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Escherichia coli Long-term Evolution Experiment 500 and 1000 Generation Population Sequencing

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NIAID Data Ecosystem2026-03-10 收录
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https://www.ncbi.nlm.nih.gov/sra/SRP047501
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New mutations leading to structural variation (SV) in genomes — in the form of mobile element insertions, large deletions, gene duplications, and other chromosomal rearrangements — can play a key role in microbial evolution. Yet, SV is considerably more difficult to predict from short-read genome resequencing data than single-nucleotide variation and small indels, so it is not yet routinely identified in DNA sequencing data that profiles population-level genetic diversity over time in evolution experiments. We implemented an algorithm for detecting polymorphic SV as part of the breseq computational pipeline for analyzing resequencing data from haploid microbial genomes. This procedure examines split-read alignments, in which the two ends of a single sequencing read match disjoint locations in the reference genome, in order to detect structural variants and estimate their frequencies within a sample. We tested our algorithm on 500- and 1000-generation population samples from the Lenski E. coli long-term evolution experiment (LTEE). Knowledge of genes that are targets of selection in the LTEE and mutations present in previously sequenced clonal isolates allowed us to evaluate the accuracy of our procedure and to analyze the contribution of SV to total genetic diversity in these 12 independently evolving population.
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2017-09-17
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