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利用靶向水稻14个基因的新型功能标记进行粒型选择

Grain Size Selection Using Novel Functional Markers Targeting 14 Genes in Rice.

作者信息

Zhang Lin, Ma Bin, Bian Zhong, Li Xiaoyuan, Zhang Changquan, Liu Jiyun, Li Qun, Liu Qiaoquan, He Zuhua

机构信息

Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding /Joint International Research Laboratory of Agriculture and Agri-Product Safety of the Ministry of Education, Yangzhou University, Yangzhou, 225009, China.

Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Jiangsu Key Laboratory of Crop Genetics and Physiology, Yangzhou University, Yangzhou, 225009, China.

出版信息

Rice (N Y). 2020 Sep 9;13(1):63. doi: 10.1186/s12284-020-00427-y.

DOI:10.1186/s12284-020-00427-y
PMID:32902771
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7481322/
Abstract

BACKGROUND

Grain size is an extremely important aspect of rice breeding, affecting both grain yield and quality traits. It is controlled by multiple genes and tracking these genes in breeding schemes should expedite selection of lines with superior grain yield and quality, thus it is essential to develop robust, efficient markers.

RESULT

In this study, 14 genes related to grain size (GW2, GS2, qLGY3, GS3, GL3.1, TGW3, GS5, GW5, GS6, TGW6, GW6a, GLW7, GL7 and GW8) were selected for functional marker development. Twenty-one PCR-gel-based markers were developed to genotype the candidate functional nucleotide polymorphisms (FNPs) of these genes, and all markers can effectively recognize the corresponding allele types. To test the allele effects of different FNPs, a global collection of rice cultivars including 257 accessions from the Rice Diversity Panel 1 was used for allele mining, and four grain-size-related traits were investigated at two planting locations. Three FNPs for GW2, GS2 and GL3.1 were genotyped as rare alleles only found in cultivars with notably large grains, and the allele contributions of the remaining FNPs were clarified in both the indica and japonica subspecies. Significant trait contributions were found for most of the FNPs, especially GS3, GW5 and GL7. Of note, GW5 could function as a key regulator to coordinate the performance of other grain size genes. The allele effects of several FNPs were also tested by QTL analysis using an F population, and GW5 was further identified as the major locus with the largest contribution to grain width and length to width ratio.

CONCLUSIONS

The functional markers are robust for genotyping different cultivars and may facilitate the rational design of grain size to achieve a balance between grain yield and quality in future rice breeding efforts.

摘要

背景

粒型是水稻育种中极为重要的一个方面,它影响着谷物产量和品质性状。粒型受多个基因控制,在育种方案中追踪这些基因应能加快对具有优良谷物产量和品质的品系的选择,因此开发强大、高效的标记至关重要。

结果

在本研究中,选择了14个与粒型相关的基因(GW2、GS2、qLGY3、GS3、GL3.1、TGW3、GS5、GW5、GS6、TGW6、GW6a、GLW7、GL7和GW8)用于功能标记开发。开发了21个基于PCR凝胶的标记,用于对这些基因的候选功能核苷酸多态性(FNP)进行基因分型,所有标记都能有效识别相应的等位基因类型。为了测试不同FNP的等位基因效应,使用了包括来自水稻多样性面板1的257份材料的全球水稻品种收集群体进行等位基因挖掘,并在两个种植地点对四个与粒型相关的性状进行了调查。GW2、GS2和GL3.1的三个FNP被基因分型为仅在具有明显大粒的品种中发现的稀有等位基因,其余FNP的等位基因贡献在籼稻和粳稻亚种中均得到了阐明。发现大多数FNP对性状有显著贡献,尤其是GS3、GW5和GL7。值得注意的是,GW5可以作为一个关键调节因子来协调其他粒型基因的表现。还使用一个F群体通过QTL分析测试了几个FNP的等位基因效应,GW5被进一步确定为对粒宽和长宽比贡献最大的主要位点。

结论

这些功能标记对于不同品种的基因分型是可靠的,并且可能有助于在未来的水稻育种工作中合理设计粒型,以实现谷物产量和品质之间的平衡。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d0d/7481322/845edb0b0c5e/12284_2020_427_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d0d/7481322/e23b405c9377/12284_2020_427_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d0d/7481322/cbecdf286eac/12284_2020_427_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d0d/7481322/aefeb02892a9/12284_2020_427_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d0d/7481322/a3aa1caccdcd/12284_2020_427_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d0d/7481322/bf510974e6e3/12284_2020_427_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d0d/7481322/e41223637fa6/12284_2020_427_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d0d/7481322/845edb0b0c5e/12284_2020_427_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d0d/7481322/e23b405c9377/12284_2020_427_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d0d/7481322/cbecdf286eac/12284_2020_427_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d0d/7481322/aefeb02892a9/12284_2020_427_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d0d/7481322/a3aa1caccdcd/12284_2020_427_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d0d/7481322/bf510974e6e3/12284_2020_427_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d0d/7481322/e41223637fa6/12284_2020_427_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d0d/7481322/845edb0b0c5e/12284_2020_427_Fig7_HTML.jpg

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