This review summarizes the allelic series, effects, interactions between genes and with the environment, for the major flowering time genes that drive phenological adaptation of barley. The optimization of phenology is a major goal of plant breeding addressing the production of high-yielding varieties adapted to changing climatic conditions. Flowering time in cereals is regulated by genetic networks that respond predominately to day length and temperature. Allelic diversity at these genes is at the basis of barley wide adaptation. Detailed knowledge of their effects, and genetic and environmental interactions will facilitate plant breeders manipulating flowering time in cereal germplasm enhancement, by exploiting appropriate gene combinations. This review describes a catalogue of alleles found in QTL studies by barley geneticists, corresponding to the genetic diversity at major flowering time genes, the main drivers of barley phenological adaptation: VRN-H1 (HvBM5A), VRN-H2 (HvZCCTa-c), VRN-H3 (HvFT1), PPD-H1 (HvPRR37), PPD-H2 (HvFT3), and eam6/eps2 (HvCEN). For each gene, allelic series, size and direction of QTL effects, interactions between genes and with the environment are presented. Pleiotropic effects on agronomically important traits such as grain yield are also discussed. The review includes brief comments on additional genes with large effects on phenology that became relevant in modern barley breeding. The parallelisms between flowering time allelic variation between the two most cultivated Triticeae species (barley and wheat) are also outlined. This work is mostly based on previously published data, although we added some new data and hypothesis supported by a number of studies. This review shows the wide variety of allelic effects that provide enormous plasticity in barley flowering behavior, which opens new avenues to breeders for fine-tuning phenology of the barley crop.

/pdf/major-flowering-time-genes-of-barley-allelic-diversity-154isiqa78.pdf

Major flowering time genes of barley: allelic diversity, effects, and comparison with wheat

The dynamics of the Green Leaf Area Index (GLAI) is of great interest for numerous applications such as yield prediction and plant breeding. We present a high-throughput model-assisted method for characterizing GLAI dynamics in maize (Zea mays subsp. mays) using multispectral imagery acquired from an Unmanned Aerial Vehicle (UAV). Two trials were conducted with a high diversity panel of 400 lines under well-watered and water-deficient treatments in 2016 and 2017. For each UAV flight, we first derived GLAI estimates from empirical relationships between the multispectral reflectance and ground level measurements of GLAI achieved over a small sample of microplots. We then fitted a simple but physiologically sound GLAI dynamics model over the GLAI values estimated previously. Results show that GLAI dynamics was estimated accurately throughout the cycle (R2 > 0.9). Two parameters of the model, biggest leaf area and leaf longevity, were also estimated successfully. We showed that GLAI dynamics and the parameters of the fitted model are highly heritable (0.65 ≤ H2 ≤ 0.98), responsive to environmental conditions, and linked to yield and drought tolerance. This method, combining growth modeling, UAV imagery and simple non-destructive field measurements, provides new high-throughput tools for understanding the adaptation of GLAI dynamics and its interaction with the environment. GLAI dynamics is also a promising trait for crop breeding, and paves the way for future genetic studies.

/pdf/a-high-throughput-model-assisted-method-for-phenotyping-19sgjrxisb.pdf

A High-Throughput Model-Assisted Method for Phenotyping Maize Green Leaf Area Index Dynamics Using Unmanned Aerial Vehicle Imagery.

Comparative physiology and transcriptome response patterns in cold-tolerant and cold-sensitive varieties of Zanthoxylum bungeanum Maxim

Drought is a major abiotic stress reducing maize yield worldwide especially before and during silking. The mechanism underlying drought tolerance in maize has not been elucidated especially from the perspective of different organs. Hence, we conducted field trials under pre-silking drought using two maize genotypes, FM985 (drought tolerant) and ZD958 (drought sensitive). The two genotypes did not differ in plant height, grain number, and yield under control. However, grain number per ear and yield of FM985 were 38.1% and 35.1% higher and plant height was 17.6% shorter than ZD958 under drought. More 13 C-photosynthates were transported to the ear in FM985 than in ZD958, which increased floret fertility and grain number. The number of differentially expressed genes were greatly higher in stem than in other organs. Stem-ear interactions are key determinants of drought tolerance, in which genes expression related to ABA, lignin and flavonoid biosynthesis, and carbon metabolism in the stem were induced by drought, which inhibited stem elongation and promoted assimilates allocation to the ear in FM985. In comparison with ZD958, the activities of trehalose-6-phosphate phosphatase and sucrose non-fermentation-associated kinase 1 were higher in the stem and lower in the kernel of FM958, which facilitated kernel formation. These results reveal that, beyond ear response, stem elongation is involved in the whole process of drought tolerance before silking. ABA together with T6P, lignin and flavonoid suppresses stem elongation and allocates assimilate into ear, providing a novel and systematic regulatory pathway for drought tolerance in maize.

ABA collaborates with lignin and flavonoid to improve pre-silking drought tolerance by tuning stem elongation and ear development in maize (Zea mays L.).

Long noncoding RNAs (lncRNAs) serve important roles in the biology of autoimmune diseases and immune‑associated disorders. To identify lncRNAs specifically associated with psoriasis, the expression of lncRNAs from biopsies obtained from patients with psoriasis were compared with samples obtained from healthy volunteers using a microarray. Reverse transcription‑quantitative polymerase chain reaction (RT‑qPCR) was performed to detect the expression of 10 identified dysregulated lncRNAs. Cis‑ and trans‑regulated target genes of lncRNAs were predicted. The results of microarray analysis indicated that 2,194 lncRNAs and 1,725 mRNAs were significantly dysregulated. Gene Ontology and pathway analyses among the dysregulated genes were performed. Co‑expression network analysis was also performed to study molecular interactions. Several identified pathways were associated with psoriasis. Among the 2,194 dysregulated lncRNAs, 1,549 of these had cis‑ or trans‑regulated predicted target genes. Among the 1,725 dysregulated mRNAs, 289 of the cis‑regulated target genes and 262 of the trans‑regulated target genes may be regulated by the differentially expressed lncRNAs; 10 differentially expressed lncRNAs were randomly selected and then validated. Of these lncRNAs, 7 exhibited the same expression profile as determined via microarray analysis, of which 3 lncRNAs were upregulated and 4 lncRNAs were downregulated. To the best of our knowledge, the present study is the first in which a microarray has been used to investigate the expression profile of lncRNAs associated with psoriasis. Additionally, the expression levels of the 10 aforementioned lncRNAs associated with psoriasis were validated in the present study for the first time using RT‑qPCR. The findings demonstrated that lncRNAs may contribute to the pathogenesis of psoriasis and suggested their potential diagnostic and therapeutic value. Furthermore, the findings of the present study suggest that the combined actions of several lncRNAs may contribute to the pathogenesis of psoriasis.

/pdf/long-noncoding-rna-expression-profile-and-functional-4y0yy746y5.pdf

Long noncoding RNA expression profile and functional analysis in psoriasis

Weighted gene co-expression network analysis was explored to find key hub genes involved in plant height regulation. Plant height, an important trait for maize breeding because of its close relatedness to lodging resistance and yield, has been reported to be determined by multiple qualitative and quantitative genes. However, few genes related to plant height have been characterized in maize. Herein, three different maize hybrids, with extremely distinct plant height, which were further classified into low (L), middle (M) and high (H) group, were selected for RNA sequencing at three key developmental stages, namely, jointing stage (I), big flare period (II) and tasseling stage (III). Intriguingly, transcriptome profiles for hybrids ranging from low to high group exhibited significantly similarity in both jointing stage and big flare period. However, remarkably larger differentially expressed genes could be detected between hybrid from low to either middle or high group in tasseling stage. These results were repeatedly observed in both phenotyping and gene ontology enrichment analysis, indicating that transition from big flare period to tasseling stage plays a critical role in determination of plant height. Furthermore, weighted gene co-expression network analysis was explored to find key hub genes involved in plant height regulation. Hundreds of candidate genes, encoding various transcription factors, and regulators involved in internode cell regulation and cell wall synthesis were identified in our network. More importantly, great majority of candidates were correlated to either metabolism or signaling pathway of several plant phytohormones. Particularly, numerous functionally characterized genes in gibberellic acid as well as brassinosteroids signaling transduction pathways were also discovered, suggesting their critical roles in plant height regulation. The present study could provide a modestly comprehensive insight into networks for regulation of plant height in maize.

Global transcriptome and weighted gene co-expression network analyses reveal hybrid-specific modules and candidate genes related to plant height development in maize

Genome-wide association study of maize plant architecture using F1 populations can better dissect various genetic effects that can provide precise guidance for genetic improvement in maize breeding. Maize grain yield has increased at least eightfold during the past decades. Plant architecture, including plant height, leaf angle, leaf length, and leaf width, has been changed significantly to adapt to higher planting density. Although the genetic architecture of these traits has been dissected using different populations, the genetic basis remains unclear in the F1 population. In this work, we perform a genome-wide association study of the four traits using 573 F1 hybrids with a mixed linear model approach and QTXNetwork mapping software. A total of 36 highly significant associated quantitative trait SNPs were identified for these traits, which explained 51.86–79.92% of the phenotypic variation and were contributed mainly by additive, dominance, and environment-specific effects. Heritability as a result of environmental interaction was more important for leaf angle and leaf length, while major effects (a, aa, and d) were more important for leaf width and plant height. The potential breeding values of the superior lines and superior hybrids were also predicted, and these values can be applied in maize breeding by direct selection of superior genotypes for the associated quantitative trait SNPs. A total of 108 candidate genes were identified for the four traits, and further analysis was performed to screen the potential genes involved in the development of maize plant architecture. Our results provide new insights into the genetic architecture of the four traits, and will be helpful in marker-assisted breeding for maize plant architecture.

Genome-wide association study of maize plant architecture using F 1 populations

Plant height, which is an important trait for maize breeding because of its relationship with lodging resistance and yield production, is reportedly determined by multiple qualitative and quantitative genes. However, only a few plant height-related genes have been cloned or characterized in maize. In the present study, previously characterized genes involved in the regulation of plant height were collected from maize, Arabidopsis thaliana, Oryza sativa and sorghum. A collinearity analysis was subsequently performed to identify homologs in the maize genome. A total of 82 new homologous genes were identified as possibly influencing plant height in maize. Interestingly, most of the candidates were involved in the synthesis or signaling of various phytohormones, particularly gibberellin (GA), implying that phytohormones are critical for regulating plant height. Moreover, in a comprehensive analysis of the expression patterns for these genes, substantial variability was observed across tissues and developmental stages, and each tissue exhibited diverse gene expression patterns. An RNA-sequencing analysis of tall and dwarf inbred lines revealed that 15 candidates were differentially expressed, among which six (40.0%) genes were functionally characterized as affecting various phytohormone pathways. Furthermore, the expression of candidate genes potentially involved in the GA signaling pathway was strongly induced by an exogenous GA treatment. This increased expression may have contributed to the observed faster growth rate of the GA-treated plants compared with the mock controls. Our results indicate that the spatial or temporal expression of genes involved in various phytohormone pathways may be associated with the regulation of plant height in maize.

Systematic identification and characterization of candidate genes for the regulation of plant height in maize

The invention discloses a corn stress-resistance-related gene ZmDi19-5 and application thereof. The gene ZmDi19-5 has a nucleotide sequence shown in SEQ ID NO.1, and encoded protein of the gene ZmDi19-5 has an amino acid sequence shown in SEQ ID NO.2. The gene ZmDi19-5 is a new plant stress-resistance-related gene and can improve the stress resistance performance of plants, and the discovery of the gene ZmDi19-5 enriches stress-resistance-related gene resources and has great significance in the selective breeding of new corn stress-resistance species.

Corn stress-resistance-related gene ZmDi19-5 and application thereof

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Global transcriptome and weighted gene co-expression network analyses reveal hybrid-specific modules and candidate genes related to plant height development in maize

Genome-wide association study of maize plant architecture using F 1 populations

Systematic identification and characterization of candidate genes for the regulation of plant height in maize

Corn stress-resistance-related gene ZmDi19-5 and application thereof