A compendium of Caenorhabditis elegans regulatory transcription factors: a resource for mapping transcription regulatory networks

Background Transcription regulatory networks are composed of interactions between transcription factors and their target genes. Whereas unicellular networks have been studied extensively, metazoan transcription regulatory networks remain largely unexplored. Caenorhabditis elegans provides a powerful model to study such metazoan networks because its genome is completely sequenced and many functional genomic tools are available. While C. elegans gene predictions have undergone continuous refinement, this is not true for the annotation of functional transcription factors. The comprehensive identification of transcription factors is essential for the systematic mapping of transcription regulatory networks because it enables the creation of physical transcription factor resources that can be used in assays to map interactions between transcription factors and their target genes. Results By computational searches and extensive manual curation, we have identified a compendium of 934 transcription factor genes (referred to as wTF2.0). We find that manual curation drastically reduces the number of both false positive and false negative transcription factor predictions. We discuss how transcription factor splice variants and dimer formation may affect the total number of functional transcription factors. In contrast to mouse transcription factor genes, we find that C. elegans transcription factor genes do not undergo significantly more splicing than other genes. This difference may contribute to differences in organism complexity. We identify candidate redundant worm transcription factor genes and orthologous worm and human transcription factor pairs. Finally, we discuss how wTF2.0 can be used together with physical transcription factor clone resources to facilitate the systematic mapping of C. elegans transcription regulatory networks. Conclusion wTF2.0 provides a starting point to decipher the transcription regulatory networks that control metazoan development and function

The Transcriptional Landscape of Marek’s Disease Virus in Primary Chicken B Cells Reveals Novel Splice Variants and Genes

Marek’s disease virus (MDV) is an oncogenic alphaherpesvirus that infects chickens and poses a serious threat to poultry health. In infected animals, MDV efficiently replicates in B cells in various lymphoid organs. Despite many years of research, the viral transcriptome in primary target cells of MDV remained unknown. In this study, we uncovered the transcriptional landscape of the very virulent RB1B strain and the attenuated CVI988/Rispens vaccine strain in primary chicken B cells using high-throughput RNA-sequencing. Our data confirmed the expression of known genes, but also identified a novel spliced MDV gene in the unique short region of the genome. Furthermore, de novo transcriptome assembly revealed extensive splicing of viral genes resulting in coding and non-coding RNA transcripts. A novel splicing isoform of MDV UL15 could also be confirmed by mass spectrometry and RT-PCR. In addition, we could demonstrate that the associated transcriptional motifs are highly conserved and closely resembled those of the host transcriptional machinery. Taken together, our data allow a comprehensive re-annotation of the MDV genome with novel genes and splice variants that could be targeted in further research on MDV replication and tumorigenesis

Cryptic transcripts from a ubiquitous plasmid origin of replication confound tests for cis-regulatory function.

A vast amount of research on the regulation of gene expression has relied on plasmid reporter assays. In this study, we show that plasmids widely used for this purpose constitutively produce substantial amounts of RNA from a TATA-containing cryptic promoter within the origin of replication. Readthrough of these RNAs into the intended transcriptional unit potently stimulated reporter activity when the inserted test sequence contained a 3' splice site (ss). We show that two human sequences, originally reported to be internal ribosome entry sites and later to instead be promoters, mimic both types of element in dicistronic reporter assays by causing these cryptic readthrough transcripts to splice in patterns that allow efficient translation of the downstream cistron. Introduction of test sequences containing 3' ss into monocistronic luciferase reporter vectors widely used in the study of transcriptional regulation also created the false appearance of promoter function via the same mechanism. Across a large number of variants of these plasmids, we found a very highly significant correlation between reporter activity and levels of such spliced readthrough transcripts. Computational estimation of the frequency of cryptic 3' ss in genomic sequences suggests that misattribution of cis-regulatory function may be a common occurrence

Characterization of the Ca2+-gated and voltage-dependent k+-channel slo-1 of nematodes and its interaction with emodepside

The cyclooctadepsipeptide emodepside and its parent compound PF1022A are broad-spectrum nematicidal drugs which are able to eliminate nematodes resistant to other anthelmintics. The mode of action of cyclooctadepsipeptides is only partially understood, but involves the latrophilin Lat-1 receptor and the voltage- and calcium-activated potassium channel Slo-1. Genetic evidence suggests that emodepside exerts its anthelmintic activity predominantly through Slo-1. Indeed, slo-1 deficient Caenorhabditis elegans strains are completely emodepside resistant. However, direct effects of emodepside on Slo-1 have not been reported and these channels have only been characterized for C. elegans and related Strongylida. Molecular and bioinformatic analyses identified full-length Slo-1 cDNAs of Ascaris suum, Parascaris equorum, Toxocara canis, Dirofilaria immitis, Brugia malayi, Onchocerca gutturosa and Strongyloides ratti. Two paralogs were identified in the trichocephalids Trichuris muris, Trichuris suis and Trichinella spiralis. Several splice variants encoding truncated channels were identified in Trichuris spp. Slo-1 channels of trichocephalids form a monophyletic group, showing that duplication occurred after the divergence of Enoplea and Chromadorea. To explore the function of a representative protein, C. elegans Slo-1a was expressed in Xenopus laevis oocytes and studied in electrophysiological (voltage-clamp) experiments. Incubation of oocytes with 1-10 µM emodepside caused significantly increased currents over a wide range of step potentials in the absence of experimentally increased intracellular Ca2+, suggesting that emodepside directly opens C. elegans Slo-1a. Emodepside wash-out did not reverse the effect and the Slo-1 inhibitor verruculogen was only effective when applied before, but not after, emodepside. The identification of several splice variants and paralogs in some parasitic nematodes suggests that there are substantial differences in channel properties among species. Most importantly, this study showed for the first time that emodepside directly opens a Slo-1 channel, significantly improving the understanding of the mode of action of this drug class

DNA Steganalysis Using Deep Recurrent Neural Networks

Recent advances in next-generation sequencing technologies have facilitated the use of deoxyribonucleic acid (DNA) as a novel covert channels in steganography. There are various methods that exist in other domains to detect hidden messages in conventional covert channels. However, they have not been applied to DNA steganography. The current most common detection approaches, namely frequency analysis-based methods, often overlook important signals when directly applied to DNA steganography because those methods depend on the distribution of the number of sequence characters. To address this limitation, we propose a general sequence learning-based DNA steganalysis framework. The proposed approach learns the intrinsic distribution of coding and non-coding sequences and detects hidden messages by exploiting distribution variations after hiding these messages. Using deep recurrent neural networks (RNNs), our framework identifies the distribution variations by using the classification score to predict whether a sequence is to be a coding or non-coding sequence. We compare our proposed method to various existing methods and biological sequence analysis methods implemented on top of our framework. According to our experimental results, our approach delivers a robust detection performance compared to other tools

Mutations in multidomain protein MEGF8 identify a Carpenter syndrome subtype associated with defective lateralization

Carpenter syndrome is an autosomal-recessive multiple-congenital-malformation disorder characterized by multisuture craniosynostosis and polysyndactyly of the hands and feet; many other clinical features occur, and the most frequent include obesity, umbilical hernia, cryptorchidism, and congenital heart disease. Mutations of RAB23, encoding a small GTPase that regulates vesicular transport, are present in the majority of cases. Here, we describe a disorder caused by mutations in multiple epidermal-growth-factor-like-domains 8 (MEGF8), which exhibits substantial clinical overlap with Carpenter syndrome but is frequently associated with abnormal left-right patterning. We describe five affected individuals with similar dysmorphic facies, and three of them had either complete situs inversus, dextrocardia, or transposition of the great arteries; similar cardiac abnormalities were previously identified in a mouse mutant for the orthologous Megf8. The mutant alleles comprise one nonsense, three missense, and two splice-site mutations; we demonstrate in zebrafish that, in contrast to the wild-type protein, the proteins containing all three missense alterations provide only weak rescue of an early gastrulation phenotype induced by Megf8 knockdown. We conclude that mutations in MEGF8 cause a Carpenter syndrome subtype frequently associated with defective left-right patterning, probably through perturbation of signaling by hedgehog and nodal family members. We did not observe any subject with biallelic loss-of function mutations, suggesting that some residual MEGF8 function might be necessary for survival and might influence the phenotypes observed

A Recessive Mutation Resulting in a Disabling Amino Acid Substitution (T194R) in the LHX3 Homeodomain Causes Combined Pituitary Hormone Deficiency

Background/Aims: Recessive mutations in the LHX3 homeodomain transcription factor gene are associated with developmental disorders affecting the pituitary and nervous system. We describe pediatric patients with combined pituitary hormone deficiency (CPHD) who harbor a novel mutation in LHX3. Methods: Two female siblings from related parents were examined. Both patients had neonatal complications. The index patient had CPHD featuring deficiencies of GH, LH, FSH, PRL, and TSH, with later onset of ACTH deficiency. She also had a hypoplastic anterior pituitary, respiratory distress, hearing impairment, and limited neck rotation. The LHX3 gene was sequenced and the biochemical properties of the predicted altered proteins were characterized. Results: A novel homozygous mutation predicted to change amino acid 194 from threonine to arginine (T194R) was detected in both patients. This amino acid is conserved in the DNA-binding homeodomain. Computer modeling predicted that the T194R change would alter the homeodomain structure. The T194R protein did not bind tested LHX3 DNA recognition sites and did not activate the a-glycoprotein and PRL target genes. Conclusion: The T194R mutation affects a critical residue in the LHX3 protein. This study extends our understanding of the phenotypic features, molecular mechanism, and developmental course associated with mutations in the LHX3 gene. copyright (C) 2012 S. Karger AG, Base

Law of Genome Evolution Direction : Coding Information Quantity Grows

The problem of the directionality of genome evolution is studied. Based on the analysis of C-value paradox and the evolution of genome size we propose that the function-coding information quantity of a genome always grows in the course of evolution through sequence duplication, expansion of code, and gene transfer from outside. The function-coding information quantity of a genome consists of two parts, p-coding information quantity which encodes functional protein and n-coding information quantity which encodes other functional elements except amino acid sequence. The evidences on the evolutionary law about the function-coding information quantity are listed. The needs of function is the motive force for the expansion of coding information quantity and the information quantity expansion is the way to make functional innovation and extension for a species. So, the increase of coding information quantity of a genome is a measure of the acquired new function and it determines the directionality of genome evolution.Comment: 16 page