The neural development and organization of letter recognition: Evidence from functional neuroimaging, computational modeling, and behavioral studies

Although much of the brain’s functional organization is genetically predetermined, it appears that some noninnate functions can come to depend on dedicated and segregated neural tissue. In this paper, we describe a series of experiments that have investigated the neural development and organization of one such noninnate function: letter recognition. Functional neuroimaging demonstrates that letter and digit recognition depend on different neural substrates in some literate adults. How could the processing of two stimulus categories that are distinguished solely by cultural conventions become segregated in the brain? One possibility is that correlation-based learning in the brain leads to a spatial organization in cortex that reflects the temporal and spatial clustering of letters with letters in the environment. Simulations confirm that environmental co-occurrence does indeed lead to spatial localization in a neural network that uses correlation-based learning. Furthermore, behavioral studies confirm one critical prediction of this co-occurrence hypothesis, namely, that subjects exposed to a visual environment in which letters and digits occur together rather than separately (postal workers who process letters and digits together in Canadian postal codes) do indeed show less behavioral evidence for segregated letter and digit processing.

Catalytic mechanism of the adenylyl and guanylyl cyclases: Modeling and mutational analysis

The adenylyl and guanylyl cyclases catalyze the formation of 3′,5′-cyclic adenosine or guanosine monophosphate from the corresponding nucleoside 5′-triphosphate. The guanylyl cyclases, the mammalian adenylyl cyclases, and their microbial homologues function as pairs of homologous catalytic domains. The crystal structure of the rat type II adenylyl cyclase C2 catalytic domain was used to model by homology a mammalian adenylyl cyclase C1-C2 domain pair, a homodimeric adenylyl cyclase of Dictyostelium discoideum, a heterodimeric soluble guanylyl cyclase, and a homodimeric membrane guanylyl cyclase. Mg2+ATP or Mg2+GTP were docked into the active sites based on known stereochemical constraints on their conformation. The models are consistent with the activities of seven active-site mutants. Asp-310 and Glu-432 of type I adenylyl cyclase coordinate a Mg2+ ion. The D310S and D310A mutants have 10-fold reduced Vmax and altered [Mg2+] dependence. The NTP purine moieties bind in mostly hydrophobic pockets. Specificity is conferred by a Lys and an Asp in adenylyl cyclase, and a Glu, an Arg, and a Cys in guanylyl cyclase. The models predict that an Asp from one domain is a general base in the reaction, and that the transition state is stabilized by a conserved Asn-Arg pair on the other domain.

Ultrastructural Analysis of Transcription and Splicing in the Cell Nucleus after Bromo-UTP Microinjection

In this study we demonstrate, at an ultrastructural level, the in situ distribution of heterogeneous nuclear RNA transcription sites after microinjection of 5-bromo-UTP (BrUTP) into the cytoplasm of living cells and subsequent postembedding immunoelectron microscopic visualization after different labeling periods. Moreover, immunocytochemical localization of several pre-mRNA transcription and processing factors has been carried out in the same cells. This high-resolution approach allowed us to reveal perichromatin regions as the most important sites of nucleoplasmic RNA transcription and the perichromatin fibrils (PFs) as in situ forms of nascent transcripts. Furthermore, we show that transcription takes place in a rather diffuse pattern, without notable local accumulation of transcription sites. RNA polymerase II, heterogeneous nuclear ribonucleoprotein (hnRNP) core proteins, general transcription factor TFIIH, poly(A) polymerase, splicing factor SC-35, and Sm complex of small nuclear ribonucleoproteins (snRNPs) are associated with PFs. This strongly supports the idea that PFs are also sites of major pre-mRNA processing events. The absence of nascent transcripts, RNA polymerase II, poly(A) polymerase, and hnRNPs within the clusters of interchromatin granules rules out the possibility that this domain plays a role in pre-mRNA transcription and polyadenylation; however, interchromatin granule-associated zones contain RNA polymerase II, TFIIH, and Sm complex of snRNPs and, after longer periods of BrUTP incubation, also Br-labeled RNA. Their role in nuclear functions still remains enigmatic. In the nucleolus, transcription sites occur in the dense fibrillar component. Our fine structural results show that PFs represent the major nucleoplasmic structural domain involved in active pre-mRNA transcriptional and processing events.

Importance of replication in microarray gene expression studies: Statistical methods and evidence from repetitive cDNA hybridizations

We present statistical methods for analyzing replicated cDNA microarray expression data and report the results of a controlled experiment. The study was conducted to investigate inherent variability in gene expression data and the extent to which replication in an experiment produces more consistent and reliable findings. We introduce a statistical model to describe the probability that mRNA is contained in the target sample tissue, converted to probe, and ultimately detected on the slide. We also introduce a method to analyze the combined data from all replicates. Of the 288 genes considered in this controlled experiment, 32 would be expected to produce strong hybridization signals because of the known presence of repetitive sequences within them. Results based on individual replicates, however, show that there are 55, 36, and 58 highly expressed genes in replicates 1, 2, and 3, respectively. On the other hand, an analysis by using the combined data from all 3 replicates reveals that only 2 of the 288 genes are incorrectly classified as expressed. Our experiment shows that any single microarray output is subject to substantial variability. By pooling data from replicates, we can provide a more reliable analysis of gene expression data. Therefore, we conclude that designing experiments with replications will greatly reduce misclassification rates. We recommend that at least three replicates be used in designing experiments by using cDNA microarrays, particularly when gene expression data from single specimens are being analyzed.

Statistical modeling of large microarray data sets to identify stimulus-response profiles

A statistical modeling approach is proposed for use in searching large microarray data sets for genes that have a transcriptional response to a stimulus. The approach is unrestricted with respect to the timing, magnitude or duration of the response, or the overall abundance of the transcript. The statistical model makes an accommodation for systematic heterogeneity in expression levels. Corresponding data analyses provide gene-specific information, and the approach provides a means for evaluating the statistical significance of such information. To illustrate this strategy we have derived a model to depict the profile expected for a periodically transcribed gene and used it to look for budding yeast transcripts that adhere to this profile. Using objective criteria, this method identifies 81% of the known periodic transcripts and 1,088 genes, which show significant periodicity in at least one of the three data sets analyzed. However, only one-quarter of these genes show significant oscillations in at least two data sets and can be classified as periodic with high confidence. The method provides estimates of the mean activation and deactivation times, induced and basal expression levels, and statistical measures of the precision of these estimates for each periodic transcript.