Location: Crop Improvement and Genetics ResearchTitle: Multiple variant calling pipelines in wheat whole exome sequencing
|CAGIRICI, BUSRA - Orise Fellow
|AKPINAR, BALA ANI - University Of Helsinki
|BUDAK, HIKMET - Montana Bioagriculture Inc
Submitted to: International Journal of Molecular Sciences
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/23/2021
Publication Date: 9/27/2021
Citation: Cagirici, B.H., Akpinar, B., Sen, T.Z., Budak, H. 2021. Multiple variant calling pipelines in wheat whole exome sequencing. International Journal of Molecular Sciences. 22(19). Article 10400. https://doi.org/10.3390/ijms221910400.
Interpretive Summary: Wheat is among the top three staple crops in the world that provides 20% of protein and calorie needs globally. The genome for common bread is recently sequenced and assembled, allowing facilitated discovery of genomic differences called variants and their relation to important agricultural traits. However, different computational methods exist to identify these variants with varying reliability and reproducibility. In this study, we compare performances of various aligner and variant calling methods by focusing on exonic regions of 48 elite wheat cultivar genomes. Our study provides guidelines to choose best computational tools for variant identification in common bread wheat that would enable more precise linking between genomic differences to agronomic traits.
Technical Abstract: With the recent releases and availability of the wheat reference genomes, the highly-challenging wheat genome has become more accessible to mine for the variants responsible for important traits of interest. However, as with every analysis, there is a need to ensure that results are both reliable and reproducible. Although calling for variants in plants became relatively straightforward with the broad availability of computational tools for read alignment and variant calling stages, the optimal choice of tools for each stage of the analysis pipeline is not always a trivial task, especially in wheat. Previous studies analyzed the impact of methods of choice on the metrics for result quality in organisms including humans, where exome sequencing plays a large role in the clinical settings, and Arabidopsis, but not in wheat. Given that variation identification in wheat largely relies on the accurate mining of exome data, there is a critical need to better characterize and understand how different methods affect the analysis of whole exome capture and sequencing in common bread wheat (Triticum aestivum). This study aims to address this gap by performing the whole exome capture sequencing (WES) of 48 elite wheat cultivars and assessing the performance of various computational methods at all stages in a WES variant calling pipeline using the IWGSC Chinese Spring wheat reference genome v1.0.