Academic journal article Genetics

Discovery of Lineage-Specific Genome Change in Rice through Analysis of Resequencing Data

Academic journal article Genetics

Discovery of Lineage-Specific Genome Change in Rice through Analysis of Resequencing Data

Article excerpt

ONE of the primary questions in biology is the origin of genetic change. Evolutionary biologists routinely use comparative genomic analyses to identify the changes that differentiate individuals within a species or between species. However, these methods uncover variations that are the outcomes of multiple phenomena, including rates and natures of de novo mutation, natural selection acting on these changes, and transmission issues associated with mating strategies, population sizes, and geographical distributions. Mutation may arise due to spontaneous or environmentally driven base modification, errors during DNA replication, inaccurate DNA repair, transposon insertion/deletion, or chromosome breakage (Burrus and Waldor 2004; Aminetzach et al. 2005). Multiple DNA repair mechanisms work in concert to minimize change, such that the tens of thousands of DNA changes generated every cell generation still yield mutation rates of only 1 x 10_9 to 1 x 10_12 per base per organismal generation (Vazquez et al. 2000; Ossowski et al. 2010; Roach et al. 2010; Lee et al. 2012). For instance, in the model plant Arabidopsis, withjust over 108 bp in its nuclear genome, around one de novo mutation is expected to be transmitted in a single plant generation (Ossowski et al. 2010).

The rate at which mutations occur can vary within or between species, and taxa also differ in the relative frequencies of types of mutation, although point mutations (both substitutions and tiny indels) are routinely far more common than larger indels (Drake et al. 1998; Vazquez et al. 2000; Ossowski et al. 2010; Roach et al. 2010; Walser and Furano 2010; Lee etal. 2012). Within genomes, genic regions exhibit a lower number of accumulated mutations, at least partly due to the fact that coding sequences are usually subject to purifying selection (Drake et al. 1998). Regions in genomes that are methylated, such as CG dinucleotides in many animals and all plants, also display a higher point mutation rate because 5-methyl cytosine deaminates at a higher rate than unmethylated cytosine, leading to frequent cytosine-tothymidine transitions (Ma and Bennetzen 2004; Walser and Furano 2010; Wang et al. 2012). Taxa with active transposable elements (TEs) can accumulate dozens of de novo insertion mutations per generation, while sister lineages with quiescent TEs can go thousands, perhaps millions, of years without any new TE insertions (International Rice Genome Sequencing Project 2005; Huang et al. 2012; Kawahara et al. 2013).

While most mutation analysis studies have focused on changes that have accumulated over evolutionary time, few studies have investigated de novo change because of the cost and temporal demands of such investigations. Estimation of the spontaneous mutation rate in Escherichia coli was ~ 2.1 X 10-10 de novo changes per genome per generation, with point mutations outnumbering indels by > 9:1 (Lee et al. 2012). In Schizosaccharomyces pombe, the rate of point mutations was 2.4 X 10-10 bases/generation (Behringer and Hall 2016). In humans, sperm DNA sequencing was utilized to investigate de novo DNA change and predicted a mutation rate of ~ 2.4 X 10-8 mutations/base/generation (Wang etal. 2012). In the plant kingdom, Ossowski and colleagues conducted a mutation-accumulation study in Arabidopsis thaliana that discovered 99 new base substitutions and 17 indels that had accumulated in 5 lineages within 30 generations, yielding an overall mutation rate of ~ 7 X 10-9 for point mutations/base/generation and 0.3 X 10-9 - 0.6 X 10-9 for insertions and deletions/base/generation, respectively (Ossowski et al. 2010).

Rather than spend several plant generations creating mutation-accumulation lines (Drake et al. 1998; Vazquez et al. 2000; Ossowski etal. 2010; Roach etal. 2010; Lee etal. 2012) and then demanding deep full-genome sequencing to identify/confirm any de novo mutations, we have chosen to utilize currently available genome data to enrich for de novo mutations without any investment of plant growth time or sequencing expense. …

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