Estimating genetic parameters with molecular relatedness and pedigree reconstruction for growth traits in early mixed breeding of juvenile turbot

Sun Song Wang Weiji Hu Yulong Luan Sheng Lyu Ding Kong Jie

Sun Song, Wang Weiji, Hu Yulong, Luan Sheng, Lyu Ding, Kong Jie. Estimating genetic parameters with molecular relatedness and pedigree reconstruction for growth traits in early mixed breeding of juvenile turbot[J]. Acta Oceanologica Sinica. doi: 10.1007/s13131-021-1799-z
Citation: Sun Song, Wang Weiji, Hu Yulong, Luan Sheng, Lyu Ding, Kong Jie. Estimating genetic parameters with molecular relatedness and pedigree reconstruction for growth traits in early mixed breeding of juvenile turbot[J]. Acta Oceanologica Sinica. doi: 10.1007/s13131-021-1799-z

doi: 10.1007/s13131-021-1799-z

Estimating genetic parameters with molecular relatedness and pedigree reconstruction for growth traits in early mixed breeding of juvenile turbot

Funds: The Agriculture Variety Improvement Project of Shandong Province under contract No. 2019LZGC013.
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  • Figure  1.  Number of offspring in each family.

    Figure  2.  Relationship between estimated breeding values (EBVs) from molecular relatedness (MR) and pedigree reconstruction (PR).

    Figure  3.  Relationship between MR-based observed and predicted values.

    Figure  4.  Relationship between the observed and predicted values based on PR.

    Figure  5.  Distribution of Person correlation coefficients for 500 times cross validations. PR, pedigree reconstruction; MR, molecular relatedness; BW, body weight; BL, body length.

    Table  1.   Characteristics of SSR primers (Ruan et al., 2010)

    LociPrimer sequence (5’-3’)RepeatsSizeFluorescent dyeTemperature/°C
    YSKr61F: TCAGTGGGCAGTGAGGTG
    R: AAGTCAGAGAAACATCCAGA
    GTCT164–173HEX62.0
    YSKr71F: TGGGATACATACACATTC
    R: AGTGAGTTGACAGACAGAG
    ACGC172–178TAMRA53.4
    YSKr72F: CCAGACAGATAACTACACA
    R: GTAAGGCTCGTTAGTCAC
    ACGC132–168FAM58.0
    YSKr85F: TACTTACACTGTGTATGTGC
    R: GAGAACCGAAGAAATGAGA
    GTGC252–290ROX56.0
    YSKr92F: CCACGCTGTGTATTTCCTCAT
    R: GGTCAACATTCAAACCCAACT
    GTGC188–208HEX60.0
    YSKr101F: CGGATAGTTAGTACCTCAT
    R: GAAAACTGAAGCTGAATG
    ACGC112–133TAMRA56.0
    YSKr111F: AACTGGGACTGGAGTGGAC
    R: CTCATTAGAGCCGCTGTAT
    TGCG340–366FAM62.0
    YSKr119F: GCTCTTCCAAGTGCCA
    R: TGTAGTGTACCAAATGC
    ACGC242–271ROX54.6
    YSKr121F: CAGAGGACAGCGACGAAGAC
    R: AGCATTGCATTGGGTTGAGT
    ACGC183–188HEX62.0
    YSKr124F: CAGCCGTTCTGACCTCGTAG
    R: ACCCTCCACTGCTTGTCCTTG
    GTGC178–187TAMRA62.0
    YSKr125F: ACTTATTTGCCTATGGAGAG
    R: TTCATTCACATCACTGGTC
    CGTG138–151FAM56.0
    YSKr6F: CTAACAAACAACGCAGTCG
    R: AGAAACAGGGTAGCATCAC
    CTT299–313ROX62.0
    YSKr141F: TTCTGCTCCCTTCTTCGTGT
    R: TCGGTGCTTGTGGAAATCG
    GCG171–189FAM61.0
    YSKr169F: TAATCTCCTGTTGCCTAATG
    R: AACGGACGAGTTCGGTGC
    AAC179–185ROX62.0
    YSKr170F: GCTACAGTGATGTCGCA
    R: ATTTATCCAGTGTTTCG
    AAC276–304HEX54.6
    YSKr173F: CTGGATTTGCCACGTCAGTAC
    R: TCTCGCTAACGCTTCACCTC
    AAG323–474TAMRA59.0
    下载: 导出CSV

    Table  2.   Genetic diversity information of 16 SSR loci

    LociKnHObsHExpPICNE-1PNE-2PNE-PPNE-INE-SIHWF (Null)
    YSKr6139090.3590.4980.4370.8760.7460.6060.3130.580***0.175 0
    YSKr7197150.8150.7620.7270.6250.4470.2580.0920.392***0.042 9
    YSKr72109090.7920.8310.8130.4950.3250.1460.0470.346***0.026 3
    YSKr85149040.8850.8480.8310.4620.2990.1280.0400.336***0.021 4
    YSKr9299070.8820.8010.7740.5660.3880.2050.0670.366***–0.050 0
    YSKr101109010.6850.7080.6740.6830.5020.3020.1190.426***0.018 5
    YSKr111149010.9210.8610.8480.4280.2710.1060.0330.328***0.035 7
    YSKr119118990.8710.8430.8230.4830.3150.1440.0440.340***0.014 7
    YSKr12189060.9250.8240.8010.5230.3490.1720.0540.352***0.060 3
    YSKr124109050.7830.7530.7310.6140.4280.2230.0830.394***0.023 1
    YSKr12569090.6740.7060.6540.7150.5460.3690.1390.432***0.029 9
    YSKr669030.8580.7620.7200.6460.4680.2900.0980.394***0.061 9
    YSKr14169020.6270.6190.5710.7880.6220.4420.1930.489***0.008 8
    YSKr16949010.6150.6270.5540.7930.6490.4890.2120.490***0.013 2
    YSKr170138880.5550.8260.8050.5100.3380.1580.0510.350***0.197 1
    YSKr173258670.7800.9020.8940.3310.1980.0630.0180.304***0.072 8
    Note: Number of individuals, 931; number of loci, 16; mean number of alleles per locus, 9.875 0; mean proportion of loci typed, 0.955 0; mean expected heterozygosity, 0.760 8; mean polymorphic information content (PIC), 0.728 5; combined non-exclusion probability (first parent), 0.000 157; combined non-exclusion probability (second parent), 0.000 000 55; combined non-exclusion probability (parent pair), 2.396×10–11; combined non-exclusion probability (identity), 1.366×10–18; combined non-exclusion probability (sib identity), 0.000 000 28. K, number of alleles at the locus; n, number of individuals typed at the locus; HObs, observed heterozygosity; HExp, expected heterozygosity; PIC, polymorphic information content; NE-1P, average non-exclusion probability for one candidate parent; NE-2P, average non-exclusion probability for one candidate parent given the genotype of a known parent of the opposite sex; NE-PP, average non-exclusion probability for a candidate parent pair; NE-I, average non-exclusion probability for identity of two unrelated individuals; NE-SI, average non-exclusion probability for identity of two siblings; HW, significance of deviation from Hardy-Weinberg equilibrium; F(Null), Estimated null allele frequency. ***, significant at the 0.1% level. The significance level includes a Bonferroni correction if the Bonferroni correction option was selected.
    下载: 导出CSV

    Table  3.   Variance component of body weight

    $ {\sigma }_{a}^{2} $$ {\sigma }_{d}^{2} $$ {\sigma }_{e}^{2} $$ {\sigma }_{p}^{2} $$ {h}^{2} $±SE
    PR0.326±0.1720.705±0.3030.488±0.1241.519±0.2980.214±0.121
    MR0.139±0.0360.631±0.2510.608±0.0331.379±0.2530.101±0.031
    Note: $ {\sigma }_{a}^{2} $, additive genetic variance (Unit, g2); $ {\sigma }_{d}^{2} $, maternal common environmental variance (Unit, g2); $ {\sigma }_{e}^{2} $, residual variance (Unit, g2); $ {\sigma }_{p}^{2} $, phenotypic variance (Unit, g2); h2, heritability; SE, stardard error.
    下载: 导出CSV

    Table  4.   Variance component of body length

    $ {\sigma }_{a}^{2} $$ {\sigma }_{d}^{2} $$ {\sigma }_{e}^{2} $$ {\sigma }_{p}^{2} $$ {h}^{2} $±SE
    PR0.038±0.0460.126±0.0520.162±0.0340.327±0.0530.117±0.141
    MR0.031±0.0010.106±0.0450.169±0.0010.306±0.0450.102±0.034
    Note: $ {\sigma }_{a}^{2} $, additive genetic variance (Unit, cm2); $ {\sigma }_{d}^{2} $, maternal common environmental variance (Unit, cm2); $ {\sigma }_{e}^{2} $, residual variance (Unit, cm2); $ {\sigma }_{p}^{2} $, phenotypic variance (Unit, cm2); h2, heritability; SE, stardard error.
    下载: 导出CSV

    Table  5.   Genetic correlation and phenotypic correlation of body weight (BW) and body length (BL) based on pedigree reconstruction (PR) and molecular relatedness (MR)

    Correlation coefficientGenetic correlationPhenotypic correlation
    MR0.8560.668
    PR0.7230.624
    下载: 导出CSV

    Table  6.   Results of cross validation between observations and predicted values

    Pearson correlation
    coefficient of
    body weight
    Pearson correlation
    coefficient of
    body length
    Molecular relatedness0.717±0.0450.629±0.058
    Pedigree reconstruction0.692±0.0520.615±0.060
    下载: 导出CSV
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出版历程
  • 收稿日期:  2020-09-30
  • 录用日期:  2020-12-29
  • 网络出版日期:  2021-06-25

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