二代基因组测序鉴别狮头鹅拷贝数变异及其与体重体尺关联

doi:10.3864/j.issn.0578-1752.2024.14.015

Abstract

Abstract:

【Background】 Many previous studies have reported that copy number variation (CNV) is a kind of deletion or duplication with the length of 50 bp-5 Mb, which can affect the expression of genes. It is closely associated with economically important traits of livestock, which is one kind of promising molecular markers. Lion-head goose is one of the largest goose species in the world. It is originated in Raoping, Guangdong Province and is the raw material for Guangdong marinated geese. So far, there has no genome-wide association study on investigating the relationship between CNV and body weight and size in lion-head geese. 【Objective】 This study identified the CNV and CNV region (CNVR) of lion-head geese by using the second-generation genome sequencing data, and then detected CNV and candidate genes significantly affecting body weight and size through the association between them, which could provide the valuable reference information for molecular breeding of lion-head geese. 【Method】 A total of 111 lion-head geese were collected from Baisha Poultry and Livestock Origin Research Institute in Shantou, including 20 males and 91females. All geese were raised and managed under the uniform standards. The body weight and size traits of 111 geese were measured, and the body size traits included body oblique length, chest depth, chest width and so on. The next-generation genome sequencing data (5×) was generated using blood samples for these geese. SOAPnuke was used for the quality control of sequencing data.The BWA module of Speedseq was used for alignment, and the LUMPY and CNVnator modules of Speedseq were used to detect structural variations (SVs). CNV were selected from SV. The software SVtools was used to genotype CNV, and the association analysis between CNV and body weight and size traits was performed by using the single maker mixed model. CNV significantly associated with traits was screened through the chromosome significance level (0.05/number of CNV on the chromosome), and then annotated the significant CNV including their upstream and downstream 50 kb to identify candidate genes for the body weight and size of lion-head geese. The R package CNVrd2 was used to analyze the linkage disequilibrium (LD) of chromosome-significant CNV and chromosome-significant SNP with physical distance less than 1 Mb. 【Result】 For 111 lion-head geese, this study detected 99158 CNV including 94 560 deletions and 4 598 duplications. The average length of CNV was 11 858 bp, and most (74.06%) of them were located in the range of 50 bp-1 Kb. A total of 5 225 CNVR were detected, which contained 5 029 loss types, 110 gain types, and 86 mixed types. The average length of CNVR was 7 136 bp, and the lengths of most (81.03%) of the CNVRs were 50 bp-1 Kb. Functional annotation showed that 46.92% of CNVR were located in the inter gene region, 10.30% were located the upstream, and 9.35% were located the downstream. There were 6 217 CNV accurately genotyped for association analysis. By the association analysis of body weight and size traits and CNV, a total of 55 CNV exceeded the significance level of chromosomes, and then annotated 45 candidate genes based on these 55 CNV. Among these 45 candidate genes, it was found that 10 genes, such as SETD2, UBR7 and G2E3, simultaneously influenced two or more traits. Chromosome-significant CNV affected body weight and size traits independently of chromosome-significant SNP (r²<0.02). 【Conclusion】 This study for the first time reported the distribution of CNV and CNVR in the genome of lion-head geese as well as the association between CNV and body weight and size by using the next-generation genome sequencing data. It was found that a total of 45 candidate genes influencing the body weight and size traits, in which 11 genes were reported to be related to signal pathways of animal growth, among these 11 genes, SETD2, UBR7, ASB1 and HDAC4 were involved in muscle proliferation, differentiation and metabolism, G2E3, P3C2B, NOVA1 and PDE1B were involved in adipogenesis and obesity, ILKAP was involved in regulating growth factors, KIF1B was involved in bone metabolism, and ZFP37 was involved in glycogen metabolism. These results laid a solid foundation for analyzing molecular genetic mechanism and detecting molecular marker for the growth performance of lion-head goose.

Key words: lion-head goose, body weight and size traits, CNV, candidate gene

ZHANG LiYun, HUANG ZhiRong, YANG Liu, CHEN JunPeng, LIN ZhenPing, HUANG HongYan, WU ZhongPing, ZHANG XuMeng, TIAN YunBo, HUANG YunMao, LI XiuJin. Identification of Copy Number Variation and Its Association with Body Weight and Size of Lion-Head Geese by Next-Generation Sequencing[J].Scientia Agricultura Sinica, 2024, 57(14): 2889-2900.

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Figures/Tables 6

Table 1

Table 2

Fig. 1

Fig. 2

Fig. 3

Table 3

Significant CNV related to traits"

性状 Trait	染色体 Chromosome	起始位点 Start	结束位点 End	长度 Length	类型 Type	-log10（P）	相关基因 Related genes
体重 Body weight	5	55963996	55964083	87	缺失Deletion	5.02339	/
体重 Body weight	24	1950171	1950304	133	缺失Deletion	3.141067	Z385B
体斜长 Body oblique length	6	31426281	31426385	104	缺失Deletion	3.639657	DDX18
	9	11618900	11619036	136	缺失Deletion	4.089755	ILKAP/KIF1B
	22	1376313	1376455	142	缺失Deletion	3.331442	/
胸深 Chest depth	1	84857253	84865163	7910	缺失Deletion	4.517457	FV1/POL/RTJK
	1	210370756	210372242	1486	重复Duplication	3.263032	ARHGH
	2	160644096	160644154	58	缺失Deletion	4.443069	SETD2
	4	15223434	15223523	89	缺失Deletion	4.153697	S4A4
	10	6195488	6218381	22893	重复Duplication	1.653918	G2E3/ATRIP
	13	1664315	1664903	588	缺失Deletion	3.539736	/
	17	2574412	2574457	45	缺失Deletion	3.435763	RASL1/DTX1
	29	103884	104329	445	缺失Deletion	3.703085	CCD81
胸宽 Chest width	2	160644096	160644154	58	缺失Deletion	4.350129	SETD2
	10	6195488	6218381	22893	重复Duplication	1.723656	G2E3/ATRIP
	17	2574412	2574457	45	缺失Deletion	3.542544	RASL1/DTX1
	28	3222132	3222472	340	重复Duplication	3.257708	ZSCA2/ZFP37
半潜水 Semi-diving length	4	2157550	2157732	182	缺失Deletion	4.634255	/
	4	8817672	8823590	5918	重复Duplication	2.308129	UNC5C
	5	16355316	16355899	583	缺失Deletion	3.854071	UBR7
	6	31818027	31818610	583	缺失Deletion	3.899274	/
	7	5970465	5970944	479	缺失Deletion	5.360049	SAC2
	21	217452	217543	91	缺失Deletion	3.38304	TRI62
	25	3103542	3103852	310	缺失Deletion	5.069086	P3C2B
龙骨长 Keel length	3	55501233	55502372	1139	缺失Deletion	4.406552	/
	5	16355316	16355899	583	缺失Deletion	4.230954	UBR7
	7	5970465	5970944	479	缺失Deletion	5.829223	SAC2
	23	704175	705047	872	缺失Deletion	3.383816	/
	27	5248917	5249250	333	重复Duplication	2.710029	SNUT2/PSPB
	29	1343087	1344453	1366	重复Duplication	3.203918	/
颈围 Neck circumference	5	42586859	42588820	1961	缺失Deletion	3.846584	NOVA1
	6	10553749	11214369	660620	重复Duplication	1.826926	MIPT3/SH3B4/UBP40/Y1987/UD11/ASB1/ HDAC4
	7	6788342	6788420	78	缺失Deletion	3.685163	/
	22	6766873	6767052	179	缺失Deletion	3.107965	ETS1B
	27	4307876	4308376	500	重复Duplication	5.511413	MAD1
	29	11596987	11597562	575	重复Duplication	3.322661	PDE1B
颈长 Neck length	1	172772838	172773175	337	缺失Deletion	6.429338	/
	2	137370413	137371244	831	缺失Deletion	4.648816	/
	3	31975113	31975866	753	缺失Deletion	4.845833	RIMS1
	3	66963985	66964154	169	缺失Deletion	5.058238	CNKR3
	5	7767038	7767532	494	缺失Deletion	4.447119	C1TC
	7	5970465	5970944	479	缺失Deletion	4.742051	SAC2
	11	3014235	3014444	209	缺失Deletion	5.683303	UN13C
	13	5144239	5144542	303	缺失Deletion	3.701915	/
	27	5263207	5263333	126	缺失Deletion	3.504056	NPCL1
胫围 Tibia circumference	4	56511073	56513948	2875	重复Duplication	2.630038	/
胫围 Tibia circumference	23	4097467	4097922	455	缺失Deletion	3.768919	/
胫长 Tibia length	2	91195210	91196835	1625	缺失Deletion	5.487168	DESP
	8	19010486	19028003	17517	重复Duplication	2.605107	RTJK/PO11
	12	2163032	2163872	840	缺失Deletion	3.346685	/
	12	9787236	9787501	265	缺失Deletion	3.333377	/
	14	2803528	2803597	69	缺失Deletion	4.215348	/
	26	3921754	3922149	395	重复Duplication	2.072884	MAST3
	27	5478241	5478319	78	缺失Deletion	3.459357	RETST/ELMD3
	28	3221975	3222472	497	重复Duplication	3.463797	ZSCA2/ZFP37

Table 3

References 52

[1]	郭精奇. 饶平狮头鹅美誉传四方. 源流, 2022(8): 40-41.
	GUO J Q. Raoping lion goose’s reputation spread everywhere. Origins, 2022(8): 40-41. (in Chinese)
[2]	FREEMAN J L, PERRY G H, FEUK L, REDON R, MCCARROLL S A, ALTSHULER D M, ABURATANI H, JONES K W, TYLER- SMITH C, HURLES M E, et al. Copy number variation: New insights in genome diversity. Genome Research, 2006, 16(8): 949-961. pmid: 16809666
[3]	SEBAT J, LAKSHMI B, TROGE J, ALEXANDER J, YOUNG J, LUNDIN P, MÅNÉR S, MASSA H, WALKER M, CHI M, et al. Large-scale copy number polymorphism in the human genome. Science, 2004, 305(5683): 525-528. doi: 10.1126/science.1098918 pmid: 15273396
[4]	党李苹, 周雯馨, 刘瑞芳, 白云, 王哲鹏.略阳乌鸡体重和产蛋数性状遗传参数估计. 中国农业科学, 2020, 53(17): 3620-3628.
	DANG L P, ZHOU W X, LIU R F, BAI Y, WANG Z P. Estimation of genetic parameters of body weight and egg number traits of Lueyang black-boned chicken. Scientia Agricultura Sinica, 2020, 53(17): 3620-3628. (in Chinese) doi: 10.3864/j.issn.0578-1752.2020.17.018
[5]	黄勋和, 翁茁先, 李威娜, 王庆, 何丹林, 罗威, 张细权, 杜炳旺. 中国地方品种黄鸡线粒体DNA D-loop遗传多样性研究. 中国农业科学, 2022, 55(22): 4526-4538. doi: 10.3864/j.issn.0578-1752.2022.22.016.
	HUANG X H, WENG Z X, LI W N, WANG Q, HE D L, LUO W, ZHANG X Q, DU B W, Genetic diversity of indigenous yellow- feathered chickens in Southern China inferred from mitochondrial DNA D-loop region. Scientia Agricultura Sinica, 2022, 55(22): 4526-4538. doi: 10.3864/j.issn.0578-1752.2022.22.016. (in Chinese)
[6]	HAN R L, YANG P K, TIAN Y D, WANG D D, ZHANG Z X, WANG L L, LI Z J, JIANG R R, KANG X T. Identification and functional characterization of copy number variations in diverse chicken breeds. BMC Genomics, 2014, 15(1): 934.
[7]	LIN S D, LIN X R, ZHANG Z H, JIANG M Y, RAO Y S, NIE Q H, ZHANG X Q. Copy number variation in SOX6 contributes to chicken muscle development. Genes, 2018, 9(1): 42.
[8]	BAI H, HE Y H, DING Y, CHU Q, LIAN L, HEIFETZ E M, YANG N, CHENG H H, ZHANG H M, CHEN J L, SONG J Z. Genome-wide characterization of copy number variations in the host genome in genetic resistance to Marek’s disease using next generation sequencing. BMC Genetics, 2020, 21(1): 77.
[9]	DE ALMEIDA SANTANA M H, JUNIOR G A O, CESAR A S M, FREUA M C, DA COSTA GOMES R, DA LUZ E SILVA S, LEME P R, FUKUMASU H, CARVALHO M E, VENTURA R V, et al. Copy number variations and genome-wide associations reveal putative genes and metabolic pathways involved with the feed conversion ratio in beef cattle. Journal of Applied Genetics, 2016, 57(4): 495-504. pmid: 27001052
[10]	FERNANDES A C, DA SILVA V H, GOES C P, MOREIRA G C M, GODOY T F, IBELLI A M G, DE OLIVEIRA PEIXOTO J, CANTÃO M E, LEDUR M C, DE REZENDE F M, COUTINHO L L. Genome-wide detection of CNVs and their association with performance traits in broilers. BMC Genomics, 2021, 22: 354. doi: 10.1186/s12864-021-07676-1 pmid: 34001004
[11]	CENDRON F, CASSANDRO M, PENASA M. Genome-wide investigation to assess copy number variants in the Italian local chicken population. Journal of Animal Science and Biotechnology, 2024, 15(1): 2.
[12]	YU S M, LIU Z H, LI M, ZHOU D K, HUA P, CHENG H, FAN W L, XU Y X, LIU D P, LIANG S Y, et al. Resequencing of a Pekin duck breeding population provides insights into the genomic response to short-term artificial selection. GigaScience, 2023, 12. doi.org/10.1093/gigascience/giad016.
[13]	ZHANG L H, LI H Y, TANG B H, ZHAO X Y, WU Y P, JIANG T, YAO Y Y, LI J H, YAO Y, WANG L. Genomic signatures reveal selection in Chinese and European domesticated geese. Animal Genetics, 2023, 54(6): 763-771.
[14]	中华人民共和国农业农村部. 家禽生产性能名词术语和度量计算方法: NY/T 823—2020[S]. 北京: 中国农业出版社, 2020.
	Ministry of Agriculture and Rural Affairs of the People’s Republic of China. Terms and Measurement Calculation Methods of Poultry Production Performance: NY/T 823—2020[S]. Beijing: China Agriculture Press, 2020. (in Chinese)
[15]	CHEN Y X, CHEN Y S, SHI C M, HUANG Z B, ZHANG Y, LI S K, LI Y, YE J, YU C, LI Z, et al. SOAPnuke: a MapReduce acceleration- supported software for integrated quality control and preprocessing of high-throughput sequencing data. GigaScience, 2018, 7(1): 1-6.
[16]	CHIANG C, LAYER R M, FAUST G G, LINDBERG M R, ROSE D B, GARRISON E P, MARTH G T, QUINLAN A R, HALL I M. SpeedSeq: ultra-fast personal genome analysis and interpretation. Nature Methods, 2015, 12: 966-968. doi: 10.1038/nmeth.3505 pmid: 26258291
[17]	NANDOLO W, MÉSZÁROS G, WURZINGER M, BANDA L J, GONDWE T N, MULINDWA H A, NAKIMBUGWE H N, CLARK E L, WOODWARD-GREENE M J, LIU M, et al. Detection of copy number variants in African goats using whole genome sequence data. BMC Genomics, 2021, 22(1): 398.
[18]	SUN T, PEI S W, LIU Y K, HANIF Q, XU H Y, CHEN N B, LEI C Z, YUE X P. Whole genome sequencing of Simmental cattle for SNP and CNV discovery. BMC Genomics, 2023, 24(1): 179.
[19]	ZHOU J H, LIU L Y, LOPDELL T J, GARRICK D J, SHI Y G. HandyCNV: standardized summary, annotation, comparison, and visualization of copy number variant, copy number variation region, and runs of homozygosity. Frontiers in Genetics, 2021, 12: 731355.
[20]	LADEIRA G C, PINEDO P J, SANTOS J E P, THATCHER W W, REZENDE F M. PSXII-1 CNV and cnvr detection from high-density SNP genotyping in Holstein cattle. Journal of Animal Science, 2022, 100(Suppl_3): 207.
[21]	GINESTET C. ggplot2: elegant graphics for data analysis. Journal of the Royal Statistical Society Series A: Statistics in Society, 2011, 174(1): 245-246.
[22]	CINGOLANI P. Variant annotation and functional prediction: SnpEff. Methods in Molecular Biology, 2022, 2493: 289-314. doi: 10.1007/978-1-0716-2293-3_19 pmid: 35751823
[23]	LARSON D E, ABEL H J, CHIANG C, BADVE A, DAS I, ELDRED J M, LAYER R M, HALL I M. Svtools: population-scale analysis of structural variation. Bioinformatics, 2019, 35(22): 4782-4787. doi: 10.1093/bioinformatics/btz492 pmid: 31218349
[24]	YANG L, NIU Q H, ZHANG T L, ZHAO G Y, ZHU B, CHEN Y, ZHANG L P, GAO X, GAO H J, LIU G E, LI J Y, XU L Y. Genomic sequencing analysis reveals copy number variations and their associations with economically important traits in beef cattle. Genomics, 2021, 113(1): 812-820.
[25]	ZOUBAREV A, HAMER K M, KESHAV K D, MCCARTHY E L, SANTOS J R C, VAN ROSSUM T, MCDONALD C, HALL A, WAN X, LIM R, et al. Gemma: a resource for the reuse, sharing and meta-analysis of expression profiling data. Bioinformatics, 2012, 28(17): 2272-2273. doi: 10.1093/bioinformatics/bts430 pmid: 22782548
[26]	QUINLAN A R, HALL I M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics, 2010, 26(6): 841-842. doi: 10.1093/bioinformatics/btq033 pmid: 20110278
[27]	NGUYEN H T, MERRIMAN T R, BLACK M A. The CNVrd2 package: measurement of copy number at complex loci using high-throughput sequencing data. Frontiers in Genetics, 2014, 5: 248. doi: 10.3389/fgene.2014.00248 pmid: 25136349
[28]	DA SILVA V H. Genome-wide association of copy number variation with egg-laying date in a wild songbird[D]. Wageningen: Wageningen University, 2020.
[29]	HOU Y L, LIU G E, BICKHART D M, CARDONE M F, WANG K, KIM E S, MATUKUMALLI L K, VENTURA M, SONG J Z, VANRADEN P M, et al. Genomic characteristics of cattle copy number variations. BMC Genomics, 2011, 12(1): 127.
[30]	DING R R, ZHUANG Z W, QIU Y B, WANG X W, WU J, ZHOU S P, RUAN D L, XU C N, HONG L J, GU T, et al. A composite strategy of genome-wide association study and copy number variation analysis for carcass traits in a Duroc pig population. BMC Genomics, 2022, 23(1): 590.
[31]	YANG L, XU L Y, ZHOU Y, LIU M, WANG L, KIJAS J W, ZHANG H P, LI L, LIU G E. Diversity of copy number variation in a worldwide population of sheep. Genomics, 2018, 110(3): 143-148. doi: S0888-7543(17)30082-4 pmid: 28917637
[32]	RAO Y S, LI J, ZHANG R, LIN X R, XU J G, XIE L, XU Z Q, WANG L, GAN J K, XIE X J, et al. Copy number variation identification and analysis of the chicken genome using a 60K SNP BeadChip. Poultry Science, 2016, 95(8): 1750-1756. doi: 10.3382/ps/pew136 pmid: 27118864
[33]	YI G Q, QU L J, LIU J F, YAN Y Y, XU G Y, YANG N. Genome-wide patterns of copy number variation in the diversified chicken genomes using next-generation sequencing. BMC Genomics, 2014, 15(1): 962.
[34]	GORLA E, COZZI M C, PONCE S I R, RUIZ LÓPEZ F J, VEGA MURILLO V E, CEROLINI S, BAGNATO A, STRILLACCI M G. Genomic variability in Mexican chicken population using Copy Number Variation. International Journal of Health, Animal Science and Food Safety, 2017, 4(1s). doi.org/10.13130/2283-3927/8414.
[35]	WANG X F, NAHASHON S, FEASTER T K, BOHANNON- STEWART A, ADEFOPE N. An initial map of chromosomal segmental copy number variations in the chicken. BMC Genomics, 2010, 11(1): 351.
[36]	林燕, 黄敏, 李秀金, 张续勐, 黄运茂, 田允波, 伍仲平. 利用全基因组重测序数据检测8个鸭品种基因组拷贝数变异. 畜牧兽医学报, 2023: 1-12.
	LIN Y, HUANG M, LI X J, ZHANG X M, HUANG Y M, TIAN Y B, WU Z P. Uncovering genome-wide copy number variations in 8 duck breeds using whole genome resequencing data. Acta Veterinaria et Zootechnica Sinica, 2023: 1-12. (in Chinese)
[37]	XU Y X, HU J, FAN W L, LIU H H, ZHANG Y S, GUO Z B, HUANG W, LIU X L, HOU S S. Genome-wide association analysis reveals 6 copy number variations associated with the number of cervical vertebrae in Pekin ducks. Frontiers in Cell and Developmental Biology, 2022, 10: 1041088.
[38]	YI X, TAO Y, LIN X, DAI Y, YANG T L, YUE X J, JIANG X J, LI X Y, JIANG D S, ANDRADE K C, CHANG J. Histone methyltransferase Setd2 is critical for the proliferation and differentiation of myoblasts. Biochimica et Biophysica Acta (BBA) - Molecular Cell Research, 2017, 1864(4): 697-707.
[39]	HUGHES D, BAEHR L, SHARPLES A, WADDELL D, BODINE S. The effect of Akt-induced skeletal muscle hypertrophy on the UBR family of E3 ubiquitin ligases. Physiology, 2023, 38(S1): 5730427.
[40]	PEZESHKIAN Z, MIRHOSEINI S Z, GHOVVATI S. Identification of hub genes involved in apparent metabolizable energy of chickens. Animal Biotechnology, 2022, 33(2): 242-249.
[41]	MCGEE S L, HARGREAVES M. Histone modifications and skeletal muscle metabolic gene expression. Clinical and Experimental Pharmacology and Physiology, 2010, 37(3): 392-396. doi: 10.1111/j.1440-1681.2009.05311.x pmid: 19793100
[42]	李恒, 字向东, 王会, 熊燕, 吕明杰, 刘宇, 蒋旭东. 基于全基因组重测序的山羊产羔数性状关键调控基因的筛选. 中国农业科学, 2022, 55(23): 4753-4768. doi: 10.3864/j.issn.0578-1752.2022.23.015.
	LI H, ZI X D, WANG H, XIONG Y, LÜ M J, LIU Y, JIANG X D. Screening of key regulatory genes for litter size trait based on whole genome re-sequencing in goats(Capra hircus). Scientia Agricultura Sinica, 2022, 55(23): 4753-4768. doi: 10.3864/j.issn.0578-1752.2022.23.015. (in Chinese)
[43]	POWELL D R, DOREE D D, DACOSTA C M, PLATT K A, HANSEN G M, VAN SLIGTENHORST I, DING Z M, REVELLI J P, BROMMAGE R. Obesity of G2e3 knockout mice suggests that obesity-associated variants near human G2E3 decrease G2E3 activity. Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy, 2020, 13: 2641-2652.
[44]	RASHEED S, YAN J S, LAU A, CHAN A S. HIV replication enhances production of free fatty acids, low density lipoproteins and many key proteins involved in lipid metabolism: a proteomics study. PLoS ONE, 2008, 3(8): e3003.
[45]	YANG Z G, DONG P, CAO J K, LIN N, MA S Z, CAO R, CAI L, WANG L, CAO C C, XUE Y C, PAN J, LI X, WANG K, LIU Q W, LI C, GONG F X, FU X, XIAO R. NOVA1 prevents overactivation of the unfolded protein response and facilitates chromatin access during human white adipogenesis. Nucleic Acids Research, 2023, 51(13): 6981-6998.
[46]	PAN D N, MAO C X, QUATTROCHI B, FRIEDLINE R H, ZHU L J, JUNG D Y, KIM J K, LEWIS B, WANG Y X. MicroRNA-378 controls classical brown fat expansion to counteract obesity. Nature Communications, 2014, 5: 4725. doi: 10.1038/ncomms5725 pmid: 25145289
[47]	LEUNG-HAGESTEIJN C. Modulation of integrin signal transduction by ILKAP, a protein phosphatase 2C associating with the integrin- linked kinase, ILK1. The EMBO Journal, 2001, 20(9): 2160-2170.
[48]	CHRISTOU M A, NTZANI E E, KARASIK D. Genetic pleiotropy of bone-related phenotypes: insights from osteoporosis. Current Osteoporosis Reports, 2020, 18(5): 606-619.
[49]	LI C Y, WANG J P, SONG K, MENG J, XU F, LI L, ZHANG G F. Construction of a high-density genetic map and fine QTL mapping for growth and nutritional traits of Crassostrea gigas. BMC Genomics, 2018, 19(1): 626.
[50]	WU Y Y, LIU F, WAN R H, JIAO B Q. A novel SETD2 variant causing global development delay without overgrowth in a Chinese 3-year-old boy. Frontiers in Genetics, 2023, 14: 1153284.
[51]	VALIENTE A, LAFUENTE A, BERNARDO M. Systematic review of the Genomewide Association Studies (GWAS) in schizophrenia. Revista De Psiquiatría y Salud Mental (English Edition), 2011, 4(4): 218-227.
[52]	ZAIN S M, MOHAMED R, COOPER D N, RAZALI R, RAMPAL S, MAHADEVA S, CHAN W K, ANWAR A, ROSLI N S M, MAHFUDZ A S, et al. Genome-wide analysis of copy number variation identifies candidate gene loci associated with the progression of non-alcoholic fatty liver disease. PLoS ONE, 2014, 9(4): e95604.

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测定指标 Trait	观测数（只） Number	平均值 Mean	标准差 SD	最大值 Max	最小值 Min	变异系数 CV(%)
体重 Body weight (kg)	111	6.11	0.94	8.63	3.98	15.38
胸深Chest depth (cm)	111	11.74	0.54	13.46	10.64	4.63
胸宽Chest width (cm)	111	11.7	0.54	13.86	10.4	4.57
胫长Tibia length (cm)	111	10.27	0.41	11.39	9.21	3.99
体斜长Body oblique length (cm)	111	36.95	1.74	41.8	33.8	4.71
龙骨长Keel length (cm)	111	18.94	1.15	22.5	16.1	6.07
半潜水长Semi-diving length (cm)	111	63.79	3.85	73.9	59.8	6.04
胫围Tibia circumference (cm)	111	6.39	0.35	7.73	5.67	5.48
颈围Neck circumference (cm)	111	12.52	1.03	15.6	11.5	8.23
颈长Neck length (cm)	111	35.3	2.35	42.3	32.5	6.66

	类型 Type	数量（个） Number	平均长度（bp） Average length	长度中位数（bp） Median length	长度最小值（bp） Min length	长度最大值（bp） Max length
CNV	缺失Deletion	94560	8704	420	51	3588041
	重复Duplication	4598	76734	3389	88	4871547
	总体All	99158	11858	441	51	4871547
CNVR	缺失Deletion	5029	2015	265	51	3588041
	重复Duplication	110	12595	384	88	644201
	混合Mixed	86	299583	1614	153	6430879
	总体All	5225	7136	277	51	6430879

Identification of Copy Number Variation and Its Association with Body Weight and Size of Lion-Head Geese by Next-Generation Sequencing

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