Isolation and genome characterization of Paenibacillus polymyxa 188, a potential biocontrol agent against fungi.

AIMS: In this work, we aimed to isolate marine bacteria that produce metabolites with antifungal properties. METHODS AND RESULTS: Paenibacillus polymyxa 188 was isolated from a marine sediment sample, and it showed excellent antifungal activity against many fungi pathogenic to plants (Fusarium tricinctum, Pestalotiopsis clavispora, Fusarium oxysporum, F. oxysporum f. sp. Cubense (Foc), Curvularia plantarum, and Talaromyces pinophilus) and to humans (Aspergillus terreus, Penicillium oxalicum, and Microsphaeropsis arundinis). The antifungal compounds produced by P. polymyxa 188 were extracted and analyzed using matrix-assisted laser desorption ionization time-of-flight mass spectrometry. The complete genome sequence and biosynthetic gene clusters of P. polymyxa 188 were characterized and compared with those of other strains. A total of 238 carbohydrate-active enzymes (CAZymes) were identified in P. polymyxa 188. Two antibiotic gene clusters, fusaricidin and tridecaptin, exist in P. polymyxa 188, which is different from other strains that typically have multiple antibiotic gene clusters. CONCLUSIONS: Paenibacilluspolymyxa 188 was identified with numerous biosynthetic gene clusters, and its antifungal ability against pathogenic fungi was verified.

Whole genome sequence characterization of Aspergillus terreus ATCC 20541 and genome comparison of the fungi A. terreus.

Aspergillus terreus is well-known for lovastatin and itaconic acid production with biomedical and commercial importance. The mechanisms of metabolite formation have been extensively studied to improve their yield through genetic engineering. However, the combined repertoire of carbohydrate-active enzymes (CAZymes), cytochrome P450s (CYP) enzymes, and secondary metabolites (SMs) in the different A. terreus strains has not been well studied yet, especially with respect to the presence of biosynthetic gene clusters (BGCs). Here we present a 30 Mb whole genome sequence of A. terreus ATCC 20541 in which we predicted 10,410 protein-coding genes. We compared the CAZymes, CYPs enzyme, and SMs across eleven A. terreus strains, and the results indicate that all strains have rich pectin degradation enzyme and CYP52 families. The lovastatin BGC of lovI was linked with lovF in A. terreus ATCC 20541, and the phenomenon was not found in the other strains. A. terreus ATCC 20541 lacked a non-ribosomal peptide synthetase (AnaPS) participating in acetylaszonalenin production, which was a conserved protein in the ten other strains. Our results present a comprehensive analysis of CAZymes, CYPs enzyme, and SM diversities in A. terreus strains and will facilitate further research in the function of BGCs associated with valuable SMs.

Comparative transcriptome analysis of skin color-associated genes in leopard coral grouper (Plectropomus leopardus).

BACKGROUND: The leopard coral grouper (Plectropomus leopardus) is an important economic species in East Asia-Pacific countries. To meet the market demand, leopard coral grouper is facing overfishing and their population is rapidly declining. With the improvement of the artificial propagation technique, the leopard coral grouper has been successfully cultured by Fisheries Research Institute in Taiwan. However, the skin color of farmed individuals is often lacking bright redness. As such, the market price of farmed individuals is lower than wild-type. RESULTS: To understand the genetic mechanisms of skin coloration in leopard coral grouper, we compared leopard coral grouper with different skin colors through transcriptome analysis. Six cDNA libraries generated from wild-caught leopard coral grouper with different skin colors were characterized by using the Illumina platform. Reference-guided de novo transcriptome data of leopard coral grouper obtained 24,700 transcripts, and 1,089 differentially expressed genes (DEGs) were found between red and brown skin color individuals. The results showed that nine candidate DEGs (epha2, sema6d, acsl4, slc7a5, hipk1, nol6, timp2, slc25a42, and kdf1) significantly associated with skin color were detected by using comparative transcriptome analysis and quantitative real-time polymerase chain reaction (qRT-PCR). CONCLUSIONS: The findings may provide genetic information for further skin color research, and to boost the market price of farmed leopard coral grouper by selective breeding.

Editing Aspergillus terreus using the CRISPR-Cas9 system.

CRISPR-Cas9 technology has been utilized in different organisms for targeted mutagenesis, offering a fast, precise and cheap approach to speed up molecular breeding and study of gene function. Until now, many researchers have established the demonstration of applying the CRISPR/Cas9 system to various fungal model species. However, there are very few guidelines available for CRISPR/Cas9 genome editing in Aspergillus terreus. In this study, we present CRISPR/Cas9 genome editing in A. terreus. To optimize the guide ribonucleic acid (gRNA) expression, we constructed a modified single-guide ribonucleic acid (sgRNA)/Cas9 expression plasmid. By co-transforming an sgRNA/Cas9 expression plasmid along with maker-free donor deoxyribonucleic acid (DNA), we precisely disrupted the lovB and lovR genes, respectively, and created targeted gene insertion (lovF gene) and iterative gene editing in A. terreus (lovF and lovR genes). Furthermore, co-delivering two sgRNA/Cas9 expression plasmids resulted in precise gene deletion (with donor DNA) in the ku70 and pyrG genes, respectively, and efficient removal of the DNA between the two gRNA targeting sites (no donor DNA) in the pyrG gene. Our results showed that the CRISPR/Cas9 system is a powerful tool for precise genome editing in A. terreus, and our approach provides a great potential for manipulating targeted genes and contributions to gene functional study of A. terreus.

Acid external and internal environment exchange the Oreochromis niloticus tissue immune gene expression compared to the mouse macrophage polarization model.

The water environment plays an important role in animal physiology. In this study, we sought to evaluate the effect of the acid environment on the Oreochromis niloticus (Nile tilapia) internal microenvironment immune response compare to the mouse macrophage model (J77A.1). The acid environment treated mouse macrophage J774A.1 model have shown that acidic treatment is able to polarize macrophages into M2-like macrophages via an increase in Ym1, Tgm2, Arg1, Fizz1, and IL-10 expression. Metabolic analysis of mouse macrophages (J774A.1) at pH 2 vs. pH 7 and pH 4 vs. pH 7 have been shown to promote the expression of intracellular acetylcholine, choline, prochlorperazine, L-leucine, and bisphenol A,2-amino-3-methylimidazo[4,5-f] quinolone metabolites in the M2-like macrophage. Immune gene expression of the O. niloticus spleen and liver treated at pH 2, 4, and 7 was shown to reduce TNF-α, IL-1 ß, IL-8, and IL-12 expression compared to pH 7 treatment. Immune gene was induced in O. niloticus following culture at pH 5, 6, and 7 fresh water environment. Taken together, we found that the acid internal environment polarizes tissues into an M2 macrophage developmental microenvironment. However, if the external environment is acid, tissues are exposed to an M1 macrophage developmental microenvironment.

Estimating the Yield of Compounds on the TLC Plate via the Blue-LED Illumination Technique.

Thin-layer chromatography (TLC) is an accessible analytical technique that has been extensively used in organic chemistry research to quantify the yield of unknown samples. The present study developed an effective, cheap, and safe method to estimate the yield of samples on a TLC plate using the blue-LED illuminator. Lovastatin extracted from Aspergillus terreus was the example compound used in the present study. Regression models based on the lovastatin standard were used to evaluate the yield of lovastatin. Three methods were compared: bioassay, UV detection, and blue-LED illumination. The result showed that the blue-LED illumination method is significantly more time-effective than UV detection and bioassay methods. Additionally, the blue-LED illumination was a relatively safe option because of the concern of biological hazards in the bioassay method (e.g., microbial infection) and ultraviolet exposure in the UV detection method. Compared to the expensive methods requiring specialized instruments and long-term training before working independently, such as GC, HPLC, and HPTLC, using the blue-LED illuminator was an economical option to estimate the yield of samples from a TLC plate.

Use of multiple traits genomic prediction, genotype by environment interactions and spatial effect to improve prediction accuracy in yield data.

Genomic selection has been extensively implemented in plant breeding schemes. Genomic selection incorporates dense genome-wide markers to predict the breeding values for important traits based on information from genotype and phenotype records on traits of interest in a reference population. To date, most relevant investigations have been performed using single trait genomic prediction models (STGP). However, records for several traits at once are usually documented for breeding lines in commercial breeding programs. By incorporating benefits from genetic characterizations of correlated phenotypes, multiple trait genomic prediction (MTGP) may be a useful tool for improving prediction accuracy in genetic evaluations. The objective of this study was to test whether the use of MTGP and including proper modeling of spatial effects can improve the prediction accuracy of breeding values in commercial barley and wheat breeding lines. We genotyped 1,317 spring barley and 1,325 winter wheat lines from a commercial breeding program with the Illumina 9K barley and 15K wheat SNP-chip (respectively) and phenotyped them across multiple years and locations. Results showed that the MTGP approach increased correlations between future performance and estimated breeding value of yields by 7% in barley and by 57% in wheat relative to using the STGP approach for each trait individually. Analyses combining genomic data, pedigree information, and proper modeling of spatial effects further increased the prediction accuracy by 4% in barley and 3% in wheat relative to the model using genomic relationships only. The prediction accuracy for yield in wheat and barley yield trait breeding, were improved by combining MTGP and spatial effects in the model.

Author Correction: Genomic prediction and GWAS of yield, quality and disease-related traits in spring barley and winter wheat.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Genomic prediction and GWAS of yield, quality and disease-related traits in spring barley and winter wheat.

Genome-wide association study (GWAS) and genomic prediction (GP) are extensively employed to accelerate genetic gain and identify QTL in plant breeding. In this study, 1,317 spring barley and 1,325 winter wheat breeding lines from a commercial breeding program were genotyped with the Illumina 9 K barley or 15 K wheat SNP-chip, and phenotyped in multiple years and locations. For GWAS, in spring barley, a QTL on chr. 4H associated with powdery mildew and ramularia resistance were found. There were several SNPs on chr. 4H showing genome-wide significance with yield traits. In winter wheat, GWAS identified two SNPs on chr. 6A, and one SNP on chr. 1B, significantly associated with quality trait moisture, as well as one SNP located on chr. 5B associated with starch content in the seeds. The significant SNPs identified by multiple trait GWAS were generally the same as those found in single trait GWAS. GWAS including genotype-location information in the model identified significant SNPs in each tested location, which were not found previously when including all locations in the GWAS. For GP, in spring barley, GP using the Bayesian Power Lasso model had higher accuracy than ridge regression BLUP in powdery mildew and yield traits, whereas the prediction accuracies were similar using Bayesian Power Lasso model and rrBLUP for yield traits in winter wheat.

Genotype Imputation To Improve the Cost-Efficiency of Genomic Selection in Farmed Atlantic Salmon.

Genomic selection uses genome-wide marker information to predict breeding values for traits of economic interest, and is more accurate than pedigree-based methods. The development of high density SNP arrays for Atlantic salmon has enabled genomic selection in selective breeding programs, alongside high-resolution association mapping of the genetic basis of complex traits. However, in sibling testing schemes typical of salmon breeding programs, trait records are available on many thousands of fish with close relationships to the selection candidates. Therefore, routine high density SNP genotyping may be prohibitively expensive. One means to reducing genotyping cost is the use of genotype imputation, where selected key animals (e.g., breeding program parents) are genotyped at high density, and the majority of individuals (e.g., performance tested fish and selection candidates) are genotyped at much lower density, followed by imputation to high density. The main objectives of the current study were to assess the feasibility and accuracy of genotype imputation in the context of a salmon breeding program. The specific aims were: (i) to measure the accuracy of genotype imputation using medium (25 K) and high (78 K) density mapped SNP panels, by masking varying proportions of the genotypes and assessing the correlation between the imputed genotypes and the true genotypes; and (ii) to assess the efficacy of imputed genotype data in genomic prediction of key performance traits (sea lice resistance and body weight). Imputation accuracies of up to 0.90 were observed using the simple two-generation pedigree dataset, and moderately high accuracy (0.83) was possible even with very low density SNP data (∼250 SNPs). The performance of genomic prediction using imputed genotype data was comparable to using true genotype data, and both were superior to pedigree-based prediction. These results demonstrate that the genotype imputation approach used in this study can provide a cost-effective method for generating robust genome-wide SNP data for genomic prediction in Atlantic salmon. Genotype imputation approaches are likely to form a critical component of cost-efficient genomic selection programs to improve economically important traits in aquaculture.

Genomic prediction of host resistance to sea lice in farmed Atlantic salmon populations.

BACKGROUND: Sea lice have significant negative economic and welfare impacts on marine Atlantic salmon farming. Since host resistance to sea lice has a substantial genetic component, selective breeding can contribute to control of lice. Genomic selection uses genome-wide marker information to predict breeding values, and can achieve markedly higher accuracy than pedigree-based methods. Our aim was to assess the genetic architecture of host resistance to sea lice, and test the utility of genomic prediction of breeding values. Individual lice counts were measured in challenge experiments using two large Atlantic salmon post-smolt populations from a commercial breeding programme, which had genotypes for ~33 K single nucleotide polymorphisms (SNPs). The specific objectives were to: (i) estimate the heritability of host resistance; (ii) assess its genetic architecture by performing a genome-wide association study (GWAS); (iii) assess the accuracy of predicted breeding values using varying SNP densities (0.5 to 33 K) and compare it to that of pedigree-based prediction; and (iv) evaluate the accuracy of prediction in closely and distantly related animals. RESULTS: Heritability of host resistance was significant (0.22 to 0.33) in both populations using either pedigree or genomic relationship matrices. The GWAS suggested that lice resistance is a polygenic trait, and no genome-wide significant quantitative trait loci were identified. Based on cross-validation analysis, genomic predictions were more accurate than pedigree-based predictions for both populations. Although prediction accuracies were highest when closely-related animals were used in the training and validation sets, the benefit of having genomic-versus pedigree-based predictions within a population increased as the relationships between training and validation sets decreased. Prediction accuracy reached an asymptote with a SNP density of ~5 K within populations, although higher SNP density was advantageous for cross-population prediction. CONCLUSIONS: Host resistance to sea lice in farmed Atlantic salmon has a significant genetic component. Phenotypes relating to host resistance can be predicted with moderate to high accuracy within populations, with a major advantage of genomic over pedigree-based methods, even at relatively sparse SNP densities. Prediction accuracies across populations were low, but improved with higher marker densities. Genomic selection can contribute to lice control in salmon farming.

Bone Healing Improvements Using Hyaluronic Acid and Hydroxyapatite/Beta-Tricalcium Phosphate in Combination: An Animal Study.

The purpose of this study was to investigate whether the use of HLA as an aqueous binder of hydroxyapatite/beta-tricalcium phosphate (HA-ßTCP) particles can reduce the amount of bone graft needed and increase ease of handling in clinical situations. In this study, HA/ßTCP was loaded in commercially available crosslinking HLA to form a novel HLA/HA-ßTCP composite. Six New Zealand White rabbits (3.0-3.6 kg) were used as test subjects. Four 6 mm defects were prepared in the parietal bone. The defects were filled with the HLA/HA-ßTCP composite as well as HA-ßTCP particle alone. New bone formation was analyzed by micro-CT and histomorphometry. Our results indicated that even when the HA-ßTCP particle numbers were reduced, the regenerative effect on bone remained when the HLA existed. The bone volume density (BV/TV ratio) of HLA/HA-ßTCP samples was 1.7 times larger than that of the control sample at week 2. The new bone increasing ratio (NBIR) of HLA/HA-ßTCP samples was 1.78 times higher than the control group at week 2. In conclusion, HA-ßTCP powder with HLA contributed to bone healing in rabbit calvarial bone defects. The addition of HLA to bone grafts not only promoted osteoconduction but also improved handling characteristics in clinical situations.

Genome wide association and genomic prediction for growth traits in juvenile farmed Atlantic salmon using a high density SNP array.

BACKGROUND: The genetic architecture of complex traits in farmed animal populations is of interest from a scientific and practical perspective. The use of genetic markers to predict the genetic merit (breeding values) of individuals is commonplace in modern farm animal breeding schemes. Recently, high density SNP arrays have become available for Atlantic salmon, which facilitates genomic prediction and association studies using genome-wide markers and economically important traits. The aims of this study were (i) to use a high density SNP array to investigate the genetic architecture of weight and length in juvenile Atlantic salmon; (ii) to assess the utility of genomic prediction for these traits, including testing different marker densities; (iii) to identify potential candidate genes underpinning variation in early growth. RESULTS: A pedigreed population of farmed Atlantic salmon (n = 622) were measured for weight and length traits at one year of age, and genotyped for 111,908 segregating SNP markers using a high density SNP array. The heritability of both traits was estimated using pedigree and genomic relationship matrices, and was comparable at around 0.5 and 0.6 respectively. The results of the GWA analysis pointed to a polygenic genetic architecture, with no SNPs surpassing the genome-wide significance threshold, and one SNP associated with length at the chromosome-wide level. SNPs surpassing an arbitrary threshold of significance (P < 0.005, ~ top 0.5 % of markers) were aligned to an Atlantic salmon reference transcriptome, identifying 109 SNPs in transcribed regions that were annotated by alignment to human, mouse and zebrafish protein databases. Prediction of breeding values was more accurate when applying genomic (GBLUP) than pedigree (PBLUP) relationship matrices (accuracy ~ 0.7 and 0.58 respectively) and 5,000 SNPs were sufficient for obtaining this accuracy increase over PBLUP in this specific population. CONCLUSIONS: The high density SNP array can effectively capture the additive genetic variation in complex traits. However, the traits of weight and length both appear to be very polygenic with only one SNP surpassing the chromosome-wide threshold. Genomic prediction using the array is effective, leading to an improvement in accuracy compared to pedigree methods, and this improvement can be achieved with only a small subset of the markers in this population. The results have practical relevance for genomic selection in salmon and may also provide insight into variation in the identified genes underpinning body growth and development in salmonid species.

The origin of the bifurcated axial skeletal system in the twin-tail goldfish.

Twin-tail goldfish possess a bifurcated caudal axial skeleton. The scarcity of this trait in nature suggests that a rare mutation, which drastically altered the mechanisms underlying axial skeleton formation, may have occurred during goldfish domestication. However, little is known about the molecular development of twin-tail goldfish. Here we show that the bifurcated caudal skeleton arises from a mutation in the chordin gene, which affects embryonic dorsal-ventral (DV) patterning. We demonstrate that formation of the bifurcated caudal axial skeleton requires a stop-codon mutation in one of two recently duplicated chordin genes; this mutation may have occurred within approximately 600 years of domestication. We also report that the ventral tissues of the twin-tail strain are enlarged, and form the embryonic bifurcated fin fold. However, unlike previously described chordin-deficient embryos, this is not accompanied by a reduction in anterior-dorsal neural tissues. These results provide insight into large-scale evolution arising from artificial selection.

Embryonic development of goldfish (Carassius auratus): a model for the study of evolutionary change in developmental mechanisms by artificial selection.

BACKGROUND: Highly divergent morphology among the different goldfish strains (Carassius auratus) may make it a suitable model for investigating how artificial selection has altered developmental mechanisms. Here we describe the embryological development of the common goldfish (the single fin Wakin), which retains the ancestral morphology of this species. RESULTS: We divided goldfish embryonic development into seven periods consisting of 34 stages, using previously reported developmental indices of zebrafish and goldfish. Although several differences were identified in terms of their yolk size, epiboly process, pigmentation patterns, and development rate, our results indicate that the embryonic features of these two teleost species are highly similar in their overall morphology from the zygote to hatching stage. CONCLUSIONS: These results provide an opportunity for further study of the evolutionary relationship between domestication and development, through applying well-established zebrafish molecular biological resources to goldfish embryos.