Statistical Models Commons^™

Genomic Neighborhoods For Arabidopsisretrotransposons: A Role For Targeted Integration In The Distribution Of The Metaviridae, Brooke D. Peterson-Burch, Dan Nettleton, Daniel F. Voytas

Dan Nettleton

Background: Retrotransposons are an abundant component of eukaryotic genomes. The high quality of the Arabidopsis thaliana genome sequence makes it possible to comprehensively characterize retroelement populations and explore factors that contribute to their genomic distribution.

Results: We identified the full complement of A. thaliana long terminal repeat (LTR) retroelements using RetroMap, a software tool that iteratively searches genome sequences for reverse transcriptases and then defines retroelement insertions. Relative ages of full-length elements were estimated by assessing sequence divergence between LTRs: the Pseudoviridae were significantly younger than the Metaviridae. All retroelement insertions were mapped onto the genome sequence and their distribution …

Non-Syntenic Genes Drive Rtcs-Dependent Regulation Of The Embryo Transcriptome During Formation Of Seminal Root Primordia In Maize (Zea Mays L.), Huanhuan Tai, Nina Opitz, Andrew Lithio, Xin Lu, Dan Nettleton, Frank Hochholdinger

Dan Nettleton

Seminal roots of maize are pivotal for early seedling establishment. The maize mutant rootless concerning crown and seminal roots (rtcs) is defective in seminal root initiation during embryogenesis. In this study, the transcriptomes of wild-type and rtcs embryos were analyzed by RNA-Seq based on histological results at three stages of seminal root primordia formation. Hierarchical clustering highlighted that samples of each genotype grouped together along development. Determination of their gene activity status revealed hundreds of genes specifically transcribed in wild-type or rtcs embryos, while K-mean clustering revealed changes in gene expression dynamics between wild-type and rtcs during embryo …

Unified Methods For Feature Selection In Large-Scale Genomic Studies With Censored Survival Outcomes, Lauren Spirko-Burns, Karthik Devarajan

COBRA Preprint Series

One of the major goals in large-scale genomic studies is to identify genes with a prognostic impact on time-to-event outcomes which provide insight into the disease's process. With rapid developments in high-throughput genomic technologies in the past two decades, the scientific community is able to monitor the expression levels of tens of thousands of genes and proteins resulting in enormous data sets where the number of genomic features is far greater than the number of subjects. Methods based on univariate Cox regression are often used to select genomic features related to survival outcome; however, the Cox model assumes proportional hazards …