Stripe rust caused by Puccinia striiformis f. sp. tritici threatens worldwide wheat production. Growing resistant cultivars is the best way to control this disease. Chinese wheat cultivar Qinnong 142 (QN142) has a high level of adult-plant resistance to stripe rust. To identify quantitative trait loci (QTLs) related to stripe rust resistance, we developed a recombinant inbred line (RIL) population from a cross between QN142 and susceptible cultivar Avocet S. The parents and 165 F6 RILs were evaluated in terms of their stripe rust infection type and disease severity in replicated field tests with six site-year environments. The parents and RILs were genotyped with single-nucleotide polymorphism (SNP) markers. Four stable QTLs were identified in QN142 and mapped to chromosome arms 1BL, 2AL, 2BL, and 6BS. The 1BL QTL was probably the known resistance gene Yr29, the 2BL QTL was in a resistance gene-rich region, and the 2AL and 6BS QTLs might be new. Kompetitive allele specific polymerase chain reaction markers developed from the SNP markers flanking these QTLs were highly polymorphic in a panel of 150 wheat cultivars and breeding lines. These markers could be used in marker-assisted selection for incorporating the stripe rust resistance QTL into new wheat cultivars.

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. Conclusion 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.

Summary The peduncle vascular system of maize is critical for the transport of photosynthetic products, nutrients, and water from the roots and leaves to the ear. Accordingly, it positively affects the grain yield. However, the genetic basis of peduncle vascular bundle (PVB)‐related traits in maize remains unknown. Thus, 15 PVB‐related traits of 386 maize inbred lines were investigated at three locations (Yongcheng, 17YC; Kaifeng, 20KF; and Yuanyang, 20YY). The repeatability for the 15 traits ranged from 35.53% to 92.13%. A genome‐wide association study was performed and 69 non‐redundant quantitative trait loci (QTL) were detected, including 9, 41, and 27 QTL identified at 17YC, 20KF, and 20YY, respectively. These QTL jointly explained 4.72% (SLL) to 37.30% (NSVB) of the phenotypic variation. Eight QTL were associated with the same trait at two locations. Furthermore, four pleiotropic QTL were identified. Moreover, one QTL (qPVB44), associated with NSVB_20KF, was co‐localized with a previously reported locus related to kernel width, implying qPVB44 may affect the kernel width by modulating the number of small vascular bundles. Examinations of the 69 QTL identified 348 candidate genes that were classified in five groups. Additionally, 26 known VB‐related homologous genes (e.g. VLN2, KNOX1, and UGT72B3) were detected in 20 of the 69 QTL. A comparison of the NSVB between a Zmvln2 EMS mutant and its wild type elucidated the function of the candidate gene ZmVLN2. These results are important for clarifying the genetic basis of PVB‐related traits and may be useful for breeding new high‐yielding maize cultivars.

Background The chlorophyll content (CC) is a key factor affecting plant 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.Conclusion This study 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.