Identification of Crowding Stress Tolerance Co-Expression Networks Involved in Sweet Corn Yield

Mapping of flumioxazin tolerance in a snap bean diversity panel leads to the discovery of a master genomic region controlling multiple stress resistance genes

Introduction

Effective weed management tools are crucial for maintaining the profitable production of snap bean (Phaseolus vulgaris L.). Preemergence herbicides help the crop to gain a size advantage over the weeds, but the few preemergence herbicides registered in snap bean have poor waterhemp (Amaranthus tuberculatus) control, a major pest in snap bean production. Waterhemp and other difficult-to-control weeds can be managed by flumioxazin, an herbicide that inhibits protoporphyrinogen oxidase (PPO). However, there is limited knowledge about crop tolerance to this herbicide. We aimed to quantify the degree of snap bean tolerance to flumioxazin and explore the underlying mechanisms.

Methods

We investigated the genetic basis of herbicide tolerance using genome-wide association mapping approach utilizing field-collected data from a snap bean diversity panel, combined with gene expression data of cultivars with contrasting response. The response to a preemergence application of flumioxazin was measured by assessing plant population density and shoot biomass variables.

Results

Snap bean tolerance to flumioxazin is associated with a single genomic location in chromosome 02. Tolerance is influenced by several factors, including those that are indirectly affected by seed size/weight and those that directly impact the herbicide's metabolism and protect the cell from reactive oxygen species-induced damage. Transcriptional profiling and co-expression network analysis identified biological pathways likely involved in flumioxazin tolerance, including oxidoreductase processes and programmed cell death. Transcriptional regulation of genes involved in those processes is possibly orchestrated by a transcription factor located in the region identified in the GWAS analysis. Several entries belonging to the Romano class, including Bush Romano 350, Roma II, and Romano Purpiat presented high levels of tolerance in this study. The alleles identified in the diversity panel that condition snap bean tolerance to flumioxazin shed light on a novel mechanism of herbicide tolerance and can be used in crop improvement.

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.

Historical Trends in Sweet Corn Plant Density Tolerance Using Era Hybrids (1930-2010s)

Over the last six decades, steady improvement in plant density tolerance (PDT) has been one of the largest contributors to genetic yield gain in field corn. While recent research indicates that PDT in modern sweet corn hybrids could be exploited to improve yield, historical changes in PDT in sweet corn are unknown. The objectives of this study were to: (a) quantify the extent to which PDT has changed since introduction of hybrid sweet corn and (b) determine the extent to which changes over time in PDT are associated with plant morpho-physiological and ear traits. An era panel was assembled by recreating 15 sugary1 sweet corn hybrids that were widely used at one time in the United States, representing hybrids since the 1930s. Era hybrids were evaluated in field experiments in a randomized complete block design with a split-plot arrangement of treatments, including hybrid as the main factor and density as the split-plot factor. Plant density treatments included "Low" plant density (9,900 plants/ha) free of crowding stress or "High" plant density (79,000 plants/ha) with crowding stress. On average, per-area marketable ear mass (Mt/ha) increased at a rate of 0.8 Mt/ha/decade at High densities, whereas per-plant yield (i.e., kg/plant) remained unchanged over time regardless of the density level. Crate yield, a fresh market metric, improved for modern hybrids. However, processing sweet corn yield metrics like fresh kernel mass and recovery (amount of kernel mass contributing to the fresh ear mass) showed modest or no improvement over time, respectively. Modern sweet corn hybrids tend to have fewer tillers and lower fresh shoot biomass, potentially allowing the use of higher plant density; however, plant architecture alone does not accurately predict PDT of individual hybrids.

Transcriptional analysis of sweet corn hybrids in response to crowding stress

Crop tolerance to crowding stress, specifically plant population density, is an important target to improve productivity in processing sweet corn. Due to limited knowledge of biological mechanisms involved in crowding stress in sweet corn, a study was conducted to 1) investigate phenotypic and transcriptional response of sweet corn hybrids under different plant densties, 2) compare the crowding stress response mechanisms between hybrids and 3) identify candidate biological mechanisms involved in crowding stress response. Yield per hectare of a tolerant hybrid (DMC21-84) increased with plant density. Yield per hectare of a sensitive hybrid (GSS2259P) declined with plant density. Transcriptional analysis found 694, 537, 359 and 483 crowding stress differentially expressed genes (DEGs) for GSS2259P at the Fruit Farm and Vegetable Farm and for DMC21-84 at the Fruit Farm and Vegetable Farm, respectively. Strong transcriptional change due to hybrid was observed. Functional analyses of DEGs involved in crowding stress also revealed that protein folding and photosynthetic processes were common response mechanisms for both hybrids. However, DEGs related to starch biosynthetic, carbohydrate metabolism, and ABA related processes were significant only for DMC21-84, suggesting the genes have closer relationship to plant productivity under stress than other processes. These results collectively provide initial insight into potential crowding stress response mechanisms in sweet corn.

Friends, neighbours and enemies: an overview of the communal and social biology of plants

Plants were traditionally seen as rather passive actors in their environment, interacting with each other only in so far as they competed for the same resources. In the last 30 years, this view has been spectacularly overturned, with a wealth of evidence showing that plants actively detect and respond to their neighbours. Moreover, there is evidence that these responses depend on the identity of the neighbour, and that plants may cooperate with their kin, displaying social behaviour as complex as that observed in animals. These plant-plant interactions play a vital role in shaping natural ecosystems, and are also very important in determining agricultural productivity. However, in terms of mechanistic understanding, we have only just begun to scratch the surface, and many aspects of plant-plant interactions remain poorly understood. In this review, we aim to provide an overview of the field of plant-plant interactions, covering the communal interactions of plants with their neighbours as well as the social behaviour of plants towards their kin, and the consequences of these interactions. We particularly focus on the mechanisms that underpin neighbour detection and response, highlighting both progress and gaps in our understanding of these fascinating but previously overlooked interactions.

Sweet Corn Research around the World 2015–2020

Modern sweet corn is distinguished from other vegetable corns by the presence of one or more recessive alleles within the maize endosperm starch synthesis pathway. This results in reduced starch content and increased sugar concentration when consumed fresh. Fresh sweet corn originated in the USA and has since been introduced in countries around the World with increasing popularity as a favored vegetable choice. Several reviews have been published recently on endosperm genetics, breeding, and physiology that focus on the basic biology and uses in the US. However, new questions concerning sustainability, environmental care, and climate change, along with the introduction of sweet corn in other countries have produced a variety of new uses and research activities. This review is a summary of the sweet corn research published during the five years preceding 2021.

Transcriptome Analysis of Carbohydrate Metabolism Genes and Molecular Regulation of Sucrose Transport Gene LoSUT on the Flowering Process of Developing Oriental Hybrid Lily 'Sorbonne' Bulb

The quality of Lily cut flower was determined by the quality of bulbs. During the process of vernalization and flower bud differentiation, sugar massively accumulated in the bulb, which influenced the bulb development. However, the details of sugar genes’ regulation mechanism for these processes were not fully understood. Here, morphological physiology, transcriptomes and gene engineering technology were used to explore this physiological change. Seventy-two genes of 25 kinds of sugar metabolism-related genes were annotated after re-analyzing transcriptome data of Oriental hybrid lily ‘Sorbonne’ bulbs, which were generated on Hiseq Illumina 2000. The results showed that these genes were closely related to lily bulb vernalization and development. Combining gene expression pattern with gene co-expression network, five genes (Contig5669, Contig13319, Contig7715, Contig1420 and Contig87292) were considered to be the most potential signals, and the sucrose transporter gene (SUT) was the focus of this study. Carbohydrate transport pathway and genes’ regulation mechanism were inferred through a physiological and molecular test. SUT seemed to be the sugar sensor that could sense and regulate sugar concentration, which might have effects on other genes, such as FT, LFY and so on. LoSUT2 and LoSUT4 genes were cloned from Oriental hybrid lily ‘Sorbonne’ by RACE, which was the first time for these genes in Oriental hybrid lily ‘Sorbonne’. The physiological properties of these proteins were analyzed such as hydrophobicity and phosphorylation. In addition, secondary and tertiary structures of proteins were predicted, which indicated the two proteins were membrane proteins. Their cellular locations were verified through positioning the experiment of the fluorescent vector. They were highly expressed in cells around phloem, which illustrated the key role of these genes in sugar transport. Furthermore, transient expression assays showed that overexpressed LoSUT2 and LoSUT4 in Arabidopsis thaliana bloomed significantly earlier than the wild type and the expression of FT, SOC1 and LFY were also affected by LoSUT2 and LoSUT4, which indicated that LoSUT2 and LoSUT4 may regulate plants flowering time.

Optimum plant density for crowding stress tolerant processing sweet corn

Globally, gains in sweet corn [Zea mays L.var. rugosa (or saccharata)] are a fraction of the yield advances made in field corn (Zea mays L.) in the last half-century. Grain yield improvement of field corn is associated with increased tolerance to higher plant densities (i.e., crowding stress). Processing sweet corn hybrids that tolerate crowding stress have been identified; however, such hybrids appear to be under-planted in the processing sweet corn. Using crowding stress tolerant (CST) hybrids, the objectives of this study were to: (1) identify optimum plant densities for a range of growing conditions; (2) quantify gaps in production between current and optimum plant densities; and (3) enumerate changes in yield and ear traits when shifting from current to optimum plant densities. Using a CST shrunken-2 (sh2) processing sweet corn hybrid, on-farm plant density trials were conducted in thirty fields across the states of Illinois, Minnesota and Wisconsin, from 2013 to 2017 in order to capture a wide variety of growing conditions. Linear mixed-effects models were used to identify the optimum plant density corresponding to maximum ear mass (Mt ha^-1), case production (cases ha^-1), and profitability to the processor ($ ha^-1). Kernel moisture, indicative of plant development, was unaffected by plant density. Ear traits, such as ear number and ear mass per plant, average ear length, and filled ear length declined linearly with increasing plant density. Nonetheless, there was a large economic benefit to the grower and processor by shifting to higher plant densities in most environments. This research shows that increasing plant densities of CST hybrids from current (58,475 plants ha^-1) to optimum (73,075 plants ha^-1) could improve processing sweet corn green ear yield and processor profitability on average of 1.13 Mt ha^-1 and $525 ha^-1, respectively.

QTL mapping for maize starch content and candidate gene prediction combined with co-expression network analysis

A major QTL Qsta9.1 was identified on chromosome 9, combined with GWAS, and co-expression network analysis showed that GRMZM2G110929 and GRMZM5G852704 are the potential candidates for association with maize kernel starch content. Increasing maize kernel starch content may not only lead to higher maize kernel yields and qualities, but also help meet industry demands. By using the intermated B73 × Mo17 population, QTLs were mapped for starch content in this study. A major QTL Qsta9.1 was detected in a 1.7 Mb interval on chromosome 9 and validated by allele frequency analysis in extreme tails of a newly constructed segregating population. According to genome-wide association study (GWAS) based on genotyping of a natural population, we identified a significant SNP for starch content within the ORF region of GRMZM5G852704_T01 colocalized with QTL Qsta9.1. Co-expression network analysis was also conducted, and 28 modules were constructed during six seed developmental stages. Functional enrichment was performed for each module, and one module showed the most possibility for the association with carbohydrate-related processes. In this module, one transcripts GRMZM2G110929_T01 located in the Qsta9.1 assigned 1.7 Mb interval encoding GLABRA2 expression modulator. Its expression level in B73 was lower than that in Mo17 across all seed developmental stages, implying the possibility for the candidate gene of Qsta9.1. Our studies combined GWAS, mRNA profiling, and traditional QTL analyses to identify a major locus for controlling seed starch content in maize.

Transcriptional Regulatory Network of GA Floral Induction Pathway in LA Hybrid Lily

BACKGROUND

The LA hybrid lily 'Aladdin' has both excellent traits of Longiflorum hybrids and Asiatic hybrids-such as big and vivid flower, strong stem, high self-propagation coefficient, and shorter low temperature time required to release bulb dormancy in contrast to Oriental hybrids. A genome-wide transcriptional analysis using transcriptome RNA-Seq was performed in order to explore whether there is a gibberellin floral induction pathway in the LA hybrid lily. Subsequently, gene co-expression network analysis was used to analyze the possible interactions of key candidate genes screened from transcriptome data. At the same time, a series of physiological, biochemical, and cultivation tests were carried out.

RESULTS

The content of five endogenous hormones changed sharply in the shoot apex during the treatment of 200 mg/L exogenous gibberellin and the ratio of ABA/GA3 dropped and stayed at a lower level after 4 hours' treatment from the higher levels initially, reaching a dynamic balance. In addition, the metabolism of carbohydrates in the bulbs increase during exogenous gibberellin treatment. A total of 124,041 unigenes were obtained by RNA-seq. With the transcriptome analysis, 48,927 unigenes and 48,725 unigenes respectively aligned to the NR database and the Uniprot database. 114,138 unigenes, 25,369 unigenes, and 19,704 unigenes respectively aligned to the COG, GO, and KEGG databases. 2148 differentially expression genes (DEGs) were selected with the indicators RPKM ≥ 0, FDR ≤ 0.05 and |log2(ratio)| ≥ 2. The number of the upregulated unigenes was significantly more than the number of the downregulated unigenes. Some MADS-box genes related to flowering transformation-such as AGL20, SOC1, and CO-were found to be upregulated. A large number of gibberellin biosynthesis related genes such as GA2ox, GA3ox, GA20ox, Cytochrome P450, CYP81, and gibberellin signal transduction genes such as DELLA, GASA, and GID1 were significantly differentially expressed. The plant hormones related genes such as NCED3 and sugar metabolism related genes such as α-amylase, sucrose synthase hexokinase, and so on were also found expressing differentially. In addition, stress resistance related genes such as LEA1, LEA2, LEA4, serine/threonine protein kinase, LRR receptor-like serine/threonine protein kinase, P34 kinase, histidine kinase 3 and epigenetic related genes in DNA methylation, histone methylation, acetylation, ubiquitination of ribose were also found. Particularly, a large number of transcription factors responsive to the exogenous gibberellin signal including WRKY40, WRKY33, WRKY27, WRKY21, WRKY7, MYB, AP2/EREBP, bHLH, NAC1, NAC2, and NAC11 were found to be specially expressing. 30 gene sequences were selected from a large number of differentially expressed candidate genes for qRT-PCR expression verification (0, 2, 4, 8, and 16 h) and compared with the transcriptome expression levels.

CONCLUSIONS

200mg/L exogenous GA3 can successfully break the bulb's dormancy of the LA hybrid lily and significantly accelerated the flowering process, indicating that gibberellin floral induction pathway is present in the LA lily 'Aladdin'. With the GCNs analysis, two second messenger G protein-coupled receptor related genes that respond to gibberellin signals in the cell were discovered. The downstream transport proteins such as AMT, calcium transport ATPase, and plasma membrane ATPase were also discovered participating in GA signal transduction. Transcription factors including WRKY7, NAC2, NAC11, and CBF specially regulated phosphorylation and glycosylation during the ubiquitination degradation process of DELLA proteins. These transcription factors also activated in abscisic acid metabolism. A large number of transcription factors such as WRKY21, WRKY22, NAC1, AP2, EREB1, P450, and CYP81 that both regulate gibberellin signaling and low-temperature signals have also been found. Finally, the molecular mechanism of GA floral induction pathway in the LA hybrid lily 'Aladdin' was constructed.

The genetics underlying natural variation of plant-plant interactions, a beloved but forgotten member of the family of biotic interactions

Despite the importance of plant-plant interactions on crop yield and plant community dynamics, our understanding of the genetic and molecular bases underlying natural variation of plant-plant interactions is largely limited in comparison with other types of biotic interactions. By listing 63 quantitative trait loci (QTL) mapping and global gene expression studies based on plants directly challenged by other plants, we explored whether the genetic architecture and the function of the candidate genes underlying natural plant-plant interactions depend on the type of interactions between two plants (competition versus commensalism versus reciprocal helping versus asymmetry). The 16 transcriptomic studies are unevenly distributed between competitive interactions (n = 12) and asymmetric interactions (n = 4, all focusing on response to parasitic plants). By contrast, 17 and 30 QTL studies were identified for competitive interactions and asymmetric interactions (either weed suppressive ability or response to parasitic plants), respectively. Surprisingly, no studies have been carried out on the identification of genetic and molecular bases underlying natural variation in positive interactions. The candidate genes underlying natural plant-plant interactions can be classified into seven categories of plant function that have been identified in artificial environments simulating plant-plant interactions either frequently (photosynthesis, hormones), only recently (cell wall modification and degradation, defense pathways against pathogens) or rarely (ABC transporters, histone modification and meristem identity/life history traits). Finally, we introduce several avenues that need to be explored in the future to obtain a thorough understanding of the genetic and molecular bases underlying plant-plant interactions within the context of realistic community complexity.