Charles D. Johnson

The let-7 MicroRNA Represses Cell Proliferation Pathways in Human Cells

MicroRNAs play important roles in animal development, cell differentiation, and metabolism and have been implicated in human cancer. The let-7 microRNA controls the timing of cell cycle exit and terminal differentiation in Caenorhabditis elegans and is poorly expressed or deleted in human lung tumors. Here, we show that let-7 is highly expressed in normal lung tissue, and that inhibiting let-7 function leads to increased cell division in A549 lung cancer cells. Overexpression of let-7 in cancer cell lines alters cell cycle progression and reduces cell division, providing evidence that let-7 functions as a tumor suppressor in lung cells. let-7 was previously shown to regulate the expression of the RAS lung cancer oncogenes, and our work now shows that multiple genes involved in cell cycle and cell division functions are also directly or indirectly repressed by let-7. This work reveals the let-7 microRNA to be a master regulator of cell proliferation pathways.

Genome-Scale MicroRNA and Small Interfering RNA Screens Identify Small RNA Modulators of TRAIL-Induced Apoptosis Pathway

Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) binds to death receptors 4/5 and selectively induces caspase-dependent apoptosis. The RNA interference screening approach has led to the discovery and characterization of several TRAIL pathway components in human cells. Here, libraries of synthetic small interfering RNA (siRNA) and microRNAs (miRNA) were used to probe the TRAIL pathway. In addition to known genes, siRNAs targeting CDK4, PTGS1, ALG2, CLCN3, IRAK4, and MAP3K8 altered TRAIL-induced caspase-3 activation responses. Introduction of the miRNAs let-7c, mir-10a, mir-144, mir-150, mir-155, and mir-193 also affected the activation of the caspase cascade. Putative targets of these endogenous miRNAs included genes encoding death receptors, caspases, and other apoptosis-related genes. Among the novel genes revealed in the screen, CDK4 was selected for further characterization. CDK4 was the only member of the cyclin-dependent kinase gene family that bore a unique function in apoptotic signal transduction.

Using RNA sample titrations to assess microarray platform performance and normalization techniques

We have assessed the utility of RNA titration samples for evaluating microarray platform performance and the impact of different normalization methods on the results obtained. As part of the MicroArray Quality Control project, we investigated the performance of five commercial microarray platforms using two independent RNA samples and two titration mixtures of these samples. Focusing on 12,091 genes common across all platforms, we determined the ability of each platform to detect the correct titration response across the samples. Global deviations from the response predicted by the titration ratios were observed. These differences could be explained by variations in relative amounts of messenger RNA as a fraction of total RNA between the two independent samples. Overall, both the qualitative and quantitative correspondence across platforms was high. In summary, titration samples may be regarded as a valuable tool, not only for assessing microarray platform performance and different analysis methods, but also for determining some underlying biological features of the samples.

Analyzing micro-RNA expression using microarrays.

The discovery of micro-RNAs (miRNAs) and the growing appreciation of the importance of micro-RNAs in the regulation of gene expression are driving increasing interest in miRNA expression profiling. Early studies have suggested prominent roles for these genetically encoded regulatory molecules in a variety of normal biological processes and diseases, particularly cancer. However, the field of miRNA expression profiling is in its infancy. Several factors, including the small size, the unknown but limited number of miRNAs, and the tissue-to-tissue and tissue-to-disease state variability in miRNA expression, make the adaptation of microarray technology to the evaluation of miRNA expression nontrivial. This chapter describes the unique features of miRNA microarray experiments and analysis and provides a case study demonstrating our approach to miRNA expression analysis.

Evaluation of the coverage and depth of transcriptome by RNA-Seq in chickens

BackgroundRNA-Seq is the recently developed high-throughput sequencing technology for profiling the entire transcriptome in any organism. It has several major advantages over current hybridization-based approach such as microarrays. However, the cost per sample by RNA-Seq is still prohibitive for most laboratories. With continued improvement in sequence output, it would be cost-effective if multiple samples are multiplexed and sequenced in a single lane with sufficient transcriptome coverage. The objective of this analysis is to evaluate what sequencing depth might be sufficient to interrogate gene expression profiling in the chicken by RNA-Seq.ResultsTwo cDNA libraries from chicken lungs were sequenced initially, and 4.9 million (M) and 1.6 M (60 bp) reads were generated, respectively. With significant improvements in sequencing technology, two technical replicate cDNA libraries were re-sequenced. Totals of 29.6 M and 28.7 M (75 bp) reads were obtained with the two samples. More than 90% of annotated genes were detected in the data sets with 28.7-29.6 M reads, while only 68% of genes were detected in the data set with 1.6 M reads. The correlation coefficients of gene expression between technical replicates within the same sample were 0.9458 and 0.8442. To evaluate the appropriate depth needed for mRNA profiling, a random sampling method was used to generate different number of reads from each sample. There was a significant increase in correlation coefficients from a sequencing depth of 1.6 M to 10 M for all genes except highly abundant genes. No significant improvement was observed from the depth of 10 M to 20 M (75 bp) reads.ConclusionThe analysis from the current study demonstrated that 30 M (75 bp) reads is sufficient to detect all annotated genes in chicken lungs. Ten million (75 bp) reads could detect about 80% of annotated chicken genes, and RNA-Seq at this depth can serve as a replacement of microarray technology. Furthermore, the depth of sequencing had a significant impact on measuring gene expression of low abundant genes. Finally, the combination of experimental and simulation approaches is a powerful approach to address the relationship between the depth of sequencing and transcriptome coverage.

Novel transcriptome assembly and improved annotation of the whiteleg shrimp (Litopenaeus vannamei), a dominant crustacean in global seafood mariculture

We present a new transcriptome assembly of the Pacific whiteleg shrimp (Litopenaeus vannamei), the species most farmed for human consumption. Its functional annotation, a substantial improvement over previous ones, is provided freely. RNA-Seq with Illumina HiSeq technology was used to analyze samples extracted from shrimp abdominal muscle, hepatopancreas, gills and pleopods. We used the Trinity and Trinotate software suites for transcriptome assembly and annotation, respectively. The quality of this assembly and the affiliated targeted homology searches greatly enrich the curated transcripts currently available in public databases for this species. Comparison with the model arthropod Daphnia allows some insights into defining characteristics of decapod crustaceans. This large-scale gene discovery gives the broadest depth yet to the annotated transcriptome of this important species and should be of value to ongoing genomics and immunogenetic resistance studies in this shrimp of paramount global economic importance.

Whole-Genome sequencing and genetic variant analysis of a quarter Horse mare

BackgroundThe catalog of genetic variants in the horse genome originates from a few select animals, the majority originating from the Thoroughbred mare used for the equine genome sequencing project. The purpose of this study was to identify genetic variants, including single nucleotide polymorphisms (SNPs), insertion/deletion polymorphisms (INDELs), and copy number variants (CNVs) in the genome of an individual Quarter Horse mare sequenced by next-generation sequencing.ResultsUsing massively parallel paired-end sequencing, we generated 59.6 Gb of DNA sequence from a Quarter Horse mare resulting in an average of 24.7X sequence coverage. Reads were mapped to approximately 97% of the reference Thoroughbred genome. Unmapped reads were de novo assembled resulting in 19.1 Mb of new genomic sequence in the horse. Using a stringent filtering method, we identified 3.1 million SNPs, 193 thousand INDELs, and 282 CNVs. Genetic variants were annotated to determine their impact on gene structure and function. Additionally, we genotyped this Quarter Horse for mutations of known diseases and for variants associated with particular traits. Functional clustering analysis of genetic variants revealed that most of the genetic variation in the horses genome was enriched in sensory perception, signal transduction, and immunity and defense pathways.ConclusionsThis is the first sequencing of a horse genome by next-generation sequencing and the first genomic sequence of an individual Quarter Horse mare. We have increased the catalog of genetic variants for use in equine genomics by the addition of novel SNPs, INDELs, and CNVs. The genetic variants described here will be a useful resource for future studies of genetic variation regulating performance traits and diseases in equids.

Modulation of RNA polymerase II phosphorylation downstream of pathogen perception orchestrates plant immunity.

Perception of microbe-associated molecular patterns (MAMPs) elicits host transcriptional reprogramming as part of the immune response. Although pathogen perception is well studied, the signaling networks orchestrating immune gene expression remain less clear. In a genetic screen for components involved in the early immune gene transcription reprogramming, we identified Arabidopsis RNA polymerase II C-terminal domain (CTD) phosphatase-like 3 (CPL3) as a negative regulator of immune gene expression. MAMP perception induced rapid and transient cyclin-dependent kinase C (CDKC)-mediated phosphorylation of Arabidopsis CTD. The CDKCs, which are in turn phosphorylated and activated by a canonical MAP kinase (MAPK) cascade, represent a pointxa0of signaling convergence downstream of multiple immune receptors. CPL3 directly dephosphorylated CTD to counteract MAPK-mediated CDKC regulation. Thus, modulation of the phosphorylation dynamics of eukaryotic RNA polymerase II transcription machinery by MAPKs, CTD kinases,xa0and phosphatases constitutes an essential mechanism for rapid orchestration of host immune gene expression and defense upon pathogen attacks.

A draft de novo genome assembly for the northern bobwhite (Colinus virginianus) reveals evidence for a rapid decline in effective population size beginning in the Late Pleistocene.

Wild populations of northern bobwhites (Colinus virginianus; hereafter bobwhite) have declined across nearly all of their U.S. range, and despite their importance as an experimental wildlife model for ecotoxicology studies, no bobwhite draft genome assembly currently exists. Herein, we present a bobwhite draft de novo genome assembly with annotation, comparative analyses including genome-wide analyses of divergence with the chicken (Gallus gallus) and zebra finch (Taeniopygia guttata) genomes, and coalescent modeling to reconstruct the demographic history of the bobwhite for comparison to other birds currently in decline (i.e., scarlet macaw; Ara macao). More than 90% of the assembled bobwhite genome was captured within <40,000 final scaffolds (N50u200a=u200a45.4 Kb) despite evidence for approximately 3.22 heterozygous polymorphisms per Kb, and three annotation analyses produced evidence for >14,000 unique genes and proteins. Bobwhite analyses of divergence with the chicken and zebra finch genomes revealed many extremely conserved gene sequences, and evidence for lineage-specific divergence of noncoding regions. Coalescent models for reconstructing the demographic history of the bobwhite and the scarlet macaw provided evidence for population bottlenecks which were temporally coincident with human colonization of the New World, the late Pleistocene collapse of the megafauna, and the last glacial maximum. Demographic trends predicted for the bobwhite and the scarlet macaw also were concordant with how opposing natural selection strategies (i.e., skewness in the r-/K-selection continuum) would be expected to shape genome diversity and the effective population sizes in these species, which is directly relevant to future conservation efforts.

Modeling the next generation sequencing sample processing pipeline for the purposes of classification

BackgroundA key goal of systems biology and translational genomics is to utilize high-throughput measurements of cellular states to develop expression-based classifiers for discriminating among different phenotypes. Recent developments of Next Generation Sequencing (NGS) technologies can facilitate classifier design by providing expression measurements for tens of thousands of genes simultaneously via the abundance of their mRNA transcripts. Because NGS technologies result in a nonlinear transformation of the actual expression distributions, their application can result in data that are less discriminative than would be the actual expression levels themselves, were they directly observable.ResultsUsing state-of-the-art distributional modeling for the NGS processing pipeline, this paper studies how that pipeline, via the resulting nonlinear transformation, affects classification and feature selection. The effects of different factors are considered and NGS-based classification is compared to SAGE-based classification and classification directly on the raw expression data, which is represented by a very high-dimensional model previously developed for gene expression. As expected, the nonlinear transformation resulting from NGS processing diminishes classification accuracy; however, owing to a larger number of reads, NGS-based classification outperforms SAGE-based classification.ConclusionsHaving high numbers of reads can mitigate the degradation in classification performance resulting from the effects of NGS technologies. Hence, when performing a RNA-Seq analysis, using the highest possible coverage of the genome is recommended for the purposes of classification.