Nucleotide resolution genetic mapping in pigs by publicly accessible whole genome imputation

Ding, Rongrong; Savegnago, Rodrigo Pelicioni; Liu, Jinding; Long, Norton E.; Tan, Cheng; Cai, Guangyan; Zhuang, Zhanwei; Wu, Jie; Yang, Ming; Qiu, Yibin; Ruan, Donglin; Quan, Jianping; Zheng, Enqin; Hong, Linjun; Li, Zicong; Tan, Suxu; Bedhane, Mohammed; Schnabel, Robert D.; Steibel, Juan P.; Gondro, Cedric; Yang, Jie; Huang, Wen; Wu, Zhenfang

doi:10.1101/2022.05.18.492518

Cited by 4 publications

(2 citation statements)

References 47 publications

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“…A total of 31,174 SNPs and 271 animals were retained for further GWAS. To improve the marker density, imputation was performed using two online software programs: the Pig Haplotype Reference Panel (PHARP v2) ( , accessed on 21 October 2022) [ 27 ] and Swine Imputation Server (SWIM 1.0) ( , 21 October 2022) [ 28 ]. After imputation with PHARP v2, quality control (R 2 > 0.8 and MAF > 0.05) was performed, and 9,093,720 SNPs were obtained.…”

Section: Methodsmentioning

confidence: 99%

Genome-Wide Association Study on Reproductive Traits Using Imputation-Based Whole-Genome Sequence Data in Yorkshire Pigs

Sun

Xiao

Jiang

et al. 2023

Genes

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Reproductive traits have a key impact on production efficiency in the pig industry. It is necessary to identify the genetic structure of potential genes that influence reproductive traits. In this study, a genome-wide association study (GWAS) based on chip and imputed data of five reproductive traits, namely, total number born (TNB), number born alive (NBA), litter birth weight (LBW), gestation length (GL), and number of weaned (NW), was performed in Yorkshire pigs. In total, 272 of 2844 pigs with reproductive records were genotyped using KPS Porcine Breeding SNP Chips, and then chip data were imputed to sequencing data using two online software programs: the Pig Haplotype Reference Panel (PHARP v2) and Swine Imputation Server (SWIM 1.0). After quality control, we performed GWAS based on chip data and the two different imputation databases by using fixed and random model circulating probability unification (FarmCPU) models. We discovered 71 genome-wide significant SNPs and 25 potential candidate genes (e.g., SMAD4, RPS6KA2, CAMK2A, NDST1, and ADCY5). Functional enrichment analysis revealed that these genes are mainly enriched in the calcium signaling pathway, ovarian steroidogenesis, and GnRH signaling pathways. In conclusion, our results help to clarify the genetic basis of porcine reproductive traits and provide molecular markers for genomic selection in pig breeding.

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Section: Methodsmentioning

confidence: 99%

Genome-Wide Association Study on Reproductive Traits Using Imputation-Based Whole-Genome Sequence Data in Yorkshire Pigs

Sun

Xiao

Jiang

et al. 2023

Genes

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“…After genotyping, we increased the genotype data to whole genome sequence level by imputation strategy. The Swine Imputation (SWIM) Server tool [ 14 ] was used to conduct genotyping imputation between target and reference genotype data using default parameter values. Reference haplotype panels were generated from whole genome sequencing data of 2259 pigs, which represented 44 breeds, and the genotype imputation accuracy was of an average concordance rate in excess of 97%, non-reference concordance rate 91%, and r 2 0.89.…”

Section: Methodsmentioning

confidence: 99%

Genome-Wide Association Studies Revealed Significant QTLs and Candidate Genes Associated with Backfat and Loin Muscle Area in Pigs Using Imputation-Based Whole Genome Sequencing Data

Jian³

et al. 2022

Animals

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Improvement of carcass features is an essential goal in pig genetic breeding programs. Backfat (BF) and loin muscle area (LMA) are important carcass production metrics and useful indicators of pig production performance and lean meat rate. However, the genetic architecture of BF and LMA traits remains elusive. To identify quantitative trait loci (QTLs) and genes associated with these traits, we performed a genome-wide association study (GWAS) using imputation-based whole genome sequencing data for four phenotypes (adjusted 100 kg BF and LMA, adjusted 100 kg BF EBV and LMA EBV) in 1131 pigs from 3 breeds (French Yorkshire, Landrace, and Duroc). After genotype imputation and quality control, 14,163,315 single nucleotide polymorphisms (SNPs) were retained for further analysis. For the adjusted 100 kg BF trait, using the 2-LOD drop method, a QTL with a 13.4 Kb interval (2.91 to 2.93 Mb on SSC2) and containing a SHANK2 gene was defined. In addition, two QTLs with 135.40 Kb (from 66.10 to 66.23 Mb) and 3.12 Kb (from 66.886 to 66.889 Mb) intervals containing CCND2 and TSPAN11 genes, respectively, were found on SSC5. For the BF-EBV trait, two QTLs (128.77 Kb from 66.10 to 66.23 Mb on SSC5 and 42.10 Kb from 2.89 to 2.93 Mb on SSC2) were identified. Notably, CCND2 and SHANK2 were the only candidate genes in their respective QTL interval. Furthermore, we detected a 3.33 Kb (66.106 to 66.110 Mb on SSC2) haplotype block which was detected as affecting the BF_EBV trait, which only contained the CCND2 gene. Thus, we suggested CCND2 and SHANK2 as strong candidate genes for regulating the BF trait for pigs. The empirical confidence intervals of the QTLs were 1.14 Mb (165.65 to 166.79 Mb on SSC6) for adjusted 100 kg LMA and 1.49 Mb (165.26–166.74 Mb on SSC6) for LMA-EBV. These two confidence intervals contained 13 and 28 annotated genes, respectively. Our results provide a deeper understanding of the genetic basis of pig carcass traits. The identified molecular markers will be useful for selecting breeding lines for breeding pigs with superior carcass traits.

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Comparison of two multi-trait association testing methods and sequence-based fine mapping of six additive QTL in Swiss Large White pigs

et al. 2023

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Background Genetic correlations between complex traits suggest that pleiotropic variants contribute to trait variation. Genome-wide association studies (GWAS) aim to uncover the genetic underpinnings of traits. Multivariate association testing and the meta-analysis of summary statistics from single-trait GWAS enable detecting variants associated with multiple phenotypes. In this study, we used array-derived genotypes and phenotypes for 24 reproduction, production, and conformation traits to explore differences between the two methods and used imputed sequence variant genotypes to fine-map six quantitative trait loci (QTL). Results We considered genotypes at 44,733 SNPs for 5,753 pigs from the Swiss Large White breed that had deregressed breeding values for 24 traits. Single-trait association analyses revealed eleven QTL that affected 15 traits. Multi-trait association testing and the meta-analysis of the single-trait GWAS revealed between 3 and 6 QTL, respectively, in three groups of traits. The multi-trait methods revealed three loci that were not detected in the single-trait GWAS. Four QTL that were identified in the single-trait GWAS, remained undetected in the multi-trait analyses. To pinpoint candidate causal variants for the QTL, we imputed the array-derived genotypes to the sequence level using a sequenced reference panel consisting of 421 pigs. This approach provided genotypes at 16 million imputed sequence variants with a mean accuracy of imputation of 0.94. The fine-mapping of six QTL with imputed sequence variant genotypes revealed four previously proposed causal mutations among the top variants. Conclusions Our findings in a medium-size cohort of pigs suggest that multivariate association testing and the meta-analysis of summary statistics from single-trait GWAS provide very similar results. Although multi-trait association methods provide a useful overview of pleiotropic loci segregating in mapping populations, the investigation of single-trait association studies is still advised, as multi-trait methods may miss QTL that are uncovered in single-trait GWAS.

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Nucleotide resolution genetic mapping in pigs by publicly accessible whole genome imputation

Cited by 4 publications

References 47 publications

Genome-Wide Association Study on Reproductive Traits Using Imputation-Based Whole-Genome Sequence Data in Yorkshire Pigs

Genome-Wide Association Study on Reproductive Traits Using Imputation-Based Whole-Genome Sequence Data in Yorkshire Pigs

Genome-Wide Association Studies Revealed Significant QTLs and Candidate Genes Associated with Backfat and Loin Muscle Area in Pigs Using Imputation-Based Whole Genome Sequencing Data

Comparison of two multi-trait association testing methods and sequence-based fine mapping of six additive QTL in Swiss Large White pigs

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