Pyrophosphate-dependent phosphofructokinase from pollen: properties and possible roles in sugar metabolism

To evaluate the role of pyrophosphate-dependent phosphofructokinase (PFP. EC 2.7.1.90) in the sugar metabolism of pollen. its occurrence and properties were studied in pollen grains of several plants including camellia ( Camellia japonica L.). In all pollen samples, PFP was strongly activated by fructose-2,6-bisphosphate (F2,6BP), and the activity of F2,6BP-activated PFP was higher than that of phosphofructokinase (PFK. EC 2.7.1.11). PFP partially purified from camellia pollen required Mg²⁺ for activity with an optimum at 1 m M . and was almost unaflected by a variety of metabolites at 1 m M . Its molecular mass was around 220 kDa, and apparent K_m values for F6P, PP_i. F1, 6BP and P_i were 294, 4, 20 and 580 u M , respectively. The levels of F2.6BP. PP_i and F6P in camellia pollen were sufficent to support the forward reaction by PFP, and PFP, was 20- to 40-fold more active than PFK during pollen growth. These results suggest that pollen PFP plays a role in glycolysis but not gluconeogenesis. and the possible relevance of this to pollen tube growth is discussed.     

Morphological variation associated with dispersal capacity in a tree‐killing bark beetle Dendroctonus ponderosae Hopkins

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Comparative population genomics identified genomic regions and candidate genes associated with fruit domestication traits in peach

Crop evolution is a long‐term process involving selection by natural evolutionary forces and anthropogenic influences; however, the genetic mechanisms underlying the domestication and improvement of fruit crops have not been well studied to date. Here, we performed a population structure analysis in peach (Prunus persica) based on the genome‐wide resequencing of 418 accessions and confirmed the presence of an obvious domestication event during evolution. We identified 132 and 106 selective sweeps associated with domestication and improvement, respectively. Analysis of their tissue‐specific expression patterns indicated that the up‐regulation of selection genes during domestication occurred mostly in fruit and seeds as opposed to other organs. However, during the improvement stage, more up‐regulated selection genes were identified in leaves and seeds than in the other organs. Genome‐wide association studies (GWAS) using 4.24 million single nucleotide polymorphisms (SNPs) revealed 171 loci associated with 26 fruit domestication traits. Among these loci, three candidate genes were highly associated with fruit weight and the sorbitol and catechin content in fruit. We demonstrated that as the allele frequency of the SNPs associated with high polyphenol composition decreased during peach evolution, alleles associated with high sugar content increased significantly. This indicates that there is genetic potential for the breeding of more nutritious fruit with enhanced bioactive polyphenols without disturbing a harmonious sugar and acid balance by crossing with wild species. This study also describes the development of the genomic resources necessary for evolutionary research in peach and provides the large‐scale characterization of key agronomic traits in this crop species.     

A metabolome‐based core hybridisation strategy for the prediction of rice grain weight across environments

Marker‐based prediction holds great promise for improving current plant and animal breeding efficiencies. However, the predictabilities of complex traits are always severely affected by negative factors, including distant relatedness, environmental discrepancies, unknown population structures, and indeterminate numbers of predictive variables. In this study, we utilised two independent F₁ hybrid populations in the years 2012 and 2015 to predict rice thousand grain weight (TGW) using parental untargeted metabolite profiles with a partial least squares regression method. A stable predictive model for TGW was built based on hybrids from the population in 2012 (r = 0.75) but failed to properly predict TGW for hybrids from the population in 2015 (r = 0.27). After integrating hybrids from both populations into the training set, the TGW of hybrids could be predicted but was largely dependent on population structures. Then, core hybrids from each population were determined by principal component analysis and the TGW of hybrids in both environments were successfully predicted (r > 0.60). Moreover, adjusting the population structures and numbers of predictive analytes increased TGW predictability for hybrids in 2015 (r = 0.72). Our study demonstrates that the TGW of F₁ hybrids across environments can be accurately predicted based on parental untargeted metabolite profiles with a core hybridisation strategy in rice. Metabolic biomarkers identified from early developmental stage tissues, which are grown under experimental conditions, may represent a workable approach towards the robust prediction of major agronomic traits for climate‐adaptive varieties.     

New pollen classification of Chenopodiaceae for exploring and tracing desert vegetation evolution in eastern arid central Asia

Members of the Chenopodiaceae are the most dominant elements in the central Asian desert. The different genera and species within this family are common in desert vegetation types. Should it prove possible to link pollen types in this family to specific desert vegetation, it would be feasible to trace vegetation successions in the geological past. Nevertheless, the morphological similarity of pollen grains in the Chenopodiaceae rarely permits identification at the generic level. Although some pollen classifications of Chenopodiaceae have been proposed, none of them tried to link pollen types to specific desert vegetation types in order to explore their ecological significance. Based on the pollen morphological characters of 13 genera and 24 species within the Chenopodiaceae of eastern central Asia, we provide a new pollen classification of this family with six pollen types and link them to those plant communities dominated by Chenopodiaceae, for example, temperate dwarf semi‐arboreal desert (Haloxylon type), temperate succulent halophytic dwarf semi‐shrubby desert (Suaeda, Kalidium, and Atriplex types), temperate annual graminoid desert (Kalidium type), temperate semi‐shrubby and dwarf semi‐shrubby desert (Kalidium, Iljini, and Haloxylon types), and alpine cushion dwarf semi‐shrubby desert (Krascheninnikovia type). These findings represent a new approach for detecting specific desert vegetation types and deciphering ecosystem evolution in eastern central Asia.     

The effects of immunization against gonadotropin-releasing hormone on growth performance,reproductive activity and carcass traits of heavy weight gilts

Heavy weight gilts commonly show signs of oestrus during the late finishing phase, which results in a period of reduced feed intake and growth rate. Immunization against gonadotropin-releasing hormone (GnRH) (IM, immunocastration) was developed for finishing boars and recently extrapolated to females. Immunocastration acts by suppressing reproductive activity and improving the growth potential. The objective of this study was to evaluate the effects of IM on growth performance, reproductive activity and carcass characteristics of late finishing gilts. Seventy-two gilts (63.49 ± 0.39 kg) were either injected with saline (Intact) or immunized against GnRH (Immunized). The study consisted of three experimental periods: between the first to second immunization (V1 to V2, 15 to 19 weeks of age), from the second immunization to the beginning of daily boar exposure (DBE) (V2 to DBE, 19 to 21 weeks of age) and from the beginning of DBE to slaughter (S) (DBE to S, 21 to 25 weeks of age). Immunized gilts showed an overall increase (from 15 to 25 weeks) of 3.90 kg (P < 0.05) of live weight, 56 g (P < 0.05) of average daily gain (ADG) and 250 g (P < 0.001) of average daily feed intake (ADFI). Immunized gilts had a greater ADFI (+240 g, P < 0.05) and worse feed conversion ratio (+0.26, P < 0.05) from 19 (V2) to 21 weeks of age (before DBE). Furthermore, those females had higher feed intake (+410 g; P < 0.001) plus greater daily weight gain (+92 g; P < 0.05) from V2 to S, and from DBE to S (+470 g of ADFI, P < 0.001; +129 g of ADG, P < 0.01, respectively). Immunocastration had no effect on backfat thickness, lean meat percentage and weight, cold carcass yield or loin depth (P > 0.05). Immunized gilts showed 4.4% increased cold carcass weight (P < 0.01) and 10.6% greater gross flank weight (P < 0.001). Immunization against GnRH did not influence shoulder, collar, loin, belly or ham weights. Nor did it influence belly fat thickness, or meat, skin plus fat and bones yields of cold ham (P > 0.05). Immunocastration reduced ovarian and uterine weights by 82% (P < 0.001) and 93% (P < 0.001), respectively, and suppressed oestrus manifestation in all gilts in the immunized group (P < 0.001). These results indicate that immunization against GnRH is a promising tool for stimulating growth performance with no detrimental effects on carcass quality of heavy weight finishing gilts, by means of oestrus suppression.     

Vegetation and environment changes inferred from pollen records since 3000 cal. yr BP in Kanas wetland,Xinjiang

Aims Climate change can significantly affect the vegetation worldwide. Thus, paleovegetation and paleoclimate reconstruction should consider the quantitative relationship between modern vegetation and climate. The specific objectives of this study were (i) to assess the influence of environmental variables on pollen assemblages in the Kanas region, (ii) to reconstruct the evolution of vegetation over the past 3000 years using pollen records and (iii) to quantify historical climate change (including mean annual temperature and total annual precipitation) using a weighted averaging partial least squares regression method (WAPLS) applied to fossil pollen data from the Kanas wetland in Xinjiang, China.     

Adaptive neuro-fuzzy inference system: Estimation of soil aggregates stability

In present study, the capabilities of multiple linear regression (MLR) and adaptive neuro-fuzzy inference system (ANFIS) in developing pedotransfer functions (PTFs) for estimating geometric mean diameter (GMD) and mean weight diameter (MWD), from routine soil properties and combination of routine soil properties and fractal dimension of aggregates were evaluated. For this reason 101 samples were collected form the Northwest of Iran and some their properties such as soil texture, pH, cation exchange capacity (CEC), and organic matter (OM), fractal dimension of aggregates between number-diameter (Dn), mass-diameter (Dmt), and bulk density-diameter (Dmy) were determined and used as an input variables for determining of mean weight diameter (MWD) and geometric mean diameter (GMD) by MLR and ANFIS PTFs. Results showed that the application of fractal dimension of aggregates as a predictor in two methods improved the accuracy of PTFs. As well as, results showed that ANFIS have greater potential for determination of the relationships between soil aggregate stability indices and other soil properties in compared with MLR. Therefore using of adaptive neuro-fuzzy inference system (ANFIS) in developing pedotransfer functions is recommended.