Introduction: The most common clinical manifestation of mango allergy is contact dermatitis, which can be localized or systemic. The sensitising substances that have long been suspected are alk(en)yl catechols and/or alk(en)yl resorcinols. Methods: We reviewed the original articles published on Pubmed, Embase and Cochrane Library before 15 September 2021, on the topic of contact allergy induced by mango and we synthesized the key data. Results: We found 12 case reports and four case series, with a total of 37 patients. Only seven of these cases were reported in patients from mango-cultivating countries, the other 30 were from countries where mango cultivation does not occur, and 26 were also from countries where poison ivy/oak are commonly found. We found that contact dermatitis may occur on the first exposure to mango due to previous sensitisation to urushiol-containing plants. The diagnosis was confirmed by patch testing in some of the cases. There was great heterogeneity between the reagents used. Conclusion: Mango fruit is frequently consumed, but mango induced contact dermatitis, the main hypersensitivity reaction induced by mango, is rare. Further data is necessary for a better understanding of sensitising substances and, consecutively, standardization of patch test reagents. Mangoes are consumed almost everywhere in the world; nevertheless, few reports of hypersensitivity reactions (both immediate and delayed) have been mentioned in the literature. From the first allergic reaction to mango reported in 1939 [Mango allergy may occur as type I hypersensitivity reactions ranging from erythema, hives, angioedema, wheezing or oral allergy syndrome to severe anaphylactic reactions, or as type IV hypersensitivity reaction such as contact dermatitis. The latter appears to be more prevalent.Mangifera indica) and a concise review of mango-induced contact dermatitis published cases.The present manuscript is a compilation of essential concepts on physiopathology, clinical manifestations, and allergenic profile of mango  and South America  and as far as Australia. Half of the mangoes produced worldwide originate from India. They are the widest spread fruit crop within the subcontinent of India, which ranks first among the world’s mango producing countries [ountries .The mango fruit is a drupe, consisting of the peel (epicarp) that covers the pulp  inside of which is found a single seed ,5.Mango is consumed throughout the year, both in fresh forms  and in processed forms . It is also used in indigenous and traditional medicines for its anti-oxidant, anti-inflammatory, anti-viral, anti-bacterial, anti-atherosclerotic, anti-diabetic and anti-cancer properties .Two types of hypersensitivity responses to mango have been described with distinct clinical manifestations that include immediate hypersensitivity and delayed hypersensitivity reactions.Immediate hypersensitivity reaction to mango is an IgE-mediated reaction (type I hypersensitivity as classified by Gell & Coombs), which involves mast cell degranulation in individuals sensitised to its antigens. The release of inflammatory mediators, such as proteases, lysosomal enzymes and particularly histamine, leads to vasodilation, eosinophils and leukocytes recruitment, resulting in inflammation and possibly bronchoconstriction .Symptoms may be limited to the contact area or may be systemic including erythema, urticaria, angioedema, wheezing, coughing, sneezing, nasal congestion, and bronchospasm, some leading to severe anaphylaxis. Even though rare, cases of anaphylactic shock related to mango consumption have been reported in the literature ,9.A review of the immediate hypersensitivity reactions induced by mango  showed tOral allergy syndrome (OAS) to mango is defined as an IgE antibody-mediated allergic reaction that occurs in response to eating fresh mango that typically develops in patients with clinical sensitisation to pollen. OAS is not a distinct food allergy; symptoms rather arise due to cross-reactivity between pollen and mango. The main sensitisation is to pollen . The comThe delayed hypersensitivity reaction to mango (type IV hypersensitivity reaction in Gell & Coombs classification) is mediated by T helper 1 cells. The pathogenic response involves a local inflammatory response after the close contact with the antigen of mango fruit or with the bark of the mango tree. After the initial contact, the antigen is presented to T helper cells by macrophages, thereby T helper cells become sensitised and start to release cytokines and chemokines that enhance the inflammatory response, damaging the keratinocytes and causing epithelial tissue disruptions ,15.The most common clinical manifestation is contact dermatitis, which can be localised or systemic (disseminated) and is represented by rash, pruritus, eczema and blisters. Dermatitis may appear on the extremities after contact with mango fruit, peel, stem, sap, or even the tree itself ,17. OtheSome cases presenting with allergic contact dermatitis to mango without previous exposure to the fruit or tree have been described . NotablyMango allergens have not been fully characterized because the allergenic composition of the fruit is not completely known. There are 334 different proteins that were found in mango peel, and 2855 in the fruit flesh and some of these proteins may have immunizing properties .Only three mango allergens  have been identified so far using sera from patients with mango IgE-mediated sensitisation. These are mentioned in Despite enzymatic degradation, mechanical fragmentation, and heating, during peeling or pasteurization, mango allergens were found to be relatively stable throughout technological processing. Mango purées and nectar extracts showed no significant decrease in allergenicity ,22. The Profilins, well-known pan-allergens, are proteins with highly conserved structure that can be found in all eukaryotic cells, are involved in processes related to cell motility and share sequence identities of more than 75%, even between members of distantly related organisms . Mango pHevein  is the allergen that causes most latex–fruit syndrome cases; its homologous proteins were found in mango along with avocado, chestnut, banana, kiwi, tomato, passion fruit and papaya .Although significant cross-reactivity between certain species from the family and genus  is possible, it is not commonly observed . All theThe sensitising substances that have long been suspected of inducing delayed hypersensitivity reactions to mango are alk(en)yl catechols and/or alk(en)yl resorcinols ,28,29.The term “Mangol” refers to the three resorcinol derivatives: hepta-decadienylresorcinol (I), hepta-decenylresorcinol (II), and penta-decylresorcinol (III), that have been identified as mango “allergens” . These aThe “Mangol” has the potential to cross-react with urushiol, therefore mango contact dermatitis has been associated with a history of poison ivy and poison oak exposure, which can induce sensitisation via urushiol. As a result, mango allergic contact dermatitis may occur in people who are exposed to mango for the first time through direct contact with mango tree and fruit or after ingestion of mango fruit, especially unpeeled mango ,31. ThisDiagnosis of mango sensitivity is guided by the clinical presentation. In order to confirm the suspicion of mango contact dermatitis, patch tests can be done with various mango extracts, prepared from mango peel, pulp, leaf, sap, stem, and with resorcinol fractions or urushiol. Usually contact reactions to mango are induced by direct contact with the peel of the fruit, but rare cases of mango pulp contact dermatitis have been reported, thus both peel and pulp should be tested in this context . In caseThere is heterogeneity regarding testing reagents; patch testing can be adapted depending on clinical presentation and history of the patient, as is shown in the reviewed published cases.We reviewed the relevant published literature on Pubmed, Embase, Cochrane Library on the topic of contact allergy induced by mango published before 15 September 2021 and synthesized the key data. Medical Subject Heading (MeSH) and key-words were used together, including mango, contact hypersensitivity, contact allergy. This approach was also combined with a manual search of references in all selected studies.We found 12 case reports and four case series, with a total of 37 patients diagnosed with mango contact dermatitis. The most important features of the 37 selected cases are summarized in We did not include in our analysis a study assessing different patch reagents (mango peel or pulp in aqueous or ether solution) in patients with “itchy dermatitis on the face and hands possibly due to eating mango” and a control group consisting of patients with non-eczematous diseases of the skin. The article did not offer any other information about the patients who tested positive on patch tests .Out of the 37 cases described in Contact dermatitis can occur on the first exposure to mango due to previous sensitisation to urushiol-containing plants, primarily those in the Anacardiaceae family. Seven patients had previous known sensitisation to poison ivy, poison oak and Lithracea caustica ,38,40,41Exposure to contact allergens found in mango can occur in different ways. Of the 30 patients described above, 23 had been in direct contact with the mango fruit, skin, stem, sap, or even the tree itself ,18,28,36In case of mango ingestion, patients developed lesions consistent either with localised contact dermatitis , or with disseminated dermatitis (patients displaying skin lesions in areas that were not in contact with the fruit) ,38,42. IDisseminated contact dermatitis was suspected in the three cases where the patients presented diffuse pruritic rash in one case , recurreThe time to onset of symptoms amongst the 37 cases ranges from a few hours (4–5 h) to several days (up to 9 days). Therefore, the clinical suspicion of a delayed reaction had to be confirmed by patch testing. This was done in 16 out of 37 patients and was positive in all of them. Unfortunately, in the available data there were insufficient details regarding the patch testing protocol. The allergy testing method was heterogenous, with patch testing using either mango skin, sap, leaf, stem, flesh or juice, without providing details on mango reagents’ preparation ,39,40,42Even so, there is another report in which the authors tested different preparations of mango in aqueous solution and ether solution and concluded that a conventional preparation of 10% mango extract in ether might be used to test suspected individuals for mango contact dermatitis .Skin prick tests were done only in four cases since an immediate hypersensitivity was not the main suspected diagnosis. Skin prick tests with mango were negative in three out of these four cases ,35,39,40Nevertheless, there was one reported case in which both type I and type IV hypersensitivity were suspected . The patMango-induced allergic contact dermatitis remains a rare clinical condition; however, we must consider it in patients with suggestive exposure history and clinical presentation. Contact with the mango fruit, skin, stem, sap, or even the tree itself may induce localised or systemic symptoms. When the history is suggestive, patch testing with different parts of the mango plant, urushiol and resorcinol may significantly contribute to a correct diagnosis. Until today there have been few published cases. We reviewed four studies and 12 case reports that totalized 37 patients. The reagents used for patch testing were heterogenous, using different parts of the fruit or of the tree. Although immediate hypersensitivity to mango is more prevalent in atopic patients, there are no data available on the presence of atopy in patients diagnosed with delayed hypersensitivity to mango. One must keep in mind that mango allergic contact dermatitis may occur on first contact with the fruit or other part of the plant, especially in people living in areas of the world where poison ivy or poison oak grow.


Populus. Here, we reported a GWAS of tree height measured at multiple time points from a randomized complete block design (RCBD), which was established with clones from an F1 hybrid population of Populus deltoides and Populus simonii. A total of 22,670 SNPs across 172 clones in the RCBD were obtained with restriction site-associated DNA sequencing (RADseq) technology. The multivariate mixed linear model was applied by incorporating the pedigree relationship matrix of individuals to test the association of each SNP to the tree heights over 8 time points. Consequently, 41 SNPs were identified significantly associated with the tree height under the P-value threshold determined by Bonferroni correction at the significant level of 0.01. These SNPs were distributed on all but two chromosomes (Chr02 and Chr18) and explained the phenotypic variance ranged from 0.26% to 2.64%, amounting to 63.68% in total. Comparison with previous mapping studies for poplar height as well as the candidate genes of these detected SNPs were also investigated. We therefore showed that the application of multivariate linear mixed model to the longitudinal phenotypic data from the traditional breeding experimental design facilitated to identify far more genome-wide variants for tree height in poplar. The significant SNPs identified in this study would enhance understanding of molecular mechanism for growth traits and would accelerate marker-assisted breeding programs in Populus.With the advances in high-throughput sequencing technologies, it is not difficult to extract tens of thousands of single-nucleotide polymorphisms (SNPs) across many individuals in a fast and cheap way, making it possible to perform genome-wide association studies (GWAS) of quantitative traits in outbred forest trees. It is very valuable to apply traditional breeding experiments in GWAS for identifying genome variants associated with ecologically and economically important traits in  Populus  is a deciduous and dioecious tree taxon, comprising aspens, poplars, and cottonwoods, widely distributed in the Northern Hemisphere. Because of its unique biological characteristics, such as rapid growth rate, small genome size, facile asexual reproduction, and easy transgenesis, the genus has been selected as a model system in forest trees  and the male ‘LM50’ (P. tomentosa). These previous studies applied the traditional molecular markers such as RAPD, RFLP, AFLP and SSR, probably limiting the power of detecting QTLs due to their low throughput  have been widely used with multiple available software packages such as TASSEL 1 hybrid progeny of P. deltoides and P. simonii as described above. Each clone has several cuttings planted in different blocks, which have the same genome as a single seedling tree in the F1 population. In the previous studies . To compare with the multivariate method, we also conducted a univariate GWAS of the tree height at each single time point using a two-stage approach with the software TASSEL . The design was established with clones from the F1 hybrid population, which was derived by crossing P. deltoides and P. simonii in the springs from 2009 to 2011. The two parents have substantial differences in growth and adaptability and their hybrids display significant segregation traits in morphology and physiology , which possibly include the ratios of 1:1, 1:2:1, and 1:1:1:1 due to the complicated genetic structure of the F1 hybrid population in outbred forest species  can be expressed as: The mvLMM was applied to find an SNP association to the tree height as follows: Since the clones in the RCBD were from a full-sib family and their parents were unrelated and not inbred, the coefficient of additive genetic covariance between any two different clones is 0.5 in theory , leadinghttps://cran.r-project.org/web/packages/EMMREML, accessed January 6, 2021). To test the effects of SNP genotypes, an M Vec (B) = 0for a full-rank P-value for testing each SNP was adjusted based on Bonferroni-correction and the genome-wide false discovery rate (FDR) was set to be 0.01. As the method described in We used the R package EMMREML to calculate the REML estimates of t as follows: To compare the multivariate GWAS approach to the univariate method, we performed GWAS of the tree height at each time point separately with two-stage approach using the software TASSEL  to first estimate the genetic and residual variance components with EMMREML and then to calculate the heritability as: P. trichocarpa at Phytozome . These genes were annotated afresh by first performing blast searches with their coding sequences against the non-redundant protein database (https://www.blast2go.com). The result of these gene annotations was saved in a text file, in which we searched the keywords related to the tree growth and development as well as response to stresses. Furthermore, these candidate genes were used to perform GO enrichment analysis with Blast2GO for finding which GO terms are over-represented for the growth of tree height.The upstream and downstream genes of the significant SNPs were investigated for candidate genes affecting the tree height. If a gene harbored an SNP that had a linkage disequilibrium (LD) value  with accession numbers presented in Supplementary Table S1. The phenotypic and genotypic data generated for GWAS in this study can be found in Supplementary Tables S2 and S6, respectively. All of the supplemental materials  for this study are available at figshare DOI: P < 0.01) between adjacent time points and a minimum coefficient value of 0.541 between the first and the last measure time points (Supplementary Table S4). Furthermore, we also calculated the genetic correlation coefficients of the tree heights at different time points from the genetic covariance matrix estimated with model (1) by ignoring SNP effects. The result showed that the genetic correlation coefficients were consistently higher than the phenotypic correlation coefficients and that the genetic coefficients between adjacent time points were all greater than 0.960 (Supplementary Table S4). Moreover, multivariate analysis of variance for the longitudinal data showed that the effects of tree height were significantly different among the blocks, the clones, and the interactions of blocks and clones (Supplementary Table S5). These primary statistical analyses showed that the tree height over multiple time points in the RCBD variated largely and was worth further exploring the molecular mechanism.We successfully obtained tree height and SNP genotype data of 172 clones and a total of 1664 individual trees (Supplementary Table S2). The tree heights were measured at 8 different times during the growth season in 2017. Histograms showed that the tree height basically followed a normal distribution at each time point . The aveP. trichocarpa . Each clone had an average of 16.89 million RADseq reads and 4.61 Gb data with a mean genome coverage depth of 9.6X (Supplementary Table S1). After a stringent quality control with NGS QC toolkit, an average amount of 4.45 Gb HQ reads data per clone was remained for calling SNP genotypes. Since the clones were from the F1 hybrid population in Populus, as expected, the majority of SNPs were segregated in the ratio of 1:1 (P > 0.01) with a minority in 1:2:1 and 1:1:1:1  were obtained by mapping their RADseq data separately to the reference genome of  1:1:1:1 . Each SNPopulus. The P-value threshold for significant SNPs was set to 4.41E–7  = 6.36) based on the Bonferroni correction at the 0.01 significant level. If a small region (<1000 bp) harbored several significant SNPs, the most significant was chosen to represent that region. As a result, 41 SNPs were found to be significantly associated with the tree height. P-value. It can be seen that these significant SNPs were distributed on all but 2 (Chr02 and Chr18) chromosomes with one SNP on scaffold 45. The physical distance between adjacent significant SNPs was greater than 123 kb, the minimum distance found between the second and the third significant SNPs on chromosome 5 . The SNP IDs were named after the two parents of the clones currently used in this study, the chromosome and scaffold name, and the order within a chromosome, where D stands for P. deltoides, S for P. simonii, C for chromosome, and T for scaffold . We found that all the SNPs segregated in the ratio of 1:1 with 21 segregating in the type of aa×ab and 20 in ab×aa. The percent of phenotypic variance (R2) explained by the SNPs ranged from 0.26% to 2.64%, amounting to 63.68% in total. Moreover, the effect of each SNP at each time point was also estimated, which was defined as the difference between the homozygous (aa) and heterozygous (ab) effects , which were distributed on chromosomes 4, 10, 17, and 19 . However, no significant SNPs were found for the tree height at time points T2–T8.P. trichocarpa at Phytozome . To obtain enough annotation information, the coding sequences were first blasted against the non-redundant (nr) protein database (http://geneontology.org) terms. With the newly annotation result, we searched keywords related to tree growth and development, such as “brassinosteroid,” “gibberellin,” “leaf,” “xylem,” “photosynthesis,” “salt,” and “disease.” Consequently, 248 genes nearby the significant SNPs corresponded to at least one of the 17 keywords; all but one SNP (DSC13H2) had at least one candidate genes related to these words  as a reference set. As a result, 289 GO terms were significantly enriched with the FDR value <0.05, of which 223 belonged to the category of biological process, 40 to molecular function, and 26 to cellular component (Supplementary Table S9). Interestingly, almost all the searched words except “disease” were contained in at least one significant GO terms in the category of biological process (http://geneontology.org).To further understand the function of the 248 candidate genes described above, we conducted the GO enrichment analysis using all the 34,698 genes in the annotation database of  process . For theWe also performed GO enrichment analyses to investigate the difference of candidate gene functions between the significant SNP group with positive effects and the group with negative effects . There wPopulus. The poplar hybrid F1 clones were planted repeatedly not only among blocks but also within plots in the RCBD. One advantage of these repeated clones is to allow us to obtain repeated phenotypic data for a genotype that originated from a seed. Theoretically, the repeated data can control spatial effects in field and reduce the systematic errors, thus improving the accuracy and power in GWAS. Another advantage is that each genotype can be preserved almost forever especially in forest trees because the repeated plants provide redundancy for the same genotype in the case of natural damages caused by insect, disease or wind. On the contrary, in most previous GWAS or QTL mapping studies in Populus , 1:2:1 (ab×bb), or 1:1:1:1 (ab×ac). Apparently, these SNPs cannot be applied into the GWAS software only for biallelic SNPs. To solve this problem, we used SNP genotype effects of each SNP in the LMM (1) with the restriction of the sum of expected genotype effects equal to zero. Next, the function emmremlMultivariate in the R package EMMREML was used to calculate the estimates of the genetic and residual matrices of variances. This function is flexible for the design matrix of the fixed effects and focuses on dealing with multivariate phenotypic traits, but it cannot flexibly provide statistics for testing SNPs if their genotype effects correspond to more than two columns in the design matrix. We resolved the hypothesis testing problem by converting the multivariate LMM (1) into univariate LMM through matrix vectorization  is expected to be 0.25 for full-sibs assuming random mating  procedure  is in accord with the infinitesimal model, assuming that a quantitative trait is typically controlled by an infinite number of genes each with a tiny effect  awarded to CT and the Priority Academic Program Development of Jiangsu Higher Education Institutions.Conflicts of interest: None declared.


Trachinotus blochii) has rapidly developed into the one of the main valuable fish species in Chinese marine aquaculture. Due to its rapid growth, active metabolism, and high oxygen consumption, hypoxia will increase its mortality and cause serious economic losses. We constructed two experimental groups of fish with different degrees of tolerance to hypoxia, used BSR-Seq analysis based on genome and genetic linkage groups to locate SNPs and genes that were related to the differences in hypoxia tolerance. The results showed that hypoxia tolerance SNPs of golden pompano may be jointly determined by multiple linkage groups, especially linkage groups 18 and 22. There were 768 and 348 candidate genes located in the candidate regions of the brain and liver, respectively. These genes were mainly involved in anaerobic energy metabolism, stress response, immune response, waste discharge, and cell death. The prostaglandin-endoperoxide synthase 2 (PTGS2) on LG8, which is involved in the metabolism of arachidonic acid, has a G/A nonsynonymous mutation at position 20641628, and the encoded amino acid was changed from hydrophobic aspartic acid to asparaginate. The specific pathway of the RIG-I-like receptor signaling pathway in the liver may mediate the metabolic system and the immune system, linking glucose metabolism with immune regulation. The death of the hypoxia-intolerant group may be due to the accumulation of lactic acid caused by the activation of anaerobic glycolysis during the early stage of hypoxia stress, and the activation of type I interferon was inhibited, which resulted in decreased immunity. Among the genes involved in the RIG-I-like receptor signaling pathway, the CYLD Lysine 63 Deubiquitinase (CYLD) located on LG16 had a G/T nonsynonymous mutation at position 13629651, and the encoded amino acid was changed from alanine acid to valine. The interferon induced with helicase C domain 1 (Ifih1) located on LG18 has a G/C nonsynonymous mutation at position 16153700, and the encoded hydrophilic glycine was changed to hydrophobic alanine. Our findings suggest these SNPs may assist in the molecular breeding of hypoxia-tolerant golden pompano, and speculate that the balance of glucose and lipid metabolism plays a key role in Trachinotus blochii under acute hypoxia.Golden Pompano ( Oxygen is essential for most organisms as it plays a crucial role in aerobic metabolism  and dissin vivo  has delicious meat without the intermuscular bone. It contains a variety of amino acids and fatty acids required by the human body, with high nutritional value and fast growth. The market demand for golden pompano is increasing at the moment, promoting interest in breeding  were obtained randomly from the Hainan Blue Ocean Aquaculture Co., Ltd.  as the experimental subjects. After transporting them back to the laboratory, they were temporarily kept in 400 L tanks of circulating aerated seawater and in a stable water environment, i.e., temperature 27.0 ± 0.5°C; ammonia nitrogen and nitrite <0.02 mg/L; DO 7.0 ± 0.2 mg/L; pH 7.5 ± 0.2; salinity 20–30‰; and an equal photoperiod of 12 h of light and 12 h darkness. Commercial pellet feed  was fed daily in the morning and evening. The experimental fish were adapted to this experimental condition for 1 week. Feeding was stopped 24 h before the start of the formal experiment.We constructed three parallel tanks, each with a volume of 400 L, and randomly assigned 80 experimental fish to each tank. Initially all environmental conditions in each tank were kept the same as those of the temporary reception tanks. When the experiment started (t = 0 h), the DO was reduced to the level required for the experiment  within 2 h by the introduction of nitrogen into the tanks. Under these conditions, the first 14 fish in each tank that exhibited raised heads and loss of balance within 1 h of hypoxic stress were taken as the hypoxic intolerant group (Intol). Similarly, the last 14 fish in each tank still exhibiting normal behavior after 24 h of hypoxic stress were taken as the hypoxic tolerant group (Tol). Water samples from each experimental tank were collected every hour. The DO level was monitored using the classic iodine quantity method , and adjAfter selection, as described above, fish were anesthetized with excess MS-222 (100 mg/L) which quickly killed the fish. In total, the Tol and Intol group each consisted of 42 experimental fish . Brain and liver samples were taken from each fish, immediately frozen in liquid nitrogen and stored at −80°C until analysis. TRIzol reagent  was used, following the manufacturer’s instructions, to extract total RNA samples from the brain and liver of each fish and these were also stored at −80°C.All RNA samples were standardized to 500 ng/μl, with associated quality parameters of: OD ratios of 260/280 and 260/230 greater than 1.8 and RNA Integrity Number (RIN) greater than 8.0. The 14 RNA samples obtained from each tank were mixed to construct RNA sequencing libraries, three for the Tol group and three for the Intol group, using a TruSeq™ RNA Sample Preparation Kit . This was followed by KAPA quantification and dilution, after which each library was sequenced on an Illumina HiSeq 2500 (Illumina Inc.) with 125-bp paired-end reads. RNA-seq library preparation and sequencing was performed by BGI Technology Co., Ltd .p < 0.05. For this determination we used the OmicShare tool (www.omicshare.com/tools). DEGs were randomly selected for quantitative real-time PCR (qRT-PCR) to determine the accuracy of the sequencing data. Based on the sequencing, specific primers were designed using the Primer5 software , and low-quality sequences , the remaining clean reads were assembled using the Trinity software package .To identify SNPs and InDels, filtered reads were aligned to the reference genome using the Burrows-Wheeler Aligner  with the parameter “mem -M,” -M is an option used to mark shorter split alignment hits as secondary alignments . Then Pi1) markers with any missing genotypes were excluded; 2) markers with reading depth <10X or >500X in per bulk were excluded to eliminate those with low confidence due to low coverage, or those that may be in repetitive regions and thus have inflated read depths; 3) markers with SNP-index values in both bulks <0.3 or >0.7 were excluded.Variant calling was carried out using GATK UnifiedGenotyper (v3.5). SNPs and InDels were filtered using the GATK VariantFiltration function with proper standards . Several additional conditions were used for further marker filtering, i.e.: 1) Calculation of SNP-index and ∆(SNP-Index)Here we used commonly applied methods for BSR-Seq analysis, including the SNP-index method, the Euclidean Distance (ED) method and the G statistic method.The SNP-index and the ∆(SNP-Index)  of each ADr/(ADd+ADr)SNP-index = AD, Average depth of mixed pool samples; ADr, Average depth of recessive/mutation bulk; ADd, Average depth of dominance/wild bulk.2) Calculation of G statistic∆(SNP-Index) = SNP-index(recessive/mutation bulk) − SNP-index(dominance/wild bulk).O is the observed AD , E is the expected AD under the null hypothesis and is calculated as in the original G-statistic method (3) Calculation of Euclidean Distance (ED)The formula used to calculate the G statistic of each SNP was:c method , and ln Altr, Altd, Refr and Refd represent non-reference allele depth in recessive/mutation bulk, non-reference allele depth in dominance/wild bulk, reference allele depth in recessive/mutation bulk, reference allele depth in dominance/wild bulk, respectively. To eliminate the background noise, all ED values were powered, and the ED5 was used as the final ED value  and KEGG pathways (p < 0.05) compared with the whole transcriptome background. The KEGG database was used to integrate the focal pathways  raw reads (150 bp) were obtained from 12 mixed samples of different groups on the Illumina HiSeq platform. After integrating raw reads and filtering the low-quality sequences, the clean read count was 978.64 (M). The clean reads of four samples were aligned with the reference genome, and high-quality alignment results were obtained . The totp < 0.05) (seeq < 0.05). However, 77 DEGs were classified into carbohydrate and lipid metabolism processes, including Pentose and glucuronate interconversions, Glycolysis/Gluconeogenesis, Glyoxylate and dicarboxylate metabolism, Butanoate metabolism, Amino sugar and nucleotide sugar metabolism, Pentose phosphate pathway, Fructose and mannose metabolism, Ascorbate and aldarate metabolism, Propanoate metabolism, Steroid biosynthesis, Steroid hormone biosynthesis, Fatty acid degradation and biosynthesis (A previous study of ours described the mRNA profile from the brain and liver of golden pompano . The res < 0.05) , indicatynthesis .A total of 1,411,727 SNPs and 106,475 InDels were detected in the brain, and a total of 770,770 variants were detected in the liver, including 715,889 SNPs and 54,881 InDels . These SIn order to determine the reasonable fluctuation range of SNP-index and Δ (SNP-index), we performed 10,000 simulations on the ratio of dominant and recessive alleles based on population type, mixed pool size, and sequencing depth. After simulation, 95% (SNP-index) and 99% (Δ (SNP-index)) confidence intervals in the simulated values were taken as reasonable fluctuation ranges. After fitting, values exceeding the range were regarded as significant values, and the intervals corresponding to the significant values were regarded as candidate intervals. Combining this with the distribution of Δ (SNP-index) on the linkage group allowed the Manhattan scatter plot to be drawn . In the p values of each site were calculated by combining the Hampel rule and the Log-normal distribution. The p value was corrected using FDR to obtain the q value, and 0.01 and 0.05 were used as the threshold values, respectively. Combined with the distribution of the G value on the linkage group, the Manhattan scatter plot was drawn   , and the < 0.05) . Among tp < 0.05). The 30 main pathways are shown in A KEGG pathway analysis was performed for 768 candidate genes in the brain to identify the biochemical pathways operating. The results revealed 300 enriched pathways, and 12 pathways were significantly enriched (p < 0.05)  ; there wp < 0.05). The 30 main pathways are shown in A KEGG pathway analysis was performed for 348 candidate genes in the liver to identify the biochemical pathways operating. The results revealed 233 enriched pathways, and 14 pathways were significantly enriched (p < 0.05)  . In shorPTGS2), Trachinotus _GLEAN_10010124 (pla2g4a), Trachinotus_GLEAN_10015446 (ALOX5), Trachinotus_GLEAN _10015447 (ALOX5) and Trachinotus_GLEAN_10017022 (PLA2G12B). Among these important genes, the PTGS2 gene located on LG8 has a G/A nonsynonymous mutation at position 20641628, and the encoded amino acid was changed from hydrophobic aspartic acid to asparaginate (CYLD), Trachinotus_GLEAN_10017046 (trim72), Trachinotus_GLEAN_10018773 (Ifih1), and Trachinotus _GLEAN_10018778 (TANK). Among these important genes, the CYLD gene located on LG16 has a G/T nonsynonymous mutation at position 13629651, and the encoded amino acid was changed from alanine acid to valine. The Ifih1 gene located on LG18 has a G/C nonsynonymous mutation at position 16153700, the encoded amino acid was changed from hydrophilic glycine to hydrophobic alanine  using BSA along with pooled RNA-seq. First, clean reads were compared with the reference genome, and the number of trusted reads that were compared to a unique position accounted for more than 86%. After mutation detection and screening, a total of 555,478 SNPs and 65,157 InDels were detected in the brain, and a total of 265,920 SNPs and 30,684 InDels were detected in the liver. Integrating the results of the SNP-index analysis method, Gstatistic method, and ED analysis method, it was found that candidate regions in the brain were located in linkage groups 8, 18, and 22, and candidate regions in the liver were located in linkage groups 10, 16, 18, and 22. It is speculated that hypoxia tolerance of golden pompano may be determined by multiple linkage groups, especially linkage groups 18 and 22. In our experiments, BSR-Seq analysis identified 768 candidate genes in the brain and 348 candidate genes in the liver. We annotated these candidate genes to gain an insight into the biological processes and pathways of the key genes involved in the hypoxia adaptation of golden pompano. These pathways were involved in anaerobic energy metabolism, stress response, immune response, waste discharge, and cell death, enhancing the hypoxia tolerance and survival ability of fish. These results are consistent with previous research on other fish species, such as ruffe , flounder (Platichthys flesus) (Pelteobagrus vachelli)   and darkachelli) .Minpp1, Pcbd1, haao, Ephx1, and RBMS1 were classified as the metabolism pathways    by induc idella) . Additio idella) . Other rus hasta  and giltus hasta , as wellus hasta . COX encus hasta , among win vivo requires p53  and the oxidative phosphorylation pathway in the liver of the Gulf killifish (Fundulus grandis) were significantly increased under short-term hypoxia stress  in cells are stimulated, RLRs can activate RIG-I-like receptor signaling pathways associated with a viral infection . During Our results indicate candidate genes in the liver were significantly enriched in the RIG-I-like receptor signaling pathway. Therefore, we suggest that in our experimental fish, the death of the Intol-group under acute hypoxia stress may be due to the accumulation of lactic acid caused by the activation of the early anaerobic glycolysis pathway, which reduces the immunity of the fish. In future work, a major research direction will be to find the activation mechanisms of various signaling pathways under hypoxia conditions in fish. The results presented here show that the brain and liver have a certain synergistic effect during hypoxia which promotes hypoxia adaptation.in vivo, which reduces the immunity of the fish. Therefore, the balance of glucose and lipid metabolism plays a key role in the hypoxic tolerance of fish under acute hypoxia stress. Although additional research is needed to confirm these possibilities, our findings suggest these SNPs will help carry out the molecular breeding of hypoxia-tolerant golden pompano, and at the same time confirm that under acute hypoxia stress, the balance of glucose and lipid metabolism plays a key role in the hypoxia tolerance of fish.In this study, we used BSR-Seq analysis to explore the reasons for the differential hypoxia tolerance of the golden pompano population under acute hypoxia conditions. the arachidonic acid metabolism pathway in the brain of the Tol group may promote lipid metabolism and energy supply by regulating lipid decomposition, thereby improving the ability to adapt to hypoxia. However, the death of the Intol group under acute hypoxia stress may be due to the activation of the early anaerobic glycolysis pathway resulting in the accumulation of lactic acid, and the decrease of type I interferon production


The examined phenotypic data considered birth (BW), weaning (WW), and yearling weights. The association analysis was performed using the principal components method via the egscore function of the GenABEL version 1.8-0 package in the R environment. The marker rs133262280 located in BTA 22 was associated with BW, and two SNPs were associated with WW, rs43668789 (BTA 11) and rs136155567 (BTA 27). New QTL associated with these liveweight traits and four positional and functional candidate genes potentially involved in variations of the analyzed traits were identified. The most important genes in these genomic regions were MCM2 (minichromosome maintenance complex component 2), TPRA1 (transmembrane protein adipocyte associated 1), GALM , and NRG1 (neuregulin 1), related to embryonic cleavage, bone and tissue growth, cell adhesion, and organic development. This study is the first to present a GWAS conducted in Braunvieh cattle in Mexico providing evidence for genetic architecture of assessed growth traits. Further specific analysis of found associated genes and regions will clarify its contribution to the genetic basis of growth-related traits.A genome-wide association study (GWAS) was performed to elucidate genetic architecture of growth traits in Braunvieh cattle. Methods: The study included 300 genotyped animals by the GeneSeek The identification of causal genetic variability is one of the main goals in the genetic improvement of cattle. Commonly, liveweight traits are used as the primary selection criterion in cow-calf production systems in Mexico . UsuallyBos indicus cattle [Braunvieh is a worldwide cattle breed used in the beef industry that has been used in both specialized beef and dual-purpose production herds ,4. Due ts cattle ,6. Howevs cattle ,6,7. TheThe use of microarrays of thousands of SNP markers in genome-wide association studies (GWAS) has allowed discovering the genetic basis of complex traits and diseases by detecting genotype–phenotype associations in a group of individuals . GWAS apHair follicle samples from 236 females and 64 males registered in the Mexican Braunvieh Cattle Association database were collected. The cattle were born between 2000 and 2015. This population came from herds located in the east, west, and central highlands of Mexico. Herds from west and east were raised under extensive production systems, while central highlands herds were under intensive regimens. The sampled population’s genetic background included Austrian, Swiss, Canadian, American, and Mexican animals. Phenotypic data were provided by the breeding association and included records of birth weight , weaning weight , yearling weight . Weaning and yearling weights were adjusted to perform the GWAS analysis.® Genomic Profiler Bovine LDv.4 panel . Before association analysis, the genotypic data quality was verified using the SNPQC program [n = 1623). Those SNPs that were monomorphic (n = 3604), presented call rates of less than 90% (n = 1290) or minor allele frequencies < 0.01 (n = 1325), or deviated from the Hardy–Weinberg equilibrium according to Fisher’s exact test and exhibited p-values >1 × 10−15 (n = 0) were also eliminated. Additionally, SNPs with unknown coordinates in the assembly of the bovine genome UMD v3.1 [n = 1484) and SNPs that were not located on autosomal chromosomes (n = 1820) were discarded.The animals were genotyped using 30,125 SNP markers from the GeneSeek program . The genUMD v3.1  (n = 148n = 0) or levels of heterozygosity (HE) above 3 SD (n = 1), considering that the mean and SD of the observed HE were 0.32 and 0.019, respectively. A Pearson correlation was computed for detecting potentially duplicate samples, considering a maximum of r = 0.98, according to their genotype information obtaining an average of r = 0.817 and minimum and maximum values of 0.66 and 0.90, respectively. A total of 22,734 SNPs and 276 samples passed the quality control procedure and were retained for further analysis. Quality control and subsequent analyses were performed in the R environment.Samples were also eliminated if they exhibited call rates of less than 80% , where N was the number of genotyped individuals, and K was the number of PCs.A linear model for each trait was fitted, including the first two PC as covariates. For the analysis of BW, the model also included the contemporary group (CG) and the linear and quadratic effects of cow age at the birth and weaning of her calf. The CG included herd, sex, year, and calving season. The statistical model used to adjust the other traits only included the CG and the PCs as covariates; cow age was excluded because it was not significant in the previous analysis. Finally, the association between corrected genotypes and phenotypes was assessed via correlation. p-values < 5 × 10−5 were considered significantly associated with studied traits. The proportion of phenotypic variance explained by the SNPs was estimated by dividing the x2 value for a df by the number of individuals used to analyze each SNP marker, followed by multiplication by 100. All described analyses and estimations were performed using the GenABEL package [Minimum allele frequencies, allele substitution effect (β), and percentage of phenotypic variance explained by the SNP were estimated. SNP with  package .The closest genes to significant markers and those located within a 250 kb window on both SNP location sides were identified. The list of genes was obtained using the snp2gene.LD function from the Postgwas package . DistancAnnotations from humans or mice were used when there was no information on the genes in cattle. Genes were considered functional and positional candidates if they were biologically related to the trait under study, supported by experimental evidence in the literature. Finally, we determined whether significant SNPs mapped against QTLs previously associated with growth-related traits such as BW, carcass, and reproduction traits, deposited in the cattle AnimalQTLdb . For thi® Genomic Profiler Bovine LD v4 microarray panel  were used for association with live weight traits of Braunvieh cattle. On average, 1004 SNP markers were evaluated in each BTA. Bos taurus chromosomes 1 and 27 exhibited the highest (1602) and lowest (512) SNP numbers. The average distance between adjacent SNP was 87,641 bp, the minimum distance (0 bp) between adjacent SNP were found on BTA 1, 6, 7, 12, 17, 18, 22, 25, 26, 28, and 29, while the maximum distance  was found on BTA 6. A total of 30,125 SNP markers from the GeneSeekp < 5 × 10−5), 3 SNP were associated with the studied growth traits. Two SNP was associated with BW and one SNP was associated to WW. The rs133262280 located in BTA22 was associated with BW, showing an allelic substitution effect of 0.320 ± 0.02 kg. The rs43668789 and rs136155567, located in BTA11 and 27, respectively, were associated with WW. These markers showed allelic substitution effects of −9.590 ± 0.25 and 1.110 ± 0.72 kg, respectively , MCM2 (mini-chromosome maintenance complex component 2), PLXNA1 (plexin A1), PODXL2 , TPRA1 (transmembrane protein adipocyte associated 1), and uncharacterized LOC10105309  which is the putative replicative helicase essential for “once per cell cycle” DNA replication initiation and elongation in eukaryotic cells [MCM2 gene.Birth weight in Braunvieh cattle represents an important trait to consider in the genetic improvement programs due to its association with calving difficulty in young heifers, especially when the Braunvieh is used as a sire for smaller-size breeds . In the 10105309 . The mosic cells . Additioic cells . Gao et ic cells  reportedic cells  found byTPRA1 gene belonging to the G protein-coupled receptor (GPCR) family. Functions related to this gene include regulating early embryonic cleavage and enhancing the hedgehog signaling pathway [The other associated gene with biological importance was the  pathway ,39. Seve pathway  determinMCM2 and TPRA1 could participate in the early stages of cattle development and, therefore, influence BW. There were no quantitative trait loci previously located in this region, which could be a specific QTL of the studied population.This evidence suggests that The present study identified two regions (ARHGEF33 (Rho guanine nucleotide exchange factor 33), CDKL4 (cyclin-dependent kinase-like 4), DHX57 (DExH-box helicase 57), GALM , GEMIN6 (gem nuclear organelle associated protein 6), LOC104973309 , LOC107132913 (uncharacterized LOC107132913), LOC782845 , MAP4K3 (mitogen-activated protein kinase 3), MIR2284Z-2 (microRNA 2284z-2), MORN2 (MORN repeat containing 2), SOS1 (SOS Ras/Rac guanine nucleotide exchange factor 1), and SRSF7 (serine and arginine-rich splicing factor 7)  . Interespossible .GALM. This gene is located 217.4 kb upstream of the rs43668789 and belongs to the proteins that convert the α-aldose to β-anomer. GALM is involved in the pathway hexose metabolism, which is part of carbohydrate metabolism [GALM with the weaning weight in Angus cattle. Shin et al. [GALM and the weaning weight in Holstein and Hanwoo cattle lies in quantity and the quality of the calves’ milk consumption. Quantitative trait loci located in this region have been previously associated with weaning weight in Angus [The most important gene identified in this region was tabolism . McCluretabolism  reportedin Angus , conformin Angus ,28, and in Angus .LOC104976093 (uncharacterized LOC104976093) and NRG1 (neuregulin 1)  included gulin 1) . NRG1 waelopment ,45. In celopment . Zhao [4elopment  mentioneIn general, the phenotypic variance explained by the SNPs identified in this study was marginal (1.39% on average). In growth trait studies, it is expected that most SNP markers will explain only a tiny proportion of the observed phenotypic variance due to the polygenic control over such traits and because individual genes only slightly influence a phenotype. However, consideration of SNPs’ sets that are significantly associated with each trait may allow a greater proportion of phenotypic variance to be explained. For example, the two SNPs associated with WW could explain 4.08% of the variance in that trait. It is important to note the lack of significant association for YW. Although not a highly strict threshold was chosen, the amount of data reduction from BW and WW to YW might be related to these outcomes. However, the present outcomes increase knowledge of the genetic architecture of growth traits important in beef cattle production.ARHGEF33 gene. Additionally, evidence shows that some of the genes closer to the three identified SNPs markers are functionally related to growth through embryonic cleavage, bone and tissue growth, cell adhesion, and organ development. There were four candidate genes with potential associations with assessed live weight traits in Braunvieh cattle, including MCM2, TPRA1, GALM, and NRG1. Subsequent studies examining these genomic regions could lead to the identification of polymorphisms with potential uses in the marker-assisted selection, providing a deeper understanding of the genetic basis and genetic architecture of growth traits in cattle. This study represents the first study to describe a GWAS conducted in Braunvieh cattle in Mexico. Further analysis using the present information would allow to conduct assessments on the ontogeny and specific search of causative mutations for live weight traits. Furthermore, examining particular and general genic effects would indicate the possibility of including genomic information into current genetic evaluations.In conclusion, in the present study, three SNPs were associated with the assessed growth traits of Braunvieh cattle. Two SNPs were located in intergenic regions, and one was located in an intronic region of the


Ecologically relevant factors such as exercise and diet quality can directly influence how physiological systems work including those involved in maintaining oxidative balance; however, to our knowledge, no studies to date have focused on how such factors directly affect expression of key components of the endogenous antioxidant system  in several metabolically active tissues of a migratory songbird. We conducted a three-factor experiment that tested the following hypotheses: (H1) Daily flying over several weeks increases the expression of transcription factors NRF2 and PPARs as well as endogenous antioxidant genes , and upregulates endogenous antioxidant enzyme activities . (H2) Songbirds fed diets composed of more 18:2n-6 PUFA are more susceptible to oxidative damage and thus upregulate their endogenous antioxidant system compared with when fed diets with less PUFA. (H3) Songbirds fed dietary anthocyanins gain additional antioxidant protection and thus upregulate their endogenous antioxidant system less compared with songbirds not fed anthocyanins. Flight training increased the expression of 3 of the 6 antioxidant genes and transcription factors measured in the liver, consistent with H1, but for only one gene (SOD2) in the pectoralis. Dietary fat quality had no effect on antioxidant pathways (H2), whereas dietary anthocyanins increased the expression of select antioxidant enzymes in the pectoralis, but not in the liver (H3). These tissue-specific differences in response to flying and dietary antioxidants are likely explained by functional differences between tissues as well as fundamental differences in their turnover rates. The consumption of dietary antioxidants along with regular flying enables birds during migration to stimulate the expression of genes involved in antioxidant protection likely through increasing the transcriptional activity of NRF2 and PPARs, and thereby demonstrates for the first time that these relevant ecological factors affect the regulation of key antioxidant pathways in wild birds. What remains to be demonstrated is how the extent of these ecological factors  influences the regulation of these antioxidant pathways and thus oxidative balance. Aerobically respiring organisms must maintain a balanced oxidative status where excess reactive species are neutralized with antioxidants to minimize resulting oxidative damage or such damage must be repaired . MaintaiThe major cellular pathways in all animals for regulating the antioxidant response include peroxisome proliferator-activated nuclear receptors (PPARs) and nuclear factor erythroid 2-related factor 2 (NRF2). These transcription factors regulate endogenous antioxidant enzymes, and both transcription factors can be affected by ecologically relevant factors including exercise  and dietNRF2 binds to the antioxidant response element (ARE) to transcribe an array of 250 genes involved in antioxidant protection and redox homeostasis  includinExercise and the associated increases in metabolism can stimulate molecular antioxidant pathways by (1) increasing the production of reactive species resulting in increased NRF2 transcription  and (2) Exercise also stimulates PPAR pathways mainly through the generation of PPAR fat ligands and increased expression of peroxisome proliferator-activated receptor gamma coactivator (PGC-1) cofactors that bind to PPARs to increase their transcriptional activity . An 8-weBirds rely on fatty acids to fuel flight , and cerMany songbird species select fruits high in antioxidants during migration, suggesting that antioxidant consumption is important to protect against oxidative damage during this life history stage . Water-sThe goal of this experimental study was to investigate how flight training in a wind tunnel as well as consumption of certain dietary fats  and dietary antioxidants  affected the expression of NRF2 and PPAR transcription factors, select antioxidant genes, and corresponding antioxidant enzymes in the liver and the pectoralis muscle of a migratory songbird. We tested the following three hypotheses: Flight training effect (H1): flying regularly over several weeks (1) increases the expression of NRF2 and PPARs, and thereby (2) increases the expression of endogenous antioxidant genes , and (3) produces a coordinated upregulation of endogenous antioxidant enzyme activities . Dietary fat effect (H2): migratory songbirds fed diets composed of more PUFA are more susceptible to oxidative damage and thus have increased expression levels of NRF2 and PPAR transcription factors, selected antioxidant genes, and corresponding antioxidant enzyme activities compared with birds fed diets with less PUFA. Dietary antioxidant effect (H3): migratory songbirds fed dietary anthocyanins have less need to upregulate their endogenous antioxidant system and thus have decreased expression levels of the NRF2 and PPAR transcription factors, selected antioxidant genes, and corresponding antioxidant enzymes compared with songbirds not fed anthocyanins. We also examined whether these three ecologically relevant factors  significantly interacted to affect key components of the antioxidant system. For example, the compensatory function of dietary antioxidants may be most evident in birds that are flight trained due to their inhibitory effect on NRF2 and PPARs and the transcription of antioxidant enzymes. Whereas, a stimulatory function of dietary antioxidants may be evident in untrained birds due to their stimulatory effects on NRF2 activity in organisms at rest.Sturnus vulgaris) as representative songbirds for this study because they are abundant in the New World and Old World, they are omnivorous and acclimate well to captivity and new diets, and they have been successfully trained and flown in wind tunnels in other studies  and differed only in fatty acid composition. We manipulated the proportions of canola, sunflower, and palm oil so that the diets were either high (32%) or low (13%) in 18:2n-6 PUFA (linoleic acid) that was primarily traded off with 16:0 . Thus, our experimental design requires us to attribute any observed dietary fat effects to both 18:2n-6 and 16:0 content. However, our interpretations focus on the potential effects of 18:2n-6 due to its demonstrated importance in metabolic signaling (N = 23); 13% 18:2n-6, anthocyanin supplemented (N = 23); 32% 18:2n-6, anthocyanin unsupplemented (N = 21); and 32% 18:2n-6, anthocyanin supplemented (N = 20). We chose the anthocyanin concentration used by researchers studying the effects of anthocyanin supplementation on food choice and immunocompetence in European blackcaps, Sylvia atricapilla . Anthocyanins are particularly relevant to songbirds since they are prevalent in fruits consumed during migration  following kit instructions including the recommended DNase treatment step, but without the proteinase K digestion step for the liver. RNA concentrations and quality were verified using a NanoDrop . RNA (0.5 μg) was reverse transcribed using the SuperScript IV First-strand Synthesis System Kit , and cDNA was used as a template for qPCR. Each 17.5 μL PCR reaction mixture was comprised of 1:15 diluted cDNA template, 400 nM gene-specific primers, and The Applied Biosystems™ PowerUp™ SYBR™ Green Master Mix . The temperature cycles for each PCR reaction were as follows: 2 min at 50°C, 2 min at 95°C, 45 cycles of 95°C for 15 s, and a primer-specific optimal temperature (62–68°C) for 1 min. Each PCR run was completed with a melt curve analysis to confirm the presence of a single PCR product, and amplification efficiency was verified for every primer pair. The gene expression values were derived from a standard curve generated for each primer set. Primer sequences were derived using NCBI's BLASTN v2.10.0 program and searching the European starling's genome database (Sturnus_vulgaris-1.0 reference Annotation Release 100) for predicted genes. Primers were designed so that at least one primer was exon spanning. Primers in our study met the following criteria: amplification of a single product indicated by a single peak in the melting curve analysis and efficiency of amplification between 98% and 100%. In all cases, cycle threshold (Ct) values ranged from 18 to 29, except for PPARγ that was detected between 30 and 32 range. Primer sequences and GenBank accession numbers are shown in Quantitative reverse transcription PCR (qRT-polymerase chain reaction (PCR)) was performed to quantify relative expression of select antioxidant genes, NRF2, and PPARs. Total RNA was extracted from liver and pectoralis muscle (25–30 mg) using RNeasy® Fibrous Mini Kit  or liver  or over the course of the experiment in the pectoralis  or liver . Transcript expression normalized to β-actin was used for causal pathway analyses. Normalized transcript expression relative to the 13% 18:2n-6, low antioxidant, untrained reference group was used for all linear models, a quantification method referred to as relative gene expression.Transcript expression levels were normalized to the reference gene β-actin, which codes for the β-actin gene responsible for the structure and motility of cells, and is highly conserved across tissues and avian species . β-Acting for 10 min at 4°C , and the supernatant was aliquoted to three separate tubes (∼200 μL per tube) to conduct the four separate assays . A chelating agent (EDTA) was added to the tubes used to measure enzymatic antioxidant activity to protect the sample from the rapid autoxidation from trace metal ions within the sample, resulting in a final buffer containing 0.05 M phosphate-buffered saline and 0.1 mM EDTA, pH 7. Supernatant was immediately frozen at −80°C until the time of the assay (1–3 months after homogenization).In preparation for the measurement of antioxidant enzyme activity, approximately 250 mg of tissue was homogenized on ice in nine volumes of 0.1 M phosphate buffer, pH 7 with 3 × 10 s pulses of a high-speed stainless-steel homogenizer . Homogenate was centrifuged at 10,000 The activities of CAT, SOD, and GPx enzymes were assayed according to Cayman Chemical  commercial kit protocols , and all enzyme activities were normalized to soluble protein content (mg/mL) as measured by the Bradford protein assay  using a bovine albumin serum standard (Fisher Scientific AAJ6477709) . All assWe used R v3.5.3; .To test the hypothesis that NRF2 and PPAR transcription factors regulate antioxidant gene expression, and thereby regulate antioxidant enzyme activities we conducted a unidirectional path analysis that tests the causal relationships between regulatory genes (NRF2 and PPARs) and downstream antioxidant genes , and between antioxidant genes and antioxidant enzyme activities . We conducted a path analysis in the liver and pectoralis separately for flight-trained and untrained birds. We did not control for diet in our liver models since we found no effects of dietary fat and antioxidants (see the “Results” section). However, due to the positive effect of anthocyanins on select antioxidant gene expression in the pectoralis (see the “Results” section), we initially conducted path analyses for each anthocyanin diet in the pectoralis for flight-trained and untrained birds . We presCausal Equation 1.Causal Equation 2.87 = 2.909, P = 0.0047; SOD2, T87 = 2.472, P = 0.016; GPX1, T87 = 2.904, P = 0.0047). Flight training did not significantly affect expression of SOD1 or GPX4 in the liver . The expression of transcription factors NRF2  despite their effect sizes that were similar to the expression of CAT, SOD2, and GPX1 in response to flight training. In general, we found greater variability in the expression of transcription factors compared with antioxidant genes and this may have affected the detection of statistical significance. PPARα was not affected by flight training . In the pectoralis, flight training increased the expression of only SOD2 , decreased the expression of PPARδ , and did not influence expression of the other four antioxidant genes  or NRF2 .Flight training consistently increased the expression of three of the five measured antioxidant enzyme genes in the liver A but affors NRF2 A and PPAors NRF2  was grea86 = −2.744, P = 0.0075; liver CAT activity, T86 = −4.093, P < 0.001; pectoralis CAT activity, T90 = −4.189, P < 0.001), while SOD activity in the liver and pectoralis and GPX activity in the pectoralis were unchanged by flight training .Contrary to hypothesis 1, expression patterns of the antioxidant genes and antioxidant enzyme activities were not well coordinated in response to flight training in either tissue. In fact, antioxidant enzymes displayed an opposite pattern compared with antioxidant genes in relation to flight training. For example, GPx activity in the liver and CAT activity in the liver and pectoralis were lowest in flight-trained birds relative to untrained birds , and a positive effect of date on GPx activity in the pectoralis . There was no effect of date on GPx activity in the liver . Our experimental design allowed us to determine the specific time intervals that affected antioxidant enzyme activity by utilizing cohorts that were sampled across the 3-month experiment. We constructed linear models using the experimental cohort (1–5) as a covariate instead of Julian date. In accordance with the effect of Julian date, the declines in CAT and SOD activity in the liver and pectoralis were primarily due to the last cohort sampled  or in the pectoralis . PPARα was positively affected by dietary 18:2n-6 , and these results are discussed in a companion study  although there was a trend for CAT expression to be less in birds supplemented with anthocyanins , although there was no other effect of dietary anthocyanin on the other antioxidant genes or NRF2 expression .Dietary anthocyanin had a more targeted effect on antioxidant genes compared with flight training. Dietary anthocyanin did not significantly influence NRF2 or antioxidant gene expression in the liver  NRF2 and PPAR expression and thereby increases (2) the expression of their antioxidant genes and the (3) activities of their related antioxidant enzyme activities, we constructed a causal model for flight-trained and untrained birds for both the liver  and pectIn general, flight training altered the relationships among transcription factors and antioxidant genes in a tissue-specific manner. For example, in the liver , flight We found little evidence that antioxidant gene expression related to antioxidant enzyme activities. For example, in the liver , antioxiWe found support for hypothesis 1 (flight training stimulated the expression of antioxidant genes) that was tissue specific: flight-trained birds had significantly higher expression of three of the five antioxidant genes  measured in liver but only one of five (SOD2) measured in pectoralis. The mitochondria produce superoxide radicals that are among the most reactive , and thePython molurus bivittatus) post-feeding during which rapid organ growth and 44-fold increases in metabolism occur  was also provided by the PPAR transcription factors, but again the patterns were tissue specific  and 6. IIn contrast to our predictions, our causal models  and 6 prOncorhynchus mykiss) larvae with the highest PUFA fatty acid compositions in the first week of growth had the highest levels of CAT, SOD, and GPX expression compared with later growth periods with lower PUFA composition (Pelteobagrus vachelli) fed higher levels of linseed oil containing more PUFA had higher serum antioxidant enzyme activities   . It is pOD, GPX) . Lipid pOD, GPX) . Future Sylvia atricapilla)   perhaps capilla)  indicaticapilla) , and theWe propose that the distinct gene expression profiles for the antioxidant genes for the two tissues are driven by the metabolic state and main functions of the liver and pectoralis. A companion study demonstrated that key genes involved in fat metabolism were upregulated in the pectoralis of flight-trained songbirds, but not in the liver . In contWe provide some of the first evidence for how antioxidant pathways respond to ecological factors that are relevant to songbirds during migration. Exercise, dietary fat, and dietary antioxidants have been shown to influence antioxidant transcription factors  and their downstream antioxidant genes in other organisms , althougobab035_Supplemental_FileClick here for additional data file.


Until recently, Nurr1 (NR4A2) was known as an orphan nuclear receptor without a canonical ligand-binding domain, featuring instead a narrow and tight cavity for small molecular ligands to bind. In-depth characterization of its ligand-binding pocket revealed that it is highly dynamic, with its structural conformation changing more than twice on the microsecond-to-millisecond timescale. This observation suggests the possibility that certain ligands are able to squeeze into this narrow space, inducing a conformational change to create an accessible cavity. The cocrystallographic structure of Nurr1 bound to endogenous ligands such as prostaglandin E1/A1 and 5,6-dihydroxyindole contributed to clarifying the crucial roles of Nurr1 and opening new avenues for therapeutic interventions for neurodegenerative and/or inflammatory diseases related to Nurr1. This review introduces novel endogenous and synthetic Nurr1 agonists and discusses their potential effects in Nurr1-related diseases. Compounds that activate a gene-regulating protein called Nurr1 could help treat Parkinson’s disease and other brain disorders related to abnormal dopamine signaling. A team led by Kwang-Soo Kim from Harvard Medical School, Belmont, USA, reviews the various compounds, both synthetic and natural, known to enhance the activity of Nurr1. This protein binds DNA to regulate the expression of target genes and was long thought not to have such triggering molecules or ligands, which have recently been identified by the team. These activating compounds seem to protect dopamine-producing neurons from cell injury in various Parkinson’s-related cell and animal models. Given Nurr1’s role in the development, differentiation, and survival of dopaminergic neurons in the midbrain, these compounds could help boost the capacity of malfunctioning dopaminergic neurons in patients with Parkinson’s disease, schizophrenia, bipolar disorder, and other neuropsychiatric conditions. Nuclear receptors with no known specific ligand(s) are referred to as orphan nuclear receptors2. Until recently, the transcription factor Nurr1, which belongs to the NR4A subfamily, was considered an orphan nuclear receptor. The NR4A subfamily of nuclear receptors includes Nur77 (NR4A1), Nurr1 (NR4A2), and Nor1 (NR4A3)4. All family members have a ligand-binding domain (LBD) that shares sequence homology with the LBDs of canonical nuclear receptors6. Nevertheless, it was widely believed that Nurr1 is constitutively active in a ligand-independent manner6. In fact, crystal structural analysis revealed that the Nurr1-LBD lacks a classical binding pocket for coactivators and/or ligands due to the tight packing of bulky hydrophobic side chain residues7. However, recent NMR solution and HDX-MS characterizations revealed that the Nurr1-LBD is highly dynamic with high solvent accessibility, showing a change in structural conformation more than twice on the microsecond-to-millisecond timescale8. Numerous researchers are gradually identifying and validating the endogenous and synthetic ligands that activate Nurr1. Furthermore, recent characterization of Nurr1’s endogenous ligands has aroused further interest in the development of Nurr1 agonists and therapeutic drugs for diseases related to the receptor10. Therefore, this review focuses on putative ligands known to induce/enhance Nurr1 transcriptional activity.In general, a nuclear receptor is a ligand-regulated transcription factor that regulates downstream gene transcription in the nucleus in response to binding to its specific ligand(s)12. Nurr1 is known to regulate the transcription of dopamine-related crucial genes, including tyrosine hydroxylase (TH), dopamine transporter (DAT), vesicular monoamine transporter 2 (VMAT2), and aromatic amino acid decarboxylase (AADC), which significantly influence striatal dopamine levels13. To modulate the expression of these genes, Nurr1 binds to the nerve growth factor-induced clone B (NGFI-B) response element specific sequence  as a monomer or to the inverted repeat octanucleotide Nur response element  as a homodimer15. In addition, Nurr1 can interact with retinoid-X receptor alpha (RXRα), forming a heterodimer that binds to the DR5-specific sequence element (5’-GGTTCACCGAAAGGTCA-3’)15. Indeed, Nurr1-deficient mice fail to generate midbrain dopaminergic neurons16, and tamoxifen-induced disruption of Nurr1 in the midbrain of adult mice also results in a progressive reduction in the number of striatal dopaminergic neurons17. Thus, these findings support Nurr1’s critical roles in both the development and maintenance of midbrain dopaminergic neurons.In the midbrain, Nurr1 is indispensable for the differentiation, maturation, and maintenance of midbrain dopaminergic neuron clusters (referred to as A9 and A10), which reside in the ventral tegmental area (VTA) and the substantia nigra pars compacta (SNpc), respectively18. Thus, it is possible that G-protein coupled receptors that increase intracellular cAMP levels, such as brain-derived neurotrophic factor (BDNF) and prostanoid receptors, which are involved in the neuroprotective pathways for dopaminergic neurons, are highly associated with Nurr1. In neuroprotective pathways, Nurr1 is known to regulate the expression of various nuclear-encoded mitochondrial genes in dopaminergic neurons17. It was found that a significant reduction in the levels of superoxide dismutase 1 (SOD1), which is one of these mitochondrial genes, is strongly implicated in oxidative stress detoxification in Nurr1-ablated cells17. Furthermore, Nurr1 is known to transcriptionally repress proinflammatory genes in microglia and astrocytes upon exposure to bacterial lipopolysaccharide (LPS), suggesting that it exerts neuroprotection by suppressing neurotoxic proinflammatory genes in the brain during inflammation21. Taken together, this evidence indicates that Nurr1 transcriptionally promotes the expression of anti-inflammatory genes, represses the expression of proinflammatory genes, and protects dopaminergic neurons.In addition, Nurr1 is also known to exert neuroprotective effects against neuroinflammation of dopaminergic neurons. The promoter region of Nurr1 contains the transcriptional binding site of cAMP-responsive element-binding protein (CREB), and its interaction induces the upregulation of Nurr1 transcripts. This CREB-mediated Nurr1 upregulation seems to be involved in neuroprotection as a regulatory mechanism downstream of CREB24. To date, no mechanistic hypothesis has been put forth to explain this reduced expression. Therefore, the development of selective Nurr1 agonists offers the possibility to provide target-based therapeutic interventions for PD and other related diseases.While Nurr1 is important for the maintenance and protection of dopaminergic neurons, it has been reported that Nurr1 expression in the brains of Parkinson’s disease (PD) patients and in the brains of rodent models of PD induced by forced expression of α-synuclein or exposure to neurotoxins (6-OHDA or MPTP) is downregulatedContrary to the existing concept that Nurr1 is constitutively active, several studies have attempted to identify potent Nurr1 agonists from established chemical libraries. Because Nurr1 binds to the promoter region of target genes, cell-based luciferase reporter assays using specific Nurr1-binding sequence(s) have been used for high-throughput screenings.25. 6-Mercaptopurine is commonly used for treating cancer and autoimmune diseases such as acute/chronic leukemia, ulcerative colitis, and Crohn’s disease27. It was shown to robustly enhance Nurr1 transcriptional activity using the NurRE target sequence in a concentration-dependent manner in CV-1 cells25. In the following year, reports indicated that bicyclic isoxazolopyridinone-based compounds increase Nurr1 reporter gene activity as a homodimer and a heterodimer using the NurRE and DR5 sequence elements, respectively  and striatumof OF1 mice at doses of 5 to 30 mg/kg28.6-Mercaptopurine was the first Nurr1 agonist identified from a 340,800 compound prototypic library Fig. 25. 6-Merely Fig. 28. The m29. They synthesized 3840 compounds harboring the benzimidazole scaffold and tested for potential agonists using a Nurr1 DNA binding domain (DBD)-containing luciferase construct in MN9D cells. To rule out the possibility of heterodimer activation of Nurr1 and RXRα, they also assessed luciferase activity in the RXRα-overexpressing cell line. Using this reporter assay, they identified three potent Nurr1 agonists active with an EC50 in the nanomolar range (8–70 nM)29. In 2008, the pharmaceutical company Sanofi Aventis introduced the bicyclic-based Nurr1 agonist SA00025, a 2-aryl-6-phenylimidazopyridine derivative  for 32 days protects dopaminergic neurons in a 6-OHDA-induced lesion rat model of PD exacerbated by inflammation31.Based on the benzimidazole scaffold, a bicyclic compound of fused benzene and imidazole Fig. , Dubois ive Fig. 30. In vi32. The identified imidazopyridine-derived compounds are N-phenyl-6-(pyrid-2-yl)imidazopyridine-2-carboxamide C33. Moreover, using radiolabeled [3H]-CQ, the researchers showed saturable binding to Nurr1-LBD with a dissociation constant (Kd) of 0.27 μM and a maximal binding capacity (Bmax) of 13.9 μM33. Unlabeled AQ competed for the binding of [3H]-CQ to Nurr1-LBD, indicating that AQ/CQ binds to similar Nurr1-LBD residues. Furthermore, nuclear magnetic resonance (NMR) spectroscopy also suggested the existence of molecular interactions between AQ/CQ and Nurr1-LBD. The comparison of Nurr1-LBD spectra for free and AQ-bound showed that multiple residues were shifted in the helix α2 region  and the helix α11 region 33. CQ-bound spectra showed perturbed residues mostly in the helix α4 (Ser441) and the helix α12 region  of Nurr1-LBD34.Using a cell-based luciferase assay system, Kim and colleagues screened a chemical library composed of 960 FDA-approved drugs and identified 3 potential Nurr1 activators, namely, amodiaquine (AQ) Fig. , chloroqPlasmodium parasites through mosquito bites35. Originally, AQ/CQ was developed as anti-malaria drugs, and they are still commonly used to treat malaria36. Since AQ/CQ is known as active Nurr1 ligands, several studies have demonstrated the therapeutic effects of AQ/CQ based on Nurr1 modulation in several neurodegenerative and inflammatory diseases34.Malaria is a serious tropical disease associated with high fever, chills, and flu-like symptoms and is typically transmitted by 33. Furthermore, this study revealed that CQ had neuroprotective effects against the neurotoxin 6-OHDA both in vitro and in vivo, resulting in significant improvements in PD-like motor behaviors in 6-OHDA-lesioned rats33. Hedya et al., using the rotenone rat model of PD, showed that the less toxic derivative hydroxychloroquine (HCQ) exerts an anti-inflammatory effect associated with increased Nurr1 expression, reduced activity of GSK-3β, and diminished expression levels of inflammatory mediators 37. Consequently, treatment with HCQ resulted in amelioration of rotenone-induced impaired motor behaviors37.The biological effects of AQ/CQ were demonstrated in the dopaminergic system. In cultured rat dopaminergic neurons, exposure to AQ was shown to significantly enhance the mRNA levels of Nurr1-target genes such as TH, DAT, VMAT, and AADC in a concentration-dependent manner39. By overexpressing and silencing Nurr1 in the hippocampal area, the researchers demonstrated that Nurr1 ameliorates AD‐related pathological symptoms, including Aβ‐plaque deposition, in 5XFAD mice38. In line with these findings, 5XFAD mice treated with AQ exhibited marked improvements in typical AD pathogenesis, including deposition of Aβ plaques, neuronal loss, impaired adult hippocampal neurogenesis, and cognitive defects38. Further investigation of adult hippocampal neural stem cells determined that AQ increases hippocampal adult neurogenesis through cell cycle progression40.Since Nurr1 is highly expressed in hippocampal neurons as well, Moon and colleagues attempted to clarify the function of Nurr1 and the effect of AQ in Alzheimer’s disease (AD), which is characterized by memory loss (dementia) caused by neuronal loss in the hippocampus starting in the early stage of disease41. Intraperitoneal injection of AQ (40 mg/kg) after IHC induction prominently attenuated the activation of microglia/macrophages and astrocytes in the perihematomal area, consequently improving impaired motor deficits41. Given that CQ is commonly used to treat autoimmune diseases such as rheumatoid arthritis44, it is possible that Nurr1 is involved in the differentiation of naïve T cells into regulatory T cells, which are critical to immune homeostasis47. Indeed, Park et al. found that CQ facilitates differentiation into regulatory T cells via induction of the Foxp3 gene by Nurr134. Intraperitoneal injection of CQ (50 mg/kg) was shown to mitigate colitis inflammation in a dextran sulfate sodium (DSS)-induced colitis mouse model, a valid animal model of inflammatory bowel disease34.Recently, Kinoshita et al. demonstrated AQ’s anti-inflammatory effect from a different perspective. Nurr1 is highly expressed in microglia/macrophages and astrocytes in the perihematomal area of the striata of mice with intracerebral hemorrhage (ICH)49. Subsequently, L-dopa is converted to dopamine by the enzyme AADC49. The resulting dopamine is transported into the synaptic vesicle by VMAT250. Released dopamine is recycled by DAT, which takes it back into the cytosol from the synaptic cleft51.The biosynthesis and storage of the neurotransmitter dopamine are regulated by several enzymes and cofactors, all of which can control dopamine levels. In dopamine synthesis, TH is a rate-limiting enzyme that converts amino acid tyrosine to L-dopa13. Therefore, it is possible that Nurr1’s activity in dopamine processing could be tightly regulated by dopamine, its precursors, and/or its metabolites to maintain dopamine homeostasis. In support of this possibility, using biophysical assays and X-ray crystallography, Bruning and colleagues found that the dopamine metabolite 5,6-dihydroxyindole (DHI) directly binds to Nurr1-LBD , vesicle packaging VMAT2), and dopamine reuptake DAT, which could significantly influence striatal dopamine levels, and dop52. Thus, oxidative stress induces pathological accumulation of cytosolic dopamine in dopaminergic neurons. In particular, the dopamine oxidation product DHI could influence the deposition of α-synuclein aggregates in dopaminergic neurons, a pathogenic feature of PD53. Taken together, this evidence suggests that because excessive dopamine proportionally increases the levels of these reactive metabolites, it is likely that DHI-induced Nurr1 activation regulates the transcription levels of Nurr1 target genes, including those involved in the synthesis, packaging, and reuptake of dopamine.Little is known about the effect of the recently identified DHI on the dopaminergic system. Under oxidative stress, dopamine can be oxidized into two DHI and 5,6-indolequinone molecules, which are cytotoxic intermediates in the biosynthetic pathway of neuromelanin9. However, the dependence of these changes on Nurr1 expression remains to be elucidated. Nurr1 knockdown and overexpression systems would offer conclusive evidence. In addition, the roles of DHI in the dopaminergic system should be further investigated in rodent models.To verify this possibility, the changes in the transcription levels of several Nurr1 target genes induced by DHI were evaluated in zebrafish. Exposure of zebrafish embryos (3 days post-fertilization) to 100 µM DHI resulted in a significant increase in VMAT2 and DAT transcript levels after 6 h as well as increases in VMAT2 and TH levels after 24 h54. Fatty acids are converted into well-known functional metabolites such as arachidonic acid, eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA)55. These unsaturated fatty acids have two long hydrocarbon tails, which may allow them to squeeze into the hydrophobic and narrow cavity of the canonical pocket of NR4A-LBDs. In fact, some remarkable studies have highlighted the interaction between unsaturated fatty acids and NR4A-LBDs. For example, a metabolomics-based study of immobilized Nur77-LBD revealed its interaction with unsaturated fatty acids, including arachidonic acid and DHA56. Using a pull-down assay, it was later shown that DHA also interacts with Nurr1-LBD  induced Nurr1 transcriptional activity using the NBRE target sequence in HEK293T and MN9D cells57. Further in-depth analysis revealed that unsaturated fatty acids, including arachidonic acid, linoleic acid, and oleic acid, bind to Nurr1-LBD and induce conformational expansion, which allows more ligands to access the ligand-binding pocket8.Prostaglandins (PGs) are bioactive lipid metabolites derived from the metabolism of membrane polyunsaturated fatty acidsLBD Fig. 57. Titra59. Kagaya and colleagues demonstrated a direct interaction between PGA2 and Nor1-LBD using a cell-free Biacore system. Moreover, they showed that PGA2 (10 μM) is a transcriptional activator of Nor1 in NIH3T3 cells58. In addition, incubation of recombinant Nur77 with PGA2-biotin allowed the identification of the PGA2-Nur77 complex through the covalent interaction between PGA2 and the Cys566 residue of Nur7759. In a Nur77-specific reporter assay, treatment with PGA2 caused dose-dependent transcriptional activation of Nur77 but not PGE2 in human bronchial epithelial (NHBE) cells59.The cyclopentenone PGA2 was the first PG identified as an active ligand of Nor1 and Nur7710. Initially, using the DAD of the yeast transcription factor GAL4 fused to the Nurr1-LBD in a human neuroblastoma cell line (SK-N-BE(2)C), the authors found that treatment with several tissue extracts increased Nurr1 transcriptional activity. To isolate the active components from the brain extracts, they performed sequential purification using boiling, acetone precipitation, and ultrafiltration to identify the Nurr1 activity-enriched fractions. Finally, PGE1 and 8-iso PGE1 were identified from several candidate compounds in the final active fraction. In the process of crystallizing the Nurr1-LBD-PGE1 complex, the dehydrated PGE1 metabolite PGA1 was found to form a covalent adduct between the C11 atom of the cyclopentenone ring and the thiol group of the Cys566 residue of Nurr1-LBD. It is likely that crystallization conditions  lead to the spontaneous dehydration of PGE1 to PGA1. This is supported by several reports showing PGE1 dehydration in acidic/basic environments61. An added intriguing feature of Nurr1-LBD binding to PGA1 is that the two long fatty acid tails of PGA1 are squeezed into a hydrophobic space surrounded by helices H4, H11, and H12, inducing the outward movement of helix H12 from the core of Nurr1 at an angle of 21°.Most recently, an extensive study performed by Rajan et al. in which active compounds were isolated from homogenized mouse tissue extracts identified PGE1 Fig.  and PGA155. PGE1 is synthesized from dihomo-γ-linolenic acid, which originates from linoleic acid (omega-6)55. PGE2 and PGE3 are enzymatically produced from arachidonic acids originating from linoleic acids and α-linolenic acid-mediated EPA/DHA. PGE1-3 is further converted to PGA1-3 by a nonenzymatic dehydration process63. In general, PGEs activate prostaglandin E receptors (EP1-EP4), which subsequently regulate the levels of intracellular second messengers, cAMP, and Ca2+, via G proteins67. Despite extensive investigations across various fields on the roles of PGs, little is known about the actions of PGE1 and PGA1 in dopaminergic neurons where Nurr1 is functionally expressed16.As shown in Fig. 68. Unlike EP2- and EP3-selective agonists, a EP1 receptor-specific agonist (17-phenyl trinor PGE2) was shown to exert significant toxic effects on dopaminergic neurons at nanomolar concentrations68. Conversely, antagonism by EP1 receptor blockers (SC-19220 and SC-51089) was shown to protect dopaminergic neurons against 6-OHDA-induced toxicity in rat primary mesencephalic culture68. Moreover, 6-OHDA-induced dopaminergic neuronal death was alleviated by treatment with an EP2 receptor-selective agonist (butaprost)69. Taken together, these findings suggest that the EP2 receptor-mediated cAMP pathway seems to be crucially involved in the survival of dopaminergic neurons.Double immunohistochemistry for specific EP receptors and TH revealed that EP1/EP2 receptors and EP2/EP3 receptors are selectively expressed in dopaminergic and nondopaminergic neurons in the rat SN3H]-PGE1 and [3H]-PGA1 demonstrated that PGE1 interacts with both EP2 and Nurr1 and that PGA1 binds only to Nurr110. Taken together, this evidence indicates that PGE1 regulates the transcriptional activity of Nurr1 via two distinct mechanisms: an EP2-mediated pathway and direct binding to Nurr1-LBD. In contrast, PGA1 covalently binds to the Cys566 residue of Nurr1-LBD and activates its transactivation.Based on reporter assays, both PGE1 and PGA1 induce transcriptional activation of Nurr1 in a dose-dependent manner. Interestingly, PGE1-induced Nurr1 activation is inhibited by an EP2-selective antagonist (PF-04418948), whereas PGA1-mediated activation is not. In fact, radiolabeled ligand binding assays with EP2 and Nurr1-LBD proteins using [+-induced toxicity in a Nurr1-dependent manner. PGE1 and PGA1 ameliorated both MPP+- and LPS-induced losses of TH-positive dopaminergic neurons in the nanomolar range in primary dopaminergic neuron-glia cocultures isolated from the rat embryonic ventral mesencephalic area. Moreover, intraperitoneal injection of PGE1 (2 mg/kg) or PGA1 (2 mg/kg) significantly rescued dopaminergic neurons in the SN and the striatum and alleviated impaired motor behaviors in a subchronic MPTP-induced animal model of PD.In the midbrain, the PGE1- and PGA1-mediated Nurr1 axis seems to be crucial for protection against dopaminergic neuronal degeneration. PGE1 (3 μM) or PGA1 (5 μM) treatment was shown to protect MN9D and N27-A cells from MPP71, it is also possible that Nurr1’s protein stability and/or transcriptional activity may be regulated by altered levels of intracellular cAMP. Further studies are warranted for clarification of these mechanisms as well as for therapeutic development of these Nurr1 ligands.In this review, we introduced recent findings on potent synthetic and endogenous ligands of Nurr1 ligands, a nuclear receptor that has long been referred to as a ligand-independent nuclear receptor Tables . The actIn conclusion, in vitro and in vivo studies have recently provided strong evidence that Nurr1-activating compounds/ligands have the potential to protect dopaminergic neurons in various PD-related cell and animal models. Consequently, modulators that enhance Nurr1 function have great potential to be developed as novel mechanism-based disease-modifying therapeutics for PD from a transcriptional regulation perspective.


The recent availability of dense panels of single nucleotide polymorphism (SNP) markers has permitted a finer investigation of genome architecture, a deeper understanding of biology and evolution, and the implementation of marker-assisted and genomic selection in livestock species. Paradigmatic examples of the use of SNP panels include understanding domestication, population diversity, inbreeding, admixture, demographic trajectories, identification of loci associated with economically important traits, and accurate prediction of breeding values. The common denominator of the vast majority of the research conducted in livestock to date has relied on analytical tools that treat genetic markers as individual and independent variables. We know, however, that genetic inheritance is driven by segments of closely interlinked nucleotides. Thus, utilizing phased multi-marker segments  holds the potential of improving existing models. This is particularly true in genome-wide association studies (GWAS) and genomic predictions, which are analyses that rely on the concept that information of unobserved causal variants is captured by correlation (linkage disequilibrium—LD) with nearby (observed) markers.in silico procedure that allows us to expand upon our information on sparse SNP markers produced by existing microarray data up to the whole-genome sequence level without additional genotyping and sequencing.The potential utilization of haplotypes in genetic analysis is highly varied. Haplotypes are used in the imputation process. Imputation is the Since haplotypes may serve as better proxies for causal variants than single SNP markers, the incorporation of haplotype data in genomic predictions seems promising in the absence of information on functional alleles. In extensive conditions, e.g., in the tropics, haplotypes could be used to select favorable combinations of variants in crossbreds and advanced backcross programs to retain those important for adaptation to local environmental conditions as well as those for improved production. Also, the models applied to the characterization of livestock genetic diversity could be re-designed to better estimate relationship and inbreeding, facilitate the investigation of difficult traits, as those involved in adaptation to different production systems and ecosystems, and extend the investigation of genotype-by-environment interaction. Future developments in animal breeding and genetics will be strongly based on the increasing availability of data, both molecular and phenotypic. However, our ability to dissect and understand livestock complex traits is still limited. The use of haplotypes instead of single markers and of more correct inheritance models may contribute to a better understanding of the genetics underlying livestock trait complexity and biology.The “Haplotype Analysis Applied to Livestock” Research Topic is intended to collect empirical studies and theoretical papers exploring, evaluating, and improving the use of haplotype analysis in livestock. After its conclusion, it managed to collect 12 articles from 89 authors, with subjects ranging from relatively straightforward diversity analyses to complex applications to unravel the genetic architecture of quantitative traits. Data used in the research studies were SNP microarray data, whole-genome sequences, or a combination of both.Qanbari, with a focus on cattle and chicken populations. The study provides insights into pair-wise allelic correlations and haplotype structure in the genomes of livestock.Haplotype size is influenced by recombination, and consequently by the level of linkage disequilibrium (LD) existing in a population. In livestock, LD has been largely influenced by human decisions since domestication, as humans have ruled livestock demography and recent selection intensity and direction. The extent of LD in livestock is reviewed by Won et al. Their study showed increased accuracies when haplotypes, rather than single SNPs, were used to predict genomic breeding values. Importantly, the authors found that not all traits benefit from the use of haplotype data equally, and that haplotype size should be optimized on a case-by-case basis. Therefore, their results suggest a need for further improvements in methods for haplotype size selection that can consider both population structure and trait architecture.The concept of LD was also utilized in the development of hierarchical clustering methods for haplotype-based genomic predictions by Aliloo et al., who sought genomic regions influencing milk production and carrying selection signals related to variation in environment, climate, and disease challenges on the African continent. The study focused on highly admixed populations of exotic and local cattle breeds. Finding selection signatures related to tolerance to African animal trypanosomiasis in Sheko cattle was the goal of Mekonnen et al. The identified genomic regions were further investigated to find promising candidate genes and over-represented genomic pathways influencing trypanotolerance. A promising regulator appears to be Caspase protease, which could play a role in the design of future intervention strategies to improve the health of cattle populations.Haplotypes are also used to detect selection signatures. An example of their utilization is shown by Luzuriaga-Neira et al. described the population structure and the relationships among South American chicken populations. Understanding the origin and assessing the extent of genetic diversity is pivotal in safeguarding and valuating animal genetic resources. Unfortunately, local chicken populations are often neglected in this respect. Admixture studies revealed the strong influence of commercial populations but also discovered unusual gene flows within the continent.A wider diversity study by Butty et al. compared different methods designed to optimize the selection of samples to compose a reference haplotype library supporting routine imputation. In summary, if the reference set is empty, key ancestors and animals carrying common haplotypes should be the first to be included in the library. Identification of the latter can be conducted with the new Highly Segregating Haplotype method presented by the authors. As the reference set grows, rare alleles become more important, in which case newer reference samples should be selected using the Inverse Selection Method. Faux et al. presented a method for automatically matching haplotypes used for imputation, which utilizes extremely randomized trees in a random forests method. The approach holds great potential in improving imputation accuracy, as well as in developing new applications that rely on haplotype matching, such as identification of deleterious haplotypes or prediction of carriers of complex structural variants.The correct identification of haplotypes based on reference genomic data is one of the cornerstones of imputation techniques. Meier et al. analyzed casein variants in German Black Pied cattle, Xu et al. provided insight into the genomic architecture of scrotal hernia in pigs, Oyelami et al. revealed new candidate genes and QTLs for meat quality and disease resistance in pigs, and Zhang et al. investigated hip-height and muscle development in beef cattle. The overarching theme in these studies was the use of haplotypes, instead of single SNPs, to identify relevant regions of the genome to be used in DNA-assisted breeding programs.The power of haplotypes in capturing information about unobserved sequence variants has vast applications. For example, Selle et al. combined simulation studies and cattle data with the goal to improve estimates of haplotype effects on traits of interest, especially in cases of limited data availability for rare haplotypes.From a general perspective, however, the natural hereditary processes and the genetic architecture of economic traits are profoundly complex. This is in contrast with the need for the development of reliable models. The hierarchical modeling technique developed by The papers included in the Research Topic “Haplotype Analysis Applied to Livestock” are examples of how these genomic segments could be utilized in a wide variety of ways. We invite you to browse and read them with the hope that they widen your overview and give you new ideas for future investigations.All authors contributed to the writing and revision of the manuscript to an equal extent.By the time this research topic was completed, YTU was a member of the scientific board of AgroPartners Consulting. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.