Development of a High-Density Genetic Map Based on Specific Length Amplified Fragment Sequencing and Its Application in Quantitative Trait Loci Analysis for Yield-Related Traits in Cultivated Peanut.
Development of a High-Density Genetic Map Based on Specific Length Amplified Fragment Sequencing and Its Application in Quantitative Trait Loci Analysis for Yield-Related Traits in Cultivated Peanut.
复制标题
基于特定长度扩增片段测序的高密度遗传图谱构建及其在栽培花生产量相关性状数量性状位点分析中的应用
DOI:
10.3389/fpls.2018.00827
复制
发表时间:
2018
影响因子:
5.6
通讯作者:
Liao B
中科院分区:
文献类型:
--
作者:
Wang Z;Huai D;Zhang Z;Cheng K;Kang Y;Wan L;Yan L;Jiang H;Lei Y;Liao B
High-density genetic maps (HDGMs) are very useful for genomic studies and quantitative trait loci (QTL) mapping. However, the low frequency of DNA polymorphisms in peanut has limited the quantity of available markers and hindered the construction of a HDGM. This study generated a peanut genetic map with the highest number of high-quality SNPs based on specific locus amplified fragment sequencing (SLAF-seq) technology and a newly constructed RIL population (“ZH16” × “sd-H1”). The constructed HDGM included 3,630 SNP markers belonging to 2,636 bins on 20 linkage groups (LGs), and it covers 2,098.14 cM in length, with an average marker distance of 0.58 cM. This HDGM was applied for the following collinear comparison, scaffold anchoring and analysis of genomic characterization including recombination rates and segregation distortion in peanut. For QTL mapping of investigated 14 yield-related traits, a total of 62 QTLs were detected on 12 chromosomes across 3 environments, and the co-localization of QTLs was observed for these traits which were significantly correlated on phenotype. Two stable co-located QTLs for seed- and pod-related traits were significantly identified in the chromosomal end of B06 and B07, respectively. The construction of HDGM and QTL analysis for yield-related traits in this study provide useful information for fine mapping and functional analysis of genes as well as molecular marker-assisted breeding.
登录
查看更多内容
影响因子:
5.3
作者:
Hong Y;Chen X;Liang X;Liu H;Zhou G;Li S;Wen S;Holbrook CC;Guo B
通讯作者:
Guo B
影响因子:
2.9
作者:
Chen W;Jiao Y;Cheng L;Huang L;Liao B;Tang M;Ren X;Zhou X;Chen Y;Jiang H
通讯作者:
Jiang H
影响因子:
5.6
作者:
Guo Y;Shi G;Liu Z;Zhao Y;Yang X;Zhu J;Li K;Guo X
通讯作者:
Guo X
DOI:
10.1534/g3.113.007617
发表时间:
2014-01-10
期刊:
G3 (Bethesda, Md.)
影响因子:
--
作者:
Bertioli DJ;Ozias-Akins P;Chu Y;Dantas KM;Santos SP;Gouvea E;Guimarães PM;Leal-Bertioli SC;Knapp SJ;Moretzsohn MC
通讯作者:
Moretzsohn MC
影响因子:
1.5
作者:
Belamkar, Vikas;Selvaraj, Michael Gomez;Burow, Mark D.
通讯作者:
Burow, Mark D.