CO2 Valorization in Deep Eutectic Solvents.

The deep eutectic solvent (DES) has emerged in recent years as a valuable medium for converting CO2 into valuable chemicals because of its easy availability, stability, and safety, and its capability to dissolve carbon dioxide. CO2 valorization in DES has evolved rapidly over the past 20 years. As well as being used as solvents for acid/base-promoted CO2 conversion for the production of cyclic carbonates and carbamates, DESs can be used as reaction media for electrochemical CO2 reduction for formic acid and CO. Among these products, cyclic carbonates can be used as solvents and electrolytes, carbamate derivatives include the core structure of many herbicides and pesticides, and formic acid and carbon monoxide, the C1 electrochemical products, are essential raw materials in the chemical industries. An overview of the application of DESs for CO2 valorization in recent years is presented in this review, followed by a compilation and comparison of product types and reaction mechanisms within the different types of DESs, and an outlook on how CO2 valorization will be developed in the future.

Catalyst self-assembly accelerates bimetallic light-driven electrocatalytic H2 evolution in water.

Hydrogen evolution is an important fuel-generating reaction that has been subject to mechanistic debate about the roles of monometallic and bimetallic pathways. The molecular iridium catalysts in this study undergo photoelectrochemical dihydrogen (H2) evolution via a bimolecular mechanism, providing an opportunity to understand the factors that promote bimetallic H-H coupling. Covalently tethered diiridium catalysts evolve H2 from neutral water faster than monometallic catalysts, even at lower overpotential. The unexpected origin of this improvement is non-covalent supramolecular self-assembly into nanoscale aggregates that efficiently harvest light and form H-H bonds. Monometallic catalysts containing long-chain alkane substituents leverage the self-assembly to evolve H2 from neutral water at low overpotential and with rates close to the expected maximum for this light-driven water splitting reaction. Design parameters for holding multiple catalytic sites in close proximity and tuning catalyst microenvironments emerge from this work.

Anion-Bridged Dual Hydrogen Bond Enabled Concerted Addition of Phenol to Glycal.

A noncovalent organocatalytic concerted addition of phenol to glycal is developed for the stereoselective and regioselective construction of biologically important phenolic 2-deoxyglycosides, featuring wide substrate tolerance. The method relies on an anion-bridged dual hydrogen bond interaction which is experimentally proved by Nuclear Magnetic Resonance (NMR), Ultraviolet and visible (UV-vis), and fluorescence analysis. Experimental evidence including kinetic analysis, Kinetic Isotope Effect (KIE) studies, linear free energy relationship, Hammett plot, and density functional theory (DFT) calculations is provided for a concerted mechanism where a high-energy oxocarbenium ion is not formed. In addition, the potential utility of this method is further demonstrated by the synthesis of biologically active glycosylated flavones. The benchmarking studies demonstrate significant advances in this newly developed method compared to previous approaches.

Long-term divergent selection for residual feed intake in Chinese broiler chickens.

This study aimed to assess the effect of inbreeding on production traits using a long-term closed-line population recorded for residual feed intake (RFI). The study first used data from a previously reported population to determine the appropriate period of divergent selection for RFI. The results showed that RFI had similar moderate heritability estimates (0.28-0.34) during the fast-growing period (7-12 wk), and RFI at 7 to 10 wk had the highest heritability (0.34). Therefore, divergent selection was performed in a Chinese broiler population for RFI at 7 to 10 wk; the total sample size from generations zero (G0) to 13 was 9050. The divergence between the 2 lines increased steadily throughout generations, resulting in G13 with average RFI values of 304.55 in high RFI (HRFI) males, -160.31 in low RFI (LRFI) males, 296.30 in HRFI females and -157.55 in LRFI females. The feed intake (FI) and feed conversion ratio were almost higher in HRFI broilers than in LRFI broilers, and the magnitude of the difference in FI increased from approximately 4% for both sexes in G1 to approximately 33% in G13. Body weight gain was irregular from G1 to G13 and higher in LRFI broilers than in HRFI broilers after G10. Indeed, the HRFI broilers consumed more food, but they were lighter than LRFI broilers. In G13, LRFI males had heavier slaughter weight, longer cecum length, more white blood cells (WBC), red blood cells (RBC) and hemoglobin (HGB), but triglycerides, lower dressed percentage, percentage of half eviscerated yield, and eviscerated yield than HRFI males. LRFI females had a higher percentage of breast muscle and gizzard yield, longer cecum length, and more WBCs, RBCs and HGB but less abdominal fat and serum total cholesterol than HRFI females. This study was the first to verify that long-term divergent selection for RFI in Chinese broiler chickens is positive and beneficial.

The impact of genotyping strategies and statistical models on accuracy of genomic prediction for survival in pigs.

BACKGROUND: Survival from birth to slaughter is an important economic trait in commercial pig productions. Increasing survival can improve both economic efficiency and animal welfare. The aim of this study is to explore the impact of genotyping strategies and statistical models on the accuracy of genomic prediction for survival in pigs during the total growing period from birth to slaughter.  RESULTS: We simulated pig populations with different direct and maternal heritabilities and used a linear mixed model, a logit model, and a probit model to predict genomic breeding values of pig survival based on data of individual survival records with binary outcomes (0, 1). The results show that in the case of only alive animals having genotype data, unbiased genomic predictions can be achieved when using variances estimated from pedigree-based model. Models using genomic information achieved up to 59.2% higher accuracy of estimated breeding value compared to pedigree-based model, dependent on genotyping scenarios. The scenario of genotyping all individuals, both dead and alive individuals, obtained the highest accuracy. When an equal number of individuals (80%) were genotyped, random sample of individuals with genotypes achieved higher accuracy than only alive individuals with genotypes. The linear model, logit model and probit model achieved similar accuracy. CONCLUSIONS: Our conclusion is that genomic prediction of pig survival is feasible in the situation that only alive pigs have genotypes, but genomic information of dead individuals can increase accuracy of genomic prediction by 2.06% to 6.04%.

Recent Advances in Synthetic Methodologies to Form C-18F Bonds.

Positron emission tomography (PET) is an important technique for the early diagnosis of disease. Due to the specific physical and chemical properties of Fluorine-18, this important isotope is widely used in PET for labelling and molecular imaging, and its introduction into medicine molecules could produce PET tracers. Developing with the development of organic synthetic methodologies, the introduction of Fluorine-18 into drug molecules efficiently and rapidly under mild conditions, and the formation of C-18F chemical bonds, has become one of the leading topics in both organic synthetic chemistry and radiochemistry. In this mini-review, we review a series of recent advances in the organic synthesis of C-18F bonds (2015-2021), including non-catalytic radiofluorinations via good leaving functional groups, transition metal-catalyzed radiofluorinations, and photo- or electro-catalytic synthetic radiofluorinations. As a result of the remarkable advancements in this field, organic synthetic methods for forming C-18F bonds are expected to continue growing.

Genome-Wide Association Studies Provide Insight Into the Genetic Determination for Hyperpigmentation of the Visceral Peritoneum in Broilers.

Hyperpigmentation of the visceral peritoneum (HVP) has been becoming one of the most challenging problems in yellow-feathered chicken production, which seriously affected chicken carcass quality traits. Detecting which genes dominantly impact pigmentation in the peritoneum tissues is of great benefit to the genetic improvement of HVP. To investigate the genetic mechanism of HVP in yellow-feathered broilers, genome-wide association studies (GWASs) were conducted in the F2 generation of a cross broiler population with 395 birds. A total of 115,706 single-nucleotide polymorphisms (SNPs) of 122,415 were retained to identify quantitative trait loci (QTL) associated to HVP in chicken. The GWAS results based on the logistic mixed model (LMM) revealed that a narrow genomic location on chromosomes 1 (49.2-51.3 Mb) was significantly associated (p ≤ 4.32 × 10-7) with HVP, which contained 23 SNP makers related to 14 functional genes (MFNG, POLDIP3, POLR2F, PICK1, PDXP, SGSM3, RANGAP1, MYH9, RPL3, GALP3, LGALS1, MICALL1, ATF4, and CYP2D6). Four highly associated (p < 10-5) haplotype blocks of 0.80 kb (two SNPs), 0.06 kb (two SNPs), 0.95 kb (two SNPs), and 0.03 kb (two SNPs) were identified with two, two, four, and four distinct haplotypes, respectively. As a melanoma-associated gene, CYP2D6 were also possibly involved in the development of HVP occurring in chicken with two significant variations (rs314284996 and rs317955795) in the promoter regions. Further tests revealed that the expression of CYP2D6 was obviously higher in the visceral peritoneum tissue of chicken with HVP than that in the normal group (p < 0.05). Our results provide a novel clue to understand the genetic mechanism of HVP generation in chicken, and the mapped QTL or candidate genes might serve for genomic selection to improve carcass quality in the yellow-feathered chicken industry.

Including dominance effects in the prediction model through locus-specific weights on heterozygous genotypes can greatly improve genomic predictive abilities.

The dominance effect is considered to be a key factor affecting complex traits. However, previous studies have shown that the improvement of the model, including the dominance effect, is usually less than 1%. This study proposes a novel genomic prediction method called CADM, which combines additive and dominance genetic effects through locus-specific weights on heterozygous genotypes. To the best of our knowledge, this is the first study of weighting dominance effects for genomic prediction. This method was applied to the analysis of chicken (511 birds) and pig (3534 animals) datasets. A 5-fold cross-validation method was used to evaluate the genomic predictive ability. The CADM model was compared with typical models considering additive and dominance genetic effects (ADM) and the model considering only additive genetic effects (AM). Based on the chicken data, using the CADM model, the genomic predictive abilities were improved for all three traits (body weight at 12th week, eviscerating percentage, and breast muscle percentage), and the average improvement in prediction accuracy was 27.1% compared with the AM model, while the ADM model was not better than the AM model. Based on the pig data, the CADM model increased the genomic predictive ability for all the three pig traits (trait names are masked, here designated as T1, T2, and T3), with an average increase of 26.3%, and the ADM model did not improve, or even slightly decreased, compared with the AM model. The results indicate that dominant genetic variation is one of the important sources of phenotypic variation, and the novel prediction model significantly improves the accuracy of genomic prediction.

Proton-Coupled Electron Transfer Guidelines, Fair and Square.

Proton-coupled electron transfer (PCET) reactions are fundamental to energy transformation reactions in natural and artificial systems and are increasingly recognized in areas such as catalysis and synthetic chemistry. The interdependence of proton and electron transfer brings a mechanistic richness of reactivity, including various sequential and concerted mechanisms. Delineating between different PCET mechanisms and understanding why a particular mechanism dominates are crucial for the design and optimization of reactions that use PCET. This Perspective provides practical guidelines for how to discern between sequential and concerted mechanisms based on interpretations of thermodynamic data with temperature-, pressure-, and isotope-dependent kinetics. We present new PCET-zone diagrams that show how a mechanism can switch or even be eliminated by varying the thermodynamic (ΔGPT° and ΔGET°) and coupling strengths for a PCET system. We discuss the appropriateness of asynchronous concerted PCET to rationalize observations in organic reactions, and the distinction between hydrogen atom transfer and other concerted PCET reactions. Contemporary issues and future prospects in PCET research are discussed.

High-Throughput Sequencing With the Preselection of Markers Is a Good Alternative to SNP Chips for Genomic Prediction in Broilers.

The choice of a genetic marker genotyping platform is important for genomic prediction in livestock and poultry. High-throughput sequencing can produce more genetic markers, but the genotype quality is lower than that obtained with single nucleotide polymorphism (SNP) chips. The aim of this study was to compare the accuracy of genomic prediction between high-throughput sequencing and SNP chips in broilers. In this study, we developed a new SNP marker screening method, the pre-marker-selection (PMS) method, to determine whether an SNP marker can be used for genomic prediction. We also compared a method which preselection marker based results from genome-wide association studies (GWAS). With the two methods, we analysed body weight at the12th week (BW) and feed conversion ratio (FCR) in a local broiler population. A total of 395 birds were selected from the F2 generation of the population, and 10X specific-locus amplified fragment sequencing (SLAF-seq) and the Illumina Chicken 60K SNP Beadchip were used for genotyping. The genomic best linear unbiased prediction method (GBLUP) was used to predict the genomic breeding values. The accuracy of genomic prediction was validated by the leave-one-out cross-validation method. Without SNP marker screening, the accuracies of the genomic estimated breeding value (GEBV) of BW and FCR were 0.509 and 0.249, respectively, when using SLAF-seq, and the accuracies were 0.516 and 0.232, respectively, when using the SNP chip. With SNP marker screening by the PMS method, the accuracies of GEBV of the two traits were 0.671 and 0.499, respectively, when using SLAF-seq, and 0.605 and 0.422, respectively, when using the SNP chip. Our SNP marker screening method led to an increase of prediction accuracy by 0.089-0.250. With SNP marker screening by the GWAS method, the accuracies of genomic prediction for the two traits were also improved, but the gains of accuracy were less than the gains with PMS method for all traits. The results from this study indicate that our PMS method can improve the accuracy of GEBV, and that more accurate genomic prediction can be obtained from an increased number of genomic markers when using high-throughput sequencing in local broiler populations. Due to its lower genotyping cost, high-throughput sequencing could be a good alternative to SNP chips for genomic prediction in breeding programmes of local broiler populations.

Elucidating Proton-Coupled Electron Transfer Mechanisms of Metal Hydrides with Free Energy- and Pressure-Dependent Kinetics.

Proton-coupled electron transfer (PCET) was studied in a series of tungsten hydride complexes with pendant pyridyl arms ([(PyCH2Cp)WH(CO)3], PyCH2Cp = pyridylmethylcyclopentadienyl), triggered by laser flash-generated RuIII-tris-bipyridine oxidants, in acetonitrile solution. The free energy dependence of the rate constant and the kinetic isotope effects (KIEs) showed that the PCET mechanism could be switched between concerted and the two stepwise PCET mechanisms (electron-first or proton-first) in a predictable fashion. Straightforward and general guidelines for how the relative rates of the different mechanisms depend on oxidant and base are presented. The rate of the concerted reaction should depend symmetrically on changes in oxidant and base strength, that is on the overall ΔG0PCET, and we argue that an "asynchronous" behavior would not be consistent with a model where the electron and proton tunnel from a common transition state. The observed rate constants and KIEs were examined as a function of hydrostatic pressure (1-2000 bar) and were found to exhibit qualitatively different dependence on pressure for different PCET mechanisms. This is discussed in terms of different volume profiles of the PCET mechanisms as well as enhanced proton tunneling for the concerted mechanism. The results allowed for assignment of the main mechanism operating in the different cases, which is one of the critical questions in PCET research. They also show how the rate of a PCET reaction will be affected very differently by changes of oxidant and base strength, depending on which mechanism dominates. This is of fundamental interest as well as of practical importance for rational design of, for example, catalysts for fuel cells and solar fuel formation, which operate in steps of PCET reactions. The mechanistic richness shown by this system illustrates that the specific mechanism is not intrinsic to a specific synthetic catalyst or enzyme active site but depends on the reaction conditions.

Direct Spectroscopic Detection of Key Intermediates and the Turnover Process in Catalytic H2 Formation by a Biomimetic Diiron Catalyst.

[FeFe(Cl2 -bdt)(CO)6 ] (1; Cl2 -bdt=3,6-dichlorobenzene-1,2-dithiolate), inspired by the active site of FeFe-hydrogenase, shows a chemically reversible 2 e- reduction at -1.20 V versus the ferrocene/ferrocenium couple. The rigid and aromatic bdt bridging ligand lowers the reduction potential and stabilizes the reduced forms, compared with analogous complexes with aliphatic dithiolates; thus allowing details of the catalytic process to be characterized. Herein, time-resolved IR spectroscopy is used to provide kinetic and structural information on key catalytic intermediates. This includes the doubly reduced, protonated complex 1H- , which has not been previously identified experimentally. In addition, the first direct spectroscopic observation of the turnover process for a molecular H2 evolving catalyst is reported, allowing for straightforward determination of the turnover frequency.

On the universality of the flow properties of soft-particle glasses.

We identify the minimal interparticle interactions necessary for a particle dynamics simulation to predict the structure and flow behaviour of soft particle glasses (SPGs). Generally, two kinds of forces between the particles must be accounted for in simulations of SPGs: viscous or frictional drag forces and elastic contact forces. Far field drag forces are required to dissipate energy in the simulations and capture the effect of the rheology of the suspending fluid. Elastic forces are found to be dominant compared to near-field drag or other forms of friction forces and are the most important component to compute the rheology. The shear stress, the first and second normal stress differences for different interparticle force laws collapse onto universal master curves of the Herschel-Bulkley form by non-dimensionalizing the stress with the yield stress and the shear rate with the viscosity of the suspending fluid divided by the low-frequency shear modulus. The Herschel-Bulkley exponents are close to 0.5 with a slight dependence on the repulsive pairwise elastic forces.

Accelerating proton-coupled electron transfer of metal hydrides in catalyst model reactions.

Metal hydrides are key intermediates in catalytic proton reduction and dihydrogen oxidation. There is currently much interest in appending proton relays near the metal centre to accelerate catalysis by proton-coupled electron transfer (PCET). However, the elementary PCET steps and the role of the proton relays are still poorly understood, and direct kinetic studies of these processes are scarce. Here, we report a series of tungsten hydride complexes as proxy catalysts, with covalently attached pyridyl groups as proton acceptors. The rate of their PCET reaction with external oxidants is increased by several orders of magnitude compared to that of the analogous systems with external pyridine on account of facilitated proton transfer. Moreover, the mechanism of the PCET reaction is altered by the appended bases. A unique feature is that the reaction can be tuned to follow three distinct PCET mechanisms-electron-first, proton-first or a concerted reaction-with very different sensitivities to oxidant and base strength. Such knowledge is crucial for rational improvements of solar fuel catalysts.

Assessment of the genomic prediction accuracy for feed efficiency traits in meat-type chickens.

Feed represents the major cost of chicken production. Selection for improving feed utilization is a feasible way to reduce feed cost and greenhouse gas emissions. The objectives of this study were to investigate the efficiency of genomic prediction for feed conversion ratio (FCR), residual feed intake (RFI), average daily gain (ADG) and average daily feed intake (ADFI) and to assess the impact of selection for feed efficiency traits FCR and RFI on eviscerating percentage (EP), breast muscle percentage (BMP) and leg muscle percentage (LMP) in meat-type chickens. Genomic prediction was assessed using a 4-fold cross-validation for two validation scenarios. The first scenario was a random family sampling validation (CVF), and the second scenario was a random individual sampling validation (CVR). Variance components were estimated based on the genomic relationship built with single nucleotide polymorphism markers. Genomic estimated breeding values (GEBV) were predicted using a genomic best linear unbiased prediction model. The accuracies of GEBV were evaluated in two ways: the correlation between GEBV and corrected phenotypic value divided by the square root of heritability, i.e., the correlation-based accuracy, and model-based theoretical accuracy. Breeding values were also predicted using a conventional pedigree-based best linear unbiased prediction model in order to compare accuracies of genomic and conventional predictions. The heritability estimates of FCR and RFI were 0.29 and 0.50, respectively. The heritability estimates of ADG, ADFI, EP, BMP and LMP ranged from 0.34 to 0.53. In the CVF scenario, the correlation-based accuracy and the theoretical accuracy of genomic prediction for FCR were slightly higher than those for RFI. The correlation-based accuracies for FCR, RFI, ADG and ADFI were 0.360, 0.284, 0.574 and 0.520, respectively, and the model-based theoretical accuracies were 0.420, 0.414, 0.401 and 0.382, respectively. In the CVR scenario, the correlation-based accuracy and the theoretical accuracy of genomic prediction for FCR was lower than RFI, which was different from the CVF scenario. The correlation-based accuracies for FCR, RFI, ADG and ADFI were 0.449, 0.593, 0.581 and 0.627, respectively, and the model-based theoretical accuracies were 0.577, 0.629, 0.631 and 0.638, respectively. The accuracies of genomic predictions were 0.371 and 0.322 higher than the conventional pedigree-based predictions for the CVF and CVR scenarios, respectively. The genetic correlations of FCR with EP, BMP and LMP were -0.427, -0.156 and -0.338, respectively. The correlations between RFI and the three carcass traits were -0.320, -0.404 and -0.353, respectively. These results indicate that RFI and FCR have a moderate accuracy of genomic prediction. Improving RFI and FCR could be favourable for EP, BMP and LMP. Compared with FCR, which can be improved by selection for ADG in typical meat-type chicken breeding programs, selection for RFI could lead to extra improvement in feed efficiency.

Microbial metabolite butyrate facilitates M2 macrophage polarization and function.

Metabolites from intestinal microbes modulate the mucosal immune system by regulating the polarization and expansion of T cells. Whether the microbial metabolites influence macrophage polarization, however, is poorly understood. Here, we show that the large bowel microbial fermentation product, butyrate, facilitates M2 macrophage polarization, in vitro and in vivo. The supernatant from butyrate-treated M2 macrophage increased the migration and enhanced the wound closure rate of MLE-12 cells. Butyrate attenuated intestinal inflammation in mice with dextran sulfate sodium (DSS)-induced colitis, with a significant increase in colonic expression of the M2 macrophage-associated protein, Arg1. M2 macrophage treated with butyrate, had increased activation of the H3K9/STAT6 signaling pathway, suggesting a mechanism for butyrate facilitated M2 macrophage polarization. Collectively, our study indicated that commensal microbe-derived butyrate is a novel activator of STAT6-mediated transcription through H3K9 acetylation driving M2 macrophage polarization, and delineated new insights into the immune interplay underlying inflammatory bowel disease.

Aphicidal Activity of an Ageraphorone Extract From Eupatorium adenophorum Against Pseudoregma bambucicola (Homoptera: Aphididae, Takahashi).

The bamboo aphid, Pseudoregma bambucicola, is an important insect pest of bamboo that affects normal bamboo growth and induces sooty molds. The control of P. bambucicola involves the application of chemicals, such as imidacloprid, to which many species are resistant. In this study, we isolate a novel botanical pesticide (9-oxo-10,11-dehydro-ageraphorone) from an Eupatorium adenophorum(Asteraceae: Compositae) petroleum ether extract and test the aphicidal activity of this compound against P. bambucicola in laboratory bioassay and field-based experiments. This ageraphorone compound at a concentration of 2 mg/ml caused 73.33% mortality (corrected mortality [Subtracted the mortality of the negative control]: 70%) of P. bambucicola by laboratory bioassay within 6 h. Even at lower concentrations, this compound caused greater 33% mortality (corrected mortality: 30%) of aphids. Field experiments with naturally infested bamboo plants showed that two applications of 2 mg/ml ageraphorone to infested plants completely cleared infestations within 30 d. These effects were similar to those of the positive control (imidacloprid). These results reveal that 9-oxo-10,11-dehydro-ageraphorone exhibits significant aphicidal activity against bamboo aphids. We suggest that future research be directed at developing this ageraphorone compound from E. adenophorum as an aphicidal agent for biocontrol.

Genomic selection for the improvement of antibody response to Newcastle disease and avian influenza virus in chickens.

Newcastle disease (ND) and avian influenza (AI) are the most feared diseases in the poultry industry worldwide. They can cause flock mortality up to 100%, resulting in a catastrophic economic loss. This is the first study to investigate the feasibility of genomic selection for antibody response to Newcastle disease virus (Ab-NDV) and antibody response to Avian Influenza virus (Ab-AIV) in chickens. The data were collected from a crossbred population. Breeding values for Ab-NDV and Ab-AIV were estimated using a pedigree-based best linear unbiased prediction model (BLUP) and a genomic best linear unbiased prediction model (GBLUP). Single-trait and multiple-trait analyses were implemented. According to the analysis using the pedigree-based model, the heritability for Ab-NDV estimated from the single-trait and multiple-trait models was 0.478 and 0.487, respectively. The heritability for Ab-AIV estimated from the two models was 0.301 and 0.291, respectively. The estimated genetic correlation between the two traits was 0.438. A four-fold cross-validation was used to assess the accuracy of the estimated breeding values (EBV) in the two validation scenarios. In the family sample scenario each half-sib family is randomly allocated to one of four subsets and in the random sample scenario the individuals are randomly divided into four subsets. In the family sample scenario, compared with the pedigree-based model, the accuracy of the genomic prediction increased from 0.086 to 0.237 for Ab-NDV and from 0.080 to 0.347 for Ab-AIV. In the random sample scenario, the accuracy was improved from 0.389 to 0.427 for Ab-NDV and from 0.281 to 0.367 for Ab-AIV. The multiple-trait GBLUP model led to a slightly higher accuracy of genomic prediction for both traits. These results indicate that genomic selection for antibody response to ND and AI in chickens is promising.

Accuracy of genomic prediction for growth and carcass traits in Chinese triple-yellow chickens.

BACKGROUND: Growth and carcass traits are very important traits for broiler chickens. However, carcass traits can only be measured postmortem. Genomic selection may be a powerful tool for such traits because of its accurate prediction of breeding values of animals without own phenotypic information. This study investigated the efficiency of genomic prediction in Chinese triple-yellow chickens. As a new line, Chinese triple-yellow chicken was developed by cross-breeding and had a small effective population. Two growth traits and three carcass traits were analyzed: body weight at 6 weeks, body weight at 12 weeks, eviscerating percentage, breast muscle percentage and leg muscle percentage. RESULTS: Genomic prediction was assessed using a 4-fold cross-validation procedure for two validation scenarios. In the first scenario, each test data set comprised two half-sib families (family sample) and the rest represented the reference data. In the second scenario, the whole data were randomly divided into four subsets (random sample). In each fold of validation, one subset was used as the test data and the others as the reference data in each single validation. Genomic breeding values were predicted using a genomic best linear unbiased prediction model, a Bayesian least absolute shrinkage and selection operator model, and a Bayesian mixture model with four distributions. The accuracy of genomic estimated breeding value (GEBV) was measured as the correlation between GEBV and the corrected phenotypic value. Using the three models, the correlations ranged from 0.448 to 0.468 for the two growth traits and from 0.176 to 0.255 for the three carcass traits in the family sample scenario, and were between 0.487 and 0.536 for growth traits and between 0.312 and 0.430 for carcass traits in the random sample scenario. The differences in the prediction accuracies between the three models were very small; the Bayesian mixture model was slightly more accurate. According to the results from the random sample scenario, the accuracy of GEBV was 0.197 higher than the conventional pedigree index, averaged over the five traits. CONCLUSIONS: The results indicated that genomic selection could greatly improve the accuracy of selection in chickens, compared with conventional selection. Genomic selection for growth and carcass traits in broiler chickens is promising.

Copper-catalyzed trifluoromethylthiolation of primary and secondary alkylboronic acids.

A Cu-catalyzed trifluoromethylthiolation of primary and secondary alkylboronic acids with an electrophilic trifluoromethylthiolating reagent is described. Tolerance for a variety of functional groups was observed.