彭强^,**, 李佳丽^,**, 张大双^**, 姜雪^**, 邓茹月^**, 吴健强^**, 朱速松^,*贵州省农业科学院水稻研究所, 贵州贵阳 550006

QTL Mapping for Rice Appearance Quality Traits Based on a High-density Genetic Map in Different Environments

PENG Qiang^,**, LI Jia-Li^,**, ZHANG Da-Shuang^**, JIANG Xue^**, DENG Ru-Yue^**, WU Jian-Qiang^**, ZHU Su-Song^,*Guizhou Rice Research Institute, Guizhou Academy of Agricultural Sciences, Guiyang 550006, Guizhou, China

通讯作者: *^* 通信作者(Corresponding authors): 朱速松, E-mail: susongzhu@139.com, Tel: 0851-83762727 ;^** 同等贡献(Contributed equally to this work)

第一联系人: 第一作者联系方式: 彭强, E-mail: 450058876@163.com, Tel: 0851-83762727; 李佳丽, E-mail: lilylijiali@163.com, Tel: 0851-82285571
收稿日期:2018-03-14接受日期:2018-06-12网络出版日期:2018-06-19

基金资助:

贵州省科技支撑计划项目(黔科合支撑[2018]2298号). 贵州省科研机构服务企业行动计划项目(黔科合服企[2014]4005号). 贵州省科技计划项目(黔科合平台人才[2017]5719号). 贵州省现代产业体系项目.GZCYTX2017-0602 贵州省农业科学院青年基金项目(黔农科院青年基金[2018]18号)资助.

Received:2018-03-14Accepted:2018-06-12Online:2018-06-19

Fund supported:

the Science and Technology Support Project of Guizhou Province (QKHZC20182298). the Research Institution Service Enterprise Action Plan Project of Guizhou Province (QKHFQ20144005). the Science and Technology Plan Project of Guizhou Province (QKHPTRC20175719). the Modern Industry System Project of Guizhou Province.GZCYTX2017-0602 the Youth Fund Project of Guizhou Academy of Agricultural Sciences (QNKYQN201818)..

摘要
为解析稻米外观品质遗传基础, 挖掘稳定存在的控制稻米外观品质性状的QTL, 本研究以籼稻品种V20B和爪哇稻品种CPSLO17作为亲本, 构建包含150个重组自交家系(recombinantion inbred line, RIL)的RIL作图群体, 进行外观品质性状QTL定位分析。利用特定位点扩增长度测序(SLAF-seq)技术, 构建了一个由12个连锁群包含8602个标记, 平均间距为0.29 cM的高密度遗传图谱。采用IciMapping 4.0软件的ICIM-ADD方法在3种环境(贵阳、贵定、三亚)对4个外观品质性状(粒长、粒宽、垩白度和垩白粒率)进行QTL (quantitative trait locus)定位分析。结果表明: 3种环境共检测到9个粒长QTL、6个粒宽QTL、3个垩白度QTL和4个垩白粒率QTL; 有5个QTL在多个环境被重复检测到, 其中3种环境都定位到的粒宽QTL qGW5-1和垩白度QTL qCha5-1为同一定位区间(第5染色体的Marker1642127-Marker1514505); 此外, 垩白度QTL qCha5-2的定位区间(Marker1554573-Marker1554589)和垩白粒率QTL qCGP5-2也是一样的。序列比对发现QTL qCha5-1定位区间仅51.5 kb, 是新的垩白性状主效QTL。本研究结果不仅为挖掘新的外观品质性状基因奠定基础, 也有助于开发新的分子标记进行水稻外观品质性状遗传改良。
关键词： 水稻;外观品质;QTL;高密度遗传图谱;高通量测序

Abstract
To analyze the genetic basis of appearance quality of rice, explore QTL which controlled rice appearance quality related traits stably existing, a mapping population of 150 lines (recombination inbred lines, RIL), derived from a cross between rice varieties V20B and CPSLO17, was applied to analysis QTL location of appearance quality trait. The specific locus amplified fragment sequencing (SLAF-seq) technology was employed to construct a high-density genetic map in rice (Oryza sativa L.). A genetic map included 8602 markers on the 12 linkage groups was successfully constructed, which with an average distance of 0.29 cM between adjacent markers. The ICIM-ADD method of IciMapping 4.0 software was used to analyze QTL location for four appearance quality traits, including grain length (GL), grain width (GW), chalky grain rate, and chalkiness degree in three environmental conditions (Guiyang, Guiding, and Sanya). A total of nine QTLs for grain length (GL), six QTLs for grain width (GW), four QTLs for chalkiness size, three QTLs for chalkiness degree traits were detested in three environments. Five QTLs were repeatedly detected in multiple environments, of which the QTL qGW5-1 and qCha5-1 with the same localization interval (Marker1642127-Marker1514505 on chromosome 5) were repeatedly located in all three environments. In addition, the positioning interval of chalkiness QTL qCha5-2 (Marker1554573-Marker1554589) is the same as the chalkiness size QTL qCGP5-2. The sequence alignment found that the location interval of QTL qCha5-1 was only 51.5 kb, which was a new main effect QTL for chalkiness trait. These results lay the foundation for further exploiting candidate gene of appearance quality, which also contribute to the development of new molecular markers for rice appearance quality traits genetic improvement.
Keywords：rice;appearance quality;QTL;high-density genetic map;high throughput sequencing


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本文引用格式
彭强, 李佳丽, 张大双, 姜雪, 邓茹月, 吴健强, 朱速松. 不同环境基于高密度遗传图谱的稻米外观品质QTL定位[J]. 作物学报, 2018, 44(8): 1248-1255. doi:10.3724/SP.J.1006.2018.01248
PENG Qiang, LI Jia-Li, ZHANG Da-Shuang, JIANG Xue, DENG Ru-Yue, WU Jian-Qiang, ZHU Su-Song. QTL Mapping for Rice Appearance Quality Traits Based on a High-density Genetic Map in Different Environments[J]. Acta Crops Sinica, 2018, 44(8): 1248-1255. doi:10.3724/SP.J.1006.2018.01248


近年来, 随着人们对优质稻米的需求越来越多, 如何改善我国稻米品质, 选育出适应市场需求的优质稻新品种, 是水稻育种家们进行基础研究和遗传改良的首要解决问题。外观品质是稻米品质性状最重要的评价指标和构成因素, 严重影响稻米的蒸煮食味品质和营养品质, 如高垩白米饭粒的蓬松性差, 食味口感也差^[1,2]。因此, 进行稻米外观品质的遗传基础研究, 对稻米品质遗传改良和优质水稻品种选育具有重要的理论价值和实际意义。

粒形和垩白是衡量稻米外观品质的重要指标, 也是中国水稻品种审定时稻米品质的定级指标^[3,4]。得益于水稻全基因组学的快速发展和新型分子标记的开发, ****们利用不同类型遗传群体(BIL、RIL、DH、IL等)定位到大量的粒形和垩白性状QTL^[5,6,7]。其中, 粒长基因GS3^[8,9]、粒宽基因qSW5/GW5^[10,11]及多个粒形调控基因(GS2/GL2^[12,13]、GW2^[14]、GL7/GW7^[15,16]、GW8^[17]等)被相继分离克隆; 虽然也有很多的垩白性状QTL^{[18,19,20,21]}被检测到, 但只有少数QTL (如qPGWC-7^[22]、qPGWC-8^[23]和qACE9^[24])被精细定位, Chalk5^[25]基因是被成功分离克隆的垩白主效QTL。由于粒形和垩白性状都是多基因控制的数量遗传性状, 且受制于传统分子标记(SSR、InDel、RFLP等)构建的水稻连锁图谱存在标记数量少和覆盖密度低等缺陷, 仍有很多遗漏的粒形和垩白性状QTL未被定位到^[26]。因此, 开发遗传稳定性高、分布广、数量多的SNP标记和构建高密度遗传图谱进行QTL定位分析越来越受到****们的青睐。SLAF-seq技术是一种基于RRGS策略和高通量pair- end sequencing的大规模开发SNP及其基因型鉴定的新技术, 已应用于多个物种的遗传连锁图谱构建和QTL定位^[27,28,29]。

亲本间遗传背景多样性是开发多态性分子标记的前提基础, 有助于挖掘新的粒形和垩白性状QTL。目前水稻遗传连锁图谱主要是籼籼交、籼粳交等遗传背景, 鲜有用籼爪交遗传背景绘制高密度遗传连锁图谱的报道。本研究利用籼爪交遗传背景材料(V20B/CPSLO17)创建高代RIL群体, 在不同环境(贵阳、贵定和三亚)下测定RIL群体的稻米外观品质, 借助SLAF-seq技术开发的多态性SLAF标签和构建的高密度遗传连锁图谱, 进行水稻外观品质性状QTL定位分析, 鉴定出受环境影响小、遗传稳定、贡献率高的稻米粒形和垩白性状主效QTL, 为挖掘新的水稻外观品质性状基因奠定理论基础, 也为开发新的分子标记进行水稻外观品质性状遗传改良提供科学依据。

1 材料与方法

1.1 试验材料

本研究使用的遗传群体是以籼型水稻品种V20B为母本, 爪哇稻品种CPSLO17为父本, 杂交得F₁代, 在贵州贵阳和海南三亚多年自交种植, 采用单粒传法于贵州贵阳获得150份F₁₀代重组自交系(recombinant inbred line, RIL)群体材料。

1.2 田间试验及表型数据测定

于2014年至2016年在贵州贵阳、贵州贵定和海南三亚三地试验田对亲本和RIL群体进行种植, 每个材料种植20株, 成熟时混收, 晾干保存, 共收2份亲本和150份RIL材料。对于每份供试样品表型数据测定如下: 随机挑选50粒整精米置于玻璃板上, 目测挑选出有阴影的米粒, 并记录米粒数量, 计算出该样品的垩白粒率(%); 随机挑选10粒有垩白的米粒, 逐粒目测垩白面积占整个米粒面积的百分率并取平均值, 即为该样品的垩白大小; 该样品的垩白度(%)为垩白粒率(%)与垩白大小的乘积; 随机挑取10粒饱满的种子, 纵向或横向排列, 摆成一排, 不重叠, 不留隙, 用电子游标卡尺测量10粒种子总长度和总宽度, 重复3次取平均值, 计算粒长和粒宽。

1.3 叶片DNA提取

在植株八叶期对RIL群体分家系混取成熟叶片组织, 采用 CTAB 法提取基因组 DNA。加800 μL 1.5×CTAB研磨叶片; 65℃水浴30 min; 加800 μL氯仿/异戊醇(24:1, v/v); 12 000 r min^-1离心8 min; 吸400 μL上清液至新管, 加800 μL 95%乙醇, 混匀, -20℃冷冻20 min; 12 000转 min^-1离心10 min; 弃上清, 加500 μL 75%乙醇洗DNA沉淀, 8000 r min^-1离心5 min; 弃上清, 吹干, 加150 μL ddH₂O溶解即可。

1.4 高密度遗传连锁图谱的构建

参考日本晴(Oryza sativa L. japonica)基因组采用Hae III酶切基因组DNA, 经过3°端加A处理、连接测序接头Dual-index^[30]、PCR扩增、纯化、混样等步骤构建SLAF文库(264~314 bp的DNA片段); 再基于Illumina HiSeq 2500平台(Illumina, Inc., San Diego, CA, USA)高通量测序, 在基因组范围内筛选多态性SLAP标记。参照Sun等^[27]的方法进行SLAF-seq数据分析和基因型编码(RIL群体的分离方式为aa×bb); 根据高质量SLAF标签间的mLOD值进行连锁分群, 采用HighMap软件^[31]的最大似然估计法构建高密度遗传图谱。

1.5 QTL定位

采用 IciMapping 4.0进行稻米外观品质性状QTL定位分析。所需要的文件格式按Manual的要求编辑。完备区间作图(ICIM)法对RIL群体的稻米外观品质性状进行QTL作图及遗传效应分析, 作图步长为1.00 cM, PIN设置为0.001, LOD阈值设置为 3.0。并计算每个QTL对稻米外观品质性状的贡献率和加性效应, QTL的命名遵循McCouch原则。加性效应为正值表示增效等位基因来源于高垩白亲本V20B, 为负值表示来源于低垩白亲本CPSLO17。

2 结果与分析

2.1 稻米外观品质性状的表型分析

150份V20B/CPSLO17 RIL群体种植于3个不同环境(贵阳、贵定、三亚), 每份材料收种保存3个月后进行稻米垩白粒率、垩白度、粒长和粒宽性状考种。3种种植环境(贵阳、贵定、三亚)下150份RIL家系的稻米外观品质检测结果表明, RIL群体中4个外观品质性状(垩白粒率、垩白度、粒长和粒宽)都表现出连续变异(图1), 说明水稻的垩白和粒形性状表现出受多基因控制的数量性状遗传特征。

图1

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图13种环境下RIL群体中稻米外观品质性状分布

GL: 粒长; GW: 粒宽; CGP: 垩白粒率。
Fig. 1Frequency distributions of the appearance quality traits in the RIL population under three environments

GL: grain length; GW: grain width; CGP: chalky grain percentage.


两个亲本和150份RIL群体在3种种植环境(贵阳、贵定、三亚)下外观品质性状表型数据如表1所示。表型数据表明, V20B和CPSLO17两个亲本间在垩白度和垩白粒率上的差异较大, 在粒长、粒宽上也存在差异, V20B在垩白度、垩白粒率、粒宽上为高值亲本, CPSLO17在粒长上为高值亲本。RIL群体中稻米粒形性状在3个不同生态地点变化不明显, 而稻米垩白性状在3个不同生态地点变化明显, 说明垩白易受环境影响。

Table 1
表1
表1RIL群体在3个环境下的外观品质性状表现
Table 1Performance of appearance quality traits in RIL populations under three environments

性状 Trait	环境 Environment	亲本 Parents		均值 Mean	幅度 Variance	标准误 SE	偏度 Skewness	峰度 Kurtosis	W-test	P-value
		V20B	CPSLO17
粒长 Grian length (mm)	贵州贵阳 Guiyang, Guizhou	6.9317	7.5079	7.1104	0.3837	0.6194	0.2445	-0.4229	0.9770	0
	贵州贵定 Guiding, Guizhou	6.8986	7.4041	7.0370	0.3853	0.6207	-0.0375	0.2419	0.9885	0
	海南三亚 Sanya, Hainan	6.8264	7.6673	7.0589	0.3469	0.589	0.1212	-0.6511	0.9725	0
粒宽 Grain width (mm)	贵州贵阳 Guiyang, Guizhou	2.7864	1.9939	2.4299	0.0383	0.1956	-0.005	0.1085	0.9844	0
	贵州贵定 Guiding, Guizhou	2.8194	2.1133	2.4330	0.0305	0.1746	-0.4667	-0.2171	0.9588	0
	海南三亚 Sanya, Hainan	2.9044	2.1920	2.5347	0.0341	0.1846	-0.3713	-0.3784	0.9602	0
垩白度 Chalkiness (%)	贵州贵阳 Guiyang, Guizhou	23.0488	0	9.0864	81.8183	9.0453	1.0115	0.5006	0.8656	0.2495
	贵州贵定 Guiding, Guizhou	23.4848	0	6.0706	54.2400	7.3648	1.5925	2.0456	0.7781	0.8978
	海南三亚 Sanya, Hainan	23.4286	0	8.9570	74.5756	8.6357	1.0951	0.8017	0.8732	0.0977
垩白粒率 Chalky grain percentage (%)	贵州贵阳 Guiyang, Guizhou	26.2500	0	14.5078	90.7359	9.5255	0.6304	1.1792	0.9337	0.6898
	贵州贵定 Guiding, Guizhou	25.0000	0	10.6941	78.7201	8.8724	0.7583	-0.0918	0.8983	0.0019
	海南三亚 Sanya, Hainan	25.6250	0	11.9539	71.8795	8.4782	0.7945	0.7856	0.9134	0.0030

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2.2 高密度遗传图谱构建

以水稻品种V20B/CPSLO17组合衍生的150份重组自交家系作为作图群体, 利用特定位点扩增长度测序(SLAF-seq)技术开发SLAF标签。高通量测序结果表明, V20B亲本的SLAF数为58 473, 平均测序深度为49.41×; CPSLO17亲本的SLAF 数为51 837, 平均测序深度为53.25×; SLAF标签亲本平均测序深度为51.21× (表2)。本文共开发67 017个高质量SLAF标签, 其中15 853个SLAF亲本间有多态性, 符合aa×bb基因分离类型的有效标签为13 275个, 占比19.81%; 达到绘制高质量遗传图谱要求(测序深度10 ×以上, 亲本纯合)的高质量多态性SLAF标签为8657个, 占比12.92%。

Table 2
表2
表2亲本的SLAF数量及其覆盖深度
Table 2Coverage and number of markers for parents

样品 Sample	SLAF数量 SLAF number	读取数 Reads number	平均深度 Average depth (×)
V20B	58473	2889072	49.41
CPSLO17	51837	2760145	53.25
合计 Total	110310	193277	51.21

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采用HighMap软件的最大似然估计法成功构建了一个包含12个连锁群, 总图距为2508.65 cM, 8602个上图标记, 标记间平均距离为0.29 cM的高密度遗传图谱(表3)。Chr.1连锁图上图SLAF标记数最多(1334个), 图距也最长(365.11 cM), 标记间平均距离为0.27 cM; Chr. 8连锁图上图SLAF标记数最少(386个); Chr.10连锁图的图距最短, 仅103.98 cM, 上图504个SLAF, 标记间平均距离为0.21 cM; SLAF标记间最大距离为10.5 cM, 位于Chr.3连锁图; 12个连锁图的SLAF标记平均间距最低为Chr.5连锁图的0.21 cM, 最高为Chr.3连锁图的0.60 cM (表3)。该图谱可用于重要农艺性状QTL定位。

Table 3
表3
表312连锁群基本信息统计
Table 3Description on basic characteristics of the 12 linkage groups

染色体 Chr.	长度 Length (cM)	标记数量 Marker number	标记间距 Marker interval (cM)		Spearman相关系数? Spearman correlation coefficient ?
			平均值 Mean	最大值 Max
1	365.11	1334	0.27	2.45	0.9996
2	184.38	818	0.23	6.00	0.9999
3	262.99	438	0.60	10.50	0.9995
4	241.09	908	0.27	3.67	0.9956
5	105.26	504	0.21	3.36	0.9996
6	363.05	1028	0.35	2.91	0.9900
7	149.03	817	0.18	3.09	0.9831
8	157.91	386	0.41	3.58	0.9996
9	130.07	525	0.25	7.04	0.9632
10	103.98	415	0.25	4.92	0.9791
11	245.23	782	0.31	2.82	0.9913
12	200.54	647	0.31	4.83	0.9978
合计 Total	2508.65	8602	0.29	10.50

^? Spearman correlation coefficient. The coefficient closed to 1 means the better the collinearity.
^? Spearman相关系数, 系数越接近于1, 表示共线性越好。

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2.3 RIL群体中的QTL定位分析

利用软件IciMapping 4.0的ICIM-ADD方法对水稻外观品质性状进行QTL分析, 结果表明, 在3种不同的种植环境(贵阳、贵定、三亚)中共检测到22个控制水稻粒长、粒宽、垩白度、垩白粒率4个性状的QTL (图2和表4), 分布在除了第6、第9染色体以外的其他染色体上, 3种环境下检测到的水稻外观品质性状QTL在高密度遗传图谱上的位置如图2所示。

图2

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图2稻米外观品质性状的QTL在遗传图谱上的分布

Fig. 2Distributions of identified QTL for rice appearance quality traits on genetic linkage maps



Table 4
表4
表4不同环境下稻米外观品质性状QTL分析
Table 4QTL analysis of appearance quality traits under different environments

性状 Trait	环境Environments	基因座 QTL	染色体 Chr.	位置 Position (cM)	标记区间 Marker interval	LOD	表型贡献率PVE (%)	加性效应 Add.
粒长 Grain length	贵州贵阳Guiyang, Guizhou	qGL1-2	1	361	Marker693317-Marker532394	4.13	5.87	-0.1498
		qGL3-1	3	60	Marker910209-Marker823024	5.25	7.28	0.1693
		qGL3-3	3	127	Marker891931-Marker771788	4.03	5.42	0.1466
		qGL7-1	7	118	Marker275670-Marker347375	4.85	6.95	-0.1628
		qGL8-1	8	115	Marker201080-Marker118092	17.97	31.18	0.3496
		qGL8-2	8	119	Marker191958-Marker143502	7.88	11.87	-0.2175
		qGL10-1	10	19	Marker34448-Marker23092	9.60	15.71	0.2592
	贵州贵定Guiding,Guizhou	qGL1-1	1	266	Marker587391-Marker688101	3.91	10.15	-0.1972
		qGL3-2	3	63	Marker922818-Marker757283	5.08	13.38	0.2283
	海南三亚 Sanya, Hainan	qGL1-2	1	361	Marker693317-Marker532394	3.05	8.10	-0.1673
		qGL3-1	3	60	Marker910209-Marker823024	3.79	10.22	0.1908
粒宽 Grain width	贵州贵阳Guiyang, Guizhou	qGW5-1	5	27	Marker1642127-Marker1514505	14.34	28.66	0.1051
		qGW7-2	7	114	Marker343862-Marker239518	6.18	10.49	0.0632
		qGW11-2	11	120	Marker1741595-Marker1645826	4.45	7.81	0.0545
	贵州贵定Guiding, Guizhou	qGW5-1	5	27	Marker1642127-Marker1514505	8.46	16.96	0.0721
		qGW7-1	7	106	Marker322410-Marker237275	6.83	13.24	0.0638
	海南三亚 Sanya, Hainan	qGW5-1	5	27	Marker1642127-Marker1514505	5.84	12.59	0.0657
		qGW11-1	11	114	Marker1750082-Marker1683589	4.34	8.93	0.0550
		qGW12-1	12	71	Marker1486720-Marker1380718	4.09	8.88	-0.0567
垩白度Chalkiness	贵州贵阳Guiyang, Guizhou	qCha5-1	5	27	Marker1642127-Marker1514505	4.69	12.63	0.0322
	贵州贵定Guiding, Guizhou	qCha5-1	5	27	Marker1642127-Marker1514505	5.05	14.77	0.0284
	海南三亚 Sanya, Hainan	qCha4-1	4	147	Marker403659-Marker472670	3.98	7.71	0.0241
		qCha5-1	5	27	Marker1642127-Marker1514505	8.55	17.83	0.0366
		qCha5-2	5	102	Marker1554573-Marker1554589	3.75	7.46	0.0241
垩白粒率Chalky grain percentage	贵州贵阳Guiyang, Guizhou	qCGP2-1	2	1	Marker1152260-Marker1135261	3.91	9.95	2.9960
		qCGP5-2	5	102	Marker1554573-Marker1554589	3.42	9.15	2.9475
	海南三亚 Sanya, Hainan	qCGP4-1	4	149	Marker472670-Marker400717	5.01	10.66	2.7694
		qCGP5-1	5	25	Marker1611496-Marker1557594	5.82	12.50	3.0122
		qCGP5-2	5	102	Marker1554573-Marker1554589	5.28	11.15	2.8968

GL: grian length; GW: grain width; Cha: chalkiness; CGP: chalky grain percentage; PVE: percentage of variance explained; Add: additive effect.

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3个地点共检测到9个控制粒长的QTL, 分布在第1、第3、第7、第8和第10染色体上, LOD值在3.05~17.97之间, 单个QTL的表型贡献率(percentage of variance explained, PVE)变幅为5.42%~31.18% (表4)。其中贵阳检测到7个QTL, 贵定检测到2个QTL, 三亚检测到2个QTL, 只有qGL1-2和qGL3-1在贵阳和三亚2个环境被重复检测到, 其余均为单一环境检测, 而效应较大的QTL qGL8-1分布在第8染色体Marker201080-Marker118092区间内, 其LOD值为17.97, 表型贡献率31.18%。

3个地点共检测到6个控制粒宽的QTL, 分布在第5、第7、第11和第12染色体上, LOD 值在4.09~14.34之间, 单个QTL的表型贡献率变幅为7.81%~28.66% (表4)。其中贵阳检测到3个QTL, 贵定检测到2个QTL, 三亚检测到3个QTL, 而定位于第5染色体Marker1642127- Marker1514505区间内的qGW5-1在三亚、贵阳和贵定3个环境中被反复检测到, 且对应的LOD值(14.34、8.46和5.84)和表型贡献率(28.66%、16.96%和12.59%)都比较高(表4)。

3个地点共检测到3个控制垩白度的QTL, 分布在第4和第5染色体上, LOD 值在3.75~8.55之间, 单个QTL的表型贡献率变幅为7.46%~17.83% (表4)。其中贵阳检测到1个QTL, 贵定检测到1个QTL, 三亚检测到3个QTL, 而3种环境(贵阳、贵定、三亚)都稳定检测到位于第5染色体Marker1642127-Marker1514505区间内的qCha5-1, 且对应的LOD值(4.69、5.05和8.55)和表型贡献率(12.63%、14.77%和17.83%)都比较高(表4)。

控制垩白粒率的QTL仅在贵阳和三亚2个地点检测到4个, 贵定没有检测到, 分布在第2、第4和第5染色体上, LOD 值在3.42~5.82之间, 单个QTL的表型贡献率变幅为9.15%~12.50% (表4)。其中贵阳检测到2个QTL, 三亚检测到3个QTL, 而qCGP5-2在三亚和贵阳2个环境中被同时检测到, 且对应的LOD 值为3.42和5.28, 对应的表型贡献率为9.15%和11.15%。

对定位结果分析发现, 在第5染色体上存在2个同时控制2个外观品质性状的定位区间, 其中粒宽QTL qGW5-1和垩白度QTL qCha5-1都定位于Marker1642127- Marker1514505区间内, 而控制垩白度的QTL qCha5-2和控制垩白度的QTL qCGP5-2都分布在Marker1554573- Marker1554589区间内。

3 讨论

通过多种不同环境对同一作图群体进行QTL定位, 选择受环境影响小、遗传稳定、贡献率高的QTL来改良作物的某些性状的研究思路越来越受到研究人员的关注, 而且稻米外观品质性状受环境条件的影响较大, 因此在不同生态环境下进行水稻外观品质性状的QTL定位分析, 获得稳定表达的外观品质性状主效QTL, 具有重要的理论研究和实践利用价值。

本文利用亲本V20B和CPSLO17构建的RIL群体, 借助SLAF-seq技术构建的高密度遗传图谱(8602个上图标记, 总图距为2508.65 cM, 标记间平均距离为0.29 cM), 在3种环境(贵阳、贵定、三亚)共检测到22个水稻外观品质(粒长、粒宽、垩白度和垩白粒率)性状QTL。5个QTL (qGW5-1、qCha5-1、qCGP5-2、qGL1-2和qGL3-1)被多个环境重复检测到, 其中qGW5-1和qCha5-1在贵阳、贵定、三亚3种环境被反复检测到, 且对应的LOD值和表型贡献率都比较高, 这表明粒宽QTL qGW5-1和垩白度QTL qCha5-1是受环境影响小、遗传稳定、贡献率高的主效QTL。此外, qGW5-1和qCha5-1都位于第5染色体Marker1642127-Marker1514505区间, 说明qGW5-1和qCha5-1之间可能受同一QTL或基因调控, 具有“一因多效”遗传效应, 也可能是两个独立基因的紧密连锁, 这需后续的精细定位和基因功能验证来确认。2个粒长QTL (qGL1-2和qGL3-1)和垩白粒率QTL qCGP5-2都是在贵阳和三亚被同时检测到, 而qCGP5-2与垩白度QTL qCha5-2的定位区间一样, 都位于第5染色体Marker1554573- Marker1554589区间, 表明垩白粒率与垩白度性状QTL存在紧密连锁, 可能受同一QTL或基因调控。

研究表明, 水稻的第5染色体上垩白主效基因(Chalk5)与粒宽基因(GS5, GW5/qSW5)紧密连锁, 而且通常宽粒的籼稻普遍是高垩白, 因此在育种实践中很难实现增加粒宽的同时减少垩白。利用SLAF标签Marker1642127和Marker1514505序列在NCBI网站进行blast比对, 以Nipponbare (Oryza sativa japonica)基因组序列作为参照, 发现QTL qCha5-1定位在51.5 kb区间内。在RGAP 7网站检索发现该51.5 kb区间仅包含5个候选基因, 且都不是已知的垩白Chalk5基因(LOC_Os05g 06480), 说明QTL qCha5-1为新的水稻垩白主效QTL, 为后续的候选基因挖掘奠定了基础。

The authors have declared that no competing interests exist.

作者已声明无竞争性利益关系。

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被引期刊影响因子

[1] 张昌泉, 赵冬生, 李钱峰, 顾铭洪, 刘巧泉 . 稻米品质性状基因的克隆与功能研究进展
中国农业科学, 2016,49:4267-4283
DOI:10.3864/j.issn.0578-1752.2016.22.002URL [本文引用: 1]
水稻是中国重要的粮食作物之一,高产与优质一直是品种改良的主要目标。目前,中国稻米品质表现总体偏低,在一定程度上影响了其市场竞争力。稻米品质属综合性状,是指稻米或稻米相关产品满足消费者或生产加工需求的各种特性,主要涉及稻米的物理和化学特性,包括精米率、米粒形状、透明度、蒸煮时间、米饭质地与香味、冷饭质地以及营养成分等指标。通常用碾磨品质、外观品质、蒸煮与食味品质和营养品质4个方面来评价稻米品质。近10年来,在上述稻米品质性状相关基因的克隆与功能研究领域已取得了长足的进展。水稻粒形不仅是重要的产量性状也是碾磨和外观品质的重要决定因素,目前已克隆了多个粒形相关的QTL和基因。根据粒形相关基因的表型效应可将其分为3类,即伴随植株矮化的小粒控制基因（第一类,包括D1、D2、D11、D61和SMG1等）、粒形特异基因（第二类,如GS3、GL3.1、GW7、GW2、GW5、GS5、GS6、TGW6、GW8、BG2、GW6a和GS2等）和小圆粒基因（第三类,即SRS）,其中只有第二类基因具有较好的育种利用价值。垩白是决定稻米外观品质的首要性状,同时也会影响碾磨品质。目前尽管已经鉴定了大量QTL,但只有少数QTL被精细定位和克隆,如Chalk5、cyPPDK、G1F1、OsRab5a、FLOURYENDOSPERM2、PDIL1-1和SSG4等主要通过调控胚乳灌浆和储藏物积累而影响稻米外观表现。淀粉占精米胚乳干重的90%以上,其组成与结构是决定稻米外观和蒸煮与食味品质的最重要因素。淀粉的合成是由多基因参与的复杂调控网络,直接参与淀粉合成的淀粉合成酶类基因的功能已经比较清楚;此外,参与胚乳淀粉代谢的一些转录因子如Dull、OsEBP89、OsEBP5、OsRSR1和OsbZIP58等也已被陆续鉴定和克隆。蛋白质是稻米的第二大成分,目前已克隆了众多的贮藏蛋白编码基因,并且已鉴定克隆了多个与蛋白质
Zhang C Q, Zhao D S, Li Q F, Gu M H, Liu Q Q . Progresses in research on cloning and functional analysis of key genes involving in rice grain quality
Sci Agric Sin, 2016,49:4267-4283 (in Chinese with English abstract)
DOI:10.3864/j.issn.0578-1752.2016.22.002URL [本文引用: 1]
水稻是中国重要的粮食作物之一,高产与优质一直是品种改良的主要目标。目前,中国稻米品质表现总体偏低,在一定程度上影响了其市场竞争力。稻米品质属综合性状,是指稻米或稻米相关产品满足消费者或生产加工需求的各种特性,主要涉及稻米的物理和化学特性,包括精米率、米粒形状、透明度、蒸煮时间、米饭质地与香味、冷饭质地以及营养成分等指标。通常用碾磨品质、外观品质、蒸煮与食味品质和营养品质4个方面来评价稻米品质。近10年来,在上述稻米品质性状相关基因的克隆与功能研究领域已取得了长足的进展。水稻粒形不仅是重要的产量性状也是碾磨和外观品质的重要决定因素,目前已克隆了多个粒形相关的QTL和基因。根据粒形相关基因的表型效应可将其分为3类,即伴随植株矮化的小粒控制基因（第一类,包括D1、D2、D11、D61和SMG1等）、粒形特异基因（第二类,如GS3、GL3.1、GW7、GW2、GW5、GS5、GS6、TGW6、GW8、BG2、GW6a和GS2等）和小圆粒基因（第三类,即SRS）,其中只有第二类基因具有较好的育种利用价值。垩白是决定稻米外观品质的首要性状,同时也会影响碾磨品质。目前尽管已经鉴定了大量QTL,但只有少数QTL被精细定位和克隆,如Chalk5、cyPPDK、G1F1、OsRab5a、FLOURYENDOSPERM2、PDIL1-1和SSG4等主要通过调控胚乳灌浆和储藏物积累而影响稻米外观表现。淀粉占精米胚乳干重的90%以上,其组成与结构是决定稻米外观和蒸煮与食味品质的最重要因素。淀粉的合成是由多基因参与的复杂调控网络,直接参与淀粉合成的淀粉合成酶类基因的功能已经比较清楚;此外,参与胚乳淀粉代谢的一些转录因子如Dull、OsEBP89、OsEBP5、OsRSR1和OsbZIP58等也已被陆续鉴定和克隆。蛋白质是稻米的第二大成分,目前已克隆了众多的贮藏蛋白编码基因,并且已鉴定克隆了多个与蛋白质

[2] 李一博, 赵雷 . 水稻品质性状的遗传改良及其关键科学问题
生命科学, 2016,28:1168-1179
[本文引用: 1]

Li Y B, Zhao L . Genetic improvement and key scientific questions of grain quality traits in rice
Chin Bull Life Sci, 2016,28:1168-1179 (in Chinese with English abstract)
[本文引用: 1]

[3] 江良荣, 李义珍, 王侯聪, 黄育民 . 稻米外观品质的研究进展与分子改良策略
分子植物育种, 2003,1:243-255
[本文引用: 1]

Jiang L R, Li Y Z, Wang H C, Huang Y M . Research progresses on appearance quality of rice grain and strategies for its molecular improvement
Mol Plant Breed, 2003,1:243-255 (in Chinese with English abstract)
[本文引用: 1]

[4] 王忠华, 方振华, 干建彗 . 稻米外观品质性状遗传与分子定位研究进展
生命科学, 2009,21:444-351
URL [本文引用: 1]
稻米外观品质主要是指稻米的粒 形、垩白、透明度和籽粒色泽等,它不仅直接影响到人们的喜好,还与其他品质性状诸如蒸煮食用、加工等密切相关。因此,外观品质对稻米的商品价值有着十分重 要的影响。本文从经典遗传与现代分子生物学两个方面对稻米主要外观品质的遗传研究进展进行了较全面的综述,包括粒长、粒宽、长宽比、粒厚、垩白、透明度和 籽粒色泽等。综合近年来的遗传研究结果发现,大多数稻米外观品质性状都是由数量基因控制的。利用分子标记技术已将控制外观品质的 QTL(qualitative trait locus)定位在不同的染色体上,为下一步的稻米外观品质改良提供了有利条件。
Wang Z H, Fang Z H, Gan J H . Advances in genetic research and molecular mapping of the rice grain appearance quality
Chin Bull Life Sci, 2009,21:444-351 (in Chinese with English abstract)
URL [本文引用: 1]
稻米外观品质主要是指稻米的粒 形、垩白、透明度和籽粒色泽等,它不仅直接影响到人们的喜好,还与其他品质性状诸如蒸煮食用、加工等密切相关。因此,外观品质对稻米的商品价值有着十分重 要的影响。本文从经典遗传与现代分子生物学两个方面对稻米主要外观品质的遗传研究进展进行了较全面的综述,包括粒长、粒宽、长宽比、粒厚、垩白、透明度和 籽粒色泽等。综合近年来的遗传研究结果发现,大多数稻米外观品质性状都是由数量基因控制的。利用分子标记技术已将控制外观品质的 QTL(qualitative trait locus)定位在不同的染色体上,为下一步的稻米外观品质改良提供了有利条件。

[5] Qiu X, Chen K, Lv W, Ou X, Zhu Y, Xing D, Yang L, Fan F, Yang J, Xu J, Zheng T, Li Z . Examining two sets of introgression lines reveals background-independent and stably expressed QTL that improve grain appearance quality in rice (Oryza sativa L.).
Theor Appl Genet, 2017,130:951-967
[本文引用: 1]

[6] Wan X Y, Wan J M, Weng J F, Jiang L, Bi J C, Wang C M, Zhai H Q . Stability of QTLs for rice grain dimension and endosperm chalkiness characteristics across eight environments
Theor Appl Genet, 2005,110:1334-1346
DOI:10.1007/s00122-005-1976-xURL [本文引用: 1]

[7] 杨亚春, 倪大虎, 宋丰顺, 李泽福, 易成新, 杨剑波 . 不同生态地点下稻米外观品质性状的QTL定位分析
中国水稻科学, 2011,25:43-51
DOI:10.3969/j.issn.1001-7216.2011.01.007URL [本文引用: 1]
利用两个已测序品种93-11和日本晴为亲本,采取单粒传法创建由190个家系组成的重组自交系群体,并构建了包含178个SSR、CAP和STS标记的遗传连锁图谱。采用复合区间作图方法,在3个不同生态地点(陵水、合肥和怀远)对垩白(垩白率、垩白大小、垩白度)、粒形(粒长、粒宽、长宽比)等6个外观品质的数量性状基因座(QTL)进行了定位分析。共定位到39个QTL,单个性状QTL数目在6～7个,说明垩白和粒形是多基因控制的数量性状。8个QTL可在2个以上地点检测到,其中,两个垩白度相关QTLqCD-1、qCD-3(贡献率分别为28.8%、32.1%)在3个地点同时检测到;11个QTL具有一因多效性,单个QTL位点控制的性状为2～6个,如第3染色体RM16-RM143区段控制垩白率、垩白大小、垩白度、粒长、粒宽和长宽比等6个性状。比较3个地点的检测结果,发现外观品质性状的QTL定位都受环境影响,但不同性状受影响的程度不同。长宽比和垩白度受环境影响较小,粒宽受环境影响较大。
Yang Y C, Ni D H, Song F S, Li Z F, Yi C X, Yang J B . Identification of QTLs for rice appearance quality traits across different ecological sites
Chin J Rice Sci, 2011,25:43-51 (in Chinese with English abstract)
DOI:10.3969/j.issn.1001-7216.2011.01.007URL [本文引用: 1]
利用两个已测序品种93-11和日本晴为亲本,采取单粒传法创建由190个家系组成的重组自交系群体,并构建了包含178个SSR、CAP和STS标记的遗传连锁图谱。采用复合区间作图方法,在3个不同生态地点(陵水、合肥和怀远)对垩白(垩白率、垩白大小、垩白度)、粒形(粒长、粒宽、长宽比)等6个外观品质的数量性状基因座(QTL)进行了定位分析。共定位到39个QTL,单个性状QTL数目在6～7个,说明垩白和粒形是多基因控制的数量性状。8个QTL可在2个以上地点检测到,其中,两个垩白度相关QTLqCD-1、qCD-3(贡献率分别为28.8%、32.1%)在3个地点同时检测到;11个QTL具有一因多效性,单个QTL位点控制的性状为2～6个,如第3染色体RM16-RM143区段控制垩白率、垩白大小、垩白度、粒长、粒宽和长宽比等6个性状。比较3个地点的检测结果,发现外观品质性状的QTL定位都受环境影响,但不同性状受影响的程度不同。长宽比和垩白度受环境影响较小,粒宽受环境影响较大。

[8] Fan C C, Xing Y Z, Mao H L, Lu T T, Han B, Xu C G, Li X H, Zhang Q F . GS3, a major QTL for grain length and weight and minor QTL for grain width and thickness in rice, encodes a putative transmembrane protein
Theor Appl Genet, 2006,112:1164-1171
[本文引用: 1]

[9] Mao H, Sun S, Yao J, Wang C, Yu S, Xu C, Li X, Zhang Q . Linking differential domain functions of the GS3 protein to natural variation of grain size in rice
Proc Natl Acad Sci USA, 2010,107:19579-19584
DOI:10.1073/pnas.1014419107URL [本文引用: 1]

[10] Shomura A, Izawa T, Ebana K, Ebitani T, Kanegae H, Konishi S, Yano M . Deletion in a gene associated with grain size increased yields during rice domestication
Nat Genet, 2008,40:1023-1028
DOI:10.1038/ng.169URLPMID:18604208 [本文引用: 1]
The domestication of crops involves a complex process of selection in plant evolution and is associated with changes in the DNA regulating agronomically important traits. Here we report the cloning of a newly identified QTL, qSW5 (QTL for seed width on chromosome 5), involved in the determination of grain width in rice. Through fine mapping, complementation testing and association analysis, we found that a deletion in qSW5 resulted in a significant increase in sink size owing to an increase in cell number in the outer glume of the rice flower; this trait might have been selected by ancient humans to increase yield of rice grains. In addition, we mapped two other defective functional nucleotide polymorphisms of rice domestication-related genes with genome-wide RFLP polymorphisms of various rice landraces. These analyses show that the qSW5 deletion had an important historical role in artificial selection, propagation of cultivation and natural crossings in rice domestication, and shed light on how the rice genome was domesticated.

[11] Weng J F, Gu S H, Wan X Y, Gao H, Guo T, Su N, Lei C L, Zhang X, Cheng Z J, Guo X P, Wang J L, Jiang L, Zhai H Q, Wan J M . Isolation and initial characterization of GW5, a major QTL associated with rice grain width and weight.
Cell Res, 2008,18:1199-1209
[本文引用: 1]

[12] Che R, Tong H, Shi B, Liu Y, Fang S, Liu D, Xiao Y, Hu B, Liu L, Wang H, Zhao M, Chu C . Control of grain size and rice yield by GL2-mediated brassinosteroid responses.
Nat Plants, 2015,2:15195
[本文引用: 1]

[13] Hu J, Wang Y, Fang Y, Zeng L, Xu J, Yu H, Shi Z, Pan J, Zhang D, Kang S, Zhu L, Dong G, Guo L, Zeng D, Zhang G, Xie L, Xiong G, Li J, Qian Q . A rare allele of GS2 enhances grain size and grain yield in rice.
Mol Plant, 2015,8:1455-1465
DOI:10.1016/j.molp.2015.07.002URLPMID:26187814 [本文引用: 1]
Grain size determines grain weight and affects grain quality. Several major quantitative trait loci (QTLs) regulating grain size have been cloned; however, our understanding of the underlying mechanism that regulates the size of rice grains remains fragmentary. Here, we report the cloning and characterization of a dominant QTL, GRAIN SIZE ON CHROMOSOME 2 ( GS2 ), which encodes Growth-Regulating Factor 4 (OsGRF4), a transcriptional regulator. GS2 localizes to the nucleus and may act as a transcription activator. A rare mutation of GS2 affecting the binding site for the regulatory microRNA OsmiR396c causes increased expression of GS2 / OsGRF4 . The increase of GS2 expression leads to larger cells and increased numbers of cells, which thus enhances grain weight and yield. The introduction of this rare allele of GS2 / OsGRF4 into rice cultivars could enhance grain weight and increase grain yield, with possible applications in breeding high-yield rice varieties.

[14] Song X J, Huang W, Shi M, Zhu M Z, Lin H X . A QTL for rice grain width and weight encodes a previously unknown RING type E3 ubiquitin ligase
Nat Genet, 2007,39:623-630
DOI:10.1038/ng2014URL [本文引用: 1]

[15] Wang S K, Li S, Liu Q, Wu K, Zhang J Q, Wang S S, Wang Y, Chen X B, Zhang Y, Gao C X, Wang F, Huang H X, Fu X D . The OsSPL16-GW7 regulatory module determines grain shape and simultaneously improves rice yield and grain quality.
Nat Genet, 2015,47:949-954
[本文引用: 1]

[16] Wang Y X, Xiong G S, Hu J, Jiang L, Yu H, Xu J, Fang Y X, Zeng L J, Xu E B, Xu J, Ye W J, Meng X B, Liu R F, Chen H Q, Jing Y H, Wang Y H, Zhu X D, Li J Y, Qian Q . Copy number variation at the GL7 locus contributes to grain size diversity in rice.
Nat Genet, 2015,47:944-948
DOI:10.1038/ng.3346URLPMID:26147619 [本文引用: 1]
Copy number variants (CNVs) are associated with changes in gene expression levels and contribute to various adaptive traits. Here we show that a CNV at the Grain Length on Chromosome 7 (GL7) locus contributes to grain size diversity in rice (Oryza sativa L.). GL7 encodes a protein homologous to Arabidopsis thaliana LONGIFOLIA proteins, which regulate longitudinal cell elongation. Tandem duplication of a 17.1-kb segment at the GL7 locus leads to upregulation of GL7 and downregulation of its nearby negative regulator, resulting in an increase in grain length and improvement of grain appearance quality. Sequence analysis indicates that allelic variants of GL7 and its negative regulator are associated with grain size diversity and that the CNV at the GL7 locus was selected for and used in breeding. Our work suggests that pyramiding beneficial alleles of GL7 and other yield- and quality-related genes may improve the breeding of elite rice varieties.

[17] Wang S K, Wu K, Yuan Q B, Liu X Y, Liu Z B, Lin X Y, Zeng R Z, Zhu H T, Dong G J, Qian Q, Zhang G Q, Fu X D . Control of grain size, shape and quality by OsSPL16 in rice.
Nat Genet, 2012,44:950-954
DOI:10.1038/ng.2327URLPMID:22729225 [本文引用: 1]
Abstract Grain size and shape are important components of grain yield and quality and have been under selection since cereals were first domesticated. Here, we show that a quantitative trait locus GW8 is synonymous with OsSPL16, which encodes a protein that is a positive regulator of cell proliferation. Higher expression of this gene promotes cell division and grain filling, with positive consequences for grain width and yield in rice. Conversely, a loss-of-function mutation in Basmati rice is associated with the formation of a more slender grain and better quality of appearance. The correlation between grain size and allelic variation at the GW8 locus suggests that mutations within the promoter region were likely selected in rice breeding programs. We also show that a marker-assisted strategy targeted at elite alleles of GS3 and OsSPL16 underlying grain size and shape can be effectively used to simultaneously improve grain quality and yield.

[18] Peng B, Wang L, Fan C, Jiang G, Luo L, Li Y, He Y . Comparative mapping of chalkiness components in rice using five populations across two environments
BMC Genet, 2014,15:49
[本文引用: 1]

[19] Zhao X, Daygon V D, McNally K L, Hamilton R S, Xie F, Reinke R F, Fitzgerald M A . Identification of stable QTLs causing chalk in rice grains in nine environments
Theor Appl Genet, 2016,129:141-153
DOI:10.1007/s00122-015-2616-8URLPMID:26498441 [本文引用: 1]
Key message A novel QTL cluster for chalkiness on Chr04 was identified using single environment analysis and joint mapping across 9 environments in Asia a

[20] 邱先进, 袁志华, 陈凯, 杜斌, 何文静, 杨隆维, 徐建龙, 邢丹英, 吕文恺 . 用全基因组关联分析解析籼稻垩白的遗传基础
作物学报, 2015,41:1007-1016
DOI:10.3724/SP.J.1006.2015.01007URL [本文引用: 1]
利用272份全球籼稻微核心种质的重测序SNP基因型,对海南三亚、广东深圳、浙江杭州和湖北荆州4个地点收集到的垩白粒率和垩白度性状采用TASSEL软件进行全基因组关联分析,解析籼稻垩白的遗传基础和挖掘影响垩白粒率和垩白度的优异等位基因。结果表明,依据SNP数据,可将籼稻微核心种质分成3个亚群。4个地点分别检测到42个和44个与垩白粒率和垩白度显著关联的位点,位于全部12条染色体上。2个性状分别有21个和19个位点在2个以上环境下同时被检测到,这些位点中有12个位点同时影响垩白粒率和垩白度,11个位点附近都有已克隆的水稻品质相关基因。其中,第5染色体3.3~5.3 Mb区间在4个地点都被检测到与垩白粒率显著关联,以杭州点对垩白粒率的贡献最大,优异等位基因载体品种为IRGC121689;第12染色体的17.5~18.0 Mb区间在三亚和杭州都被检测到与垩白度显著关联,以三亚点的垩白度贡献最大,优异等位基因载体品种为IRGC122285。这些位点和品种资源可作水稻外观品质分子改良的重要基因和品种资源。
Qiu X J, Yuan Z H, Chen K, Du B, He W J, Yang L W, Xu J L, Xing D Y, Lyu W K . Genetic dissection of grain chalkiness in indica mini-core germplasm using genome-wide association method.
Acta Agron Sin, 2015,41:1007-1016 (in Chinese with English abstract)
DOI:10.3724/SP.J.1006.2015.01007URL [本文引用: 1]
利用272份全球籼稻微核心种质的重测序SNP基因型,对海南三亚、广东深圳、浙江杭州和湖北荆州4个地点收集到的垩白粒率和垩白度性状采用TASSEL软件进行全基因组关联分析,解析籼稻垩白的遗传基础和挖掘影响垩白粒率和垩白度的优异等位基因。结果表明,依据SNP数据,可将籼稻微核心种质分成3个亚群。4个地点分别检测到42个和44个与垩白粒率和垩白度显著关联的位点,位于全部12条染色体上。2个性状分别有21个和19个位点在2个以上环境下同时被检测到,这些位点中有12个位点同时影响垩白粒率和垩白度,11个位点附近都有已克隆的水稻品质相关基因。其中,第5染色体3.3~5.3 Mb区间在4个地点都被检测到与垩白粒率显著关联,以杭州点对垩白粒率的贡献最大,优异等位基因载体品种为IRGC121689;第12染色体的17.5~18.0 Mb区间在三亚和杭州都被检测到与垩白度显著关联,以三亚点的垩白度贡献最大,优异等位基因载体品种为IRGC122285。这些位点和品种资源可作水稻外观品质分子改良的重要基因和品种资源。

[21] Xian J Q, Kai C, Wen K L, Xiao X O, Ya J Z, Dan Y X, Long W Y, Fang J F, Jie Y, Jian L X, Tian Q Z, Zhi K L . Examining two sets of introgression lines reveals background independent and stably expressed QTL that improve grain appearance quality in rice (Oryza sativa L.).
Theor Appl Genet, 2017,130:951-967
[本文引用: 1]

[22] Zhou L, Chen L, Jiang L, Zhang W, Liu L, Liu X, Zhao Z, Liu S, Zhang L, Wang J, Wan J . Fine mapping of the grain chalkiness QTL qPGWC-7 in rice(Oryza sativa L.).
Theor Appl Genet, 2009,118:581-590
[本文引用: 1]

[23] Guo T, Liu X, Wan X, Weng J, Liu S, Liu X, Chen M, Li J, Su N, Wu F, Cheng Z, Guo X, Lei C, Wang J, Jiang L, Wan J . Identification of a stable quantitative trait locus for percentage grains with white chalkiness in rice (Oryza sativa).
J Integr Plant Biol, 2011,53:598-607
[本文引用: 1]

[24] Gao Y, Liu C, Li Y, Zhang A, Dong G, Xie L, Zhang B, Ruan B, Hong K, Xue D, Zeng D, Guo L, Qian Q, Gao Z . QTL analysis for chalkiness of rice and fine mapping of a candidate gene for qACE9
Rice(N Y), 2016,9:41
DOI:10.1186/s12284-016-0114-5URL [本文引用: 1]
An ideal appearance is of commercial value for rice varieties. Chalkiness is one of the most important appearance quality indicators. Therefore, clarification of the heredity of chalkiness and its molecular mechanisms will contribute to reduction of rice chalkiness. Although a number of QTLs related to chalkiness were mapped, few of them have been cloned so far. In this study, using recombinant inbred lines (RILs) of PA64s and 9311, we identified 19 QTLs associated with chalkiness on chromosomes 1, 4, 6, 7, 9 and 12, which accounted for 5.1 to 30.6 % of phenotypic variations. A novel major QTLqACE9for the area of chalky endosperm (ACE) was detected in Hainan and Hangzhou, both mapped in the overlapping region on chromosome 9. It was further fine mapped to an interval of 22 kb between two insertion-deletion (InDel) markers IND9-4 and IND9-5 using a BC4F2population. Gene prediction analysis identified five putative genes, among which only one gene (OsAPS1), whose product involved in starch synthesis, was detected two nucleotide substitutions causing amino acid change between the parents. Significant difference was found in apparent amylose content (AAC) between NILqACE9and 9311. And starch granules were round and loosely packed in NILqACE9compared with 9311 by scanning electron microscopy (SEM) analysis. OsAPS1was selected as a novel candidate gene for fine-mappedqACE9. The candidate gene not only plays a critical role during starch synthesis in endosperm, but also determines the area of chalky endosperm in rice. Further cloning of the QTL will facilitate the improvement of quality in hybrid rice.

[25] Li Y, Fan C, Xing Y, Yun P, Luo L, Yan B, Peng B, Xie W, Wang G, Li X, Xiao J, Xu C, He Y . Chalk5 encodes a vacuolar H(+)-translocating pyrophosphatase influencing grain chalkiness in rice
Nat Genet, 2014,46:398-404
[本文引用: 1]

[26] 胡苗, 孙志忠, 孙学武, 谭炎宁, 余东, 刘瑞芬, 袁贵龙, 丁佳, 袁定阳, 段美娟 . 利用高密度SNP标记定位水稻粒形相关QTL
杂交水稻, 2015,30(5):54-58
DOI:10.16267/j.cnki.1005-3956.201505019URL [本文引用: 1]
以"巨穗稻"R1128与粳稻品种日本晴杂交,构建包含781个单株的F2分离群体,利用高通量测序技术开发高密度SNP标记并构建超高密度的遗传连锁图谱,对水稻粒长、粒宽和粒厚3个性状进行QTL定位分析。共检测到分布于除第1,11,12号染色体以外的9条染色体上的19个粒形相关QTL,其中10个控制粒长,5个控制粒宽,4个控制粒厚,这些QTL中,粒长QTL q GL4-2、q GL7-2、q GL10-2、q GL10-3,粒宽QTL q GW6,粒厚QTL q GT4、q GT8可能为新发现的粒形相关位点。
Hu M, Sun Z Z, Sun X W, Tan Y N, Yu D, Liu R F, Yuan G L, Ding J, Yuan D Y, Duan M J . Mapping of rice grain shape relevant QTLs using high-density SNP markers
Hybrid Rice, 2015,30(5):54-58 (in Chinese with English abstract)
DOI:10.16267/j.cnki.1005-3956.201505019URL [本文引用: 1]
以"巨穗稻"R1128与粳稻品种日本晴杂交,构建包含781个单株的F2分离群体,利用高通量测序技术开发高密度SNP标记并构建超高密度的遗传连锁图谱,对水稻粒长、粒宽和粒厚3个性状进行QTL定位分析。共检测到分布于除第1,11,12号染色体以外的9条染色体上的19个粒形相关QTL,其中10个控制粒长,5个控制粒宽,4个控制粒厚,这些QTL中,粒长QTL q GL4-2、q GL7-2、q GL10-2、q GL10-3,粒宽QTL q GW6,粒厚QTL q GT4、q GT8可能为新发现的粒形相关位点。

[27] Sun X, Liu D, Zhang X, Li W, Liu H, Hong W, Jiang C, Guan N, Ma C, Zeng H, Xu C, Song J, Huang L, Wang C, Shi J, Wang R, Zheng X, Lu C, Wang X, Zheng H . SLAF-seq: an efficient method of large-scale de novo SNP discovery and genotyping using high-throughput sequencing
PLoS One, 2013,8(3):e58700
DOI:10.1371/journal.pone.0058700URL [本文引用: 2]

[28] Wei Q, Wang Y, Qin X, Zhang Y, Zhang Z, Wang J, Li J, Lou Q, Chen J . An SNP-based saturated genetic map and QTL analysis of fruit-related traits in cucumber using specific-length amplified fragment (SLAF) sequencing
BMC Genomics, 2014,15:1158
DOI:10.1186/1471-2164-15-1158URL [本文引用: 1]

[29] Zhang Y, Wang L, Xin H, Li D, Ma C, Ding X, Hong W, Zhang X . Construction of a high-density genetic map for sesame based on large scale marker development by specific length amplified fragment (SLAF) sequencing
BMC Plant Biol, 2013,13:141
DOI:10.1186/1471-2229-13-141URL [本文引用: 1]

[30] Kozich J J, Westcott S L, Baxter N T, Highlander S K, Schloss P D . Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform
Appl Environ Microb, 2013,79:5112-5120
DOI:10.1128/AEM.01043-13URL [本文引用: 1]

[31] Liu D, Ma C, Hong W, Huang L, Liu M, Liu H, Zeng H, Deng D, Xin H, Song J, Xu C, Sun X, Hou X, Wang X, Zheng H . Construction and analysis of high-density linkage map using high-throughput sequencing data
PLoS One, 2014,9(6):e98855
DOI:10.1371/journal.pone.0098855URL [本文引用: 1]