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Most of the bioinformatics tools for enzyme annotation focus on enzymatic function assignments. Sequence similarity to well-characterized enzymes is often used for functional annotation and to assign metabolic pathways. However, these approaches are not feasible for all sequences leading to inaccurate annotations or lack of metabolic pathway information. Here we present the mApLe (metabolic pathway predictor of plant enzymes), a high-performance machine learning-based tool with models to label the metabolic pathway of enzymes rather than specifying enzymes' reactions. The mApLe uses molecular descriptors of the enzyme sequences to perform predictions without considering sequence similarities with reference sequences. Hence, mApLe can classify a diversity of enzymes, even the ones without any homolog or with incomplete EC numbers. This tool can be used to improve the quality of genomic annotation of plants or to narrow down the number of candidate genes for metabolic engineering researches. The mApLe tool is available online, and the GUI can be locally installed.Classical plant breeding has been instrumental in changing the genetic makeup of crop plants for better ecological adaptation and improved quality. This paper provides insights of the genomic changes effected in hard winter wheat (Triticum aestivum L.) through decades of breeding and selection in the Great Plains of the United States. Population structure and differentiation analyses were conducted on 185 wheat cultivars released from 1943 to 2013. Cultivars were grouped into four distinct clusters using discriminant analysis of principal components (DAPC). One of the clusters was unique in that 15 out of the 18 individuals were recent releases (2000-2010), while 12 of the 18 shared the cultivar 'Jagger' in their genetic background. Jagger carries a 2NS/2AS translocation segment from Aegilops ventricosa, an important segment for resistance to several foliar diseases. Using the outlier approach, Wright's population fixation index (Fst) identified 450 loci that were directionally selected. The largest signature of selection was found on chromosome 2A. Genetic diversity was high while the inbreeding coefficient was low, indicating extensive hybridization and germplasm exchange among breeding programs within the region. Foliar disease pressure and selection for resistance helped shape the microevolution of wheat in the southern Great Plains. The results showed that high genetic diversity remains in hard winter wheat cultivars adapted to the Great Plains of the USA, and modern plant breeding did not cause any sizable reduction in genetic diversity of the crop in this region.The identification and characterization of resistance genes should outpace the rapid emergence of new P. graminis f. sp. tritici races, such as TTRTF and TTKTT, to mitigate stem rust damage to wheat. The objective of the current study was to identify and characterize P. graminis f. sp. tritici race resistance association signals. A total of 250 North American spring wheat lines were evaluated at the seedling stage with a total of seven isolates including TKKTP, TKTTF, TKTTF, TRTTF, TTRTF, TTKSK, and TTKTT. The lines were genotyped by a GBS platform and 9,042 SNPs were used for identification of chromosome regions associated with resistance against the seven isolates. Strong association signals were detected on chromosomes 6BL (Sr11 gene region) and 4AL, likely Sr7a, for resistance against both TKKTP and TKTTF. Similarly, association signals were also detected on chromosomes 4AL (race TTRTF resistance) and 4BS (race TTKSK and TTKTT resistance). Association analysis based on mean phenotypic differences between closely related isolates identified QTL that were not elucidated by direct association mapping of the responses, individually. Itacitinib cost Overall, with the exception of race TRTTF, each race shared at least one association signal with another race. However, the number of race-specific association signals are larger than that of association signals common among races suggesting the need for identifying and characterizing QTL/genes for newly emerging stem rust pathogen races. There was also high concordance between PCA-based GWAS association signals and association signals from that of both single and multi-locus mixed models.Breeding forest species can be a costly and slow process because of the extensive areas needed for field trials and the long periods (e.g., five years) that are required to measure economically and environmentally relevant phenotypes (e.g., adult plant biomass or plant height). Genomic selection (GS) and indirect selection using early phenotypes (e.g., phenotypes collected in greenhouse conditions) are two ways by which tree breeding can be accelerated. These approaches can both reduce the costs of field-testing and the time required to make selection decisions. Moreover, these approaches can be highly synergistic. Therefore, in this study, we used a data set comprising DNA genotypes and longitudinal measurements of growth collected from a population of Populus deltoides W. Bartram ex Marshall (eastern cottonwood) in the greenhouse and the field, to evaluate the potential impact of integrating large-scale greenhouse phenotyping with conventional GS. We found that the integration of greenhouse phenotyping and GS can deliver very early selection decisions that are moderately accurate. Therefore, we conclude that the adoption of these approaches, in conjunction with reproductive techniques that shorten the generation interval, can lead to an unprecedented acceleration of selection gains in P. deltoides and, potentially, other commercially planted tree species.Brown stem rot (BSR) reduces soybean [Glycine max (L.) Merr.] yield by up to 38%. The BSR causal agent is Phialophora gregata f. sp. sojae, a slow-growing, necrotrophic fungus whose life cycle includes latent and pathogenic phases, each lasting several weeks. Brown stem rot foliar symptoms are often misdiagnosed as other soybean diseases or nutrient stress, making BSR resistance especially difficult to phenotype. To shed light on the genes and networks contributing to P. gregata resistance, we conducted RNA sequencing (RNA-seq) of a resistant genotype (PI 437970, Rbs3). Leaf, stem, and root tissues were collected 12, 24, and 36 h after stab inoculation with P. gregata, or mock infection, in the plant stem. By using multiple tissues and time points, we could see that leaves, stems, and roots use the same defense pathways. Our analyses suggest that P. gregata induces a biphasic defense response, with pathogen-associated molecular pattern (PAMP) triggered immunity observed in leaves at 12 and 24 h after infection (HAI) and effector triggered immunity detected at 36 h after infection in the stems.
Read More: https://www.selleckchem.com/products/itacitinib-incb39110.html
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