中畜草原白羽肉鸭与樱桃谷鸭的遗传差异分析

doi:10.16431/j.cnki.1671-7236.2022.03.001

摘要/Abstract

摘要： 【目的】通过基因组重测序技术对中畜草原白羽肉鸭与樱桃谷鸭的遗传差异进行分析，追溯两个品种鸭在不同人工选择下的基因组变异机制，以此阐明优异性状形成的遗传基础。【方法】选择樱桃谷鸭商品代和中畜草原白羽肉鸭商品代各16只进行基因组重测序，过滤掉高缺失率与最小等位基因频率较低的位点，获得高质量SNPs用于后续分析；对两品种的基因型数据进行主成分分析（PCA）确定其遗传分化情况；采用群体遗传分化指数（Fst）和群体核酸多样性比值（Pi）两种分析方法综合筛选中畜草原白羽肉鸭和樱桃谷鸭的受选择信号。【结果】主成分分析结果显示，中畜草原白羽肉鸭和樱桃谷鸭分化显著。以10 kb窗口5 kb步长分别计算Fst与Pi分析值，取前1%作为阈值（Fst>0.177，Pi>0.885），在两种分析方法的信号重叠区域共筛选到410 kb候选区域，共注释到21个候选基因。对候选基因进行GO与KEGG富集分析发现，12个基因显著富集到细胞组分和分子功能两大类中（P<0.05），2个基因显著富集到代谢相关通路（P<0.05）。这些基因中，与脂质代谢、氨基酸代谢、免疫调控相关的基因包括PDE3A、PRKAR2B、SEMA5A、SHANK2、STXBP6与LOC101803508（GOLGB1）受到了强选择。【结论】虽然樱桃谷鸭与中畜草原白羽肉鸭均源自北京鸭，但经过不同强度、不同方向持续的人工选育，2个品种明显分化，且中畜草原白羽肉鸭具有更高的遗传多态性。筛选到了2个品种间一系列遗传分化候选基因，并重点挖掘了参与白羽肉鸭风味肉品质调控的相关基因，为后续研究不同白羽肉鸭品种特征、筛选品种特异性分子标记提供了参考。

关键词: 中畜草原白羽肉鸭; 樱桃谷鸭; 重测序; 选择信号; 候选基因

Abstract: 【Objective】 This study was aimed to identify the genetic differentiation between IAS Grassland duck and Cherry Valley duck by genome resequencing technology, and investigate the genomic variation between the two breeds under different artificial selection to clarify the genetic basis for the formation of excellent traits.【Method】 In this study, 16 Cherry Valley ducks and 16 IAS Grassland ducks were adopted for genome resequencing.After filtering out SNP markers with high missing rates and low allele frequencies, high-quality SNPs were obtained for subsequent analysis.Then the genotypic data of the two breeds were analyzed by principal component analysis (PCA) to identify their genetic differentiation.The selected signals of IAS Grassland duck and Cherry Valley duck were comprehensively screened by population genetic differentiation index (Fst) and nucleic acid diversity ratio (Pi).【Result】 PCA analysis illustrated that IAS Grassland duck and Cherry Valley duck were significantly differentiated.The analysis values of Fst and Pi were calculated in 10 kb window and 5 kb step respectively, and the Top 1% of Fst and Pi values was taken as the threshold (Fst>0.177, Pi>0.885).A total of 410 kb candidate regions were screened in the signal overlap region of the two analysis methods, and a total of 21 candidate genes were annotated.GO and KEGG enrichment analysis showed that 12 candidate genes were enriched in two categories, including cellular component and biological process (P<0.05), and 2 genes were significantly enriched in the metabolic pathway, signal transduction, reproduction, immune response pathway, etc.(P<0.05).Among the significantly enriched genes, those related to lipid metabolism, amino acid metabolism, and immune modulation, including PDE3A, PRKAR2B, SEMA5A, SHANK2, STXBP6, and LOC101803508 (GOLGB1), were strongly selected.【Conclusion】 The results indicated that although both Cherry Valley ducks and IAS Grassland ducks were derived from Pekin ducks, they differentiated obviously after continuous artificial selection with different selection pressure and directions, IAS Grassland ducks had higher genetic diversity than Cherry Valley ducks.A series of candidate genes for genetic differentiation between the two duck breeds were predicted, and the relevant genes involved in the regulation of flavor and meat quality of White-feather meat ducks were mainly excavated, which provided a reference for the follow-up study of the characteristics of different White-feather meat ducks and the screening of variety specific molecular markers.

Key words: IAS Grassland duck; Cherry Valley duck; resequencing; selection signals; candidate genes

中图分类号:

S834.2

于思梦, 郭占宝, 胡健, 周正奎, 侯水生. 中畜草原白羽肉鸭与樱桃谷鸭的遗传差异分析[J]. 中国畜牧兽医, 2022, 49(3): 801-808.

YU Simeng, GUO Zhanbao, HU Jian, ZHOU Zhengkui, HOU Shuisheng. Analysis of Genetic Differentiation Between IAS Grassland Ducks and Cherry Valley Ducks[J]. China Animal Husbandry and Veterinary Medicine, 2022, 49(3): 801-808.

参考文献

[1] LIANG S, GUO Z, TANG J, et al.Genomic divergence during artificial selection by feed conversion ratio in Pekin ducks[J].Animal Biotechnology, 2021:1-9.
[2] 王美青, 张扬, 丛玮, 等.樱桃谷鸭不同杂交组合生产性能与肉品质分析[J].中国家禽, 2018, 40(11):9-12. WANG M Q, ZHANG Y, CONG W, et al.Analysis on growth performance and meat quality of different cross combinations of Cherry Valley duck[J].China Poultry, 2018, 40(11):9-12.(in Chinese)
[3] 杨永平.鸭脂肪组织EST鉴定、脂肪代谢相关基因多态检测及其与肉鸭脂肪、屠体和生长性状的关联分析[D].武汉:华中农业大学, 2011. YANG Y P.EST identification from duck adipose tissues, and detection of polymorphisms in tree genes related with fat metabolism and their association with fatness, carcass and growth traits in meat type duck[D].Wuhan:Huazhong Agricultural University, 2011.(in Chinese)
[4] LI J, ZHANG J, LIU J, et al.A new duck genome reveals conserved and convergently evolved chromosome architectures of birds and mammals[J].Gigascience, 2021, 10(1):giaa142.
[5] ZHOU Z, LI M, CHENG H, et al.An intercross population study reveals genes associated with body size and plumage color in ducks[J].Nature Communications, 2018, 9(1):2648.
[6] SIEGEL P B.Evolution of the modern broiler and feed efficiency[J].Annual Review Animal Bioscience, 2014, 2:375-385.
[7] LI M Z, TIAN S L, JIN L, et al.Genomic analyses identify distinct patterns of selection in domesticated pigs and Tibetan wild boars[J].Nature Genetics, 2013, 45(12):1431-1438.
[8] ZHANG H, LIANG Q, WANG N, et al.Microevolutionary dynamics of chicken genomes under divergent selection for adiposity[J].iScience, 2020, 23(6):101193.
[9] LIU D, FAN W, XU Y, et al.Genome-wide association studies demonstrate that TASP1 contributes to increased muscle fiber diameter[J].Heredity, 2021, 126:991-999.
[10] LIU H, HU J, GUO Z, et al.A SNP variant located in the cis-regulatory region of the ABCG2 gene is associated with mallard egg color[J].Molecular Ecology, 2020, 30(6):1477-1491.
[11] LI H, DURBIN R.Fast and accurate short read alignment with Burrows-Wheeler transform[J].Bioinformatics, 2009, 25(14):1754-1760.
[12] MCKENNA A, HANNA M, BANKS E, et al.The Genome analysis toolkit:A MapReduce framework for analyzing next-generation DNA sequencing data[J].Genome Research, 2010, 20(9):1297-1303.
[13] DANECEK P, AUTON A, ABECASIS G, et al.The variant call format and VCFtools[J].Bioinformatics, 2011, 27(15):2156-2158.
[14] PURCELL S, NEALE B, TODD-BROWN K, et al.PLINK:A tool set for whole-genome association and population-based linkage analyses[J].American Journal of Human Genetics, 2007, 81(3):559-575.
[15] REICH D, PRICE A L, PATTERSON N.Principal component analysis of genetic data[J].Nature Genetics, 2008, 40(5):491-492.
[16] HUANG D W, SHERMAN B T, LEMPICKI R A.Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources[J].Nature Protocals, 2009, 4(1):44-57.
[17] BU D, LUO H, HUO P, et al.KOBAS-i:Intelligent prioritization and exploratory visualization of biological functions for gene enrichment analysis[J].Nucleic Acids Research, 2021, 49(W1):W317-W325.
[18] 侯水生, 周正奎.肉鸭种业的昨天及今天和明天[J].中国畜牧业, 2021, 18:23-26. HOU S H, ZHOU Z K.Past, now and future of meat duck breeding industry[J].China Animal Industry, 2021, 18:23-26.(in Chinese)
[19] WANG X, PEI J, BAO P, et al.Mitogenomic diversity and phylogeny analysis of yak (Bos grunniens)[J].BMC Genomics, 2021, 22(1):325.
[20] JIANG Z, MICHAL J J, WU X L, et al.The heparan and heparin metabolism pathway is involved in regulation of fatty acid composition[J].International Journal of Biological Sciences, 2011, 7(5):659-663.
[21] JIANG H, RAO K S, YEE V C, et al.Characterization of four variant forms of human propionyl-CoA carboxylase expressed in Escherichia coli[J].The Journal of Biological Chemistry, 2005, 280(30):27719-27727.
[22] SAN J, DU Y, WU G, et al.Transcriptome analysis identifies signaling pathways related to meat quality in broiler chickens——The extracellular matrix (ECM) receptor interaction signaling pathway[J].Poultry Science, 2021, 100(6):101135.
[23] WRIGHT S.Evolution and the Genetics of Populations[M].Chicago:University of Chicago Press, 1978.
[24] KIM Y R, YI M, CHO S A, et al.Identification and functional study of genetic polymorphisms in cyclic nucleotide phosphodiesterase 3A (PDE3A)[J].Annals of Human Genetics, 2020, 85(2):80-91.
[25] AN J, LI Y, SONG S, et al.Electroacupuncture promotes the gastrointestinal motility of diabetic mice by CNP/NPR-B-cGMP and PDE3A-cGMP signaling[J].Neurogastroenterology & Motility, 2019, 31(4):e13539.
[26] ALAM M H, LEE J, MIYANO T.Inhibition of PDE3A sustains meiotic arrest and gap junction of bovine growing oocytes in in vitro growth culture[J].Theriogenology, 2018, 118:110-118.
[27] YADAV S K, PANDEY A, KUMAR L, et al.The thermo-sensitive gene expression signatures of spermatogenesis[J].Reporductive Biology and Endocrinology, 2018, 16:56.
[28] KHALTABADI F A H, MOHAMMADI H, MORADI M H, et al.Identification of potential genomic regions for egg weight by a haplotype-based genome-wide association study using Bayesian methods[J].British Poultry Science, 2020, 61(3):251-257.
[29] KERR A G, SINHA I, DADVAR S, et al.Epigenetic regulation of diabetogenic adipose morphology[J].Molecular Metabolism, 2019, 25:159-167.
[30] PEVERELLI E, ERMETICI F, CORBETTA S, et al.PKA regulatory subunit R2B is required for murine and human adipocyte differentiation[J].Endocrine Connections 2013, 2(4):196-207.
[31] LILLIE M, SHENG Z, HONAKER C F, et al.Genome-wide standing variation facilitates long-term response to bidirectional selection for antibody response in chickens[J].BMC Genomics, 2017, 18(1):99.
[32] HOU Q, ZHANG S, LI Y, et al.New insights on association between circadian rhythm and lipid metabolism in spontaneously hypertensive rats[J].Life Sciences, 2021, 271:119145.
[33] TOLDRA' F.Proteolysis and lipolysis in flavour development of dry-cured meat products[J].Meat Science, 1998:49:S101-S110.
[34] LI W, LIU R, ZHENG M, et al.New insights into the associations among feed efficiency, metabolizable efficiency traits and related QTL regions in broiler chickens[J].Journal of Animal Science and Biotechnology, 2020, 11:65.
[35] COLLINS S C, DO H W, HASTOY B, et al.Increased expression of the diabetes gene SOX4 reduces insulin secretion by impaired fusion pore expansion[J].Diabetes, 2016, 65(7):1952-1961.
[36] LIU C, HU Q, CHEN Y, et al.Behavioral and gene expression analysis of Stxbp6-knockout mice[J].Brain Sciences, 2021, 11(4):436.
[37] RAMALINGAM V, SONG Z, HWANG I.The potential role of secondary metabolites in modulating the flavor and taste of the meat[J].Food Research International, 2019, 122:174-182.