Identification of a candidate gene underlying qKRN5b for kernel row number in Zea mays L

Dynamic transcriptome landscape of developing maize ear

Seed number and harvesting ability in maize (Zea mays L.) are primarily determined by the architecture of female inflorescence, namely the ear. Therefore, ear morphogenesis contributes to grain yield and as such is one of the key target traits during maize breeding. However, the molecular networks of this highly dynamic and complex grain-bearing inflorescence remain largely unclear. As a first step toward characterizing these networks, we performed a high-spatio-temporal-resolution investigation of transcriptomes using 130 ear samples collected from developing ears with length from 0.1 mm to 19.0 cm. Comparisons of these mRNA populations indicated that these spatio-temporal transcriptomes were clearly separated into four distinct stages stages I, II, III, and IV. A total of 23 793 genes including 1513 transcription factors (TFs) were identified in the investigated developing ears. During the stage I of ear morphogenesis, 425 genes were predicted to be involved in a co-expression network established by eight hub TFs. Moreover, 9714 ear-specific genes were identified in the seven kinds of meristems. Additionally, 527 genes including 59 TFs were identified as especially expressed in ear and displayed high temporal specificity. These results provide a high-resolution atlas of gene activity during ear development and help to unravel the regulatory modules associated with the differentiation of the ear in maize.

GWAS and Meta-QTL Analysis of Yield-Related Ear Traits in Maize

Maize ear traits are an important component of yield, and the genetic basis of ear traits facilitates further yield improvement. In this study, a panel of 580 maize inbred lines were used as the study material, eight ear-related traits were measured through three years of planting, and whole genome sequencing was performed using the maize 40 K breeding chip based on genotyping by targeted sequencing (GBTS) technology. Five models were used to conduct a genome-wide association study (GWAS) on best linear unbiased estimate (BLUE) of ear traits to find the best model. The FarmCPU (Fixed and random model Circulating Probability Unification) model was the best model for this study; a total of 104 significant single nucleotide polymorphisms (SNPs) were detected, and 10 co-location SNPs were detected simultaneously in more than two environments. Through gene function annotation and prediction, a total of nine genes were identified as potentially associated with ear traits. Moreover, a total of 760 quantitative trait loci (QTL) associated with yield-related traits reported in 37 different articles were collected. Using the collected 760 QTL for meta-QTL analysis, a total of 41 MQTL (meta-QTL) associated with yield-related traits were identified, and 19 MQTL detected yield-related ear trait functional genes and candidate genes that have been reported in maize. Five significant SNPs detected by GWAS were located within these MQTL intervals, and another three significant SNPs were close to MQTL (less than 1 Mb). The results provide a theoretical reference for the analysis of the genetic basis of ear-related traits and the improvement of maize yield.

Phenotypic Characterization and Fine Mapping of a Major-Effect Fruit Shape QTL FS5.2 in Cucumber, Cucumis sativus L., with Near-Isogenic Line-Derived Segregating Populations

Cucumber (Cucumis sativus L.) fruit size/shape (FS) is an important yield and quality trait that is quantitatively inherited. Many quantitative trait loci (QTLs) for fruit size/shape have been identified, but very few have been fine-mapped or cloned. In this study, through marker-assisted foreground and background selections, we developed near-isogenic lines (NILs) for a major-effect fruit size/shape QTL FS5.2 in cucumber. Morphological and microscopic characterization of NILs suggests that the allele of fs5.2 from the semi-wild Xishuangbanna (XIS) cucumber (C. s. var. xishuangbannesis) reduces fruit elongation but promotes radial growth resulting in shorter but wider fruit, which seems to be due to reduced cell length, but increased cellular layers. Consistent with this, the NIL carrying the homozygous XIS allele (fs5.2) had lower auxin/IAA contents in both the ovary and the developing fruit. Fine genetic mapping with NIL-derived segregating populations placed FS5.2 into a 95.5 kb region with 15 predicted genes, and a homolog of the Arabidopsis CRABS CLAW (CsCRC) appeared to be the most possible candidate for FS5.2. Transcriptome profiling of NIL fruits at anthesis identified differentially expressed genes enriched in the auxin biosynthesis and signaling pathways, as well as genes involved in cell cycle, division, and cell wall processes. We conclude that the major-effect QTL FS5.2 controls cucumber fruit size/shape through regulating auxin-mediated cell division and expansion for the lateral and longitudinal fruit growth, respectively. The gibberellic acid (GA) signaling pathway also plays a role in FS5.2-mediated fruit elongation.

Identification of two new QTLs of maize (Zea mays L.) underlying kernel row number using the HNAU-NAM1 population

BACKGROUND

Maize kernel row number (KRN) is one of the most important yield traits and has changed greatly during maize domestication and selection. Elucidating the genetic basis of KRN will be helpful to improve grain yield in maize.

RESULTS

Here, we measured KRN in four environments using a nested association mapping (NAM) population named HNAU-NAM1 with 1,617 recombinant inbred lines (RILs) that were derived from 12 maize inbred lines with a common parent, GEMS41. Then, five consensus quantitative trait loci (QTLs) distributing on four chromosomes were identified in at least three environments along with the best linear unbiased prediction (BLUP) values by the joint linkage mapping (JLM) method. These QTLs were further validated by the separate linkage mapping (SLM) and genome-wide association study (GWAS) methods. Three KRN genes cloned through the QTL assay were found in three of the five consensus QTLs, including qKRN1.1, qKRN2.1 and qKRN4.1. Two new QTLs of KRN, qKRN4.2 and qKRN9.1, were also identified. On the basis of public RNA-seq and genome annotation data, five genes highly expressed in ear tissue were considered candidate genes contributing to KRN.

CONCLUSIONS

This study carried out a comprehensive analysis of the genetic architecture of KRN by using a new NAM population under multiple environments. The present results provide solid information for understanding the genetic components underlying KRN and candidate genes in qKRN4.2 and qKRN9.1. Single-nucleotide polymorphisms (SNPs) closely linked to qKRN4.2 and qKRN9.1 could be used to improve inbred yield during molecular breeding in maize.

Fine mapping qKRN5.04 provides a functional gene negatively regulating maize kernel row number

Zm00001d016075 was identified by fine mapping qKRN5.04. The function of Zm00001d016075, negatively modulating maize (Zea Mays L.) kernel row number (KRN), was verified by CRISPR-Cas9. InDel308 located in the promoter of Zm00001d016075 has potential for use as a molecular marker to identify KRN in maize breeding. Kernel row number (KRN), controlled by multiple quantitative trait loci (QTLs), is one of the most important traits that relate to maize production and domestication. Here, fine mapping was conducted to study a major QTL, qKRN5.04, to a 65-kb genomic region using a progeny test strategy in an advanced backcross population, in which Nong531 (N531) and the inbred line of Silunuo (SLN) were employed as the recurrent and the donor parent, respectively. Within this region, there was only one gene (Zm00001d016075) based on the B73 reference genome. Furthermore, we performed regional association mapping using a panel of 236 diverse inbred lines and observed that all significant SNPs were located within Zm00001d016075. The expression of Zm00001d016075 was significantly higher in N531 and qKRN5.04^N531 than qKRN5.04^SLN, resulting from the different promoter activity of Zm00001d016075. Sequence analysis revealed that InDel308, located in the promoter of Zm00001d016075, was related to the KRN variation in different maize inbred lines. Using the CRISPR-Cas9 strategy, we determined Zm00001d016075 played a role in negatively regulating KRN and had a moderate effect on 10-kernel width, 100-kernel weight, kernels per ear, and grain yield per ear. These results provide critical insights on the genetic basis and quantitative variation for KRN.

Genetic Architecture of Grain Yield-Related Traits in Sorghum and Maize

Grain size, grain number per panicle, and grain weight are crucial determinants of yield-related traits in cereals. Understanding the genetic basis of grain yield-related traits has been the main research object and nodal in crop science. Sorghum and maize, as very close C4 crops with high photosynthetic rates, stress tolerance and large biomass characteristics, are extensively used to produce food, feed, and biofuels worldwide. In this review, we comprehensively summarize a large number of quantitative trait loci (QTLs) associated with grain yield in sorghum and maize. We placed great emphasis on discussing 22 fine-mapped QTLs and 30 functionally characterized genes, which greatly hinders our deep understanding at the molecular mechanism level. This review provides a general overview of the comprehensive findings on grain yield QTLs and discusses the emerging trend in molecular marker-assisted breeding with these QTLs.