1,896 research outputs found
Splicing bioinformatics to biology
A report on the 2nd Symposium on Alternative Transcript Diversity, Heidelberg, Germany, 21-23 March 2006
De novo prediction of PTBP1 binding and splicing targets reveals unexpected features of its RNA recognition and function.
The splicing regulator Polypyrimidine Tract Binding Protein (PTBP1) has four RNA binding domains that each binds a short pyrimidine element, allowing recognition of diverse pyrimidine-rich sequences. This variation makes it difficult to evaluate PTBP1 binding to particular sites based on sequence alone and thus to identify target RNAs. Conversely, transcriptome-wide binding assays such as CLIP identify many in vivo targets, but do not provide a quantitative assessment of binding and are informative only for the cells where the analysis is performed. A general method of predicting PTBP1 binding and possible targets in any cell type is needed. We developed computational models that predict the binding and splicing targets of PTBP1. A Hidden Markov Model (HMM), trained on CLIP-seq data, was used to score probable PTBP1 binding sites. Scores from this model are highly correlated (Ļā=ā-0.9) with experimentally determined dissociation constants. Notably, we find that the protein is not strictly pyrimidine specific, as interspersed Guanosine residues are well tolerated within PTBP1 binding sites. This model identifies many previously unrecognized PTBP1 binding sites, and can score PTBP1 binding across the transcriptome in the absence of CLIP data. Using this model to examine the placement of PTBP1 binding sites in controlling splicing, we trained a multinomial logistic model on sets of PTBP1 regulated and unregulated exons. Applying this model to rank exons across the mouse transcriptome identifies known PTBP1 targets and many new exons that were confirmed as PTBP1-repressed by RT-PCR and RNA-seq after PTBP1 depletion. We find that PTBP1 dependent exons are diverse in structure and do not all fit previous descriptions of the placement of PTBP1 binding sites. Our study uncovers new features of RNA recognition and splicing regulation by PTBP1. This approach can be applied to other multi-RRM domain proteins to assess binding site degeneracy and multifactorial splicing regulation
A Precise Chronology of Middle to Late Holocene Bison Exploitation in the Far Southern Great Plains
In regions on the margins of the Great Plains grasslands, documenting the intermittent history of bison exploitation has presented challenges to archeologists. Chronologies based on archeological associations have long been useful in regional research, but can be imprecise and of inadequate resolution for constructing precise sequences of prehistoric events. Here, we present a record of directly dated bison from archeological contexts spanning the last 6000 years on the very southern extent of the Great Plains. This study includes 61 specimens from archeological contexts that were dated by XAD purified AMS radiocarbon, with reported errors of only 15-20 14C years for most dates. The resulting record of bison exploitation for this area defines four main periods (Calf Creek, Late Archaic 1 and 2, and early Toyah) during which bison were exploited. Several dates also indicate an early historic presence of bison; this period may represent a late facet of the Toyah horizon. This study adds significant chronological resolution to the regional record of bison in parts of Texas and begins to help correlate cultural chronologies with important climatic data. It also points to the research value of obtaining additional directly dated bison samples from temporally and geographically diverse archeological contexts in our study area and beyond
Functional Plasticity in Lamellar Autotomy by Larval Damselflies in Response to Predatory Larval Dragonfly Cues
Adaptive autotomy is the self-amputation of an appendage in response to external stimuli that benefits survival. Variation in the ease of appendage removal among populations suggests that autotomy performance is under selection, evolves, or is phenotypically plastic, although the latter has never been experimentally tested. We model an autotomy threshold that optimally balances how the benefits of surviving predator attack versus the costs of losing an appendage vary with predator presence. We test for functional plasticity in autotomy threshold in the caudal lamellae of Enallagma damselfly larvae by experimentally manipulating non-lethal cues from predatory dragonfly larvae. Predator cues lead to functional plastic responses in the form of smaller lamellar joints that required lower peak breaking force. This is the first experimental demonstration of functional plasticity in autotomy to cues from a grasping predator, a novel form of indirect predator effects on prey, realized through plasticity in morphological traits that govern the autotomy threshold. This supports the model of optimized autotomy performance and provides a novel explanation for variation in performance among populations under different predator conditions. Plastic autotomy responses that mitigate costs in the face of variation in mortality risks might be a form of inducible defense
De Novo Prediction of PTBP1 Binding and Splicing Targets Reveals Unexpected Features of Its RNA Recognition and Function
The splicing regulator Polypyrimidine Tract Binding Protein (PTBP1) has four RNA binding domains that each binds a short pyrimidine element, allowing recognition of diverse pyrimidine-rich sequences. This variation makes it difficult to evaluate PTBP1 binding to particular sites based on sequence alone and thus to identify target RNAs. Conversely, transcriptome-wide binding assays such as CLIP identify many in vivo targets, but do not provide a quantitative assessment of binding and are informative only for the cells where the analysis is performed. A general method of predicting PTBP1 binding and possible targets in any cell type is needed. We developed computational models that predict the binding and splicing targets of PTBP1. A Hidden Markov Model (HMM), trained on CLIP-seq data, was used to score probable PTBP1 binding sites. Scores from this model are highly correlated (Ļā=āā0.9) with experimentally determined dissociation constants. Notably, we find that the protein is not strictly pyrimidine specific, as interspersed Guanosine residues are well tolerated within PTBP1 binding sites. This model identifies many previously unrecognized PTBP1 binding sites, and can score PTBP1 binding across the transcriptome in the absence of CLIP data. Using this model to examine the placement of PTBP1 binding sites in controlling splicing, we trained a multinomial logistic model on sets of PTBP1 regulated and unregulated exons. Applying this model to rank exons across the mouse transcriptome identifies known PTBP1 targets and many new exons that were confirmed as PTBP1-repressed by RT-PCR and RNA-seq after PTBP1 depletion. We find that PTBP1 dependent exons are diverse in structure and do not all fit previous descriptions of the placement of PTBP1 binding sites. Our study uncovers new features of RNA recognition and splicing regulation by PTBP1. This approach can be applied to other multi-RRM domain proteins to assess binding site degeneracy and multifactorial splicing regulation
Depolarization and CaM Kinase IV Modulate NMDA Receptor Splicing through Two Essential RNA Elements
Alternative splicing controls the activity of many proteins important for neuronal excitation, but the signal-transduction pathways that affect spliced isoform expression are not well understood. One particularly interesting system of alternative splicing is exon 21 (E21) of the NMDA receptor 1 (NMDAR1 E21), which controls the trafficking of NMDA receptors to the plasma membrane and is repressed by Ca(++)/calmodulin-dependent protein kinase (CaMK) IV signaling. Here, we characterize the splicing of NMDAR1 E21. We find that E21 splicing is reversibly repressed by neuronal depolarization, and we identify two RNA elements within the exon that function together to mediate the inducible repression. One of these exonic elements is similar to an intronic CaMK IVāresponsive RNA element (CaRRE) originally identified in the 3ā² splice site of the BK channel STREX exon, but not previously observed within an exon. The other element is a new RNA motif. Introduction of either of these two motifs, called CaRRE type 1 and CaRRE type 2, into a heterologous constitutive exon can confer CaMK IVādependent repression on the new exon. Thus, either exonic CaRRE can be sufficient for CaMK IVāinduced repression. Single nucleotide scanning mutagenesis defined consensus sequences for these two CaRRE motifs. A genome-wide motif search and subsequent RT-PCR validation identified a group of depolarization-regulated alternative exons carrying CaRRE consensus sequences. Many of these exons are likely to alter neuronal function. Thus, these two RNA elements define a group of co-regulated splicing events that respond to a common stimulus in neurons to alter their activity
Hydrologic Variability and the Application of Index of Biotic Integrity Metrics to Wetlands: A Great Lakes Evaluation
Interest by land-management and regulatory agencies in using biological indicators to detect wetland degradation, coupled with ongoing use of this approach to assess water quality in streams, led to the desire to develop and evaluate an Index of Biotic Integrity (IBI) for wetlands that could be used to categorize the level of degradation. We undertook this challenge with data from coastal wetlands of the Great Lakes, which have been degraded by a variety of human disturbances. We studied six barrier beach wetlands in western Lake Superior, six drowned-river-mouth wetlands along the eastern shore of Lake Michigan, and six open shoreline wetlands in Saginaw Bay of Lake Huron. Plant, fish, and invertebrate communities were sampled in each wetland. The resulting data were assessed in various forms against gradients of human disturbance to identify potential metrics that could be used in IBI development. Our results suggested that the metrics proposed as potential components of an IBI for barrier beach wetlands of Lake Superior held promise. The metrics for Lake Michigan drowned-river-mouth wetlands were inconsistent in identifying gradients of disturbance; those for Lake Huron open embayment wetlands were yet more inconsistent. Despite the potential displayed by the Lake Superior results within the year sampled, we concluded that an IBI for use in Great Lakes wetlands would not be valid unless separate scoring ranges were derived for each of several sequences of water-level histories. Variability in lake levels from year to year can produce variability in data and affect the reproducibility of data collected, primarily due to extreme changes in plant communities and the faunal habitat they provide. Substantially different results could be obtained in the same wetland in different years as a result of the response to lake-level change, with no change in the level of human disturbance. Additional problems included limited numbers of comparable sites, potential lack of undisturbed reference sites, and variable effects of different disturbance types. We also evaluated our conclusions with respect to hydrologic variability and other major natural disturbances affecting wetlands in other regions. We concluded that after segregation of wetland types by geographic, geomorphic, and hydrologic features, a functional IBI may be possible for wetlands with relatively stable hydrology. However, an IBI for wetlands with unpredictable yet recurring influences of climate-induced, long-term high water periods, droughts, or drought-related fires or weather-related catastrophic floods or high winds (hurricanes) would also require differing scales of measurement for years that differ in the length of time since the last major natural disturbance. A site-specific, detailed ecological analysis of biological indicators may indeed be of value in determining the quality or status of wetlands, but we recommend that IBI scores not be used unless the scoring ranges are calibrated for the specific hydrologic history pre-dating any sampling year
- ā¦