Partner-assisted artificial selection of a secondary function for efficient bioremediation
Ontology highlight
ABSTRACT:
SUBMITTER: Zaccaria M
PROVIDER: S-EPMC10484969 | biostudies-literature | 2023 Aug
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Fusarium wilt is one of the most destructive chickpea diseases worldwide. Race 5 (Foc5) is the most harmful in the Mediterranean basin. The primary objective of this study is to validate a block of six SNP markers previously mapped in Ca2 in a diverse panel of cultivars, advanced and inbred lines phenotyped for resistance to fusarium wilt. Additionally, we aim to assess the effectiveness of using these markers in the selection of resistant Foc5 lines in an ongoing breeding program. The results showed a 100% coincidence between phenotype and expected haplotype in plant material evaluated for Foc5. We also analyzed 67 inbred lines previously phenotyped by different authors for fusarium wilt reaction, though the specific race was not specified. In these accessions, 65.8% of the analyzed lines exhibited complete correspondence between the phenotype and haplotype. Our results suggest that in early generations it is possible to select resistant materials with reliability, leading to the removal of a significant number of lines, thereby reducing costs and facilitating the handling of materials for additional trait evaluations. Functional annotation of genes delimited by the SNP block revealed several genes in the "response to stimulus" category with potential roles in the resistance reaction.
| S-EPMC10856910 | biostudies-literature
Project description:The study of microbe domestication has witnessed major advances that contribute to a better understanding of the emergence of artificially selected phenotypes and set the foundations of their rational improvement for biotechnology. Several features make Saccharomyces cerevisiae an ideal model for such a study, notably the availability of a catalogue of signatures of artificial selection and the extensive knowledge available on its biological processes. Here, we investigate with population and comparative genomics a set of strains used for cachaça fermentation, a Brazilian beverage based on the fermentation of sugar cane juice. We ask if the selective pressures posed by this fermentation have given rise to a domesticated lineage distinct from the ones already known, like wine, beer, bread, and sake yeasts. Our results show that cachaça yeasts derive from wine yeasts that have undergone an additional round of domestication, which we define as secondary domestication. As a consequence, cachaça strains combine features of wine yeasts, such as the presence of genes relevant for wine fermentation and advantageous gene inactivations, with features of beer yeasts like resistance to the effects of inhibitory compounds present in molasses. For other markers like those related to sulfite resistance and biotin metabolism our analyses revealed distributions more complex than previously reported that support the secondary domestication hypothesis. We propose a multilayered microbe domestication model encompassing not only transitions from wild to primarily domesticated populations, as in the case of wine yeasts, but also secondary domestications like those of cachaça yeasts.
| S-EPMC6101510 | biostudies-literature
Project description:Evolve and resequence studies combine artificial selection experiments with massively parallel sequencing technology to study the genetic basis for complex traits. In these experiments, individuals are selected for extreme values of a trait, causing alleles at quantitative trait loci (QTL) to increase or decrease in frequency in the experimental population. We present a new analysis of the power of artificial selection experiments to detect and localize quantitative trait loci. This analysis uses a simulation framework that explicitly models whole genomes of individuals, quantitative traits, and selection based on individual trait values. We find that explicitly modeling QTL provides qualitatively different insights than considering independent loci with constant selection coefficients. Specifically, we observe how interference between QTL under selection affects the trajectories and lengthens the fixation times of selected alleles. We also show that a substantial portion of the genetic variance of the trait (50-100%) can be explained by detected QTL in as little as 20 generations of selection, depending on the trait architecture and experimental design. Furthermore, we show that power depends crucially on the opportunity for recombination during the experiment. Finally, we show that an increase in power is obtained by leveraging founder haplotype information to obtain allele frequency estimates.
| S-EPMC4391575 | biostudies-literature
Project description:The stability and grafting efficiency are important for polydopamine (pDA) coatings used as platforms for secondary grafting. In this work, polyethyleneimine (PEI) was co-deposited with dopamine on various materials (PP, PTFE and PVC), then immersed in a 1.0 M HCl solution or 1.0 M NaOH solution to investigate the detachment of the coatings using UV-vis spectroscopy, SEM, FTIR spectroscopy and XPS, and the effect of PEI molecular weight on the secondary grafting of heparin on the pDA/PEI coating was investigated through clotting time tests. The results showed that the detachment rates of the pDA/PEI coating (14.6%, 23.7%) co-deposited on PTFE in 1.0 M HCl or 1.0 M NaOH solutions were both lower than that of the pDA coating (35.0%, 74.6%), indicating that pDA/PEI coatings could better remain on substrates in a 1.0 M NaOH solution. Besides, pDA/PEI coatings on a PP membrane with both a higher deposition density and stability could be obtained when the mass ratio of DA/PEI was 2 : 1-1 : 1 and PEI molecular weight was 600 Da. After grafting heparin, it was found that the pDA/PEI coating with lower molecular weight (600 Da and 1800 Da) PEI could achieve a higher grafting density of heparin with a longer clotting time. Thus, the results provided better understanding about the stability of pDA/PEI coatings and efficiency of heparin grafting.
| S-EPMC9727686 | biostudies-literature
Project description:Patients with poor inadequate bowel preparation need to undergo secondary colonoscopy. but the evaluation of intestinal cleanliness is judged by doctors subjectively. there are no objective and effective criteria to guide the evaluation. We use the deep learning technique to develop the EndoAngel with real-time intestinal cleanliness assessment. It can derive a decision curve for bowel cleanliness based on the relationship between the percentage of bowel segments with a Boston score of 1 and the adenoma detection rate. It can help doctors to identify patients who need a second colonoscopy, and provide a new way for artificial intelligence in improving the detection rate of colonoscopic adenomas.
| 2343573 | ecrin-mdr-crc
Project description:This study investigated whether a singer's coordination patterns differ when singing with an unseen human partner versus an unseen artificial partner (VOCALOID 6 voice synthesis software). We used cross-correlation analysis to compare the correlation of the amplitude envelope time series between the partner's and the participant's singing voices. We also conducted a Granger causality test to determine whether the past amplitude envelope of the partner helps predict the future amplitude envelope of the participants, or if the reverse is true. We found more pronounced characteristics of anticipatory synchronization and increased similarity in the unfolding dynamics of the amplitude envelopes in the human-partner condition compared to the artificial-partner condition, despite the tempo fluctuations in the human-partner condition. The results suggested that subtle qualities of the human singing voice, possibly stemming from intrinsic dynamics of the human body, may contain information that enables human agents to align their singing behavior dynamics with a human partner.
| S-EPMC11663750 | biostudies-literature
Project description:Salinity critically limits rice metabolism, growth, and productivity worldwide. Improvement of the salt resistance of locally grown high-yielding cultivars is a slow process. The objective of this study was to develop a new salt-tolerant rice germplasm using speed-breeding. Here, we precisely introgressed the hst1 gene, transferring salinity tolerance from "Kaijin" into high-yielding "Yukinko-mai" (WT) rice through single nucleotide polymorphism (SNP) marker-assisted selection. Using a biotron speed-breeding technique, we developed a BC3F3 population, named "YNU31-2-4", in six generations and 17 months. High-resolution genotyping by whole-genome sequencing revealed that the BC3F2 genome had 93.5% similarity to the WT and fixed only 2.7% of donor parent alleles. Functional annotation of BC3F2 variants along with field assessment data indicated that "YNU31-2-4" plants carrying the hst1 gene had similar agronomic traits to the WT under normal growth condition. "YNU31-2-4" seedlings subjected to salt stress (125 mM NaCl) had a significantly higher survival rate and increased shoot and root biomasses than the WT. At the tissue level, quantitative and electron probe microanalyzer studies indicated that "YNU31-2-4" seedlings avoided Na+ accumulation in shoots under salt stress. The "YNU31-2-4" plants showed an improved phenotype with significantly higher net CO2 assimilation and lower yield decline than WT under salt stress at the reproductive stage. "YNU31-2-4" is a potential candidate for a new rice cultivar that is highly tolerant to salt stress at the seedling and reproductive stages, and which might maintain yields under a changing global climate.
| S-EPMC6567206 | biostudies-literature
Project description:Case-control studies are designed towards studying associations between risk factors and a single, primary outcome. Information about additional, secondary outcomes is also collected, but association studies targeting such secondary outcomes should account for the case-control sampling scheme, or otherwise results may be biased. Often, one uses inverse probability weighted (IPW) estimators to estimate population effects in such studies. IPW estimators are robust, as they only require correct specification of the mean regression model of the secondary outcome on covariates, and knowledge of the disease prevalence. However, IPW estimators are inefficient relative to estimators that make additional assumptions about the data generating mechanism. We propose a class of estimators for the effect of risk factors on a secondary outcome in case-control studies that combine IPW with an additional modeling assumption: specification of the disease outcome probability model. We incorporate this model via a mean zero control function. We derive the class of all regular and asymptotically linear estimators corresponding to our modeling assumption, when the secondary outcome mean is modeled using either the identity or the log link. We find the efficient estimator in our class of estimators and show that it reduces to standard IPW when the model for the primary disease outcome is unrestricted, and is more efficient than standard IPW when the model is either parametric or semiparametric.
| S-EPMC5477998 | biostudies-literature
Project description:The absence of suitable terminal electron acceptors (TEA) in soil might limit the oxidative metabolism of environmental microbial populations. Bioelectroventing is a bioelectrochemical strategy that aims to enhance the biodegradation of a pollutant in the environment by overcoming the electron acceptor limitation and maximizing metabolic oxidation. Microbial electroremediating cells (MERCs) are devices that can perform such a bioelectroventing. We also report an overall profile of the 14 C-ATR metabolites and 14 C mass balance in response to the different treatments. The objective of this work was to use MERC principles, under different configurations, to stimulate soil bacteria to achieve the complete biodegradation of the herbicide 14 C-atrazine (ATR) to 14 CO2 in soils. Our study concludes that using electrodes at a positive potential [+600 mV (versus Ag/AgCl)] ATR mineralization was enhanced by 20-fold when compared to natural attenuation in electrode-free controls. Furthermore, ecotoxicological analysis of the soil after the bioelectroventing treatment revealed an effective clean-up in < 20 days. The impact of electrodes on soil bioremediation suggests a promising future for this emerging environmental technology.
| S-EPMC5743802 | biostudies-literature
Project description:The rate of advancement made in phenomic-assisted breeding methodologies has lagged those of genomic-assisted techniques, which is now a critical component of mainstream cultivar development pipelines. However, advancements made in phenotyping technologies have empowered plant scientists with affordable high-dimensional datasets to optimize the operational efficiencies of breeding programs. Phenomic and seed yield data was collected across six environments for a panel of 292 soybean accessions with varying genetic improvements. Random forest, a machine learning (ML) algorithm, was used to map complex relationships between phenomic traits and seed yield and prediction performance assessed using two cross-validation (CV) scenarios consistent with breeding challenges. To develop a prescriptive sensor package for future high-throughput phenotyping deployment to meet breeding objectives, feature importance in tandem with a genetic algorithm (GA) technique allowed selection of a subset of phenotypic traits, specifically optimal wavebands. The results illuminated the capability of fusing ML and optimization techniques to identify a suite of in-season phenomic traits that will allow breeding programs to decrease the dependence on resource-intensive end-season phenotyping (e.g., seed yield harvest). While we illustrate with soybean, this study establishes a template for deploying multitrait phenomic prediction that is easily amendable to any crop species and any breeding objective.
| S-EPMC7706298 | biostudies-literature