Comparative mapping of quantitative trait loci for tassel-related traits of maize in $$\hbox {F}_{2:3}$$ F 2 : 3 and RIL populations

Identification of QTLs and their candidate genes for the number of maize tassel branches in F2 from two higher generation sister lines using QTL mapping and RNA-seq analysis

Tassel branch number is an important agronomic trait that is closely associated with maize kernels and yield. The regulation of genes associated with tassel branch development can provide a theoretical basis for analyzing tassel branch growth and improving maize yield. In this study. we used two high-generation sister maize lines, PCU (unbranched) and PCM (multiple-branched), to construct an F2 population comprising 190 individuals, which were genotyped and mapped using the Maize6H-60K single-nucleotide polymorphism array. Candidate genes associated with tassel development were subsequently identified by analyzing samples collected at three stages of tassel growth via RNA-seq. A total of 13 quantitative trait loci (QTLs) and 22 quantitative trait nucleotides (QTNs) associated with tassel branch number (TBN) were identified, among which, two major QTLs, qTBN6.06-1 and qTBN6.06-2, on chromosome 6 were identified in two progeny populations, accounting for 15.07% to 37.64% of the phenotypic variation. Moreover, we identified 613 genes that were differentially expressed between PCU and PCM, which, according to Kyoto Encyclopedia of Genes and Genomes enrichment analysis, were enriched in amino acid metabolism and plant signal transduction pathways. Additionally, we established that the phytohormone content of Stage I tassels and the levels of indole-3-acetic acid (IAA) and IAA-glucose were higher in PCU than in PCM plants, whereas contrastingly, the levels of 5-deoxymonopolyl alcohol in PCM were higher than those in PCU. On the basis of these findings, we speculate that differences in TBN may be related to hormone content. Collectively, by combining QTL mapping and RNA-seq analysis, we identified five candidate genes associated with TBN. This study provides theoretical insights into the mechanism of tassel branch development in maize.

Genome wide association analysis for yield related traits in maize

BACKGROUND

Understanding the genetic basis of yield related traits contributes to the improvement of grain yield in maize.

RESULTS

Using 291 excellent maize inbred lines as materials, six yield related traits of maize, including grain yield per plant (GYP), grain length (GL), grain width (GW), kernel number per row (KNR), 100 kernel weight (HKW) and tassel branch number (TBN) were investigated in Jinan, in 2017, 2018 and 2019. The average values of three environments were taken as the phenotypic data of yield related traits, and they were statistically analyzed. Based on 38,683 high-quality SNP markers in the whole genome of the association panel, the MLM with PCA model was used for genome-wide association analysis (GWAS) to obtain 59 significantly associated SNP sites. Moreover, 59 significantly associated SNPs (P < 0.0001) referring to GYP, GL, GW, KNR, HKW and TBN, of which 14 SNPs located in yield related QTLs/QTNs previously reported. A total of 66 candidate genes were identified based on the 59 significantly associated SNPs, of which 58 had functional annotation.

CONCLUSIONS

Using genome-wide association analysis strategy to identify genetic loci related to maize yield, a total of 59 significantly associated SNP were detected. Those results aid in our understanding of the genetic architecture of maize yield and provide useful SNPs for genetic improvement of maize.

Emerging roles of the ubiquitin-proteasome pathway in enhancing crop yield by optimizing seed agronomic traits

Ubiquitin-proteasome pathway has the potential to modulate crop productivity by influencing agronomic traits. Being sessile, the plant often uses the ubiquitin-proteasome pathway to maintain the stability of different regulatory proteins to survive in an ever-changing environment. The ubiquitin system influences plant reproduction, growth, development, responses to the environment, and processes that control critical agronomic traits. E3 ligases are the major players in this pathway, and they are responsible for recognizing and tagging the targets/substrates. Plants have a variety of E3 ubiquitin ligases, whose functions have been studied extensively, ranging from plant growth to defense strategies. Here we summarize three agronomic traits influenced by ubiquitination: seed size and weight, seed germination, and accessory plant agronomic traits particularly panicle architecture, tillering in rice, and tassels branch number in maize. This review article highlights some recent progress on how the ubiquitin system influences the stability/modification of proteins that determine seed agronomic properties like size, weight, germination and filling, and ultimately agricultural productivity and quality. Further research into the molecular basis of the aforementioned processes might lead to the identification of genes that could be modified or selected for crop development. Likewise, we also propose advances and future perspectives in this regard.

Genetic Structure and Molecular Mechanisms Underlying the Formation of Tassel, Anther, and Pollen in the Male Inflorescence of Maize (Zea mays L.)

Maize tassel is the male reproductive organ which is located at the plant’s apex; both its morphological structure and fertility have a profound impact on maize grain yield. More than 40 functional genes regulating the complex tassel traits have been cloned up to now. However, the detailed molecular mechanisms underlying the whole process, from male inflorescence meristem initiation to tassel morphogenesis, are seldom discussed. Here, we summarize the male inflorescence developmental genes and construct a molecular regulatory network to further reveal the molecular mechanisms underlying tassel-trait formation in maize. Meanwhile, as one of the most frequently studied quantitative traits, hundreds of quantitative trait loci (QTLs) and thousands of quantitative trait nucleotides (QTNs) related to tassel morphology have been identified so far. To reveal the genetic structure of tassel traits, we constructed a consensus physical map for tassel traits by summarizing the genetic studies conducted over the past 20 years, and identified 97 hotspot intervals (HSIs) that can be repeatedly mapped in different labs, which will be helpful for marker-assisted selection (MAS) in improving maize yield as well as for providing theoretical guidance in the subsequent identification of the functional genes modulating tassel morphology. In addition, maize is one of the most successful crops in utilizing heterosis; mining of the genic male sterility (GMS) genes is crucial in developing biotechnology-based male-sterility (BMS) systems for seed production and hybrid breeding. In maize, more than 30 GMS genes have been isolated and characterized, and at least 15 GMS genes have been promptly validated by CRISPR/Cas9 mutagenesis within the past two years. We thus summarize the maize GMS genes and further update the molecular regulatory networks underlying male fertility in maize. Taken together, the identified HSIs, genes and molecular mechanisms underlying tassel morphological structure and male fertility are useful for guiding the subsequent cloning of functional genes and for molecular design breeding in maize. Finally, the strategies concerning efficient and rapid isolation of genes controlling tassel morphological structure and male fertility and their application in maize molecular breeding are also discussed.

QDtbn1 , an F-box gene affecting maize tassel branch number by a dominant model

Tassel branch number (TBN) is one of the important agronomic traits that directly contribute to grain yield in maize (Zea mays L.), and identification of genes precisely regulating TBN in the parental lines is important for maize hybrid breeding. In this study, a quantitative trait nucleotide (QTN), Q^Dtbn1 , related to tassel branch number was identified using a testcrossing association mapping population through association mapping with the Indels/SNPs in the 5'-UTR (untranslated region) of Zm00001d053358, which encodes a Kelch repeat-containing F-box protein. Q^Dtbn1 was further confirmed to be associated with TBN by a dominant model using an F₂ population, and over-expressing of the candidate gene resulted in a decreasing of TBN, implying that Q^Dtbn1 was governed by the candidate gene with a negative model. This makes Q^Dtbn1 very useful in maize hybrid breeding. Q^Dtbn1 could interact with a maize Skp1-like protein and a SnRK1 protein, and the SnRK1 could also interact with a SnRK2.8 protein. In addition, quantitative real-time PCR assay showed that five substrates of SnRK2 were down-regulated in the over-expressed plants. These imply that the SCF (Skp1/Cul1/F-box protein/Roc1) complex and ABA signal pathway might be involved in the modulation of TBN in maize.

QTL Analysis of Five Morpho-Physiological Traits in Bread Wheat Using Two Mapping Populations Derived from Common Parents

Traits such as plant height (PH), juvenile growth habit (GH), heading date (HD), and tiller number are important for both increasing yield potential and improving crop adaptation to climate change. In the present study, these traits were investigated by using the same bi-parental population at early (F₂ and F₂-derived F₃ families) and late (F₆ and F₇, recombinant inbred lines, RILs) generations to detect quantitative trait loci (QTLs) and search for candidate genes. A total of 176 and 178 lines were genotyped by the wheat Illumina 25K Infinium SNP array. The two genetic maps spanned 2486.97 cM and 3732.84 cM in length, for the F₂ and RILs, respectively. QTLs explaining the highest phenotypic variation were found on chromosomes 2B, 2D, 5A, and 7D for HD and GH, whereas those for PH were found on chromosomes 4B and 4D. Several QTL detected in the early generations (i.e., PH and tiller number) were not detected in the late generations as they were due to dominance effects. Some of the identified QTLs co-mapped to well-known adaptive genes (i.e., Ppd-1, Vrn-1, and Rht-1). Other putative candidate genes were identified for each trait, of which PINE1 and PIF4 may be considered new for GH and TTN in wheat. The use of a large F₂ mapping population combined with NGS-based genotyping techniques could improve map resolution and allow closer QTL tagging.