小麦主栽品种济麦22与良星99的基因组序列多态性比较分析

doi:10.3724/SP.J.1006.2020.01009

作物学报 ›› 2020, Vol. 46 ›› Issue (12): 1870-1883.doi: 10.3724/SP.J.1006.2020.01009

• 作物遗传育种·种质资源·分子遗传学 • 上一篇下一篇

小麦主栽品种济麦22与良星99的基因组序列多态性比较分析

杨正钊(), 王梓豪, 胡兆荣, 辛明明, 姚颖垠, 彭惠茹, 尤明山, 宿振起^*(), 郭伟龙^*()

中国农业大学农学院 / 农业生物技术国家重点实验室 / 杂种优势研究与利用教育部重点实验室, 北京 100193

收稿日期:2020-01-15 接受日期:2020-06-02 出版日期:2020-08-10 发布日期:2020-11-25
通讯作者: 宿振起,郭伟龙
基金资助:
国家重点研发计划项目(2018YFD0100803);国家自然科学基金项目(31701415);中央高校基本科研业务费专项资助

Comparative analysis of the genomic sequences between commercial wheat varieties Jimai 22 and Liangxing 99

YANG Zheng-Zhao(), WANG Zi-Hao, HU Zhao-Rong, XIN Ming-Ming, YAO Ying-Yin, PENG Hui-Ru, YOU Ming-Shan, SU Zhen-Qi^*(), GUO Wei-Long^*()

College of Agronomy and Biotechnology / State Key Laboratory for Agrobiotechnology / Key Laboratory of Crop Heterosis and Utilization, Ministry of Education, China Agricultural University, Beijing 100193, China

Received:2020-01-15 Accepted:2020-06-02 Online:2020-08-10 Published:2020-11-25
Contact: SU Zhen-Qi,GUO Wei-Long
Supported by:
National Key Research and Development Program of China(2018YFD0100803);National Natural Science Foundation of China(31701415);Chinese Universities Scientific Fund.

摘要/Abstract

摘要：

济麦22和良星99是我国黄淮冬麦区和北部冬麦区大面积推广的高产小麦品种, 也是目前小麦杂交育种的重要亲本。虽然济麦22和良星99的来源和系谱不同, 但在重要农艺、产量等性状上存在较高的相似性。为了从全基因组水平研究其遗传组成的异同, 本研究采用Illumina HiSeq2500测序平台对上述两个品种进行了全基因组测序(平均测序深度为5.8×), 并系统地比较了两个品种拷贝数变异(CNV)、单核苷酸多态性(SNP)和插入/缺失(InDel)的序列差异。与中国春参考基因组序列相比, 两个品种除了具有总长466 Mb的共有CNV变异区间外, 济麦22和良星99的特有CNV变异区间的总长分别为91 Mb和45 Mb, 这些特有CNV区间主要集中在2B和4B染色体上; 济麦22和良星99间存在1,547,371个SNP差异位点和137,817个InDel差异位点。以差异SNP分布规律为依据, 在全基因组水平鉴定出济麦22和良星99间存在14.2%的差异多态性热点区间, 这些区间集中分布在1D、2B和4B染色体上。通过对5个控制小麦株高和穗长基因的序列分析, 发现有2个位于多态性热点区间的基因在品种间存在移码突变。本研究为利用重测序数据在基因组水平上比较小麦品种间遗传差异提供了重要参考, 同时揭示了济麦22和良星99在全基因组的遗传相似区间和差异区间, 为今后小麦育种改良中更好利用济麦22与良星99提供了重要遗传信息。

关键词: 小麦, 济麦22, 良星99, 全基因组重测序, SNP, CNV

Abstract:

Jimai 22 and Liangxing 99 are high-yield wheat varieties widely planted in the North Huang-Huai Rivers Valley Winter Wheat Zone and Northern Winter Wheat Zone in China, and are currently used as important parents in wheat breeding programs. Although the origins and pedigrees of Jimai 22 and Liangxing 99 are different, they are highly similar in many important agronomic traits, yield-associated traits, and so on. To identify the genomic differences between the two varieties, we performed whole-genome sequencing using the Illumina HiSeq2500 platform, with an average sequencing depth of 5.8×. We aligned the raw sequencing data against the Chinese Spring reference genome and identified the difference of copy-number variation (CNV) regions, single-nucleotide polymorphisms (SNPs) and InDels in sequence between the two varieties. Lengths of 466 Mb CNV intervals were shared by the two varieties. The lengths of cultivar-specific CNV intervals in Jimai 22 and Liangxing 99 were 91 Mb and 45 Mb, respectively, and these intervals are mainly located on chromosomes 2B and 4B. Beyond the CNV intervals, 1,547,371 SNPs and 137,817 InDels were different between the two cultivars. Based on the distribution of SNP densities in the intervals, we identified the polymorphic hotspot regions on chromosomes 1D, 2B, and 4B, making up 14.2% of the whole genome. The sequences of five previous cloned dwarf genes and spike length related genes were investigated, and two genes located in the polymorphic hotspot regions were detected with the frame shift variations. This study provides an important guidance for evaluating the genetic differences between two wheat varieties in the genomic level, and also identified both genetic similarity regions and polymorphic hotspot regions between Jimai 22 and Liangxing 99, which provided a valuable genetic information for future genetic improvement utilizing Jimai 22 and Liangxing 99 as parents.

Key words: wheat, Jimai 22, Liangxing 99, whole-genome resequencing, SNP, CNV

杨正钊, 王梓豪, 胡兆荣, 辛明明, 姚颖垠, 彭惠茹, 尤明山, 宿振起, 郭伟龙. 小麦主栽品种济麦22与良星99的基因组序列多态性比较分析[J]. 作物学报, 2020, 46(12): 1870-1883.

YANG Zheng-Zhao, WANG Zi-Hao, HU Zhao-Rong, XIN Ming-Ming, YAO Ying-Yin, PENG Hui-Ru, YOU Ming-Shan, SU Zhen-Qi, GUO Wei-Long. Comparative analysis of the genomic sequences between commercial wheat varieties Jimai 22 and Liangxing 99[J]. Acta Agronomica Sinica, 2020, 46(12): 1870-1883.

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引物编号 Primer ID	引物序列 Primer sequence (5'-3')	退火温度 Annealing temperature (℃)	用途 Purpose
TraesCS2D02G055700_F	CAGGTCGAGACAGAGAACAA	56	测序引物 Sequencing primers
TraesCS2D02G055700_R	ATCGAGCCCCTCAATTTCAT	58	CNV标记特异引物 Specific primers for CNV markers
TraesCS2D02G051500_F	TCAGCTCAGGGTTATCAAGC
TraesCS2D02G051500_R	TTGGGTGCATTTTTCAGTCC
2B_LX99_CNV1_F	AGCAGGTAATCCACACCAAA
2B_LX99_CNV1_R	TGGAGAACCCACTTATCCAA
2B_LX99_CNV2_F	AGCAGGTAATCCACACCAAA
2B_LX99_CNV2_R	AATCCACACCAAATCCCCAT
2B_COM_CNV_F	CACCCTAGATACAACCGAGG
2B_COM_CNV_R	ATGTCACCGATCTTCTGAGC
2D_COM_CNV_F	ATGATCACGATGGACCTAGC
2D_COM_CNV_R	TGCCACGAAGATTTAGAGGA

表型 Phenotype	济麦22 Jimai 22		良星99 Liangxing 99		差异显著性 Statistical significance of the difference
表型 Phenotype	均值±标准误差 Mean ± SE	样本量 Sample counts	均值±标准误差 Mean ± SE	样本量 Sample counts	P-value (t-test)
旗叶长Flag leaf length (cm)	16.78±0.36	30	16.94±0.40	30	0.76
旗叶宽Flag leaf width (cm)	1.88±0.024	30	1.85±0.039	30	0.53
每穗小穗数Spikelet number per spike	21.87±0.45	30	21.80±0.28	30	0.91
每穗可育小穗数Fertile spikelet per spike	21.23±0.50	30	21.17±0.14	30	1.00
每穗不育小穗数Infertile spikelet per spike	0.63±0.14	30	0.63±0.23	30	0.90
穗长Spike length (cm)	9.57±0.13	30	10.43±0.15	30	3.98E-5 ^**
株高Plant length (cm)	75.05±0.57	30	80.23±0.75	30	1.90E-6 ^**
穗粒数Grain number per spike	52.23±0.73	30	55.20±0.35	30	0.31
千粒重Thousand seed weight (g)	49.20±0.33	6	48.30±0.03	6	0.66
粒长Grain length (cm)	6.43±0.07	6	6.53±0.03	6	0.39
粒宽Grain width (cm)	3.25±0.06	6	3.30±0.02	6	0.58

基因组 Genome	济麦22中的纯合 SNP个数 Number of homozygous SNPs in Jimai 22	良星99中的纯合 SNP个数 Number of homozygous SNPs in Liangxing 99	两者基因型相同的纯合SNP个数 Number of homozygous SNPs with the same genotype	两者基因型不同的纯合 SNP个数 Number of homozygous SNPs with different genotypes
A	6,405,063	6,395,080	6,194,047	301,206
B	8,033,789	7,781,369	7,248,448	1,148,764
D	887,462	883,555	818,951	97,401
全基因组 Whole genome	15,326,314	15,060,004	14,261,446	1,547,371

基因组 Genome	济麦22中的纯合 InDel个数 Number of homozygous InDels in Jimai 22	良星99中的纯合 InDel个数 Number of homozygous InDels in Liangxing 99	两者基因型相同的纯合InDel个数 Number of homozygous InDels with the same genotype	两者基因型不同的纯合 InDel个数 Number of homozygous InDels with different genotypes
A	464,369	459,599	438,410	28,732
B	562,658	543,395	492,112	95,316
D	116,485	115,570	104,345	13,769
全基因组Whole genome	1,143,512	1,118,564	1,034,867	137,817

基因组 Genome	济麦22的特有CNV区间 Specific CNV region in Jimai 22		良星99的特有CNV区间 Specific CNV region in Liangxing 99		两品种的共有CNV区间 Common CNV regions in the two cultivars
基因组 Genome	长度 Length (Mb)	%	长度 Length (Mb)	%	长度 Length (Mb)	%
A	8	0.06	4	0.03	135	0.96
B	80	0.57	33	0.23	226	1.61
D	3	0.02	8	0.06	105	0.75
全基因组Whole genome	91	0.65	45	0.32	466	3.31

小麦主栽品种济麦22与良星99的基因组序列多态性比较分析

Comparative analysis of the genomic sequences between commercial wheat varieties Jimai 22 and Liangxing 99

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SNP突变类型 Types of SNP mutations	多态性热点区间 Differential genetic region		相似区间 Similar genetic region		全基因组 Whole genome region
SNP突变类型 Types of SNP mutations	数量 Counts	每Mb密度 Density per Mb	数量 Counts	每Mb密度 Density per Mb	数量 Counts	每Mb密度 Density per Mb
T>A	33,545	17.52	1701	0.15	35,246	2.62
A>T	33,868	17.69	1713	0.15	35,581	2.64
G>C	49,065	25.62	2020	0.17	51,085	3.79
C>G	49,521	25.86	1956	0.17	51,477	3.82
A>C	47,712	24.91	2089	0.18	49,801	3.70
T>G	47,862	24.99	1888	0.16	49,750	3.69
G>T	65,670	34.29	3204	0.28	68,874	5.11
C>A	66,047	34.49	3226	0.28	69,273	5.14
A>G	200,697	104.80	6364	0.55	207,061	15.37
T>C	201,236	105.08	6540	0.57	207,776	15.42
G>A	289,933	151.40	11,276	0.98	301,209	22.36
C>T	290,292	151.59	11,151	0.96	301,443	22.38
转换Transition	982,158	512.88	35,331	3.06	1,017,489	75.53
颠换Transversion	393,290	205.37	17,797	1.54	411,087	30.51
全部Total	1,375,448	718.25	53,128	4.60	1,428,576	106.04

InDel类型 Types of InDel	InDel长度 Length of InDel	差异区间 Differential genetic region		相似区间 Similar genetic region		全基因组 Whole genome region
InDel类型 Types of InDel	InDel长度 Length of InDel	数量 Count	每Mb密度 Density per Mb	数量 Count	每Mb密度 Density per Mb	数量 Count	每Mb密度 Density per Mb
在济麦22中插入, 在良星99中丢失 Insertion in Jimai 22, deletion in Liangxing 99	1	34,031	17.77	7723	0.67	41,754	3.10
	2	7259	3.79	3017	0.26	10,276	0.76
	3	2664	1.39	1242	0.11	3906	0.29
	4	1685	0.88	843	0.07	2528	0.19
	5	701	0.37	419	0.04	1120	0.08
	6	883	0.46	370	0.03	1253	0.09
	7	453	0.24	225	0.02	678	0.05
	8	476	0.25	216	0.02	692	0.05
	9	363	0.19	153	0.01	516	0.04
	≥10	4131	2.16	1599	0.14	5730	0.43
	全部Total	52,646	27.49	15,807	1.37	68,453	5.08
在良星99中插入, 在济麦22中丢失 Insertion in Liangxing 99, deletion in Jimai 22	1	34,083	17.80	7796	0.67	41,879	3.11
	2	7315	3.82	3037	0.26	10,352	0.77
	3	2690	1.40	1190	0.10	3880	0.29
	4	1710	0.89	785	0.07	2495	0.19
	5	746	0.39	420	0.04	1166	0.09
	6	832	0.43	356	0.03	1188	0.09
	7	412	0.22	227	0.02	639	0.05
	8	509	0.27	208	0.02	717	0.05
	9	402	0.21	183	0.02	585	0.04
	≥10	3993	2.09	1637	0.14	5630	0.42
	全部Total	52,696	27.52	15,835	1.37	68,531	5.09

变异所在区间 Region of variations	错义突变 Missense mutation		同义突变 Synonymous mutation		移码突变 Frame-shift mutation		提前终止突变 Stop-gained mutation		终止子丢失突变 Stop-lost mutation
变异所在区间 Region of variations	数量 Count	%	数量 Count	%	数量 Count	%	数量 Count	%	数量 Count	%
差异区间Different region	2981	51.3	2431	41.9	304	5.2	68	1.2	16	0.3
相似区间Similar region	348	44.7	330	42.4	94	12.1	6	0.8	0	0
全部Total	3329	50.6	2761	42.0	398	6.1	74	1.1	16	0.2

株高基因/QTL Plant height gene/QTL	基因编号 Gene ID	染色体 Chromosome	区间 Region	基因功能注释 Function annotation	序列差异类型 Variation type
Rht-B1	TraesCS4B02G043100	4B	多态性热点区间 Polymorphic hotspot regions	编码DELLA蛋白 DELLA protein-coding gene	无 None
Rht-D1	TraesCS4D02G040400	4D	相似区间 Genetic similar region	编码DELLA蛋白 DELLA protein-coding gene	无 None
Ppd-D1	TraesCS2D02G079600	2D	相似区间 Genetic similar region	编码PRRs蛋白 PRRs protein-coding gene	无 None
QPht/Sl.cau-2D.1	TraesCS2D02G051500	2D	多态性热点区间 Polymorphic hotspot regions	编码WRKY转录因子 WRKY transcription factor protein-coding gene	InDel
QPht/Sl.cau-2D.1	TraesCS2D02G055700	2D	多态性热点区间 Polymorphic hotspot regions	编码GRAS转录因子 GRAS transcription factor protein-coding gene	InDel, SNP

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