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. 2025 Feb;104(2):104767.
doi: 10.1016/j.psj.2025.104767. Epub 2025 Jan 2.

Identification of quantitative trait loci and candidate genes associated with growth curve parameters in chinese wenshang barred chickens

Yan Zhou  1 , Jie Liu  1 , Qiuxia Lei  1 , Haixia Han  1 , Wei Liu  1 , Dapeng Li  1 , Yan Sun  1 , Dan Hao  1 , Fuwei Li  1 , Dingguo Cao  1 , Jie Wang  2
Affiliations

Identification of quantitative trait loci and candidate genes associated with growth curve parameters in chinese wenshang barred chickens

Yan Zhou et al. Poult Sci. 2025 Feb.

Abstract

The growth curve is a vital instrument for assessing and forecasting weight and developmental shifts in livestock and poultry, which reflects the changes of bodyweight traits with time and plays a key role in guiding breeding and production approaches. This study performed a genome-wide association study (GWAS) for growth curve parameters generated by nonlinear models which fit original weight-age records, to discover the SNPs and candidate genes correlated with growth traits. Data from 362 Chinese Wenshang Barred Chickens weighed at the age of 0, 2, 4, 6, 8, 10, 12, 14, 16, and 18 weeks were used to fit the Gompertz, Logistic, and von Bertalanffy growth models. The Gompertz model showed the highest coefficient of determination (R2 = 0.974). The mature body weight (A), time scale (b), and maturity rate (k) were treated as phenotypes for single-trait GWAS. The GWAS identified 44, 103, and 5 significant single nucleotide polymorphisms (SNPs) associated with A, b, and K, respectively. Among them, several candidate genes, including LDB2, TOB2, RCBTB1, KPNA3, SLIT2, LCORL, LAP3, and TPRA1, were previously reported to be associated with growth and development. Two lead SNPs (4:76022389, 4:76070237) on the LDB2 gene were significantly associated with the growth curve. Further research of these candidate genes could help explore the full genetic architecture underlying growth and development traits in poultry.

Keywords: GWAS; Growth curve model; Longitudinal data.

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Conflict of interest statement

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig 1
Fig. 1
Population genetic diversity and GWAS results. (a) PCA plot of the WB chicken breed. (b) A circle-Manhattan plot based on the GWAS for growth curve parameters. Each dot on this figure corresponds to a SNP in the dataset, and the horizontal red and blue lines denote the genome-wide significance (0.05/837,332) and the suggestive significance (1/837,332) thresholds, respectively. The Manhattan plot plots the –log10 observed P-values for genome-wide SNPs (Y-axis) against their corresponding position on each chromosome (X-axis). The horizontal axis represents the chromosome length in Mb. The colors correspond to SNP density. The circles from outside to inside are for the A, b, and K traits. (c) The Q-Q plots were derived from the GWASs for growth curve parameters. They plot the expected –log10-transformed P-values against the observed –log10-transformed P-values.
Fig 2
Fig. 2
Regional association analysis of the significant signal (GGA 4) with A. (a) A regional association plot and linkage disequilibrium (LD) blocks of the significant signal (GGA 4:74.84–76.11 Mb). (b) Phenotypic differences between individuals with different genotypes at 4:76022389 on GGA 4. *, P < 0.05; **, P < 0.01; ***, P < 0.001; ns, not significant. (c) Growth curves of individuals with different genotypes at 4:76022389 on GGA 4.
Fig 3
Fig. 3
Regional association analysis of the significant signal (GGA 4) with b. (a) A regional association plot and linkage disequilibrium (LD) blocks of the significant signal (GGA 4:74.79–76.24 Mb). (b) Phenotypic differences between individuals with different genotypes at 4:76070237 on GGA 4. *, P < 0.05; **, P < 0.01; ***, P < 0.001; ns, not significant. (c) Growth curves of individuals with different genotypes at 4:76070237 on GGA 4.
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