Genomic predictions and genome-wide association studies based on RAD-seq of quality-related metabolites for the genomics-assisted breeding of tea plants.
Genomic predictions and genome-wide association studies based on RAD-seq of quality-related metabolites for the genomics-assisted breeding of tea plants.
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DOI：
10.1038/s41598-020-74623-7
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发表时间：
2020-10-15
影响因子：
4.6
通讯作者：
Ikka T
中科院分区：
文献类型：
--
作者：
Yamashita H;Uchida T;Tanaka Y;Katai H;Nagano AJ;Morita A;Ikka T
有效利用基因组信息大大加速了传统育种，将其应用于长寿作物促进了向基因组育种的转变。由于茶树育种使用传统的方法，我们评估了基因组预测（GPs）和全基因组关联研究（GWASs）的潜力，茶叶品质相关代谢物的遗传育种使用全基因组单核苷酸多态性（SNPs）从限制性位点相关的DNA测序的150个茶叶种质。目前的GP基于全基因组SNP和六种模型，对大多数儿茶素的水平产生了中等的预测准确度值（r），以（-）-表没食子儿茶素没食子酸酯（r = 0.32-0.41）和咖啡因（r = 0.44-0.51）为代表，但游离氨基酸和叶绿素的r值较低。GWAS和GP的综合分析使用80-160个排名靠前的SNP检测每种代谢物的潜在候选基因，从而产生最大累积预测值。将GPs和GWASs应用于茶树的遗传性状，将有助于基因组辅助茶树育种。
Effectively using genomic information greatly accelerates conventional breeding and applying it to long-lived crops promotes the conversion to genomic breeding. Because tea plants are bred using conventional methods, we evaluated the potential of genomic predictions (GPs) and genome-wide association studies (GWASs) for the genetic breeding of tea quality-related metabolites using genome-wide single nucleotide polymorphisms (SNPs) detected from restriction site-associated DNA sequencing of 150 tea accessions. The present GP, based on genome-wide SNPs, and six models produced moderate prediction accuracy values (r) for the levels of most catechins, represented by ( −)-epigallocatechin gallate (r = 0.32–0.41) and caffeine (r = 0.44–0.51), but low r values for free amino acids and chlorophylls. Integrated analysis of GWAS and GP detected potential candidate genes for each metabolite using 80–160 top-ranked SNPs that resulted in the maximum cumulative prediction value. Applying GPs and GWASs to tea accession traits will contribute to genomics-assisted tea breeding.
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影响因子：
16.6
作者：
Imamura M;Takahashi A;Yamauchi T;Hara K;Yasuda K;Grarup N;Zhao W;Wang X;Huerta-Chagoya A;Hu C;Moon S;Long J;Kwak SH;Rasheed A;Saxena R;Ma RC;Okada Y;Iwata M;Hosoe J;Shojima N;Iwasaki M;Fujita H;Suzuki K;Danesh J;Jørgensen T;Jørgensen ME;Witte DR;Brandslund I;Christensen C;Hansen T;Mercader JM;Flannick J;Moreno-Macías H;Burtt NP;Zhang R;Kim YJ;Zheng W;Singh JR;Tam CH;Hirose H;Maegawa H;Ito C;Kaku K;Watada H;Tanaka Y;Tobe K;Kawamori R;Kubo M;Cho YS;Chan JC;Sanghera D;Frossard P;Park KS;Shu XO;Kim BJ;Florez JC;Tusié-Luna T;Jia W;Tai ES;Pedersen O;Saleheen D;Maeda S;Kadowaki T
通讯作者：
Kadowaki T
影响因子：
39.2
作者：
Iso, H;Date, C;Tamakoshi, A
通讯作者：
Tamakoshi, A
影响因子：
1.7
作者：
Lu, K;Gray, MA;Nathan, PJ
通讯作者：
Nathan, PJ
影响因子：
2.4
作者：
Iwata H;Minamikawa MF;Kajiya-Kanegae H;Ishimori M;Hayashi T
通讯作者：
Hayashi T
苜蓿（Medicago sativa）草料质量特征的全基因组关联映射和基因组选择。
影响因子：
3.7
作者：
Biazzi E;Nazzicari N;Pecetti L;Brummer EC;Palmonari A;Tava A;Annicchiarico P
通讯作者：
Annicchiarico P