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Abstract Background Stalk fracture caused by strong wind can severely reduce yields in maize. Stalks with higher stiffness and flexibility will exhibit stronger lodging resistance. However, stalk flexibility is rarely studied in maize. Stalk fracture of the internode above the ear before tasseling will result in the lack of tassel and pollen, which is devastating for pollination in seed production. In this study, we focused on stalk lodging before tasseling in two maize inbred lines, JING724 and its improved line JING724A1 and their F2:3 population. Results JING724A1 showed a larger stalk fracture angle than JING724, indicating higher flexibility. In addition, compared to JING724, JING724A1 also had longer and thicker stalks, with a conical, frustum-shaped internode above the ear. Microscopy and X-ray microcomputed tomography of the internal stalk architecture revealed that JING724A1 had more vascular bundles and thicker sclerenchyma tissue. Furthermore, total soluble sugar content of JING724A1, especially the glucose component, was substantially higher than in JING724. Using an F2:3 population derived from a JING724 and JING724A1 cross, we performed bulk segregant analysis for stalk fracture angle and detected one QTL located on Chr3: 14.00–19.28 Mb. Through transcriptome data analysis and ∆ (SNP-index), we identified two candidate genes significantly associated with high stalk fracture angle, which encode a RING/U-box superfamily protein (Zm00001d039769) and a MADS-box transcription factor 54 (Zm00001d039913), respectively. Two KASP markers designed from these two candidate genes also showed significant correlations with stalk fracture angle. Conclusions The internode shape and glucose content are possibly correlated with stalk flexibility in maize. Two genes in the detected QTL are potentially associated with stalk fracture angle. These novel phenotypes and associated loci will provide a theoretical foundation for understanding the genetic mechanisms of lodging, and facilitate the selection of maize varieties with improved flexibility and robust lodging resistance.

Abstract Background Kernel row number (KRN) is an important trait for the domestication and improvement of maize. Exploring the genetic basis of KRN has great research significance and can provide valuable information for molecular assisted selection. Results In this study, one single-locus method (MLM) and six multilocus methods (mrMLM, FASTmrMLM, FASTmrEMMA, pLARmEB, pKWmEB and ISIS EM-BLASSO) of genome-wide association studies (GWASs) were used to identify significant quantitative trait nucleotides (QTNs) for KRN in an association panel including 639 maize inbred lines that were genotyped by the MaizeSNP50 BeadChip. In three phenotyping environments and with best linear unbiased prediction (BLUP) values, the seven GWAS methods revealed different numbers of KRN-associated QTNs, ranging from 11 to 177. Based on these results, seven important regions for KRN located on chromosomes 1, 2, 3, 5, 9, and 10 were identified by at least three methods and in at least two environments. Moreover, 49 genes from the seven regions were expressed in different maize tissues. Among the 49 genes, ARF29 (Zm00001d026540, encoding auxin response factor 29) and CKO4 (Zm00001d043293, encoding cytokinin oxidase protein) were significantly related to KRN, based on expression analysis and candidate gene association mapping. Whole-genome prediction (WGP) of KRN was also performed, and we found that the KRN-associated tagSNPs achieved a high prediction accuracy. The best strategy was to integrate all of the KRN-associated tagSNPs identified by all GWAS models. Conclusions These results aid in our understanding of the genetic architecture of KRN and provide useful information for genomic selection for KRN in maize breeding.

Abstract Background The kernel row number (KRN) of an ear is an important trait related to yield and domestication in maize. Exploring the underlying genetic mechanisms of KRN has great research significance and application potential. Results In the present study, N531 with a KRN of 18–22 and SLN with a KRN of 4–6 were used as the recurrent parent and the donor parent, respectively, to develop two introgression lines (ILs), IL_A and IL_B, both of which have common negative-effect alleles from SLN on chromosomes 1, 5 and 10 and significantly reduced inflorescence meristem (IM) diameter and KRN compared with those of N531. We used RNA-Seq to investigate the transcriptome profiles of 5-mm immature ears of N531, IL_A and IL_B. We identified a total of 2872 differentially expressed genes (DEGs) between N531 and IL_A, 2428 DEGs between N531 and IL_B and 1811 DEGs between IL_A and IL_B. A total of 1252 DEGs were detected as overlapping DEGs, and 89 DEGs were located on the common introgression fragments. Furthermore, three DEGs (Zm00001d013277, Zm00001d015310 and Zm00001d015377) containing three SNPs associated with KRN were identified using regional association mapping. Conclusions These results will facilitate our understanding of ear development and provide important candidate genes for further study on KRN.

Abstract Background The pentatricopeptide repeat (PPR) gene family is one of the largest gene families in land plants (450 PPR genes in Arabidopsis, 477 PPR genes in rice and 486 PPR genes in foxtail millet) and is important for plant development and growth. Most PPR genes are encoded by plastid and mitochondrial genomes, and the gene products regulate the expression of the related genes in higher plants. However, the functions remain largely unknown, and systematic analysis and comparison of the PPR gene family in different maize genomes have not been performed. Results In this study, systematic identification and comparison of PPR genes from two elite maize inbred lines, B73 and PH207, were performed. A total of 491 and 456 PPR genes were identified in the B73 and PH207 genomes, respectively. Basic bioinformatics analyses, including of the classification, gene structure, chromosomal location and conserved motifs, were conducted. Examination of PPR gene duplication showed that 12 and 15 segmental duplication gene pairs exist in the B73 and PH207 genomes, respectively, with eight duplication events being shared between the two genomes. Expression analysis suggested that 53 PPR genes exhibit qualitative variations in the different genetic backgrounds. Based on analysis of the correlation between PPR gene expression in kernels and kernel-related traits, four PPR genes are significantly negatively correlated with hundred kernel weight, 12 are significantly negatively correlated with kernel width, and eight are significantly correlated with kernel number. Eight of the 24 PPR genes are also located in metaQTL regions associated with yield and kernel-related traits in maize. Two important PPR genes (GRMZM2G353195 and GRMZM2G141202) might be regarded as important candidate genes associated with maize kernel-related traits. Conclusions Our results provide a more comprehensive understanding of PPR genes in different maize inbred lines and identify important candidate genes related to kernel development for subsequent functional validation in maize.

Background: Kernel weight and size are important components of grain yield in cereals. Although some information is available concerning the map positions of quantitative trait loci (QTL) for kernel weight and size in maize, little is known about the molecular mechanisms of these QTLs. qGW4.05 is a major QTL that is associated with kernel weight and size in maize. We combined linkage analysis and association mapping to fine-map and identify candidate gene(s) at qGW4.05. Results: QTL qGW4.05 was fine-mapped to a 279.6-kb interval in a segregating population derived from a cross of Huangzaosi with LV28. By combining the results of regional association mapping and linkage analysis, we identified GRMZM2G039934 as a candidate gene responsible for qGW4.05. Candidate gene-based association mapping was conducted using a panel of 184 inbred lines with variable kernel weights and kernel sizes. Six polymorphic sites in the gene GRMZM2G039934 were significantly associated with kernel weight and kernel size. Conclusion: The results of linkage analysis and association mapping revealed that GRMZM2G039934 is the most likely candidate gene for qGW4.05. These results will improve our understanding of the genetic architecture and molecular mechanisms underlying kernel development in maize. [ABSTRACT FROM AUTHOR]

Background: Exploring genetic differentiation and genomic variation is important for both the utilization of heterosis and the dissection of the genetic bases of complex traits. Methods: We integrated 1857 diverse maize accessions from America, Africa, Europe and Asia to investigatetheir genetic differentiation, genomic variation using 43,252 high-quality single-nucleotide polymorphisms(SNPs),combing GWAS and linkage analysis strategy to exploring the function of relevant genetic segments. Results: We uncovered many more subpopulations that recently or historically formed during the breeding process. These patterns are represented by the following lines: Mo17, GB, E28, Ye8112, HZS, Shen137, PHG39, B73, 207, A634, Oh43, Reid Yellow Dent, and the Tropical/subtropical (TS) germplasm. A total of 85 highly differentiated regions with a DEST of more than 0.2 were identified between the TS and temperate subpopulations. These regions comprised 79 % of the genetic variation, and most were significantly associated with adaptive traits. For example, the region containing the SNP tag PZE.108075114 was highly differentiated, and this region was significantly associated with flowering time (FT)-related traits, as supported by a genome-wide association study (GWAS) within the interval of FTrelated quantitative trait loci (QTL). This region was also closely linked to zcn8 and vgt1, which were shown to be involved in maize adaptation. Most importantly, 197 highly differentiated regions between different subpopulation pairs were located within an FT- or plant architecture-related QTL. Conclusions: Here we reported that 700-1000 SNPs were necessary needed to robustly estimate the genetic differentiation of a naturally diverse panel. In addition, 13 subpopulations were observed in maize germplasm, 85 genetic regions with higher differentiation between TS and temperate maize germplasm, 197 highly differentiated regions between different subpopulation pairs, which contained some FT-related QTNs/QTLs/genes supported by GWAS and linkage analysis, and these regions were expected to play important roles in maize adaptation. [ABSTRACT FROM AUTHOR]