文献类型: 外文期刊
第一作者: Sun, Ziqi
作者: Sun, Ziqi;Li, Huihui;Zhang, Luyan;Wang, Jiankang
作者机构:
期刊名称:GENETICS RESEARCH ( 影响因子:1.588; 五年影响因子:1.263 )
ISSN:
年卷期:
页码:
收录情况: SCI
摘要: Linkage analysis plays an important role in genetic studies. In linkage analysis, accurate estimation of recombination frequency is essential. Many bi-parental populations have been used, and determining an appropriate population is of great importance in precise recombination frequency. In this study, we investigated the estimation efficiency of recombination frequency in 12 bi-parental populations. The criteria that we used for comparison were LOD score in testing linkage relationship, deviation between estimated and real recombination frequency, standard error (SE) of estimates and the least theoretical population size (PS) required to observe at least one recombinant and to declare the statistically significant linkage relationship. Theoretical and simulation results indicated that larger PS and smaller recombination frequency resulted in higher LOD score and smaller deviation. Lower LOD score, higher deviation and higher SE for estimating the recombination frequency in the advanced backcrossing and selfing populations are larger than those in backcross and F-2 populations, respectively. For advanced backcrossing and selfing populations, larger populations were needed in order to observe at least one recombinant and to declare significant linkage. In comparison, in F-2 and F-3 populations higher LOD score, lower deviation and SE were observed for co-dominant markers. A much larger population was needed to observe at least one recombinant and to detect loose linkage for dominant and recessive markers. Therefore, advanced backcrossing and selfing populations had lower precision in estimating the recombination frequency. F-2 and F-3 populations together with co-dominant markers represent the ideal situation for linkage analysis and linkage map construction.
分类号: Q3
- 相关文献
作者其他论文 更多>>
-
Mapping and Validation of Quantitative Trait Loci on Yield-Related Traits Using Bi-Parental Recombinant Inbred Lines and Reciprocal Single-Segment Substitution Lines in Rice (Oryza sativa L.)
作者:Manzoor, Ghulam Ali;Zhang, Luyan;Wang, Jiankang;Yin, Changbin
关键词:yield-related traits; QTL mapping; QTL validation; recombinant inbred lines (RILs); single-segment substitution lines (SSSLs); rice (
Oryza sativa L.) -
Synergistic pathogenicity of novel duck Orthoreovirus and salmonella typhimurium in ducks
作者:Li, Bing;Mao, Mingtian;Li, Huihui;Wu, Mian;Lu, Chengguang;Lu, Meixi;Guo, Zhanbao;Liang, Suyun;Zhou, Zhengkui;Hou, Shuisheng;Tang, Yi;Man, Xinhong;Yuan, Mengdi;Diao, Youxiang
关键词:Novel Duck Orthoreovirus; Salmonella Typhimurium; Co-infection; Co-pathogenicity
-
Phenylpropanoids metabolism: recent insight into stress tolerance and plant development cues
作者:Ninkuu, Vincent;Zhao, Jun;Li, Huihui;Dakora, Felix Dapare;Ninkuu, Vincent;Yan, Jianpei;Zeng, Hongmei;Aluko, Oluwaseun Olayemi;Liu, Guodao;Chen, Songbi;Zhao, Jun;Li, Huihui;Dakora, Felix Dapare
关键词:phenylpropanoids; plant interactions; post-transcription; post-translation; epigenetics modifications; plant development
-
Prediction by simulation in plant breeding
作者:Li, Huihui;Zhang, Luyan;Gao, Shang;Wang, Jiankang;Li, Huihui;Zhang, Luyan;Gao, Shang;Wang, Jiankang;Li, Huihui;Gao, Shang;Wang, Jiankang
关键词:Prediction by simulation; Plant breeding; Modeling; Genetic model; Breeding method
-
Fast-forwarding plant breeding with deep learning-based genomic prediction
作者:Gao, Shang;Yu, Tingxi;Wang, Jiankang;Li, Huihui;Gao, Shang;Yu, Tingxi;Wang, Jiankang;Li, Huihui;Rasheed, Awais;Crossa, Jose;Hearne, Sarah
关键词:artificial intelligence; deep learning; genomic prediction; plant breeding
-
Exploring the Impacts of Elevated CO2 on Food Security: Nutrient Assimilation, Plant Growth, and Crop Quality
作者:Dakora, Felix D.;Li, Huihui;Zhao, Jun;Dakora, Felix D.;Li, Huihui;Zhao, Jun
关键词:Photosynthesis; N 2 fixation; Reduced plant nitrogen; Amino acids and nutrients
-
Leveraging Automated Machine Learning for Environmental Data-Driven Genetic Analysis and Genomic Prediction in Maize Hybrids
作者:He, Kunhui;Yu, Tingxi;Gao, Shang;Chen, Shoukun;Li, Liang;Zhang, Xuecai;Huang, Changling;Xu, Yunbi;Wang, Jiankang;Li, Xinhai;Li, Huihui;He, Kunhui;Yu, Tingxi;Gao, Shang;Chen, Shoukun;Zhang, Xuecai;Huang, Changling;Wang, Jiankang;Li, Huihui;Zhang, Xuecai;Hearne, Sarah;Prasanna, Boddupalli M.
关键词:environmental data; genetic analysis; genomic selection; genotype-by-environment interactions; machine learning