277 research outputs found
Decreasing resistance in the maternal uterine and peripheral arterial system is apparently unrelated to plasma and urinary levels of nitrite/nitrate and cyclic-guanosinmonophosohate during the course of normal pregnancies
Aims: The aim of the presented study was to clarify the relationship between the pulsatility index of the uterine arteries and the maternal cubital artery and peripheral concentrations of the metabolites of nitric oxide (NO) and its second messenger cyclic guanosinmonophophate (cGMP) during the normal course of pregnancy and postpartum. Methods: 49 uncomplicated pregnancies were investigated every 46 weeks until delivery, 29 of them were additionally investigated postpartum. Paralleling each Doppler sonografic investigation maternal blood and urine samples were taken. The measurements of nitrite/ nitrate and cGMP were performed with a colorimetric and radio immuno assay. We demonstrate a significant decrease of the PI of the uterine arteries and of the cubital artery with inverse correlation to advancing gestational age. Results: The concentrations of nitrite/nitrate and cGMP remain stable during gestation and do not correlate to the PI of the uterine and cubital artery. Postpartum a reincrease in the uterine and peripheral resistance can be shown. The concentrations of urinary cGMP and nitrite/ nitrate as well as plasma cGMP remain unchanged, whereas plasma nitrite/nitrate decreases postpartum. Conclusions: The status of NO biosyntheses in normal pregnancy remains controversial. We hypothesize further systemically acting mediators which contribute to the decreasing vascular resistance
Accuracy of Genomic Prediction for Foliar Terpene Traits in Eucalyptus polybractea
Unlike agricultural crops, most forest species have not had millennia of improvement through phenotypic selection, but can contribute energy and material resources and possibly help alleviate climate change. Yield gains similar to those achieved in agricultural crops over millennia could be made in forestry species with the use of genomic methods in a much shorter time frame. Here we compare various methods of genomic prediction for eight traits related to foliar terpene yield in Eucalyptus polybractea, a tree grown predominantly for the production of Eucalyptus oil. The genomic markers used in this study are derived from shallow whole genome sequencing of a population of 480 trees. We compare the traditional pedigree-based additive best linear unbiased predictors (ABLUP), genomic BLUP (GBLUP), BayesB genomic prediction model, and a form of GBLUP based on weighting markers according to their influence on traits (BLUP|GA). Predictive ability is assessed under varying marker densities of 10,000, 100,000 and 500,000 SNPs. Our results show that BayesB and BLUP|GA perform best across the eight traits. Predictive ability was higher for individual terpene traits, such as foliar α-pinene and 1,8-cineole concentration (0.59 and 0.73, respectively), than aggregate traits such as total foliar oil concentration (0.38). This is likely a function of the trait architecture and markers used. BLUP|GA was the best model for the two biomass related traits, height and 1 year change in height (0.25 and 0.19, respectively). Predictive ability increased with marker density for most traits, but with diminishing returns. The results of this study are a solid foundation for yield improvement of essential oil producing eucalypts. New markets such as biopolymers and terpene-derived biofuels could benefit from rapid yield increases in undomesticated oil-producing species.Funding for this project was provided by the Australian Research
Council Linkage Program (LP110100184) toWJF, the Rural Industries
Research and Development Corporation (RIRDC), Australia. Support
was also provided by the Center for BioEnergy Innovation (CBI), a
U.S DOE Bioenergy Research Center supported by the DOE office of
science
Partnering for greater success: local stakeholders and research in tropical biology.
Local communities are important stakeholders in resource management and conservation efforts, particularly in the developing world. Although evidence is mixed in suggesting that these resident stakeholders are optimal forest stewards, it is highly unlikely that large tracts of tropical forests will be conserved without engaging local people who depend on them daily for their livelihoods. Stakeholders, who reside in biodiverse ecosystems like tropical forests, are the largest direct users and ultimate decision-makers of forest fate, can be important investors in conservation, harbor local ecological knowledge that complements Western science and frequently have long-term legitimate claims on lands where they reside. Research partnerships with local stakeholders can increase research relevance, enhance knowledge exchange and result in greater conservation success. Different phases of the research cycle present distinct opportunities for partnership, with flexibility in timing, approaches and strategies depending on researcher and local stakeholder needs and interests. Despite being the last step in the research process, dissemination of results can be the best starting point for researchers interested in experimenting with local stakeholder engagement. Still, tropical biologists might not choose to partner with local people because of lack of institutional rewards, insufficient training in stakeholder engagement, insecure research infrastructure in community settings, and time and funding limitations. Although not appropriate in all cases and despite significant challenges, some biological scientists and research institutions have successfully engaged local stakeholders in the research process, proving mutually beneficial for investigators and local people alike and resulting in important innovations in tropical biology and conservation
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Finding New Cell Wall Regulatory Genes in Populus trichocarpa Using Multiple Lines of Evidence.
Understanding the regulatory network controlling cell wall biosynthesis is of great interest in Populus trichocarpa, both because of its status as a model woody perennial and its importance for lignocellulosic products. We searched for genes with putatively unknown roles in regulating cell wall biosynthesis using an extended network-based Lines of Evidence (LOE) pipeline to combine multiple omics data sets in P. trichocarpa, including gene coexpression, gene comethylation, population level pairwise SNP correlations, and two distinct SNP-metabolite Genome Wide Association Study (GWAS) layers. By incorporating validation, ranking, and filtering approaches we produced a list of nine high priority gene candidates for involvement in the regulation of cell wall biosynthesis. We subsequently performed a detailed investigation of candidate gene GROWTH-REGULATING FACTOR 9 (PtGRF9). To investigate the role of PtGRF9 in regulating cell wall biosynthesis, we assessed the genome-wide connections of PtGRF9 and a paralog across data layers with functional enrichment analyses, predictive transcription factor binding site analysis, and an independent comparison to eQTN data. Our findings indicate that PtGRF9 likely affects the cell wall by directly repressing genes involved in cell wall biosynthesis, such as PtCCoAOMT and PtMYB.41, and indirectly by regulating homeobox genes. Furthermore, evidence suggests that PtGRF9 paralogs may act as transcriptional co-regulators that direct the global energy usage of the plant. Using our extended pipeline, we show multiple lines of evidence implicating the involvement of these genes in cell wall regulatory functions and demonstrate the value of this method for prioritizing candidate genes for experimental validation
A phylogenomic approach reveals a low somatic mutation rate in a long-lived plant.
Somatic mutations can have important effects on the life history, ecology, and evolution of plants, but the rate at which they accumulate is poorly understood and difficult to measure directly. Here, we develop a method to measure somatic mutations in individual plants and use it to estimate the somatic mutation rate in a large, long-lived, phenotypically mosaic Eucalyptus melliodora tree. Despite being 100 times larger than Arabidopsis, this tree has a per-generation mutation rate only ten times greater, which suggests that this species may have evolved mechanisms to reduce the mutation rate per unit of growth. This adds to a growing body of evidence that illuminates the correlated evolutionary shifts in mutation rate and life history in plants
Nut production in Bertholletia excelsa across a logged forest mosaic: implications for multiple forest use
Although many examples of multiple-use forest management may be found in tropical smallholder systems, few studies provide empirical support for the integration of selective timber harvesting with non-timber forest product (NTFP) extraction. Brazil nut (Bertholletia excelsa, Lecythidaceae) is one of the world’s most economically-important NTFP species extracted almost entirely from natural forests across the Amazon Basin. An obligate out-crosser, Brazil nut flowers are pollinated by large-bodied bees, a process resulting in a hard round fruit that takes up to 14 months to mature. As many smallholders turn to the financial security provided by timber, Brazil nut fruits are increasingly being harvested in logged forests. We tested the influence of tree and stand-level covariates (distance to nearest cut stump and local logging intensity) on total nut production at the individual tree level in five recently logged Brazil nut concessions covering about 4000 ha of forest in Madre de Dios, Peru. Our field team accompanied Brazil nut harvesters during the traditional harvest period (January-April 2012 and January-April 2013) in order to collect data on fruit production. Three hundred and ninety-nine (approximately 80%) of the 499 trees included in this study were at least 100 m from the nearest cut stump, suggesting that concessionaires avoid logging near adult Brazil nut trees. Yet even for those trees on the edge of logging gaps, distance to nearest cut stump and local logging intensity did not have a statistically significant influence on Brazil nut production at the applied logging intensities (typically 1–2 timber trees removed per ha). In one concession where at least 4 trees ha-1 were removed, however, the logging intensity covariate resulted in a marginally significant (0.09) P value, highlighting a potential risk for a drop in nut production at higher intensities. While we do not suggest that logging activities should be completely avoided in Brazil nut rich forests, when a buffer zone cannot be observed, low logging intensities should be implemented. The sustainability of this integrated management system will ultimately depend on a complex series of socioeconomic and ecological interactions. Yet we submit that our study provides an important initial step in understanding the compatibility of timber harvesting with a high value NTFP, potentially allowing for diversification of forest use strategies in Amazonian Perù
Finding New Cell Wall Regulatory Genes in Populus trichocarpa Using Multiple Lines of Evidence
Understanding the regulatory network controlling cell wall biosynthesis is of great interest in Populus trichocarpa, both because of its status as a model woody perennial and its importance for lignocellulosic products. We searched for genes with putatively unknown roles in regulating cell wall biosynthesis using an extended network-based Lines of Evidence (LOE) pipeline to combine multiple omics data sets in P. trichocarpa, including gene coexpression, gene comethylation, population level pairwise SNP correlations, and two distinct SNP-metabolite Genome Wide Association Study (GWAS) layers. By incorporating validation, ranking, and filtering approaches we produced a list of nine high priority gene candidates for involvement in the regulation of cell wall biosynthesis. We subsequently performed a detailed investigation of candidate gene GROWTH-REGULATING FACTOR 9 (PtGRF9). To investigate the role of PtGRF9 in regulating cell wall biosynthesis, we assessed the genome-wide connections of PtGRF9 and a paralog across data layers with functional enrichment analyses, predictive transcription factor binding site analysis, and an independent comparison to eQTN data. Our findings indicate that PtGRF9 likely affects the cell wall by directly repressing genes involved in cell wall biosynthesis, such as PtCCoAOMT and PtMYB.41, and indirectly by regulating homeobox genes. Furthermore, evidence suggests that PtGRF9 paralogs may act as transcriptional co-regulators that direct the global energy usage of the plant. Using our extended pipeline, we show multiple lines of evidence implicating the involvement of these genes in cell wall regulatory functions and demonstrate the value of this method for prioritizing candidate genes for experimental validation
Evaluation of methods and marker systems in genomic selection of oil palm (Elaeis guineensis Jacq.)
Background
Genomic selection (GS) uses genome-wide markers as an attempt to accelerate genetic gain in breeding programs of both animals and plants. This approach is particularly useful for perennial crops such as oil palm, which have long breeding cycles, and for which the optimal method for GS is still under debate. In this study, we evaluated the effect of different marker systems and modeling methods for implementing GS in an introgressed dura family derived from a Deli dura x Nigerian dura (Deli x Nigerian) with 112 individuals. This family is an important breeding source for developing new mother palms for superior oil yield and bunch characters. The traits of interest selected for this study were fruit-to-bunch (F/B), shell-to-fruit (S/F), kernel-to-fruit (K/F), mesocarp-to-fruit (M/F), oil per palm (O/P) and oil-to-dry mesocarp (O/DM). The marker systems evaluated were simple sequence repeats (SSRs) and single nucleotide polymorphisms (SNPs). RR-BLUP, Bayesian A, B, Cπ, LASSO, Ridge Regression and two machine learning methods (SVM and Random Forest) were used to evaluate GS accuracy of the traits.
Results
The kinship coefficient between individuals in this family ranged from 0.35 to 0.62. S/F and O/DM had the highest genomic heritability, whereas F/B and O/P had the lowest. The accuracies using 135 SSRs were low, with accuracies of the traits around 0.20. The average accuracy of machine learning methods was 0.24, as compared to 0.20 achieved by other methods. The trait with the highest mean accuracy was F/B (0.28), while the lowest were both M/F and O/P (0.18). By using whole genomic SNPs, the accuracies for all traits, especially for O/DM (0.43), S/F (0.39) and M/F (0.30) were improved. The average accuracy of machine learning methods was 0.32, compared to 0.31 achieved by other methods.
Conclusion
Due to high genomic resolution, the use of whole-genome SNPs improved the efficiency of GS dramatically for oil palm and is recommended for dura breeding programs. Machine learning slightly outperformed other methods, but required parameters optimization for GS implementation
Manejo da castanheira (Bertholletia excelsa) para produção de Castanha-do-Brasil.
Devido às exigências sanitárias cada vez mais rígidas por parte tanto do mercado nacional quanto internacional, o Ministério da Agricultura, Pecuária e Abastecimento (Mapa)incentivou, em 2003, várias instituições a estudarem e definirem práticas de produção e pós-colheita que garantam a qualidade do produto e também seu mercado. Assim, este documento tem por objetivo fornecer subsídios para o manejo da castanheira e de seu produto visando a uma produção sustentável e de boa qualidade
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