Publications by authors named "Marc Rubenfield"
Article Synopsis
- Genetic markers are essential in genomics, but challenges in oat genome complexity and lack of sequence data make finding and testing them difficult; this study aimed to address these issues by generating oat expressed sequence tag (EST) data and developing a method for SNP identification.
- Researchers created a bioinformatics pipeline that processed around 1 million sequence reads, resulting in the identification of 96 in silico SNPs, with 52 found to be polymorphic in a specific oat mapping population, validating their utility through high-resolution melting (HRM) analysis.
- The study concludes that the newly developed high-throughput SNP discovery pipeline and HRM genotyping method are effective for identifying and analyzing genetic diversity in oats, offering a straightforward approach to understanding their complex poly
Background: The domestic cat has offered enormous genomic potential in the veterinary description of over 250 hereditary disease models as well as the occurrence of several deadly feline viruses (feline leukemia virus--FeLV, feline coronavirus--FECV, feline immunodeficiency virus--FIV) that are homologues to human scourges (cancer, SARS, and AIDS respectively). However, to realize this bio-medical potential, a high density single nucleotide polymorphism (SNP) map is required in order to accomplish disease and phenotype association discovery.
Description: To remedy this, we generated 3,178,297 paired fosmid-end Sanger sequence reads from seven cats, and combined these data with the publicly available 2X cat whole genome sequence.
Background: Arcobacter butzleri is a member of the epsilon subdivision of the Proteobacteria and a close taxonomic relative of established pathogens, such as Campylobacter jejuni and Helicobacter pylori. Here we present the complete genome sequence of the human clinical isolate, A. butzleri strain RM4018.
View Article and Find Full Text PDFComparative analysis of multiple genomes in a phylogenetic framework dramatically improves the precision and sensitivity of evolutionary inference, producing more robust results than single-genome analyses can provide. The genomes of 12 Drosophila species, ten of which are presented here for the first time (sechellia, simulans, yakuba, erecta, ananassae, persimilis, willistoni, mojavensis, virilis and grimshawi), illustrate how rates and patterns of sequence divergence across taxa can illuminate evolutionary processes on a genomic scale. These genome sequences augment the formidable genetic tools that have made Drosophila melanogaster a pre-eminent model for animal genetics, and will further catalyse fundamental research on mechanisms of development, cell biology, genetics, disease, neurobiology, behaviour, physiology and evolution.
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