Optimization of Whole-Genome Resequencing Depth for High-Throughput SNP Genotyping in Litopenaeus vannamei

The application of whole-genome resequencing in genetic research is rapidly expanding, yet the impact of sequencing depth on data quality and variant detection remains unclear, particularly in aquaculture species. This study re-sequenced 31 <i>Litopenaeus vannamei</i> (<i>L. vannamei</i>) samples at over 28× sequencing depth using the Illumina NovaSeq system and down-sampled the data to simulate depths from 0.5× to 20×. Results showed that when the sequencing depth was below 10×, the number of SNP identifications increased sharply with the rise in depth, with single nucleotide polymorphisms (SNPs) detected at 10× accounting for approximately 69.16% of those detected at 20×. The genotyping accuracy followed a similar trend to SNP detection results, being approximately 0.90 at 6×. Further analyses showed that the main cause of genotyping errors was the misidentification of heterozygous variants as homozygous variants. Therefore, considering both the quantity and quality of SNPs, a sequencing depth of 10× is recommended for whole-genome studies and genetic mapping, while a depth of 6× is more cost-effective for population structure analysis. This study underscores the importance of selecting optimal sequencing depth to ensure reliable variant detection and high data quality, providing valuable guidance for whole-genome resequencing in shrimp and other aquatic species.

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Publication Details

Journal
International Journal of Molecular Sciences
Published
2024-11-11
DOI
https://doi.org/10.3390/ijms252212083
Citations
4
Primary Topic
Aquaculture Nutrition and Growth
Type
article
Field-Weighted Citation Impact
2.39

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article

Optimization of Whole-Genome Resequencing Depth for High-Throughput SNP Genotyping in Litopenaeus vannamei

Zhenning Bao, Yang Yu, Fuhua Li, Pengfei Lin
4 citations
International Journal of Molecular Sciences
Aquaculture Nutrition and Growth
2.39
article

Optimization of Whole-Genome Resequencing Depth for High-Throughput SNP Genotyping in Litopenaeus vannamei

Zhenning Bao, Yang Yu, Fuhua Li, Pengfei Lin
article en
4 citations

Abstract

The application of whole-genome resequencing in genetic research is rapidly expanding, yet the impact of sequencing depth on data quality and variant detection remains unclear, particularly in aquaculture species. This study re-sequenced 31 <i>Litopenaeus vannamei</i> (<i>L. vannamei</i>) samples at over 28× sequencing depth using the Illumina NovaSeq system and down-sampled the data to simulate depths from 0.5× to 20×. Results showed that when the sequencing depth was below 10×, the number of SNP identifications increased sharply with the rise in depth, with single nucleotide polymorphisms (SNPs) detected at 10× accounting for approximately 69.16% of those detected at 20×. The genotyping accuracy followed a similar trend to SNP detection results, being approximately 0.90 at 6×. Further analyses showed that the main cause of genotyping errors was the misidentification of heterozygous variants as homozygous variants. Therefore, considering both the quantity and quality of SNPs, a sequencing depth of 10× is recommended for whole-genome studies and genetic mapping, while a depth of 6× is more cost-effective for population structure analysis. This study underscores the importance of selecting optimal sequencing depth to ensure reliable variant detection and high data quality, providing valuable guidance for whole-genome resequencing in shrimp and other aquatic species.

International Journal of Molecular SciencesVol. 25(22)
Chinese Academy of Sciences (CN), Institute of Oceanology (CN), Qingdao National Laboratory for Marine Science and Technology (CN), University of Chinese Academy of Sciences (CN)
Chinese Academy of Sciences, National Key Research and Development Program of China
Life below water
Openalex Percentile: Top 12%
Aquaculture Nutrition and Growth
2.39
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Optimization of Whole-Genome Resequencing Depth for High-Throughput SNP Genotyping in Litopenaeus vannamei — Zhenning Bao, Yang Yu, et al. · International Journal of Molecular Sciences (2024) | TGRS Research Map | TGRS