Waxy allele diversification in foxtail millet (Setaria italica) landraces of Taiwan

Molecular insights on the origin and development of waxy genotypes in major crop plants

Starch is a significant ingredient of the seed endosperm with commercial importance in food and industry. Crop varieties with glutinous (waxy) grain characteristics, i.e. starch with high amylopectin and low amylose, hold longstanding cultural importance in some world regions and unique properties for industrial manufacture. The waxy character in many crop species is regulated by a single gene known as GBSSI (or waxy), which encodes the enzyme Granule Bound Starch Synthase1 with null or reduced activity. Several allelic variants of the waxy gene that contribute to varying levels of amylose content have been reported in different crop plants. Phylogenetic analysis of protein sequences and the genomic DNA encoding GBSSI of major cereals and recently sequenced millets and pseudo-cereals have shown that GBSSI orthologs form distinct clusters, each representing a separate crop lineage. With the rapidly increasing demand for waxy starch in food and non-food applications, conventional crop breeding techniques and modern crop improvement technologies such as gene silencing and genome editing have been deployed to develop new waxy crop cultivars. The advances in research on waxy alleles across different crops have unveiled new possibilities for modifying the synthesis of amylose and amylopectin starch, leading to the potential creation of customized crops in the future. This article presents molecular lines of evidence on the emergence of waxy genes in various crops, including their genesis and evolution, molecular structure, comparative analysis and breeding innovations.

Variation of growth and transcriptome responses to arbuscular mycorrhizal symbiosis in different foxtail millet lines

BACKGROUND

Arbuscular mycorrhizal fungi (AMF) have been applied to promote the growth of different crop species, but knowledge about the impacts of symbiosis on foxtail millet at the physiological and molecular levels have remained limited. In this study, we compared the mycorrhization phenotypes of one cultivar and three different landraces and performed a comprehensive transcriptomic analysis to assess the effects of genetic variation on the responses to symbiosis.

RESULTS

Our results showed that colonization by AMF did not enhance biomass accumulation but significantly increased grain production only in three lines. More than 2,000 genes were affected by AMF colonization in all lines. Most AM symbiosis-conserved genes were induced, but the induction levels varied between lines. Gene Ontology (GO) analysis showed that Biological Function terms related to nitrogen transport and assimilation were only enriched in TT8. Similarly, two of phosphate starvation-induced phosphate transporters were only simultaneously downregulated in TT8. In the other two lines, the enrichment of GO terms associated with cell wall reorganization and lignification was observed, though the effects were different.

CONCLUSION

This study reveals the impacts of genetic variation of millet lines on the responses to AM symbiosis and provides information regarding AMF application for millet production.

How ambient temperature affects the heading date of foxtail millet (Setaria italica)

Foxtail millet (Setaria italica), a short-day plant, is one of the important crops for food security encountering climate change, particularly in regions where it is a staple food. Under the short-day condition in Taiwan, the heading dates (HDs) of foxtail millet accessions varied by genotypes and ambient temperature (AT). The allelic polymorphisms in flowering time (FT)-related genes were associated with HD variations. AT, in the range of 13°C-30°C that was based on field studies at three different latitudes in Taiwan and observations in the phytotron at four different AT regimes, was positively correlated with growth rate, and high AT promoted HD. To elucidate the molecular mechanism of foxtail millet HD, the expression of 14 key FT-related genes in four accessions at different ATs was assessed. We found that the expression levels of SiPRR95, SiPRR1, SiPRR59, SiGhd7-2, SiPHYB, and SiGhd7 were negatively correlated with AT, whereas the expression levels of SiEhd1, SiFT11, and SiCO4 were positively correlated with AT. Furthermore, the expression levels of SiGhd7-2, SiEhd1, SiFT, and SiFT11 were significantly associated with HD. A coexpression regulatory network was identified that shown genes involved in the circadian clock, light and temperature signaling, and regulation of flowering, but not those involved in photoperiod pathway, interacted and were influenced by AT. The results reveal how gene × temperature and gene × gene interactions affect the HD in foxtail millet and could serve as a foundation for breeding foxtail millet cultivars for shift production to increase yield in response to global warming.

Physics-Informed Machine Learning Improves Detection of Head Impacts

In this work we present a new physics-informed machine learning model that can be used to analyze kinematic data from an instrumented mouthguard and detect impacts to the head. Monitoring player impacts is vitally important to understanding and protecting from injuries like concussion. Typically, to analyze this data, a combination of video analysis and sensor data is used to ascertain the recorded events are true impacts and not false positives. In fact, due to the nature of using wearable devices in sports, false positives vastly outnumber the true positives. Yet, manual video analysis is time-consuming. This imbalance leads traditional machine learning approaches to exhibit poor performance in both detecting true positives and preventing false negatives. Here, we show that by simulating head impacts numerically using a standard Finite Element head-neck model, a large dataset of synthetic impacts can be created to augment the gathered, verified, impact data from mouthguards. This combined physics-informed machine learning impact detector reported improved performance on test datasets compared to traditional impact detectors with negative predictive value and positive predictive values of 88 and 87% respectively. Consequently, this model reported the best results to date for an impact detection algorithm for American football, achieving an F₁ score of 0.95. In addition, this physics-informed machine learning impact detector was able to accurately detect true and false impacts from a test dataset at a rate of 90% and 100% relative to a purely manual video analysis workflow. Saving over 12 h of manual video analysis for a modest dataset, at an overall accuracy of 92%, these results indicate that this model could be used in place of, or alongside, traditional video analysis to allow for larger scale and more efficient impact detection in sports such as American Football.

Functionalizing silica sol-gel with entrapped plant virus-based immunosorbent nanoparticles

Advancements in understanding and engineering of virus-based nanomaterials (VBNs) for biomedical applications motivate a need to explore the interfaces between VBNs and other biomedically-relevant chemistries and materials. While several strategies have been used to investigate some of these interfaces with promising initial results, including VBN-containing slow-release implants and VBN-activated bioceramic bone scaffolds, there remains a need to establish VBN-immobilized three dimensional materials that exhibit improved stability and diffusion characteristics for biosensing and other analyte-capture applications. Silica sol-gel chemistries have been researched for biomedical applications over several decades and are well understood; various cellular organisms and biomolecules (e.g., bacteria, algae, enzymes) have been immobilized in silica sol-gels to improve viability, activity, and form factor (i.e., ease of use). Here we present the immobilization of an antibody-binding VBN in silica sol-gel by pore confinement. We have shown that the resulting system is sufficiently diffuse to allow antibodies to migrate in and out of the matrix. We also show that the immobilized VBN is capable of antibody binding and elution functionality under different buffer conditions for multiple use cycles. The promising results of the VBN and silica sol-gel interface indicate a general applicability for VBN-based bioseparations and biosensing applications.

Domestication of Crop Metabolomes: Desired and Unintended Consequences

The majority of the crops and vegetables of today were domesticated from their wild progenitors within the past 12 000 years. Considerable research effort has been expended on characterizing the genes undergoing positive and negative selection during the processes of crop domestication and improvement. Many studies have also documented how the contents of a handful of metabolites have been altered during human selection, but we are only beginning to unravel the true extent of the metabolic consequences of breeding. We highlight how crop metabolomes have been wittingly or unwittingly shaped by the processes of domestication, and highlight how we can identify new targets for metabolite engineering for the purpose of de novo domestication of crop wild relatives.

Genetic Variation of Physicochemical Properties and Digestibility of Foxtail Millet (Setaria italica) Landraces of Taiwan

Foxtail millet is considered a 'smart food' because of nutrient richness and resilience to environments. A diversity panel of 92 foxtail millet landraces preserved by Taiwan indigenous peoples containing amylose content (AC) in the range of 0.7% to 16.9% exhibited diverse physiochemical properties revealed by a rapid viscosity analyzer (RVA). AC was significantly correlated with 5 RVA parameters, and some RVA parameters were also highly correlated with one another. In comparison to rice, foxtail millet contained less starch (65.9-73.1%) and no significant difference in totals of resistant starch (RS), slowly digestible starch (SDS), hydrolysis index (HI), and expected glycemic index (eGI) according to in vitro digestibility assays of raw flour with similar AC. RS was significantly positively correlated with AC and four RVA parameters, cold paste viscosity (CPV), setback viscosity (SBV), peak time (PeT), and pasting temperature (PaT), implying that suitable food processing to alter physicochemical properties of foxtail millet might mitigate hyperglycemia. This investigation of pasting properties and digestibility of diverse foxtail millet germplasm revealed much variation and showed potential for multi-dimensional utilizations in daily staple food and food industries.