了解种子Ni和Mo的遗传基础至关重要。由于大豆是世界上主要的作物,也是营养的主要来源,包括Ni和Mo,当前研究的目的是绘制遗传区域(数量性状基因座,QTL)与大豆种子中的Ni和Mo浓度相关。重组自交系(RIL)种群来自“Forrest”和“Williams82”(F×W82)之间的杂交。使用InfiniumSNP6KBeadChips,使用5405个单核苷酸多态性(SNP)标记对总共306个品系进行基因分型。进行了为期两年的实验,包括父母和RIL人群。2018年在北卡罗来纳州(NC)进行了一项实验,第二个实验于2020年在伊利诺伊州进行(IL)。将≥2.5的赔率(LOD)的对数设置为阈值,以使用复合间隔映射(CIM)方法报告已识别的QTL。在RIL中观察到宽范围的Ni和Mo浓度。总共四个QTL(分别在Chr2、8和9上的qNi-01,qNi-02和qNi-03,2018年,2020年Chr20上的qNi-01)被确定为种子Ni。所有这些QTL均与种子Ni显著相关(LOD阈值>2.5),LOD评分在2.71-3.44之间,表型差异在4.48-6.97%之间。2018年确定了Mo的三个QTL(分别在Chr1、3、17上的qMo-01,qMo-02和qMo-03),并在2020年确定了四个QTL(qMo-01,qMo-02,qMo-03和qMo-04,分别在Chr5、11、14和16上)。当前的一些QTL具有高LOD,并且显着促成了该性状的表型变异。例如,2018年,Chr1上的MoQTLqMo-01的LOD为7.8,解释了41.17%的表型变异,Chr17上的qMo-03的LOD为5.33,表型变异解释为41.49%。此外,一个MoQTL(Chr14上的qMo-03)的LOD为9.77,解释了与该性状相关的51.57%的表型变异,另一个MoQTL(Chr16上的qMo-04)的LOD为7.62,解释了49.95%的表型变异。此处确定的QTL均未在位置/年份中被识别两次。基于对现有文献和SoyBase的搜索,Ni的四个QTL,在Chr2、8、9和20上鉴定,以及与Mo相关的五个QTL,在Chr1、17、11、14和16上鉴定的是新颖的,以前没有报道过。这项研究为Ni和Mo的遗传作图提供了新的见解,并提供了有价值的QTL和分子标记,可以潜在地帮助选择大豆种子中的Ni和Mo水平。
Understanding the genetic basis of seed Ni and Mo is essential. Since soybean is a major crop in the world and a major source for nutrients, including Ni and Mo, the objective of the current research was to map genetic regions (quantitative trait loci, QTL) linked to Ni and Mo concentrations in soybean seed. A recombinant inbred line (
RIL) population was derived from a cross between \'Forrest\' and \'Williams 82\' (F × W82). A total of 306 lines was used for genotyping using 5405 single nucleotides polymorphism (SNP) markers using Infinium SNP6K BeadChips. A two-year experiment was conducted and included the parents and the
RIL population. One experiment was conducted in 2018 in North Carolina (NC), and the second experiment was conducted in Illinois in 2020 (IL). Logarithm of the odds (LOD) of ≥2.5 was set as a threshold to report identified QTL using the composite interval mapping (CIM) method. A wide range of Ni and Mo concentrations among RILs was observed. A total of four QTL (qNi-01, qNi-02, and qNi-03 on Chr 2, 8, and 9, respectively, in 2018, and qNi-01 on Chr 20 in 2020) was identified for seed Ni. All these QTL were significantly (LOD threshold > 2.5) associated with seed Ni, with LOD scores ranging between 2.71-3.44, and with phenotypic variance ranging from 4.48-6.97%. A total of three QTL for Mo (qMo-01, qMo-02, and qMo-03 on Chr 1, 3, 17, respectively) was identified in 2018, and four QTL (qMo-01, qMo-02, qMo-03, and qMo-04, on Chr 5, 11, 14, and 16, respectively) were identified in 2020. Some of the current QTL had high LOD and significantly contributed to the phenotypic variance for the trait. For example, in 2018, Mo QTL qMo-01 on Chr 1 had LOD of 7.8, explaining a phenotypic variance of 41.17%, and qMo-03 on Chr 17 had LOD of 5.33, with phenotypic variance explained of 41.49%. In addition, one Mo QTL (qMo-03 on Chr 14) had LOD of 9.77, explaining 51.57% of phenotypic variance related to the trait, and another Mo QTL (qMo-04 on Chr 16) had LOD of 7.62 and explained 49.95% of phenotypic variance. None of the QTL identified here were identified twice across locations/years. Based on a search of the available literature and of SoyBase, the four QTL for Ni, identified on Chr 2, 8, 9, and 20, and the five QTL associated with Mo, identified on Chr 1, 17, 11, 14, and 16, are novel and not previously reported. This research contributes new insights into the genetic mapping of Ni and Mo, and provides valuable QTL and molecular markers that can potentially assist in selecting Ni and Mo levels in soybean seeds.