Abstract
The understanding of bacterial gene function has been greatly enhanced by recent advancements in the deep sequencing of microbial genomes. Transposon insertion sequencing methods combines next-generation sequencing techniques with transposon mutagenesis for the exploration of the essentiality of genes under different environmental conditions. We propose a model-based method that uses regularized negative binomial regression to estimate the change in transposon insertions attributable to gene-environment changes in this genetic interaction study without transformations or uniform normalization. An empirical Bayes model for estimating the local false discovery rate combines unique and total count information to test for genes that show a statistically significant change in transposon counts. When applied to RB-TnSeq (randomized barcode transposon sequencing) and Tn-seq (transposon sequencing) libraries made in strains of Caulobacter crescentus using both total and unique count data the model was able to identify a set of conditionally beneficial or conditionally detrimental genes for each target condition that shed light on their functions and roles during various stress conditions.
Highlights
A central question in molecular genetics is, What genes are essential for life? Prior to the advent of high-throughput technology this question was addressed by mutagenesis and fine mapping [1, 2]
We compared the fit of the regularized negative binomial model to a zeroinflated negative binomial model of the type used by [16] and to a unregularized negative binomial model [11]
Our method was applied to Transposon sequencing (Tn-seq) data that was collected in our lab
Summary
A central question in molecular genetics is, What genes are essential for life? Prior to the advent of high-throughput technology this question was addressed by mutagenesis and fine mapping [1, 2]. The simplicity of homologous recombination in S. cerevisiae allowed for the generation of a complete mutant library containing strains each with a complete knockout of a single gene and tagged with a unique genetic barcode[3]. Subsequent analysis of this library by custom microarrays and sequencing revealed genes essential for growth in rich media as well as conditionally essential genes—genes that are dispensable in rich media, but are essential in different environmental conditions [3–5]. Transposon sequencing (Tn-seq) methods have alleviated this problem and provide a powerful method for identifying essential and dispensable genes under a variety of environmental conditions and genetic backgrounds. This type of study, with perturbations to both the genetic content and the environmental context (gene × environment) is typically referred to as a genetic interaction study; here the primary phenotype is growth
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