A combination of genome-wide association study and selection signature analysis dissects the genetic architecture underlying bone traits in chickens

Li, Y.D.; Liu, Xianjing; Li, Z.W.; Wang, W.J.; Li, Y.M.; Zhi, Cao; Luan, Ping; Fan, Xiaoxi; Gao, He; Guo, Huaishun; Wang, N.; Li, H.; Wang, S.Z.

doi:10.1016/j.animal.2021.100322

Cited by 23 publications

(16 citation statements)

References 52 publications

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“…After the redundant variants in the different groups were removed, there are 33 million variants totally. There are 17,13,19,16,11,14,12 and 19 million bi-allelic SNPs on autosomes and sex chromosomes in the groups of Daweishan, Hu, Piao, Wuding, Nine-claw chickens, broilers, layers and RJFs, respectively (Table 1). After removing the redundant ones in the different groups, we ended up with 26 million bi-allelic SNPs on autosomes and sex chromosomes, and our subsequent analyses will be focused on these bi-allelic SNPs in each chicken group (Table 1).…”

Section: Resultsmentioning

confidence: 99%

“…Indeed, many studies have been done to reveal artificial selection signatures on commercial broilers and layers (Rubin, et al 2010; Elferink, et al 2012; Qanbari, et al 2012; Fan, et al 2013; Gheyas, et al 2015; Boschiero, et al 2018; Qanbari, et al 2019) as well as on indigenous chickens (Guo, et al 2016; Wang, et al 2016; Wang, et al 2017; Zhang, Yang, et al 2017; Bortoluzzi, et al 2018; Lawal, et al 2018; Wang, Li, et al 2020). These studies have identified genes or quantitative trait loci (QTLs) related to specific traits such as body size (Kerje, et al 2003; McElroy, et al 2006; Wang, et al 2016; Wang, et al 2017; Wang, Bu, et al 2020; Wang, Cao, et al 2020; Zhang, et al 2020; Wang, Hu, et al 2021), meat quality (Jennen, et al 2005; Bihan-Duval, et al 2018; Moreira, et al 2018), egg production (Zhao, et al 2021), feathering (Zhao, et al 2016; Guo, et al 2018; Zhang, et al 2018; Yang, et al 2019; Bortoluzzi, et al 2020; Li, Lee, et al 2020; Chen, et al 2022; Qiu, et al 2022), plumage color (Zhang, Liao, et al 2017; Huang, Pu, et al 2020; Huang, Otecko, et al 2020; Nie, et al 2021), skin color (Li, Sun, et al 2020), behaviors (Luo, et al 2020; Mehlhorn and Caspers 2020), immunity (Zou, et al 2020), crest shapes (Li, Lee, et al 2021), bone traits (Wang, et al 2018; Li, Liu, et al 2021; Kondoh, et al 2022), rumpless trait (Noorai, et al 2012; Freese, et al 2014; Xu, et al 2017; Wang, Khederzadeh, et al 2021), and polydactyly (Zhang, et al 2016; Chu, et al 2017). However, genetic bases of many artificially selected traits, in particular, of indigenous chickens, are far from being fully understood.…”

Section: Introductionmentioning

confidence: 99%

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Artificial selection footprints in domestic chicken genomes

Dou

Wang

et al. 2023

Preprint

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Accurate and low-cost next generation sequencing technologies make re-sequencing of large populations of a species possible. Although many studies related to artificial selection signatures of commercial and indigenous chickens have been carried out, quite a small number of genes have been found to be under selection. In this study, we re-sequenced 85 individuals of five indigenous chicken breeds with distinct traits from Yunnan, a southwest province of China. By analyzing these indigenous chickens together with 116 individuals of commercial chickens (broilers and layers) and 35 individuals of red jungle fowl, we find a substantially large number of selective sweeps and affected genes for each chicken breed using a rigorous statistic model than previously reported. We confirm most of previously identified selective sweeps and affected genes. Meanwhile the vast majority (~98.3%) of our identified selective sweeps overlap known chicken quantitative trait loci. Thus, our predictions are highly reliable. For each breed, we also identify candidate genes and selective sweeps that might be related to the unique traits of the chickens.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Artificial selection footprints in domestic chicken genomes

Dou

Wang

et al. 2023

Preprint

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“…ZNF652 is the classical C2H2 zinc finger DNA binding protein [ 37 ] and an inhibitor of gene transcription and plays a primary role in tumor invasion [ 25 ]. ZNF652 may be involved in human lipid and carbohydrate metabolism, e.g., sex hormone binding globulin (SHBG) [ 38 ] and may be related to body weight and bone growth [ 39 , 40 ]. However, its fat and growth regulatory mechanism in chickens is not currently known.…”

Section: Discussionmentioning

confidence: 99%

Genome-Wide Association Study Revealed the Effect of rs312715211 in ZNF652 Gene on Abdominal Fat Percentage of Chickens

Zhu

Liu

Wang

et al. 2022

Biology

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Abdominal fat percentage (AFP) is an important economic trait in chickens. Intensive growth selection has led to the over-deposition of abdominal fat in chickens, but the genetic basis of AFP is not yet clear. Using 520 female individuals from selection and control lines of Jingxing yellow chicken, we investigated the genetic basis of AFP using a genome-wide association study (GWAS) and fixation indices (FST). A 0.15 MB region associated with AFP was located on chromosome 27 and included nine significant single nucleotide polymorphisms (SNPs), which could account for 3.34–5.58% of the phenotypic variation. In addition, the π value, genotype frequency, and dual-luciferase results identified SNP rs312715211 in the intron region of ZNF652 as the key variant. The wild genotype was associated with lower AFP and abdominal fat weight (AFW), but higher body weight (BW). Finally, annotated genes based on the top 1% SNPs were used to investigate the physiological function of ZNF652. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis suggested that ZNF652 may reduce AFW and BW in broilers through the TGF-β1/SMad2/3 and MAPK/FoxO pathways via EGFR and TGFB1. Our findings elucidated the genetic basis of chicken AFP, rs312715211 on the ZNF652 gene, which can affect BW and AFW and was the key variant associated with AFP. These data provide new insight into the genetic mechanism underlying AF deposition in chickens and could be beneficial in breeding chickens for AF.

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“…For example, GWAS in an F 2 resource population was conducted to identify two novel candidate genes related to three single-nucleotide polymorphisms (SNPs) associated with avian influenza antibody titers ( Sun et al, 2016 ). Another study reported that 21 candidate genes were proved to be associated with chicken bone growth based on GWAS in an F 2 crossbred experimental population ( Li et al, 2021 ). For the HVP performance, our previous studies have preliminary detected three highly associated QTL regions (GGA1:50.5–54.0 Mb, GGA1:58.5–60.5 Mb, and GGA20:10.5–12.0 Mb) using Illumina Chicken 60 K SNP Beadchip in an F 2 cross broiler population ( Luo et al, 2013 ).…”

Section: Introductionmentioning

confidence: 99%

Genome-Wide Association Studies Provide Insight Into the Genetic Determination for Hyperpigmentation of the Visceral Peritoneum in Broilers

et al. 2022

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Hyperpigmentation of the visceral peritoneum (HVP) has been becoming one of the most challenging problems in yellow-feathered chicken production, which seriously affected chicken carcass quality traits. Detecting which genes dominantly impact pigmentation in the peritoneum tissues is of great benefit to the genetic improvement of HVP. To investigate the genetic mechanism of HVP in yellow-feathered broilers, genome-wide association studies (GWASs) were conducted in the F2 generation of a cross broiler population with 395 birds. A total of 115,706 single-nucleotide polymorphisms (SNPs) of 122,415 were retained to identify quantitative trait loci (QTL) associated to HVP in chicken. The GWAS results based on the logistic mixed model (LMM) revealed that a narrow genomic location on chromosomes 1 (49.2–51.3 Mb) was significantly associated (p ≤ 4.32 × 10−7) with HVP, which contained 23 SNP makers related to 14 functional genes (MFNG, POLDIP3, POLR2F, PICK1, PDXP, SGSM3, RANGAP1, MYH9, RPL3, GALP3, LGALS1, MICALL1, ATF4, and CYP2D6). Four highly associated (p < 10−5) haplotype blocks of 0.80 kb (two SNPs), 0.06 kb (two SNPs), 0.95 kb (two SNPs), and 0.03 kb (two SNPs) were identified with two, two, four, and four distinct haplotypes, respectively. As a melanoma-associated gene, CYP2D6 were also possibly involved in the development of HVP occurring in chicken with two significant variations (rs314284996 and rs317955795) in the promoter regions. Further tests revealed that the expression of CYP2D6 was obviously higher in the visceral peritoneum tissue of chicken with HVP than that in the normal group (p < 0.05). Our results provide a novel clue to understand the genetic mechanism of HVP generation in chicken, and the mapped QTL or candidate genes might serve for genomic selection to improve carcass quality in the yellow-feathered chicken industry.

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A combination of genome-wide association study and selection signature analysis dissects the genetic architecture underlying bone traits in chickens

Cited by 23 publications

References 52 publications

Artificial selection footprints in domestic chicken genomes

Artificial selection footprints in domestic chicken genomes

Genome-Wide Association Study Revealed the Effect of rs312715211 in ZNF652 Gene on Abdominal Fat Percentage of Chickens

Genome-Wide Association Studies Provide Insight Into the Genetic Determination for Hyperpigmentation of the Visceral Peritoneum in Broilers

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