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  Efficient analysis of allele frequency variation from whole-genome pool-sequencing data

Czech, L., Peng, Y., Spence, J., Lang, P., Bellagio, T., Hildebrandt, J., et al. (2022). Efficient analysis of allele frequency variation from whole-genome pool-sequencing data. Poster presented at Population, Evolutionary, and Quantitative Genetics Conference (PEQG 2022), Pacific Grove, CA, USA.

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 Creators:
Czech, L, Author
Peng, Y, Author
Spence, J, Author
Lang, P, Author                 
Bellagio, T, Author
Hildebrandt, J1, Author           
Fritschi, K1, Author                 
Schwab, R1, 2, Author                 
Rowan, B1, Author                 
Weigel, D1, Author                 
Scheepens, JF, Author
Vasseur, F, Author           
Exposito Alonso, M1, Author                 
Affiliations:
1Department Molecular Biology, Max Planck Institute for Biology Tübingen, Max Planck Society, ou_3371687              
2Research Group Ecological Genetics, Department Molecular Biology, Max Planck Institute for Biology Tübingen, Max Planck Society, ou_3502746              

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 Abstract: In recent decades, so-called Evolve-and-Resequence (E&R) experiments have become a popular approach to survey rapid

evolution of populations over multiple generations. These experiments allow us to measure shifts in the allele frequencies of a population in response to new or shifting environmental conditions, such as a changing climate. Pool-sequencing of several individuals at once is a cost-effective and efficient tool to obtain reliable allele frequencies from a population of thousands to hundreds of thousands of individuals, and is often used in E&R experiments. However,

specialized tools to efficiently analyze these data that take sampling biases stemming from the pool-sequencing approach into account were lacking. We developed two software tools to overcome statistical and bioinformatic challenges arising in this context. First, we present grenepipe, a workflow from raw sequencing data of individuals or pooled populations to genotypes (variant calling) and population allele frequencies. The pipeline automates trimming, mapping, variant calling, and quality control, with a selection of popular software tools in each of these steps, and produces variant calls and frequency tables. While generally applicable to individual sample data, it offers specialized steps for pool-sequencing. With a single command line call, our software downloads all dependencies and runs all steps automatically, parallelizes processing for

computer cluster environments, and recovers from any failing steps. Second, to enable inferences of evolutionary signatures from frequency data, we created grenedalf, a C++ command line tool to compute population genetic statistics. It computes unbiased statistics of Fst, Pi, Tajima’s D with pool-sequencing data, far outperforming alternative tools. Further it offers novel data exploration tools such as windowed allele frequency spectrum visualizations and PCA and MDS on the allele frequencies, and built-in data filters and manipulations. These tools are designed for scalability and ease-of-use with contemporary file formats, which we showcase using the GrENE-net.org project, a large-scale Evolve-and-Resequence experiment with Arabidopsis thaliana from across the world.

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 Dates: 2022-06
 Publication Status: Published online
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Title: Population, Evolutionary, and Quantitative Genetics Conference (PEQG 2022)
Place of Event: Pacific Grove, CA, USA
Start-/End Date: 2022-06-07 - 2022-06-10

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Title: Population, Evolutionary, and Quantitative Genetics Conference (PEQG 2022)
Source Genre: Proceedings
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Pages: - Volume / Issue: - Sequence Number: 276W Start / End Page: 99 Identifier: -