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Proper pericarp thickness protects the maize kernel against pests and diseases, moreover, thinner pericarp improves the eating quality in fresh corn. In this study, we aimed to investigate the dynamic changes in maize pericarp during kernel development and identified the major quantitative trait loci (QTLs) for maize pericarp thickness. It was observed that maize pericarp thickness first increased and then decreased. During the growth and formation stages, the pericarp thickness gradually increased and reached the maximum, after which it gradually decreased and reached the minimum during maturity. To identify the QTLs for pericarp thickness, a BC 4 F 4 population was constructed using maize inbred lines B73 (recurrent parent with thick pericarp) and Baimaya (donor parent with thin pericarp). In addition, a high-density genetic map was constructed using maize 10 K SNP microarray. A total of 17 QTLs related to pericarp thickness were identified in combination with the phenotypic data. The results revealed that the heritability of the thickness of upper germinal side of pericarp (UG) was 0.63. The major QTL controlling UG was qPT1-1 , which was located on chromosome 1 (212,215,145–212,948,882). The heritability of the thickness of upper abgerminal side of pericarp (UA) was 0.70. The major QTL controlling UA was qPT2-1 , which was located on chromosome 2 (2,550,197–14,732,993). In addition, a combination of functional annotation, DNA sequencing analysis and quantitative real-time PCR (qPCR) screened two candidate genes, Zm00001d001964 and Zm00001d002283 , that could potentially control maize pericarp thickness. This study provides valuable insights into the improvement of maize pericarp thickness during breeding.

Maize (Zea mays L.) is a staple food and energy crop worldwide. As the closest related wild progenitor of maize, teosinte (Z. mays ssp. Parviglumis) can, therefore, be a rich resource for useful variants lost during domestication. Here, we used the maize inbred line, B73, as the recurrent parent and a teosinte subspecies, K67-11, as the donor, and constructed a introgression line (IL) population. In brief, 10 K single nucleotide polymorphism (SNP) chips were used to genotype 135 maize–teosinte ILs from the BC2F4 population. Then, quantitative trait locus (QTL) mapping was performed for five plant-type and five ear traits across two different environments. In total, 94 putative QTLs were detected in a single environment analysis, whereas 14 QTLs were detected in two environments. In the whole genome, four regions controlling multiple traits were detected by comparing QTL distribution. Thus, these segments were possibly related to the functional regions controlling the aforementioned traits of maize. These results may not only be helpful for fine-mapping of major QTLs related to important agronomic traits in maize but also provide a valuable reference for molecular marker-assisted breeding and related basic research in maize.

Background Argonaute proteins (AGOs) are important players in the regulation of plant development by directing sRNAs to target mRNAs. In maize ( Zea mays ), AGO18b is a tassel-enriched and grass-specific AGO. Previous studies have shown that AGO18b is highly expressed in tassels during meiosis and negatively regulates determinacy of spikelet meristems. However, binding profile on RNAs and acting mechanisms of AGO18b remain unknown. Results In this study, we explored the binding profile of AGO18b in maize tassel by UV cross-linking RNA immunoprecipitation, followed by deep sequencing of these cDNA libraries (cRIP-seq), and systematically studied AGO18b-associated small RNAs and mRNAs by bioinformatics analysis. By globally analyzing the phased small-interfering RNA (phasiRNA) and miRNA abundance bound by AGO18b, we found AGO18b primarily binds to 21-nt phasiRNAs/miRNAs with a 5′-uridine and binds less strongly to 24-nt phasiRNAs with a 5′-adenosine in the premeiotic tassels. The abundance profile of AGO18b-associated miRNAs was different from their expression profile. Moreover, AGO18b strongly binds to miR166a-3p . We then obtained the AGO18b-bound mRNA targets of miR166a-3p by cRIP-seq, and confirmed the molecular function of AGO18b in regulating spikelet meristems. Conclusions Our results indicated that AGO18b binds to phasiRNAs with obvious 5 prime end bias under different sRNA length. MiRNAs and their target mRNAs associated with AGO18b indicated the molecular mechanisms of AGO18b as a negative regulator of inflorescence meristem and tassel development through integrating both phasiRNAs and miRNA pathways, which extended our view of sRNA regulation in flower development and provided potential methods to control pollination in the future.

The growth and yield of the aboveground parts of maize (Zea mays L.) are closely associated with development of the root system. LBD (Lateral Organ Boundaries Domain) transcription factors are crucial for the regulation of lateral organ development in plants. However, to date, little information has been uncovered about the LBD gene family in maize. In this research, a genome-wide identification revealed 45 LBD gene members in maize. The subsequent phylogeny, structure, and profiles of expression were analyzed. These genes were found to be dispersed across all 10 maize chromosomes and expressed in diverse tissues, including the roots, leaves, stems, pericarp, and vegetative meristems. Notably, ZmLBD12 exhibited specific expression in roots. Subsequent over-expression of ZmLBD12 in Arabidopsis thaliana demonstrated its role in lateral root development, identifying it as a candidate gene for further investigation of root development in maize. Our findings provide a systematic analysis of ZmLBD genes and highlight ZmLBD12 as a potential target gene for developing high-yielding, lodging-resistant maize varieties.

Actin-depolymerizing factor (ADF) is a small class of actin-binding proteins that regulates the dynamics of actin in cells. Moreover, it is well known that the plant ADF family plays key roles in growth, development and defense-related functions. Results: Thirteen maize (Zea mays L., ZmADFs) ADF genes were identified using Hidden Markov Model. Phylogenetic analysis indicated that the 36 identified ADF genes in Physcomitrella patens, Arabidopsis thaliana, Oryza sativa japonica, and Zea mays were clustered into five groups. Four pairs of segmental genes were found in the maize ADF gene family. The tissue-specific expression of ZmADFs and OsADFs was analyzed using microarray data obtained from the Maize and Rice eFP Browsers. Five ZmADFs (ZmADF1/2/7/12/13) from group V exhibited specifically high expression in tassel, pollen, and anther. The expression patterns of 13 ZmADFs in seedlings under five abiotic stresses were analyzed using qRT-PCR, and we found that the ADFs mainly responded to heat, salt, drought, and ABA. Conclusions: In our study, we identified ADF genes in maize and analyzed the gene structure and phylogenetic relationships. The results of expression analysis demonstrated that the expression level of ADF genes was diverse in various tissues and different stimuli, including abiotic and phytohormone stresses, indicating their different roles in plant growth, development, and response to external stimulus. This report extends our knowledge to understand the function of ADF genes in maize.

This paper proposes a novel optimization method for hollow-core, anti-resonant fiber based on a gradient descent algorithm assisted via a radial basis-function surrogate model. This approach significantly reduces the number of optimization iterations, achieving a stable improvement in birefringence performance by an order of magnitude across the operating wavelength band. Furthermore, various optimization algorithms were compared, and the indicators of their Pareto sets were analyzed to demonstrate the effectiveness of the proposed method in multi-objective optimization.

Background Argonaute (AGO) protein is a kind of RNA binding protein that plays an integral role in the gene-silencing pathways guided by small RNAs. But there are few studies about the regulation of AGO genes responded to diverse abiotic stress in maize. Results In this study, we analyzed the expression of seventeen ZmAGO genes under heat, cold, salinity, drought and ABA treatments using quantitative PCR (qPCR). All ZmAGOs showed differential expression modes under various abiotic stress treatments. Two ZmAGOs ( ZmAGO1a and ZmAGO5d ) and other fifteen ZmAGOs exhibited specific up-regulation in response to heat separately. Several ZmAGO genes are very sensitive to cold stress, but many ZmAGO genes are slow to respond to NaCl treatment. Nine ZmAGO genes ( ZmAGO1f , ZmAGO2b , ZmAGO4 , ZmAGO5a/b/c , ZmAGO7 , ZmAGO9 and ZmAGO18a/b ) presented definite up-regulation in response to drought, which were similar to the pattern of gene regulation under abscisic acid (ABA) treatment. Conclusions Various ZmAGO genes respond to different abiotic stress treatments. These results provide fundamental information and insights for the further study on the role of abiotic stress resistance genes in maize and provide basis for further study on the function of AGO genes in response to abiotic stress in maize.

Background The bitter taste receptor gene TAS2R38 is a member of the human TAS2R gene family. Polymorphisms in TAS2R38 affect the ability to taste the bitterness of phenylthiourea (PTC) compounds, thus affecting an individual’s food preference and health status. Methods We investigated polymorphisms in the TAS2R38 gene and the sensitivity to PTC bitterness among healthy Chinese college students in Hubei province. The association of TAS2R38 polymorphisms and PTC sensitivity with body mass index (BMI), food preference, and health status was also analyzed. A total of 320 healthy college students were enrolled (male: 133, female: 187; aged 18–23 years). The threshold value method was used to measure the perception of PTC bitterness, and a questionnaire was used to analyze dietary preferences and health status. Polymerase chain reaction (PCR) was used to analyze polymorphisms at three common TAS2R38 loci (rs713598, rs1726866, and rs10246939). Results In our study population, 65.00% of individuals had medium sensitivity to the bitterness of PTC; in contrast, 20.94% were highly sensitive to PTC bitterness, and 14.06% were not sensitive. For the TAS2R38 gene, the PAV/PAV and PAV/AAI diplotypes were the most common (42.19% and 40.63%, respectively), followed by the homozygous AVI/AVI (8.75%) and PAV/AVI (5.00%) diplotypes. Conclusion There was a significant correlation between the sensitivity to PTC bitterness and sex, but there was no correlation between the common diplotypes of TAS2R38 and gender. Polymorphisms in the TAS2R38 gene were associated with the preference for tea, but not with one’s native place, BMI, health status, or other dietary preferences. There was no significant correlation between the perception of PTC bitterness and one’s native place, BMI, dietary preference, or health status. We hope to find out the relationship between PTC sensitivity and TAS2R38 gene polymorphisms and dietary preference and health status of Chinese population through this study, providing relevant guidance and suggestions for dietary guidance and prevention of some chronic diseases in Chinese population.

Immediate phenotypic variation and the lagged effect of evolutionary adaptation to climate change appear to be two key processes in tree responses to climate warming. This study examines these components in two types of growth models for predicting the 2010-2099 diameter growth change of four major boreal species Betula papyrifera, Pinus banksiana, Picea mariana, and Populus tremuloides along a broad latitudinal gradient in eastern Canada under future climate projections. Climate-growth response models for 34 stands over nine latitudes were calibrated and cross-validated. An adaptive response model (A-model), in which the climate-growth relationship varies over time, and a fixed response model (F-model), in which the relationship is constant over time, were constructed to predict future growth. For the former, we examined how future growth of stands in northern latitudes could be forecasted using growth-climate equations derived from stands currently growing in southern latitudes assuming that current climate in southern locations provide an analogue for future conditions in the north. For the latter, we tested if future growth of stands would be maximally predicted using the growth-climate equation obtained from the given local stand assuming a lagged response to climate due to genetic constraints. Both models predicted a large growth increase in northern stands due to more benign temperatures, whereas there was a minimal growth change in southern stands due to potentially warm-temperature induced drought-stress. The A-model demonstrates a changing environment whereas the F-model highlights a constant growth response to future warming. As time elapses we can predict a gradual transition between a response to climate associated with the current conditions (F-model) to a more adapted response to future climate (A-model). Our modeling approach provides a template to predict tree growth response to climate warming at mid-high latitudes of the Northern Hemisphere.

Objective: An automatic method for the optimization of importance factors was proposed to improve the efficiency of inverse planning. Methods: The automatic method consists of 3 steps: (1) First, the importance factors are automatically and iteratively adjusted based on our proposed penalty strategies. (2) Then, plan evaluation is performed to determine whether the obtained plan is acceptable. (3) If not, a higher penalty is assigned to the unsatisfied objective by multiplying it by a compensation coefficient. The optimization processes are performed alternately until an acceptable plan is obtained or the maximum iteration N max of step (3) is reached. Results: Tested on 2 kinds of clinical cases and compared with manual method, the results showed that the quality of the proposed automatic plan was comparable to, or even better than, the manual plan in terms of the dose–volume histogram and dose distributions. Conclusions: The proposed algorithm has potential to significantly improve the efficiency of the existing manual adjustment methods for importance factors and contributes to the development of fully automated planning. Especially, the more the subobjective functions, the more obvious the advantage of our algorithm.