packages have been developed for this purpose, but short reads make it a difficult problem in principle. Sequencing error and polymorphisms add further complications. It has become necessary to perform studies to determine which algorithms perform best and which if any algorithms perform adequately. However, there is a dearth of independent and unbiased benchmarking studies. Here we take an approach using both simulated and experimental benchmark data to evaluate their accuracy. Results: We conclude that most methods are inaccurate even using idealized data, and that no method is highly accurate once multiple splice forms, polymorphisms, intron signal, sequencing errors, alignment errors, annotation errors and other complicating factors are present. These results point to the pressing need for further algorithm development. Availability and implementation: Simulated datasets and other supporting information can be found at http://bioinf.itmat.upenn.edu/BEERS/bp2 Supplementary information: Supplementary data are available at Bioinformatics online. Contact: hayer@upenn.edu

A Genome-wide Screen Identifies PAPP-AA-Mediated IGFR Signaling as a Novel Regulator of Habituation Learning

Habituation represents a fundamental form of learning, yet the underlying molecular genetic mechanisms are not well defined. Here we report on a genome-wide genetic screen, coupled with whole-genome sequencing, that identified 14 zebrafish startle habituation mutants including mutants of the vertebrate-specific gene pregnancy-associated plasma protein-aa (pappaa). PAPP-AA encodes an extracellular metalloprotease known to increase IGF bioavailability, thereby enhancing IGF receptor signaling. We find that pappaa is expressed by startle circuit neurons, and expression of wild-type but not a metalloprotease-inactive version of pappaa restores habituation in pappaa mutants. Furthermore, acutely inhibiting IGF1R function in wild-type reduces habituation, while activation of IGF1R downstream effectors in pappaa mutants restores habituation, demonstrating that pappaa promotes learning by acutely and locally increasing IGF bioavailability. In sum, our results define the first functional gene set for habituation learning in a vertebrate and identify PAPPAA-regulated IGF signaling as a novel mechanism regulating habituation learning.

A comparison of Illumina and Ion Torrent sequencing platforms in the context of differential gene expression

BackgroundThough Illumina has largely dominated the RNA-Seq field, the simultaneous availability of Ion Torrent has left scientists wondering which platform is most effective for differential gene expression (DGE) analysis. Previous investigations of this question have typically used reference samples derived from cell lines and brain tissue, and do not involve biological variability. While these comparisons might inform studies of tissue-specific expression, marked by large-scale transcriptional differences, this is not the common use case.ResultsHere we employ a standard treatment/control experimental design, which enables us to evaluate these platforms in the context of the expression differences common in differential gene expression experiments. Specifically, we assessed the hepatic inflammatory response of mice by assaying liver RNA from control and IL-1β treated animals with both the Illumina HiSeq and the Ion Torrent Proton sequencing platforms. We found the greatest difference between the platforms at the level of read alignment, a moderate level of concordance at the level of DGE analysis, and nearly identical results at the level of differentially affected pathways. Interestingly, we also observed a strong interaction between sequencing platform and choice of aligner. By aligning both real and simulated Illumina and Ion Torrent data with the twelve most commonly-cited aligners in the literature, we observed that different aligner and platform combinations were better suited to probing different genomic features; for example, disentangling the source of expression in gene-pseudogene pairs.ConclusionsTaken together, our results indicate that while Illumina and Ion Torrent have similar capacities to detect changes in biology from a treatment/control experiment, these platforms may be tailored to interrogate different transcriptional phenomena through careful selection of alignment software.

Cytosine Deaminase APOBEC3A Sensitizes Leukemia Cells to Inhibition of the DNA Replication Checkpoint

Mutational signatures in cancer genomes have implicated the APOBEC3 cytosine deaminases in oncogenesis, possibly offering a therapeutic vulnerability. Elevated APOBEC3B expression has been detected in solid tumors, but expression of APOBEC3A (A3A) in cancer has not been described to date. Here, we report that A3A is highly expressed in subsets of pediatric and adult acute myelogenous leukemia (AML). We modeled A3A expression in the THP1 AML cell line by introducing an inducible A3A gene. A3A expression caused ATR-dependent phosphorylation of Chk1 and cell-cycle arrest, consistent with replication checkpoint activation. Further, replication checkpoint blockade via small-molecule inhibition of ATR kinase in cells expressing A3A led to apoptosis and cell death. Although DNA damage checkpoints are broadly activated in response to A3A activity, synthetic lethality was specific to ATR signaling via Chk1 and did not occur with ATM inhibition. Our findings identify elevation of A3A expression in AML cells, enabling apoptotic sensitivity to inhibitors of the DNA replication checkpoint and suggesting it as a candidate biomarker for ATR inhibitor therapy. Cancer Res; 77(17); 4579-88. ©2017 AACR.

Zebrafish foxc1a drives appendage-specific neural circuit development

Neural connectivity between the spinal cord and paired appendages is key to the superior locomotion of tetrapods and aquatic vertebrates. In contrast to nerves that innervate axial muscles, those innervating appendages converge at a specialized structure, the plexus, where they topographically reorganize before navigating towards their muscle targets. Despite its importance for providing appendage mobility, the genetic program that drives nerve convergence at the plexus, as well as the functional role of this convergence, are not well understood. Here, we show that in zebrafish the transcription factor foxc1a is dispensable for trunk motor nerve guidance but is required to guide spinal nerves innervating the pectoral fins, equivalent to the tetrapod forelimbs. In foxc1a null mutants, instead of converging with other nerves at the plexus, pectoral fin nerves frequently bypass the plexus. We demonstrate that foxc1a expression in muscle cells delineating the nerve path between the spinal cord and the plexus region restores convergence at the plexus. By labeling individual fin nerves, we show that mutant nerves bypassing the plexus enter the fin at ectopic positions, yet innervate their designated target areas, suggesting that motor axons can select their appropriate fin target area independently of their migration through the plexus. Although foxc1a mutants display topographically correct fin innervation, mutant fin muscles exhibit a reduction in the levels of pre- and postsynaptic structures, concomitant with reduced pectoral fin function. Combined, our results reveal foxc1a as a key player in the development of connectivity between the spinal cord and paired appendages, which is crucial for appendage mobility. Summary: The transcription factor foxc1a is dispensable for trunk motor nerve guidance but is required to guide spinal nerves innervating the pectoral fins in zebrafish.

A Cyfip2-Dependent Excitatory Interneuron Pathway Establishes the Innate Startle Threshold

SUMMARY Sensory experiences dynamically modify whether animals respond to a given stimulus, but it is unclear how innate behavioral thresholds are established. Here, we identify molecular and circuit-level mechanisms underlying the innate threshold of the zebrafish startle response. From a forward genetic screen, we isolated five mutant lines with reduced innate startle thresholds. Using whole-genome sequencing, we identify the causative mutation for one line to be in the fragile X mental retardation protein (FMRP)-interacting protein cyfip2. We show that cyfip2 acts independently of FMRP and that reactivation of cyfip2 restores the baseline threshold after phenotype onset. Finally, we show that cyfip2 regulates the innate startle threshold by reducing neural activity in a small group of excitatory hindbrain interneurons. Thus, we identify a selective set of genes critical to establishing an innate behavioral threshold and uncover a circuit-level role for cyfip2 in this process.

Rb family proteins enforce the homeostasis of quiescent hematopoietic stem cells by repressing Socs3 expression

Prolonged exit from quiescence by hematopoietic stem cells (HSCs) progressively impairs their homeostasis in the bone marrow through an unidentified mechanism. We show that Rb proteins, which are major enforcers of quiescence, maintain HSC homeostasis by positively regulating thrombopoietin (Tpo)-mediated Jak2 signaling. Rb family protein inactivation triggers the progressive E2f-mediated transactivation of Socs3, a potent inhibitor of Jak2 signaling, in cycling HSCs. Aberrant activation of Socs3 impairs Tpo signaling and leads to impaired HSC homeostasis. Therefore, Rb proteins act as a central hub of quiescence and homeostasis by coordinating the regulation of both cell cycle and Jak2 signaling in HSCs.