Genetic Mapping of the Leaf Number above the Primary Ear and Its Relationship with Plant Height and Flowering Time in Maize

Joint-GWAS, Linkage Mapping, and Transcriptome Analysis to Reveal the Genetic Basis of Plant Architecture-Related Traits in Maize

Plant architecture is one of the key factors affecting maize yield formation and can be divided into secondary traits, such as plant height (PH), ear height (EH), and leaf number (LN). It is a viable approach for exploiting genetic resources to improve plant density. In this study, one natural panel of 226 inbred lines and 150 family lines derived from the offspring of T32 crossed with Qi319 were genotyped by using the MaizeSNP50 chip and the genotyping by sequence (GBS) method and phenotyped under three different environments. Based on the results, a genome-wide association study (GWAS) and linkage mapping were analyzed by using the MLM and ICIM models, respectively. The results showed that 120 QTNs (quantitative trait nucleotides) and 32 QTL (quantitative trait loci) related to plant architecture were identified, including four QTL and 40 QTNs of PH, eight QTL and 41 QTNs of EH, and 20 QTL and 39 QTNs of LN. One dominant QTL, qLN7-2, was identified in the Zhangye environment. Six QTNs were commonly identified to be related to PH, EH, and LN in different environments. The candidate gene analysis revealed that Zm00001d021574 was involved in regulating plant architecture traits through the autophagy pathway, and Zm00001d044730 was predicted to interact with the male sterility-related gene ms26. These results provide abundant genetic resources for improving maize plant architecture traits by using approaches to biological breeding.

Combined linkage mapping and association analysis uncovers candidate genes for 25 leaf-related traits across three environments in maize

Combined linkage and association analysis revealed five co-localized genetic loci across multiple environments. The key gene Zm00001d026491 was further verified to influence leaf length by candidate gene association analysis. Leaf morphology and number determine the canopy structure and thus affect crop yield. Herein, the genetic basis and key genes for 25 leaf-related traits, including leaf lengths (LL), leaf widths (LW), and leaf areas (LA) of eight continuous leaves under the tassel, and the number of leaves above the primary ear (LAE), were dissected by using an association panel and a biparental population. Using an intermated B73 × Mo17 (IBM) Syn10 doubled haploid (DH) population, 290 quantitative trait loci (QTL) controlling these traits were detected across different locations, among which 115 QTL were individually repeatedly identified in at least two environments. Using the association panel, 165 unique significant single-nucleotide polymorphisms (SNPs) were associated with target traits (P < 2.15E-06), of which 35 were separately detected across multiple environments. In total, 42 pleiotropic QTL/SNPs (pQTL/SNPs) were responsible for at least two of the LL, LW, LA, and LAE traits across multiple environments. Combining the QTL mapping and association study, five unique SNPs were located within the confidence intervals of seven QTL, and 77 genes were identified based on the linkage disequilibrium regions of co-localized SNP loci. Gene-based association studies verified that the intragenic variants in the candidate gene Zm00001d026491 influenced LL of the third leaf counted from the top node. These findings will provide vital information to understanding the genetic basis of leaf-related traits and help to cultivate maize varieties with ideal plant architecture.

ZmCCT haplotype H5 improves yield, stalk-rot resistance, and drought tolerance in maize

The ZmCCT locus underlies both stalk-rot resistance and photoperiod sensitivity in maize (Zea mays L.). We previously introduced nine resistant ZmCCT haplotypes into seven elite but susceptible maize inbred lines (containing the haplotype H1) to generate 63 backcross families. Here, we continued backcrossing, followed by selfing, to develop 63 near-isogenic lines (NILs). We evaluated 22 of these NILs for stalk-rot resistance and flowering time under long-day conditions. Lines harboring the haplotype H5 outperformed the others, steadily reducing disease severity, while showing less photoperiod sensitivity. To demonstrate the value of haplotype H5 for maize production, we selected two pairs of NILs, 83B28 ^H1 /83B28 ^H5 and A5302 ^H1 /A5302 ^H5 , and generated F₁ hybrids with the same genetic backgrounds but different ZmCCT alleles: 83B28 ^H1 × A5302 ^H1 , 83B28 ^H1 × A5302 ^H5 , 83B28 ^H5 × A5302 ^H1 , and 83B28 ^H5 × A5302 ^H5 . We performed field trials to investigate yield/yield-related traits, stalk-rot resistance, flowering time, and drought/salt tolerance in these four hybrids. 83B28 ^H5 × A5302 ^H1 performed the best, with significantly improved yield, stalk-rot resistance, and drought tolerance compared to the control (83B28 ^H1 × A5302 ^H1 ). Therefore, the ZmCCT haplotype H5 has great value for breeding maize varieties with high yield potential, stalk-rot resistance, and drought tolerance.

Integrating genome-wide association mapping of additive and dominance genetic effects to improve genomic prediction accuracy in Eucalyptus

Genome-wide association studies (GWAS) is a powerful and widely used approach to decipher the genetic control of complex traits. Still, a significant challenge for dissecting quantitative traits in forest trees is statistical power. This study uses a population consisting of 1,123 samples derived from two successive generations of crosses between Eucalyptus grandis (W. Hill) and E. urophylla (S.T. Blake). All samples have been phenotyped for growth and wood property traits and genotyped using the EuChip60K chip, yielding 37,832 informative single nucleotide polymorphisms (SNPs). We use multi-locus GWAS models to assess additive and dominance effects to identify markers associated with growth and wood property traits in the eucalypt hybrids. Additive and dominance association models identified 78 and 82 significant SNPs across all traits, respectively, which captured between 39 and 86% of the genomic-based heritability. We also used SNPs identified from the GWAS and SNPs using less stringent significance thresholds to evaluate predictive abilities in a genomic selection framework. Genomic selection models based on the top 1% SNPs captured a substantially greater proportion of the genetic variance of traits compared with when we used all SNPs for model training. The prediction ability of estimated breeding values improved significantly for all traits when using either the top 1% SNPs or SNPs identified using a relaxed p value threshold (p < 10^-3 ). This study also highlights the added value of incorporating dominance effects for identifying genomic regions controlling growth traits in trees. Moreover, integrating GWAS results into genomic selection method provides enhanced power relative to discrete associations for identifying genomic variation potentially valuable for forest tree breeding.

Combined QTL mapping and association study reveals candidate genes for leaf number and flowering time in maize

KEY MESSAGE

Twelve QTL for flowering and leaf number were detected. The ZmWRKY14Hap4 could increase leaf number, flowering time and biomass yield which are promising for silage maize breeding. Silage maize, one of the most important feedstock for ruminants, is widely grown from temperate regions to the tropics. Flowering time and leaf number are two significantly correlated traits and important for the quality, adaptation and biomass yield of silage maize. In this study, a recombinant inbred line population consisting of 215 individuals and an association panel of 369 inbred lines were analysed in field conditions in three locations for 2 consecutive years, and five, four and three quantitative trait loci for the total leaf number, days to anthesis (DTA) and silking (DTS) were detected, which could explain 48.55, 35.37 and 34.22% of total phenotypic variation, respectively. Association analysis of qLN10 on chromosome 10 found that ZmWRKY14 was the candidate gene for leaf number, whose expression level was negatively correlated with the leaf number. There are five haplotypes for ZmWRKY14, and haplotype 4 could significantly increase flowering time, leaf number and biomass yield, but has no obvious influence on ear weight. The optimal allelic combination of ZmWRKY14 and ZCN8 could further increase leaf number and biomass yield. The results will provide important genetic information for silage maize breeding.

Mapping and Validation of a Stable Quantitative Trait Locus Conferring Maize Resistance to Gibberella Ear Rot

Gibberella ear rot (GER), a prevalent disease caused by Fusarium graminearum, can result in significant yield loss and carcinogenic mycotoxin contamination in maize worldwide. However, only a few quantitative trait loci (QTLs) for GER resistance have been reported. In this study, we evaluated a Chinese recombinant inbred line (RIL) population comprising 204 lines, developed from a cross between a resistant parent DH4866 and a susceptible line T877, in three field trials under artificial inoculation with F. graminearum. The RIL population and their parents were genotyped with an Affymetrix microarray CGMB56K SNP Array. Based on the genetic linkage map constructed using 1,868 bins as markers, 11 QTLs, including five stable QTLs, were identified by individual environment analysis. Joint multiple environments analysis and epistatic interaction analysis revealed six additive and six epistatic (additive × additive) QTLs, respectively. None of the QTLs could explain more than 10% of phenotypic variation, suggesting that multiple minor-effect QTLs contributed to the genetic component of resistance to GER, and both additive and epistatic effects contributed to the genetic architecture of resistance to GER. A novel QTL, qGER4.09, with the largest effect, identified and validated using 588 F₂ individuals, was colocalized with genomic regions for Fusarium ear rot and Aspergillus ear rot, indicating that this genetic locus likely confers resistance to multiple pathogens and can potentially be utilized in breeding maize varieties aimed at improving the resistance not only to GER but also other ear rot diseases.

Genome-Wide Association Study of Maize Aboveground Dry Matter Accumulation at Seedling Stage

Dry matter accumulation and partitioning during the early phases of development could significantly affect crop growth and productivity. In this study, the aboveground dry matter (DM), the DM of different organs, and partition coefficients of a maize association mapping panel of 412 inbred lines were evaluated at the third and sixth leaf stages (V3 and V6). Further, the properties of these phenotypic traits were analyzed. Genome-wide association studies (GWAS) were conducted on the total aboveground biomass and the DM of different organs. Analysis of GWAS results identified a total of 1,103 unique candidate genes annotated by 678 significant SNPs (P value < 1.28e-6). A total of 224 genes annotated by SNPs at the top five of each GWAS method and detected by multiple GWAS methods were regarded as having high reliability. Pathway enrichment analysis was also performed to explore the biological significance and functions of these candidate genes. Several biological pathways related to the regulation of seed growth, gibberellin-mediated signaling pathway, and long-day photoperiodism were enriched. The results of our study could provide new perspectives on breeding high-yielding maize varieties.

QTL mapping for soybean (Glycine max L.) leaf chlorophyll-content traits in a genotyped RIL population by using RAD-seq based high-density linkage map

BACKGROUND

Different soybean (Glycine max L.) leaf chlorophyll-content traits are considered to be significantly linked to soybean yield. To map the quantitative trait loci (QTLs) of soybean leaf chlorophyll-content traits, an advanced recombinant inbred line (RIL, ZH, Zhonghuang 24 × Huaxia 3) population was adopted to phenotypic data acquisitions for the target traits across six distinct environments (seasons and soybean growth stages). Moreover, the restriction site-associated DNA sequencing (RAD-seq) based high-density genetic linkage map of the RIL population was utilized for QTL mapping by carrying out the composite interval mapping (CIM) approach.

RESULTS

Correlation analyses showed that most traits were correlated with each other under specific chlorophyll assessing method and were regulated both by hereditary and environmental factors. In this study, 78 QTLs for soybean leaf chlorophyll-content traits were identified. Furthermore, 13 major QTLs and five important QTL hotspots were classified and highlighted from the detected QTLs. Finally, Glyma01g15506, Glyma02g08910, Glyma02g11110, Glyma07g15960, Glyma15g19670 and Glyma15g19810 were predicted from the genetic intervals of the major QTLs and important QTL hotspots.

CONCLUSIONS

The detected QTLs and candidate genes may facilitate to gain a better understanding of the hereditary basis of soybean leaf chlorophyll-content traits and may be valuable to pave the way for the marker-assisted selection (MAS) breeding of the target traits.

p-Aminobenzoate Organic Salts as Potential Plant Growth Regulators for Tomatoes

The discovery of environmentally friendly and inexpensive plant growth regulators (PGRs) for agronomically important crops is a necessity and must be considered a priority worldwide. This study provides the synthesis, structure determination and the biological evaluation of two binary organic salts as potential PGRs. New compounds have dual biological activity and are based on natural metabolite p-aminobenzoic acid (pABAH) and different alkanolamines. Studied compounds exhibit hydrogen-bonded 3D supramolecular architectures with different crystal packing due to the formation of one homosynthon and various heterosynthons. The biological profile of new compounds was investigated in laboratory and greenhouse on Solanum lycopersicum L., revealing the efficiency in promoting plant rooting and plant productivity. The results may have a positive impact on agricultural economics, developing new sustainable PGRs for tomatoes.