Genotypic variation and identification of QTLs for agronomic traits, using AFLP and SSR markers in RILs of sunflower (Helianthus annuus L.)

Genotypic variation and identification of QTLs for agronomic traits, using AFLP and SSR markers in RILs of sunflower (Helianthus annuus L.)
复制标题

DOI:
10.1007/s00122-004-1770-1
复制
发表时间:
2004-11-01
影响因子:
5.4
通讯作者:
Sarrafi, A
Sarrafi, A
中科院分区:
农林科学1区
文献类型:
--
作者:
Al-Chaarani, GR;Gentzbittel, L;Sarrafi, A

文献摘要

被引文献

相似文献

以"PAC-2"和"RHA-266"为亲本,通过单粒杂交选育出77个重组自交系。将上述RIL及其亲本的种子以随机完全区组设计种植在田间,重复两次。测定了RIL及其亲本的播花期、株高、茎粗、穗粗、单株粒重、千粒重和籽粒含油率等农艺性状的遗传控制。在77个RIL中观察到所有性状的遗传变异。部分性状发生了超亲分离,10%的重组自交系与最佳亲本比较,SD、HD和TGW均存在显著差异。利用409个AFLP和SSR标记对来自同一杂交组合的123个重组自交系进行了筛选,构建了基于367个标记的连锁图谱。鉴定了与所研究性状相关的多个QTL。每个QTL的影响是中等的,范围从7%到37%,但当考虑到所有的协变量时,解释了高比例的表型方差(TR2在每个性状中的平均值约为80%)。虽然检测到的区域需要更精确地映射,获得的信息应该有助于标记辅助选择。
A population of 77 recombinant inbred lines (RILs) were developed through single-seed descent from a cross between 'PAC-2' and 'RHA-266'. Seeds of the above-mentioned RILs and their parents were planted in the field in a randomised complete block design with two replications. Genetic control for some agronomical traits-sowing-to-flowering date, plant height, stem diameter (SD), head diameter (HD), grain weight per plant, 1,000-grain weight (TGW) and the percentage of oil in grains-were measured for RILs and their parents. Genetic variability was observed among 77 RILs for all traits studied. Transgressive segregation occurred for some traits, and the comparison between 10% of selected RILs with the best parent showed significant difference for SD and HD as well as for TGW. A set of 123 RILs from the same cross, including the 77 above-mentioned RILs and their two parents, were screened with 409 AFLP and SSR markers, and a linkage map was constructed based on 367 markers. Several QTLs associated with the studied traits were identified. The effects of each QTL are moderate, ranging from 7% to 37%, but a high percentage of phenotypic variance is explained when considering all the covariants (TR2 mean around 80% in each trait). Although the detected regions need to be more precisely mapped, the information obtained should help in marker-assisted selection.