Potential Markers for Selecting Self-Eliminating Apple Genotypes.
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ABSTRACT:
SUBMITTER: Starkus A
PROVIDER: S-EPMC8398410 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:High temperatures and extreme drought are increasingly more frequent in Portugal, which represents a strong threat to viticulture in certain regions of the country. These multifactorial abiotic stresses are threatening viticultural areas worldwide, and the problem can hardly be overcome only by changing cultural practices. This scenario has raised a major challenge for plant scientists to find ways to adapt existing varieties to the new conditions without loss of their characteristic flavors, yield, and associated varietal character of wines. Aragonez (syn. Tempranillo) is one such variety, widely cultivated in Portugal and Spain, with specific characteristics associated with terroir. In this context, insight into intravarietal variability to enable its exploitation for selection becomes an important tool to mitigate the effect of multifactorial stresses driven by climate changes. The present work describes an innovative selection approach: selection for abiotic stress tolerance, measured by the leaf temperature of clones under environmental conditions of drought and extreme heat. This evaluation was complemented with values of yield and quality characteristics of the must (pH, acidity, °Brix, and anthocyanins). The application of this methodology was done in an experimental population of 255 clones of Tempranillo for 3 years. The genotypes were then ranked according to their level of tolerance to abiotic stress without loss of yield/quality. To understand the differences at the transcription level that could account for such variability, several of the most tolerant and most sensitive genotypes were analyzed for key genes using reverse transcriptase-quantitative polymerase chain reaction. The results enabled the selection of a group of genotypes with increased tolerance to stress, in relation to the average of the variety, which maintained the typical must quality of Aragonez. In parallel, several transcripts previously acknowledged as markers for abiotic stress tolerance were identified in several clones and are possible targets for plant breeding and genetic modification and/or to develop screening procedures to select genotypes better adapted to the abiotic stress driven by climate change.
| S-EPMC7773708 | biostudies-literature
Project description:Identifying high-yield genotypes under low water availability is essential for soybean climate-smart breeding. However, a major bottleneck lies in phenotyping, particularly in selecting cost-efficient markers associated with stress tolerance and yield stabilization. Here, we conducted in-depth phenotyping experiments in two soybean genotypes with contrasting drought tolerance, MUNASQA (tolerant) and TJ2049 (susceptible), to better understand soybean stress physiology and identify/statistically validate drought-tolerance and yield-stabilization traits as potential breeding markers. Firstly, at the critical reproductive stage (R5), the molecular differences between the genotype's responses to mild water deficit were explored through massive analysis of cDNA ends (MACE)-transcriptomic and gene ontology. MUNASQA transcriptional profile, compared to TJ2049, revealed significant differences when responding to drought. Next, both genotypes were phenotyped under mild water deficit, imposed in vegetative (V3) and R5 stages, by evaluating 22 stress-response, growth, and water-use markers, which were subsequently correlated between phenological stages and with yield. Several markers showed high consistency, independent of the phenological stage, demonstrating the effectiveness of the phenotyping methodology and its possible use for early selection. Finally, these markers were classified and selected according to their cost-feasibility, statistical weight, and correlation with yield. Here, pubescence, stomatal density, and canopy temperature depression emerged as promising breeding markers for the early selection of drought-tolerant soybeans.
| S-EPMC9237119 | biostudies-literature
Project description:BackgroundMarker sets developed for gait analysis are often applied to more dynamic tasks with little or no validation, despite known complications of soft tissue artifact.MethodsThis study presents a comparison of hip and knee kinematics as calculated by five concurrently-worn tracking marker sets during eight different tasks. The first three marker sets were based on Helen Hayes but used (1) proximal thigh wands, (2) distal thigh wands, and (3) patellar markers instead of thigh wands. The remaining two marker sets used rigid clusters on the (4) thighs and shanks and (5) only shanks. Pelvis and foot segments were shared by all marker sets. The first three tasks were maximal femoral rotations using different knee and hip positions to quantify the ability of each marker set to capture this motion. The remaining five tasks were walking, walking a 1m radius circle, running, jumping, and lunging.FindingsIn general, few and small differences in knee and hip flexion-extension were observed between marker sets, while many and large differences in adduction-abduction and external-internal rotations were observed. The shank-only tracking marker set was capable of detecting the greatest hip external-internal rotation, yet only did so during dynamic tasks where greater hip axial motions would be expected. All data are available in the Appendix.InterpretationMarker set selection is critical to non-sagittal hip and knee motions. The shank-only tracking marker set presented here is a viable alternative that may improve knee and hip kinematics by eliminating errors from thigh soft tissue artifact.
| S-EPMC5341079 | biostudies-literature
Project description:Reconstructing the evolutionary relationships of species is a major goal in biology. Despite the increasing number of completely sequenced genomes, a large number of phylogenetic projects rely on targeted sequencing and analysis of a relatively small sample of marker genes. The selection of these phylogenetic markers should ideally be based on accurate predictions of their combined, rather than individual, potential to accurately resolve the phylogeny of interest. Here we present and validate a new phylogenomics strategy to efficiently select a minimal set of stable markers able to reconstruct the underlying species phylogeny. In contrast to previous approaches, our methodology does not only rely on the ability of individual genes to reconstruct a known phylogeny, but it also explores the combined power of sets of concatenated genes to accurately infer phylogenetic relationships of species not previously analyzed. We applied our approach to two broad sets of cyanobacterial and ascomycetous fungal species, and provide two minimal sets of six and four genes, respectively, necessary to fully resolve the target phylogenies. This approach paves the way for the informed selection of phylogenetic markers in the effort of reconstructing the tree of life.
| S-EPMC3985644 | biostudies-literature
Project description:In this study, the resistive switching scheme using TiO2 nanorod arrays synthesized by a large-scale and low-cost hydrothermal process was reported. Especially, the nonlinear I-V characteristics of TiO2 nanorod arrays with a nonlinearity of up to ~10, which suppress the leakage current less than 10-4?Acm-2, were demonstrated, exhibiting a self-selecting resistive switching behavior. It provides a simple pathway for integration of RRAM crossbar arrays without additional stacking of active devices. The mechanisms of the nonlinear resistive switching behaviors were discussed in detail. In addition, the maximum array numbers of 79 for self-selecting RRAM cells were estimated. The results demonstrate an opportunity of using the concept of self-selecting resistive switching characteristics in a single material, which offers a new strategy to tackle the sneak path issue of RRAM in the crossbar arrays structure.
| S-EPMC5437035 | biostudies-literature
Project description:BackgroundResidency recruitment is a high-stakes activity for all participants, yet there is limited information about how applicants choose among programs.ObjectiveThis study evaluated the importance applicants place on various residency program attributes; whether applicant priorities vary by sex, race/ethnicity, or specialty choice; and whether the importance of these factors changes over time.MethodsHighly ranked applicants to residency programs at 2 academic medical centers were surveyed annually from 2004 to 2012 regarding the importance of 26 characteristics in selecting a program. Mean ratings of importance for each factor were analyzed to assess priority for the overall applicant group, and whether priorities differed for subgroups (by sex, race/ethnicity, and specialty).ResultsOf 9669 applicants surveyed, 6285 (65%) responded. The 5 factors with highest rating of importance (overall and across all subgroups) were the program's ability to prepare residents for future training or position, resident esprit de corps, faculty availability and involvement in teaching, depth and breadth of faculty, and variety of patients and clinical resources. Small but significant differences in the ratings of some factors by sex and/or specialty group were identified. Institution-level characteristics, such as call rooms, salary, and benefits, were relatively unimportant. Applicant priorities were stable over the 9-year study period.ConclusionsHighly ranked applicants to competitive residency programs value educational aspects of the program most highly, along with resident morale. Top factors were consistent across subgroups and over the 9 years of the study. These findings have implications for resident recruitment strategies.
| S-EPMC4507921 | biostudies-literature
Project description:BackgroundParentage information is fundamental to various life sciences. Recent advances in sequencing technologies have made it possible to accurately infer parentage even in non-model species. The optimization of sets of genome-wide markers is valuable for cost-effective applications but requires extremely large amounts of computation, which presses for the development of new efficient algorithms.ResultsHere, for a closed half-sib population, we generalized the process of marker loci selection as a binary integer programming problem. The proposed systematic formulation considered marker localization and the family structure of the potential parental population, resulting in an accurate assignment with a small set of markers. We also proposed an efficient heuristic approach, which effectively improved the number of markers, localization, and tolerance to missing data of the set. Applying this method to the actual genotypes of apple (Malus × domestica) germplasm, we identified a set of 34 SNP markers that distinguished 300 potential parents crossed to a particular cultivar with a greater than 99% accuracy.ConclusionsWe present a novel approach for selecting informative markers based on binary integer programming. Since the data generated by high-throughput sequencing technology far exceeds the requirement for parentage assignment, a combination of the systematic marker selection with targeted SNP genotyping, such as KASP, allows flexibly enlarging the analysis up to a scale that has been unrealistic in various species. The method developed in this study can be directly applied to unsolved large-scale problems in breeding, reproduction, and ecological research, and is expected to lead to novel knowledge in various biological fields. The implementation is available at https://github.com/SoNishiyama/IP-SIMPAT .
| S-EPMC9264695 | biostudies-literature
Project description:Apple exhibits typical gametophytic self-incompatibility, in which self-S-RNase can arrest pollen tube growth, leading to failure of fertilization. To date, there have been few studies on how to resist the toxicity of self-S-RNase. In this study, pollen tube polyamines were found to respond to self-S-RNase and help pollen tubes defend against self-S-RNase. In particular, the contents of putrescine, spermidine, and spermine in the pollen tube treated with self-S-RNase were substantially lower than those treated with non-self-S-RNase. Further analysis of gene expression of key enzymes in the synthesis and degradation pathways of polyamines found that the expression of DIAMINE OXIDASE 4 (MdDAO4) as well as several polyamine oxidases such as POLYAMINE OXIDASES 3 (MdPAO3), POLYAMINE OXIDASES 4 (MdPAO4), and POLYAMINE OXIDASES 6 (MdPAO6) were significantly up-regulated under self-S-RNase treatment, resulting in the reduction of polyamines. Silencing MdPAO6 in pollen tubes alleviates the inhibitory effect of self-S-RNase on pollen tube growth. In addition, exogenous polyamines also enhance pollen tube resistance to self-S-RNase. Transcriptome sequencing data found that polyamines may communicate with S-RNase through the calcium signal pathway, thereby regulating the growth of the pollen tubes. To summarize, our results suggested that polyamines responded to the self-incompatibility reaction and could enhance pollen tube tolerance to S-RNase, thus providing a potential way to break self-incompatibility in apple.
| S-EPMC8620888 | biostudies-literature
Project description:An ANOVA type general multi-allele (GMA) model was proposed in Wang (2014) on analysis of variance components for quantitative trait loci or genetic markers with phased or unphased genotypes. In this study, by applying the GMA model, we further examine estimation of the genetic variance components for genetic markers with unphased genotypes based on a random sample from a study population. In one locus and two loci cases, we first derive the least square estimates (LSE) of model parameters in fitting the GMA model. Then we construct estimators of the genetic variance components for one marker locus in a Hardy-Weinberg disequilibrium population and two marker loci in an equilibrium population. Meanwhile, we explore the difference between the classical general linear model (GLM) and GMA based approaches in association analysis of genetic markers with quantitative traits. We show that the GMA model can retain the same partition on the genetic variance components as the traditional Fisher's ANOVA model, while the GLM cannot. We clarify that the standard F-statistics based on the partial reductions in sums of squares from GLM for testing the fixed allelic effects could be inadequate for testing the existence of the variance component when allelic interactions are present. We point out that the GMA model can reduce the confounding between the allelic effects and allelic interactions at least for independent alleles. As a result, the GMA model could be more beneficial than GLM for detecting allelic interactions.
| S-EPMC4942470 | biostudies-other
Project description:BackgroundIn genomic medical studies, one of the major objectives is to identify genomic factors with a prognostic impact on time-to-event outcomes so as to provide new insights into the disease process. Selection usually relies on statistical univariate indices based on the Cox model. Such model assumes proportional hazards (PH) which is unlikely to hold for each genomic marker.MethodsIn this paper, we introduce a novel pseudo-R2 measure derived from a crossing hazards model and designed for the selection of markers with crossing effects. The proposed index is related to the score statistic and quantifies the extent of a genomic factor to separate patients according to their survival times and marker measurements. We also show the importance of considering genomic markers with crossing effects as they potentially reflect the complex interplay between markers belonging to the same pathway.ResultsSimulations show that our index is not affected by the censoring and the sample size of the study. It also performs better than classical indices under the crossing hazards assumption. The practical use of our index is illustrated in a lung cancer study. The use of the proposed pseudo-R2 allows the identification of cell-cycle dependent genes not identified when relying on the PH assumption.ConclusionsThe proposed index is a novel and promising tool for selecting markers with crossing hazards effects.
| S-EPMC3068986 | biostudies-literature