PDF(Pubmed)
Abstract：
BACKGROUND: The chlorophyll content (CC) is a key factor affecting maize photosynthetic efficiency and the final yield. However, its genetic basis remains unclear. The development of statistical methods has enabled researchers to design and apply various GWAS models, including MLM, MLMM, SUPER, FarmCPU, BLINK and 3VmrMLM. Comparative analysis of their results can lead to more effective mining of key genes.
RESULTS: The heritability of CC was 0.86. Six statistical models (MLM, BLINK, MLMM, FarmCPU, SUPER, and 3VmrMLM) and 1.25 million SNPs were used for the GWAS. A total of 140 quantitative trait nucleotides (QTNs) were detected, with 3VmrMLM and MLM detecting the most (118) and fewest (3) QTNs, respectively. The QTNs were associated with 481 genes and explained 0.29-10.28% of the phenotypic variation. Additionally, 10 co-located QTNs were detected by at least two different models or methods, three co-located QTNs were identified in at least two different environments, and six co-located QTNs were detected by different models or methods in different environments. Moreover, 69 candidate genes within or near these stable QTNs were screened based on the B73 (RefGen_v2) genome. GRMZM2G110408 (ZmCCS3) was identified by multiple models and in multiple environments. The functional characterization of this gene indicated the encoded protein likely contributes to chlorophyll biosynthesis. In addition, the CC differed significantly between the haplotypes of the significant QTN in this gene, and CC was higher for haplotype 1.
CONCLUSIONS: This study\'s results broaden our understanding of the genetic basis of CC, mining key genes related to CC and may be relevant for the ideotype-based breeding of new maize varieties with high photosynthetic efficiency.
RESULTS: The heritability of CC was 0.86. Six statistical models (MLM, BLINK, MLMM, FarmCPU, SUPER, and 3VmrMLM) and 1.25 million SNPs were used for the GWAS. A total of 140 quantitative trait nucleotides (QTNs) were detected, with 3VmrMLM and MLM detecting the most (118) and fewest (3) QTNs, respectively. The QTNs were associated with 481 genes and explained 0.29-10.28% of the phenotypic variation. Additionally, 10 co-located QTNs were detected by at least two different models or methods, three co-located QTNs were identified in at least two different environments, and six co-located QTNs were detected by different models or methods in different environments. Moreover, 69 candidate genes within or near these stable QTNs were screened based on the B73 (RefGen_v2) genome. GRMZM2G110408 (ZmCCS3) was identified by multiple models and in multiple environments. The functional characterization of this gene indicated the encoded protein likely contributes to chlorophyll biosynthesis. In addition, the CC differed significantly between the haplotypes of the significant QTN in this gene, and CC was higher for haplotype 1.
CONCLUSIONS: This study\'s results broaden our understanding of the genetic basis of CC, mining key genes related to CC and may be relevant for the ideotype-based breeding of new maize varieties with high photosynthetic efficiency.
摘要：
背景：叶绿素含量（CC）是影响玉米光合效率和最终产量的关键因素。然而,其遗传基础尚不清楚。统计方法的发展使研究人员能够设计和应用各种GWAS模型，包括传销,MLMM,超级,FarmCPU,BLINK和3VmrMLM。对其结果进行比较分析可以更有效地挖掘关键基因。
结果：CC的遗传力为0.86。六个统计模型(MLM，BLINK,MLMM,FarmCPU,超级,和3VmrMLM）和125万个SNP用于GWAS。共检测到140个数量性状核苷酸(QTNs),3VmrMLM和MLM检测到最多(118)和最少(3)QTNs，分别。QTNs与481个基因相关，解释了0.29-10.28％的表型变异。此外,通过至少两种不同的模型或方法检测到10个共定位的QTNs，在至少两种不同的环境中确定了三个位于同一地点的QTNs，在不同的环境中，通过不同的模型或方法检测到6个共定位的QTNs。此外，基于B73(RefGen_v2)基因组筛选这些稳定QTNs内或附近的69个候选基因。GRMZM2G110408(ZmCCS3)由多个模型和多个环境中识别。该基因的功能表征表明编码的蛋白质可能有助于叶绿素的生物合成。此外,CC在该基因中显著QTN的单倍型之间存在显着差异，单倍型1的CC较高。
结论：这项研究的结果拓宽了我们对CC遗传基础的理解，挖掘与CC相关的关键基因，可能与基于意识形态的高光合效率玉米新品种育种有关。
结果：CC的遗传力为0.86。六个统计模型(MLM，BLINK,MLMM,FarmCPU,超级,和3VmrMLM）和125万个SNP用于GWAS。共检测到140个数量性状核苷酸(QTNs),3VmrMLM和MLM检测到最多(118)和最少(3)QTNs，分别。QTNs与481个基因相关，解释了0.29-10.28％的表型变异。此外,通过至少两种不同的模型或方法检测到10个共定位的QTNs，在至少两种不同的环境中确定了三个位于同一地点的QTNs，在不同的环境中，通过不同的模型或方法检测到6个共定位的QTNs。此外，基于B73(RefGen_v2)基因组筛选这些稳定QTNs内或附近的69个候选基因。GRMZM2G110408(ZmCCS3)由多个模型和多个环境中识别。该基因的功能表征表明编码的蛋白质可能有助于叶绿素的生物合成。此外,CC在该基因中显著QTN的单倍型之间存在显着差异，单倍型1的CC较高。
结论：这项研究的结果拓宽了我们对CC遗传基础的理解，挖掘与CC相关的关键基因，可能与基于意识形态的高光合效率玉米新品种育种有关。
