System for automated detection of homologs among the annotated genes of several completely sequenced eukaryotic genomes.

data was from HepG2 cells treated with nano-silver particles using silver nitrate as negative controls. Differentially expressed messenger RNA and microRNA were obtained by RNA sequencing and data analysis. Differentially expressed RNA and microRNA lists were than uploaded to Ingenuity Pathway Analysis to find the pathways altered by the differentially expressed genes. This dataset is associated with the following publication: Thai, S., C. Jones, B. Robinette, H. Ren, B. Vallanat, A. Fisher, and K. Kitchin. Effects of Silver Nanoparticles and Silver Nitrate on mRNA and microRNA Expression in Human Hepatocellular Carcinoma Cells (HepG2). Journal of Nanoscience and Nanotechnology. American Scientific Publishers, VALENCIA, CA, USA, 21(11): 5414-5428, (2021).

data was from HepG2 cells treated with nano-silver particles using silver nitrate as negative controls. Differentially expressed messenger RNA and microRNA were obtained by RNA sequencing and data analysis. Differentially expressed RNA and microRNA lists were than uploaded to Ingenuity Pathway Analysis to find the pathways altered by the differentially expressed genes. This dataset is associated with the following publication: Thai, S., C. Jones, B. Robinette, H. Ren, B. Vallanat, A. Fisher, and K. Kitchin. Effects of Silver Nanoparticles and Silver Nitrate on mRNA and microRNA Expression in Human Hepatocellular Carcinoma Cells (HepG2). Journal of Nanoscience and Nanotechnology. American Scientific Publishers, VALENCIA, CA, USA, 21(11): 5414-5428, (2021).

Background PCR amplification of target molecules involves sequence specific primers that flank the region to be amplified. While this technique is generally routine, its applicability may not be sufficient to generate a desired target molecule from two separate regions involving intron /exon boundaries. For these situations, the generation of full-length complementary DNAs from two partial genomic clones becomes necessary for the family of low abundance genes. Results The first approach we used for the isolation of full-length cDNA from two known genomic clones of Hox genes was based on fusion PCR. Here we describe a simple and efficient method of amplification for homeobox D13 (HOXD13) full length cDNA from two partial genomic clones. Specific 5' and 3' untranslated region (UTR) primer pairs and website program (primer3_www.cgv0.2) were key steps involved in this process. Conclusions We have devised a simple, rapid and easy method for generating cDNA clone from genomic sequences. The full length HOXD13 clone (1.1 kb) generated with this technique was confirmed by sequence analysis. This simple approach can be utilized to generate full-length cDNA clones from available partial genomic sequences.

Supplementary data for "Comparison of whole transcriptome and targeted RNA sequencing for ecological high-throughput transcriptomics". This dataset is associated with the following publication: Villeneuve, D., M. Nash, A. Biales, K. Bush, G. Evensen, L. Everett, J. Haselman, M. Hazemi, M. Le, H. Poynton, B. Seligmann , L. Wehmas, J. Yeakley, and K. Flynn. Comparison of whole transcriptome and targeted RNA sequencing for ecological high-throughput transcriptomics. REGULATORY TOXICOLOGY AND PHARMACOLOGY. Elsevier Science Ltd, New York, NY, USA, 162: 105898, (2025).

Background Better automation, lower cost per reaction and a heightened interest in comparative genomics has led to a dramatic increase in DNA sequencing activities. Although the large sequencing projects of specialized centers are supported by in-house bioinformatics groups, many smaller laboratories face difficulties managing the appropriate processing and storage of their sequencing output. The challenges include documentation of clones, templates and sequencing reactions, and the storage, annotation and analysis of the large number of generated sequences. Results We describe here a new program, named FOUNTAIN, for the management of large sequencing projects . FOUNTAIN uses the JAVA computer language and data storage in a relational database. Starting with a collection of sequencing objects (clones), the program generates and stores information related to the different stages of the sequencing project using a web browser interface for user input. The generated sequences are subsequently imported and annotated based on BLAST searches against the public databases. In addition, simple algorithms to cluster sequences and determine putative polymorphic positions are implemented. Conclusions A simple, but flexible and scalable software package is presented to facilitate data generation and storage for large sequencing projects. Open source and largely platform and database independent, we wish FOUNTAIN to be improved and extended in a community effort.

The data contained in this worksheets provide sequences submitted for public access, analysis for RNA sequences generated in this study. The data and analysis are for a manuscript "The trait repertoire enabling cyanobacterial blooms assessed through comparative genomic complexity ". This dataset is associated with the following publication: Cao, H., Y. Shimura, M.M. Steffen, Z. Yang, J. Lu, A. Joel, L. Jenkins, M. Kawachi, Y. Yin, and F. Garcia-Pichel. The Trait Repertoire Enabling Cyanobacteria to Bloom Assessed through Comparative Genomic Complexity and Metatranscriptomics. mBio. American Society for Microbiology, Washington, DC, USA, 11(3): e01155-20, (2020).

Background Very small genomes have evolved repeatedly in eubacterial lineages that have adopted obligate associations with eukaryotic hosts. Complete genome sequences have revealed that small genomes retain very different gene sets, raising the question of how final genome content is determined. To examine the process of genome reduction, the tiny genome of the endosymbiont Buchnera aphidicola was compared to the larger ancestral genome, reconstructed on the basis of the phylogenetic distribution of gene orthologs among fully sequenced relatives of Escherichia coli and Buchnera. Results The reconstructed ancestral genome contained 2,425 open reading frames (ORFs). The Buchnera genome, containing 564 ORFs, consists of 153 fragments of 1-34 genes that are syntenic with reconstructed ancestral regions. On the basis of this reconstruction, 503 genes were eliminated within syntenic fragments, and 1,403 genes were lost from the gaps between syntenic fragments, probably in connection with genome rearrangements. Lost regions are sometimes large, and often span functionally unrelated genes. In addition, individual genes and regulatory regions have been lost or eroded. For the categories of DNA repair genes and rRNA genes, most lost loci fall in regions between syntenic fragments. This history of gene loss is reflected in the sequences of intergenic spacers at positions where genes were once present. Conclusions The most plausible interpretation of this reconstruction is that Buchnera lost many genes through the fixation of large deletions soon after the acquisition of an obligate endosymbiotic lifestyle. An implication is that final genome composition may be partly the chance outcome of initial deletions and that neighboring genes influence the likelihood of loss of particular genes and pathways.

A repository of DNA sequence chromatograms (traces), base calls, and quality estimates for single-pass reads from various large-scale sequencing projects.

Genetics studies are used by wildlife managers and researchers to gain inference into a population of a species of interest. To gain these insights, micro-satellites have been the primary method, however, there currently is a shift from micro-satellites to single nucleotide polymorphisms (SNPs). With the DNA requirements being different, an investigation into which samples can provide adequate DNA yield is warranted. Using samples that were collected from previous genetic projects from regions in the USA from 2014 to 2021, we investigated the DNA yield of eight sample categories to gain insights into which provided adequate DNA to be used in various panels. We found four sample categories that met the DNA requirements for use in all three panels, three sample categories that only met the DNA requirements for two panels, and one sample category that did not meet any of the three panels requirements. Additionally, we used linear random-effects models to determine which covariates would have the greatest influence on DNA yield. We determined that all covariates, tissue type, storage method, preservative, DNA quality, time until DNA extraction and time after DNA extraction could influence DNA yield.