PyBact

PyBact is a software written in Python for bacterial identification. The code simulates the predefined behavior of bacterial species by generating a simulated data set based on the frequency table of biochemical tests from diagnostic microbiology textbook. The generated data was used for predictive model construction by machine learning approaches and results indicated that the classifiers could accurately predict its respective bacterial class with accuracy in excess of 99 %

Transcriptional Profiling of MEq-Dependent Genes in Marek's Disease Resistant and Susceptible Inbred Chicken Lines

Abstract Marek's disease (MD) is an economically significant disease in chickens caused by the highly oncogenic Marek's disease virus (MDV). Understanding the genes and biological pathways that confer MD genetic resistance should lead towards the development of more disease resistant commercial poultry flocks or improved MD vaccines. MDV mEq, a bZIP transcription factor, is largely attributed to viral oncogenicity though only a few host target genes have been described, which has impeded our understanding of MDV-induced tumorigenesis. Given the importance of mEq in MDV-induced pathogenesis, we explored the role of mEq in genetic resistance to MDV. Using global transcriptome analysis and cells from MD resistant or susceptible birds, we compared the response to infection with either wild type MDV or a nononcogenic recombinant lacking mEq. As a result, we identified a number of specific genes and pathways associated with either MD resistance or susceptibility. Additionally, integrating prior information from ChIPseq, microarray analysis, and SNPs exhibiting allele-specific expression (ASE) in response to MDV infection, we were able to provide evidence for 24 genes that are polymorphic within mEq binding sites are likely to account for gene expression in an allele-specific manner and potentially for the underlying genetic differences in MD incidence

Transcriptome analysis of northern elephant seal (Mirounga angustirostris) muscle tissue provides a novel molecular resource and physiological insights

BackgroundThe northern elephant seal, Mirounga angustirostris, is a valuable animal model of fasting adaptation and hypoxic stress tolerance. However, no reference sequence is currently available for this and many other marine mammal study systems, hindering molecular understanding of marine adaptations and unique physiology.ResultsWe sequenced a transcriptome of M. angustirostris derived from muscle sampled during an acute stress challenge experiment to identify species-specific markers of stress axis activation and recovery. De novo assembly generated 164,966 contigs and a total of 522,699 transcripts, of which 68.70% were annotated using mouse, human, and domestic dog reference protein sequences. To reduce transcript redundancy, we removed highly similar isoforms in large gene families and produced a filtered assembly containing 336,657 transcripts. We found that a large number of annotated genes are associated with metabolic signaling, immune and stress responses, and muscle function. Preliminary differential expression analysis suggests a limited transcriptional response to acute stress involving alterations in metabolic and immune pathways and muscle tissue maintenance, potentially driven by early response transcription factors such as Cebpd.ConclusionsWe present the first reference sequence for Mirounga angustirostris produced by RNA sequencing of muscle tissue and cloud-based de novo transcriptome assembly. We annotated 395,102 transcripts, some of which may be novel isoforms, and have identified thousands of genes involved in key physiological processes. This resource provides elephant seal-specific gene sequences, complementing existing metabolite and protein expression studies and enabling future work on molecular pathways regulating adaptations such as fasting, hypoxia, and environmental stress responses in marine mammals

[Avian cytogenetics goes functional] Third report on chicken genes and chromosomes 2015

High-density gridded libraries of large-insert clones using bacterial artificial chromosome (BAC) and other vectors are essential tools for genetic and genomic research in chicken and other avian species... Taken together, these studies demonstrate that applications of large-insert clones and BAC libraries derived from birds are, and will continue to be, effective tools to aid high-throughput and state-of-the-art genomic efforts and the important biological insight that arises from them

Transcriptional profiling of mEq-dependent genes in Marek's disease resistant and susceptible inbred chicken lines.

Marek's disease (MD) is an economically significant disease in chickens caused by the highly oncogenic Marek's disease virus (MDV). Understanding the genes and biological pathways that confer MD genetic resistance should lead towards the development of more disease resistant commercial poultry flocks or improved MD vaccines. MDV mEq, a bZIP transcription factor, is largely attributed to viral oncogenicity though only a few host target genes have been described, which has impeded our understanding of MDV-induced tumorigenesis. Given the importance of mEq in MDV-induced pathogenesis, we explored the role of mEq in genetic resistance to MDV. Using global transcriptome analysis and cells from MD resistant or susceptible birds, we compared the response to infection with either wild type MDV or a nononcogenic recombinant lacking mEq. As a result, we identified a number of specific genes and pathways associated with either MD resistance or susceptibility. Additionally, integrating prior information from ChIP-seq, microarray analysis, and SNPs exhibiting allele-specific expression (ASE) in response to MDV infection, we were able to provide evidence for 24 genes that are polymorphic within mEq binding sites are likely to account for gene expression in an allele-specific manner and potentially for the underlying genetic differences in MD incidence

qPCR validation of microarray results.

<p>Validation by RT-qPCR of the microarray-based differentially expressed genes between line 6 and line 7 CEFs. Beta-actin was used as internal control. *<i>P</i><0.05 compared to uninfected CEF as controls.</p

Meq-dependent genes identified through integrated analysis.

<p>Representation of overlap between Meq-dependent genes involved in MD resistance and genes with Meq ChIP-Seq peaks and transcriptionally regulated by Meq.</p

Schematic for analysis of experimental groups.

<p>The differentially expressed genes (DEGs) between Md5-infected and Md5<b>∆</b>Meq-infected groups compared to untreated control CEFs were obtained. Then DEGs present in Md5-infected group and not in Md5<b>∆</b>Meq-infected group were designated as Meq-dependent DEGs. These were further divided into DEGs specific to lines 6 or 7, and this set was used for GO categorization and IPA Pathway analyses.</p

Significant molecular functions associated with genes dependent on Meq expression.

<p>The significant molecular functions are given identified through IPA based on the significantly expressed genes that were Meq-dependent and involved in MD resistance (A) and MD susceptibility (B). <i>P</i><0.05 and FDR<0.05 were used as thresholds.</p

Identification of Meq-dependent genes in MD resistant or susceptible chicken lines.

<p>Venn diagram of comparison between two virus-infected groups in line 6 and line 7. Each circle depicts the number of differentially expressed genes compared to uninfected controls. The portion highlighted in pink in each diagram denotes the Meq-dependent genes.</p