Search

Safflower (Carthamus tinctorius L.) is a multipurpose minor crop consumed by developed and developing nations around the world with limited research funding and genetic resources. Genomic selection (GS) is an effective modern breeding tool that can help to fast-track the genetic diversity preserved in genebank collections to facilitate rapid and efficient germplasm improvement and variety development. In the present study, we simulated four GS strategies to compare genetic gains and inbreeding during breeding cycles in a safflower recurrent selection breeding program targeting grain yield (GY) and seed oil content (OL). We observed positive genetic gains over cycles in all four GS strategies, where the first cycle delivered the largest genetic gain. Single-trait GS strategies had the greatest gain for the target trait but had very limited genetic improvement for the other trait. Simultaneous selection for GY and OL via indices indicated higher gains for both traits than crossing between the two single-trait independent culling strategies. The multi-trait GS strategy with mating relationship control (GS_GY + OL + Rel) resulted in a lower inbreeding coefficeint but a similar gain compared to that of the GS_GY + OL (without inbreeding control) strategy after a few cycles. Our findings lay the foundation for future safflower GS breeding.

In plant breeding programs, multiple traits are recorded in each trial, and the traits are often correlated. Correlated traits can be incorporated into genomic selection models, especially for traits with low heritability, to improve prediction accuracy. In this study, we investigated the genetic correlation between important agronomic traits in safflower. We observed the moderate genetic correlations between grain yield (GY) and plant height (PH, 0.272–0.531), and low correlations between grain yield and days to flowering (DF, −0.157–0.201). A 4%–20% prediction accuracy improvement for grain yield was achieved when plant height was included in both training and validation sets with multivariate models. We further explored the selection responses for grain yield by selecting the top 20% of lines based on different selection indices. Selection responses for grain yield varied across sites. Simultaneous selection for grain yield and seed oil content (OL) showed positive gains across all sites with equal weights for both grain yield and oil content. Combining g×E interaction into genomic selection (GS) led to more balanced selection responses across sites. In conclusion, genomic selection is a valuable breeding tool for breeding high grain yield, oil content, and highly adaptable safflower varieties.

Psoriasis is an autoimmune skin disease in which dendritic cells (DCs) trigger the progression of psoriasis by complex interactions with keratinocytes and other immune cells. In the present study, we aimed to load celastrol, an anti-inflammatory ingredient isolated from Chinese herbs, on mannosylated liposomes to enhance DC uptake as well as to induce DC tolerance in an imiquimod-induced psoriasis-like mouse model. Mannose was grafted onto liposomes to target mannose receptors on DCs. The results demonstrated that compared with unmodified liposomes, DCs preferred to take up more fluorescence-labeled mannosylated liposomes. After loading celastrol into mannose-modified liposomes, they effectively inhibited the expression of maturation markers, including CD80, CD86 and MHC-II, on DCs both in vitro and in vivo. Additionally, after intradermal injection with a microneedle, celastrol-loaded mannose-modified liposomes (CEL-MAN-LPs) achieved a superior therapeutic effect compared with free drug and celastrol-loaded unmodified liposomes in the psoriasis mouse model in terms of the psoriasis area and severity index, histology evaluation, spleen weight, and expression of inflammatory cytokines. In conclusion, our results clearly revealed that CEL-MAN-LPs was an effective formulation for psoriasis treatment and suggested that this treatment has the potential to be applied to other inflammatory diseases triggered by activated DCs.

Background: The coronavirus disease 2019 (COVID-19) outbreak might have a psychological impact on frontline healthcare workers. However, the effectiveness of coping strategies was less reported. Objectives: We aimed to investigate the sources of stress and coping strategies among frontline healthcare workers fighting against COVID-19. We also performed a literature review regarding the effects of coping methods on psychological health in this population. Methods: We included frontline healthcare workers who completed an online survey using self-made psychological stress questionnaires in a cross-sectional study. We evaluated the association between potential factors and high-stressed status using a logistic regression model. We performed the principal component analysis with varimax rotation for factor analysis. We also performed a systematic review of published randomized controlled studies that reported the effects of coping methods on psychological health in COVID-19 healthcare workers. Results: We included 107 [32 (29–36) years] respondents in the final analysis, with a response rate of 80.5%. A total of 41 (38.3%) respondents were high-stressed. Compared with the low-stressed respondents, those with high-stress were less likely to be male (46.3% versus 72.7%, p = 0.006), nurses (36.6% versus 80.3%, p

Psoriasis is an autoimmune inflammatory disease, where dendritic cells (DCs) play an important role in its pathogenesis. In our previous work, we have demonstrated that topical delivery of curcumin-loaded poly (lactic-co-glycolic acid) (PLGA) nanoparticles (NPs) could treat Imiquimod (IMQ)-induced psoriasis-like mice. The objective of this study is to further elucidate biofate of PLGA NPs after intradermal delivery including DCs uptake, and their further trafficking in psoriasis-like mice model by using fluorescence probes. Two-sized DiO/DiI-loaded PLGA NPs of 50 ± 4.9 nm (S-NPs) and 226 ± 7.8 nm (L-NPs) were fabricated, respectively. In vitro cellular uptake results showed that NPs could be internalized into DCs with intact form, and DCs preferred to uptake larger NPs. Consistently, in vivo study showed that L-NPs were more captured by DCs and NPs were firstly transported to skin-draining lymph nodes (SDLN), then to spleens after 8 h injection, whereas more S-NPs were transported into SDLN and spleens. Moreover, FRET imaging showed more structurally intact L-NPs distributed in skins and lymph nodes. In conclusion, particle size can affect the uptake and trafficking of NPs by DCs in skin and lymphoid system, which needs to be considered in NPs tailing to treat inflammatory skin disease like psoriasis.

We investigated the benefit from introgression of external lines into a cereal breeding programme and strategies that accelerated introgression of the favourable alleles while minimising linkage drag using stochastic computer simulation. We simulated genomic selection for disease resistance and grain yield in two environments with a high level of genotype-by-environment interaction (G × E) for the latter trait, using genomic data of a historical barley breeding programme as the base generation. Two populations (existing and external) were created from this base population with different allele frequencies for few (N = 10) major and many (N ~ 990) minor simulated disease quantitative trait loci (QTL). The major disease QTL only existed in the external population and lines from the external population were introgressed into the existing population which had minor disease QTL with low, medium and high allele frequencies. The study revealed that the benefit of introgression depended on the level of genetic variation for the target trait in the existing cereal breeding programme. Introgression of external resources into the existing population was beneficial only when the existing population lacked variation in disease resistance or when minor disease QTL were already at medium or high frequency. When minor disease QTL were at low frequencies, no extra genetic gain was achieved from introgression. More benefit in the disease trait was obtained from the introgression if the major disease QTL had larger effect sizes, more selection emphasis was applied on disease resistance, or more external lines were introgressed. While our strategies to increase introgression of major disease QTL were generally successful, most were not able to completely avoid negative impacts on selection for grain yield with the only exception being when major introgression QTL effects were very large. Breeding programmes are advised to carefully consider the level of genetic variation in a trait available in their breeding programme before deciding to introgress germplasms.

There is compelling evidence that CD4+Foxp3+ regulatory T cells (Tregs) are indispensable in the inhibition of autoimmune inflammatory responses, including psoriasis. Recently, we showed that systemically treatment with tetrandrine (TET), a two-pore channel inhibitor identified from the Chinese herb Stephania tetrandra S. Moor, could promote the proliferative expansion of Tregs in mice through stimulation of TNF-TNFR2 interaction. We thus hypothesized that topical administration of TET might also expand Tregs and consequently inhibit psoriasis. To this end, we developed a TET nanoemulsion and examined its effect on the expansion of Tregs after topical administration on mouse psoriasis induced by imiquimod. The result of our experiment showed that topical treatment with TET nanoemulsion markedly increased the proportion and number of Tregs in the spleen, as well as TNFR2 and Ki-67 expression by Tregs, in WT and TNFR1 KO mice, but not in TNFR2 KO mice. Consequently, TET nanoemulsion potently inhibited IL-17-expressing cells in the spleen and lymph nodes of imiquimod-treated WT mice, accompanied by decreased serum levels of IL-17A, INF-γ, and TNF and their mRNA levels in the flamed lesion. Importantly, TET nanoemulsion treatment markedly inhibited the development of psoriasis-like disease in WT and TNFR1 KO mice but not in TNFR2 KO mice. Therefore, our study indicates that the topical administration of TET could also stimulate the expansion of Tregs through the TNF-TNFR2 pathway. This effect of TET and its analogs may be useful in the treatment of inflammatory skin diseases such as psoriasis.

Abstract Using genomic information to predict phenotypes can improve the accuracy of estimated breeding values and can potentially increase genetic gain over conventional breeding. In this study, we investigated the prediction accuracies achieved by best linear unbiased prediction (BLUP) for nine potato phenotypic traits using three types of relationship matrices pedigree ABLUP, genomic GBLUP, and a hybrid matrix (H) combining pedigree and genomic information (HBLUP). Deep pedigree information was available for >3000 different potato breeding clones evaluated over four years. Genomic relationships were estimated from >180,000 informative SNPs generated using a genotyping‐by‐sequencing transcriptome (GBS‐t) protocol for 168 cultivars, many of which were parents of clones. Two validation scenarios were implemented, namely “Genotyped Cultivars Validation” (a subset of genotyped lines as validation set) and “Non‐genotyped 2009 Progenies Validation”. Most of the traits showed moderate to high narrow sense heritabilities (range 0.22–0.72). In the Genotyped Cultivars Validation, HBLUP outperformed ABLUP on prediction accuracies for all traits except early blight, and outperformed GBLUP for most of the traits except tuber shape, tuber eye depth and boil after‐cooking darkening. This is evidence that the in‐depth relationship within the H matrix could potentially result in better prediction accuracy in comparison to using A or G matrix individually. The prediction accuracies of the Non‐genotyped 2009 Progenies Validation were comparable between ABLUP and HBLUP, varying from 0.17–0.70 and 0.18–0.69, respectively. Better prediction accuracy and less bias in prediction using HBLUP is of practical utility to breeders as all breeding material is ranked on the same scale leading to improved selection decisions. In addition, our approach provides an economical alternative to utilize historic breeding data with current genotyped individuals in implementing genomic selection.

Breeding schemes that utilize modern breeding methods like genomic selection (GS) and speed breeding (SB) have the potential to accelerate genetic gain for different crops. We investigated through stochastic computer simulation the advantages and disadvantages of adopting both GS and SB (SpeedGS) into commercial breeding programs for allogamous crops. In addition, we studied the effect of omitting one or two selection stages from the conventional phenotypic scheme on GS accuracy, genetic gain, and inbreeding. As an example, we simulated GS and SB for five traits (heading date, forage yield, seed yield, persistency, and quality) with different genetic architectures and heritabilities (0.7, 0.3, 0.4, 0.1, and 0.3; respectively) for a tall fescue breeding program. We developed a new method to simulate correlated traits with complex architectures of which effects can be sampled from multiple distributions, e.g. to simulate the presence of both minor and major genes. The phenotypic selection scheme required 11 years, while the proposed SpeedGS schemes required four to nine years per cycle. Generally, SpeedGS schemes resulted in higher genetic gain per year for all traits especially for traits with low heritability such as persistency. Our results showed that running more SB rounds resulted in higher genetic gain per cycle when compared to phenotypic or GS only schemes and this increase was more pronounced per year when cycle time was shortened by omitting cycle stages. While GS accuracy declined with additional SB rounds, the decline was less in round three than in round two, and it stabilized after the fourth SB round. However, more SB rounds resulted in higher inbreeding rate, which could limit long-term genetic gain. The inbreeding rate was reduced by approximately 30% when generating the initial population for each cycle through random crosses instead of generating half-sib families. Our study demonstrated a large potential for additional genetic gain from combining GS and SB. Nevertheless, methods to mitigate inbreeding should be considered for optimal utilization of these highly accelerated breeding programs.

Abstract Psoriasis is a chronic, painful, disfiguring and non-contagious skin disease that has globally affected at least 200 million patients. In general, mild to moderate psoriasis patients will be treated by chemical drugs or Chinese medicine, while targeting systemic biological drugs have been successfully developed with good efficacy but high cost burden to patients with severe psoriasis. Since the underlying mechanisms of psoriasis are not well understood, in this review, psoriasis pathogenesis and clinical therapeutic principles by modern medicine and Chinese medicine are extensively described. Based on the data from the China Food and Drug Administration, the majority of chemical drugs are utilized as the topical formulations, while Chinese medicines are mainly delivered by an oral route, suggesting that the market for topical preparations of Chinese medicine to treat psoriasis is worth to exploration. Moreover, considering the unique clinical therapeutic theory and successful clinical application of Chinese medicine in the treatment of psoriasis, we believe that development of new small molecule drugs based on Chinese medicine will be a promising strategy to reduce therapeutic costs and improve safety for psoriatic patients.

Genomic selection (GS) provides an attractive option for accelerating genetic gain in perennial ryegrass () improvement given the long cycle times of most current breeding programs. The present study used simulation to investigate the level of genetic gain and inbreeding obtained from GS breeding strategies compared with traditional breeding strategies for key traits (persistency, yield, and flowering time). Base population genomes were simulated through random mating for 60,000 generations at an effective population size of 10,000. The degree of linkage disequilibrium (LD) in the resulting population was compared with that obtained from empirical studies. Initial parental varieties were simulated to match diversity of current commercial cultivars. Genomic selection was designed to fit into a company breeding program at two selection points in the breeding cycle (spaced plants and miniplot). Genomic estimated breeding values (GEBVs) for productivity traits were trained with phenotypes and genotypes from plots. Accuracy of GEBVs was 0.24 for persistency and 0.36 for yield for single plants, while for plots it was lower (0.17 and 0.19, respectively). Higher accuracy of GEBVs was obtained for flowering time (up to 0.7), partially as a result of the larger reference population size that was available from the clonal row stage. The availability of GEBVs permit a 4-yr reduction in cycle time, which led to at least a doubling and trebling genetic gain for persistency and yield, respectively, than the traditional program. However, a higher rate of inbreeding per cycle among varieties was also observed for the GS strategy.

Genomic selection (GS) has been recognized as offering numerous potential benefits for ryegrass (Lolium perenne L.) breeding. While the theoretical benefits of GS in ryegrass breeding are clear, the best way to apply GS in practical breeding programs remains to be determined. The present study aimed to investigate genomic breeding options that best balance genetic gain, breeding costs, and the level of inbreeding using stochastic simulation. Nine GS scenarios were tested, including different numbers of selection candidates (10,000, 5000, and 2000 F1 seedlings) and three reference population sizes for GS composed of plots representing a sward-based trial (500, 200, and 100 plots). Low to moderate prediction accuracy was achieved for productivity traits across cycles (i.e., 0.1–0.45 for yield [h2 = 0.3]). Scenarios with larger reference populations (i.e., 500 plots) achieved higher prediction accuracy but, when considering field trial costs, were more expensive per unit of genetic gain. All nine GS scenarios delivered significantly higher genetic gain (up to fourfold) than the conventional breeding scenario over a 20-yr period. Scenarios with moderate selection intensity on F1 seedlings with fewer plots tested in field gave the most genetic gain per dollar invested (i.e., 2000 or 5000 F1 seedlings and 100 plots). However, all GS scenarios reduced genetic diversity in the breeding population more than phenotypic selection, highlighting the need to mitigate inbreeding when applying GS in perennial ryegrass. [ABSTRACT FROM AUTHOR]