RNA markers revealed by transcriptomic analyses represent informative approaches for desired phenotypic traits in plant breeding
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ABSTRACT:
ORGANISM(S): Linum usitatissimum
PROVIDER: GSE222066 | GEO | 2023/07/12
REPOSITORIES: GEO
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Project description:RNA markers revealed by transcriptomic analyses represent informative approaches for desired phenotypic traits in plant breeding
| PRJNA917561 | ENA
Project description:BACKGROUND:Genetic markers can be used to identify and verify the origin of individuals. Motivation for the inference of ancestry ranges from conservation genetics to forensic analysis. High density assays featuring Single Nucleotide Polymorphism (SNP) markers can be exploited to create a reduced panel containing the most informative markers for these purposes. The objectives of this study were to evaluate methods of marker selection and determine the minimum number of markers from the BovineSNP50 BeadChip required to verify the origin of individuals in European cattle breeds. Delta, Wright's FST, Weir & Cockerham's FST and PCA methods for population differentiation were compared. The level of informativeness of each SNP was estimated from the breed specific allele frequencies. Individual assignment analysis was performed using the ranked informative markers. Stringency levels were applied by log-likelihood ratio to assess the confidence of the assignment test. RESULTS:A 95% assignment success rate for the 384 individually genotyped animals was achieved with <80, <100, <140 and <200 SNP markers (with increasing stringency threshold levels) across all the examined methods for marker selection. No further gain in power of assignment was achieved by sampling in excess of 200 SNP markers. The marker selection method that required the lowest number of SNP markers to verify the animal's breed origin was Wright's FST (60 to 140 SNPs depending on the chosen degree of confidence). Certain breeds required fewer markers (<100) to achieve 100% assignment success. In contrast, closely related breeds require more markers (~200) to achieve>95% assignment success. The power of assignment success, and therefore the number of SNP markers required, is dependent on the levels of genetic heterogeneity and pool of samples considered. CONCLUSIONS:While all SNP selection methods produced marker panels capable of breed identification, the power of assignment varied markedly among analysis methods. Thus, with effective exploration of available high density genetic markers, a diagnostic panel of highly informative markers can be produced.
| S-EPMC3118130 | biostudies-literature
Project description:Profiling the genetic composition and relationships among groundnut germplasm collections is essential for the breeding of new cultivars. The objectives of this study were to assess the genetic diversity and population structure among 100 improved groundnut genotypes using agronomic traits and high-density single nucleotide polymorphism (SNP) markers. The genotypes were evaluated for agronomic traits and drought tolerance at the International Crop Research Institute for the Semi-Arid Tropics (ICRISAT)/India across two seasons. Ninety-nine of the test genotypes were profiled with 16363 SNP markers. Pod yield per plant (PY), seed yield per plant (SY), and harvest index (HI) were significantly (p < 0.05) affected by genotype × environment interaction effects. Genotypes ICGV 07222, ICGV 06040, ICGV 01260, ICGV 15083, ICGV 10143, ICGV 03042, ICGV 06039, ICGV 14001, ICGV 11380, and ICGV 13200 ranked top in terms of pod yield under both drought-stressed and optimum conditions. PY exhibited a significant (p ≤ 0.05) correlation with SY, HI, and total biomass (TBM) under both test conditions. Based on the principal component (PC) analysis, PY, SY, HSW, shelling percentage (SHP), and HI were allocated in PC 1 and contributed to the maximum variability for yield under the two water regimes. Hence, selecting these traits could be successful for screening groundnut genotypes under drought-stressed and optimum conditions. The model-based population structure analysis grouped the studied genotypes into three sub-populations. Dendrogram for phenotypic and genotypic also grouped the studied 99 genotypes into three heterogeneous clusters. Analysis of molecular variance revealed that 98% of the total genetic variation was attributed to individuals, while only 2% of the total variance was due to variation among the subspecies. The genetic distance between the Spanish bunch and Virginia bunch types ranged from 0.11 to 0.52. The genotypes ICGV 13189, ICGV 95111, ICGV 14421, and ICGV 171007 were selected for further breeding based on their wide genetic divergence. Data presented in this study will guide groundnut cultivar development emphasizing economic traits and adaptation to water-limited agro-ecologies, including in Ethiopia.
| S-EPMC8598071 | biostudies-literature
Project description:<p>Functional ecology and biodiversity lack integrative reference data that combine the assessment of traits at different levels. Here, we integrate data from 16 field samples of complex thallose liverworts (order Marchantiales) collected from biological soil crust communities in Southern Sweden and Germany at three levels: (1) bioimaging (morphometric measurements from macro- and microscopy), (2) metabolomics (molecular computations performed on liquid chromatography high-resolution mass-spectrometry (UPLC/ESI-QTOF-MS) with data-dependent acquisition (DDA-MS) data) and (3) DNA marker sequencing. These data are used to construct a reference framework including a proposed naming scheme for the estimation of molecular traits and for demonstrating the systematic and standardized extraction of phenotypic and molecular traits for integration into the plant trait database TRY. Phylogenetic trees and partitioning around medoids are used to demonstrate the assessment of evolutionary relationships and the trait space connecting ecological hypotheses and documenting knowledge gains across domains. With our reference framework we want to encourage the combined assessment, reuse and integration of phenotypic and molecular traits into functional biodiversity research and related disciplines.</p>
2024-06-05 | MTBLS2239 | MetaboLights
Project description:Groundnut (Arachis hypogaea L.) is a multi-purpose legume serving millions of farmers and their value chain actors globally. Use of old poor-performing cultivars contributes to low yields (< 1 t/ha) of groundnut in sub-Saharan Africa including Tanzania. The objectives of this study were to determine the extent of genetic variation among diverse groundnut collections using phenotypic traits and simple sequence repeat (SSR) markers to select distinct and complementary genotypes for breeding. One hundred and nineteen genotypes were evaluated under field conditions for agronomic traits and susceptibility to rust and leaf spot diseases. The study was conducted in two locations across two seasons. In addition, the 119 accessions were profiled with 13 selected SSR markers. Genotype and genotype by environment interaction effects were significant (p < 0.05) for days to flowering (DTF), late leaf spot score at 85 and 100 days after planting, pod yield (PDY), kernel yield (KY), hundred seed weight (HSW) and shelling percentage (SP). Principal components analysis revealed that plant stand, KY, SP, NPP (number of pods per plant), late leaf spot and rust disease scores accounted for the largest proportion of the total variation (71.9%) among the tested genotypes. Genotypes ICGV-SM 08587 and ICGV-SM 16579 had the most stable yields across the test environments. Moderate genetic variation was recorded with mean polymorphic information content of 0.34 and gene diversity of 0.63 using the SSR markers. The majority (74%) of genotypes showed high membership coefficients to their respective sub-populations, while 26% were admixtures after structure analysis. Much of the variation (69%) was found within populations due to genotypic differences. The present study identified genotypes ICGV-SM 06737, ICGV-SM 16575, ICG 12725 and ICGV-SM 16608 to be used for development of mapping population, which will be useful for groundnut improvement. This study provided a baseline information on characterization and selection of a large sample of groundnut genotypes in Tanzania for effective breeding and systematic conservation.
| S-EPMC7811514 | biostudies-literature
Project description:We executed two live animal ranking experiments, own-flock and group-animal ranking, to identify the breeding objectives of Arab and Oromo goat keepers in northwestern Ethiopia as a preliminary step towards designing sustainable breeding programs for two goat populations. In the own-flock ranking experiment, a total of 147 households, out of which 46 were Arab and 101 were Oromo goat keepers that live in semi-arid and sub-humid agroecologies respectively, were visited at their homesteads and were asked to choose their first best, second best, third best and the most inferior does from their own flock. The reasons of ranking and life history of the does (age, previous production and reproduction information) were inquired and recorded; live body weight and some linear body measurements were taken. In the group-animal ranking experiment, 12 breeding does and 12 breeding bucks from Arab goats and the same number of animals from Oromo goats were randomly selected. Life history of selected does and bucks (age, birth type, libido and temperament) were inquired from the owners. The selected animals were randomly grouped into four in Arab goats (three animals per group) and the same was applied in Oromo goats. Twelve farmers for Arab goats and the same number of farmers for Oromo goats who have not known the experimental animals were invited to do the ranking. Each person ranked the three animals in each group as 1st, 2nd and 3rd, giving reasons of ranking. After a first round of ranking, s/he was then provided with the history of each individual animal and asked whether s/he would consider re-ranking them. This procedure was continued eight times until a person covered all groups of does and bucks. It was found out that in own-flock ranking experiment, keepers focus on productive, reproductive and behavioral traits (such as body size, mothering ability, twinning rate, kidding interval and temperament) while in group-animal ranking experiment, there was a general tendency to focus on observable physical traits like coat color, body size and body conformation. Simultaneous use of both own-flock and group-animal ranking experiments is advisable to identify breeding objective traits in production systems where record keeping is absent.
| S-EPMC7993801 | biostudies-literature
Project description:In the breeding of citrus (Citrus spp.), suitable fruit quality is essential for consumer acceptance of new cultivars. To identify parental combinations producing F1 progeny with fruit-quality traits exceeding certain selection criteria, we developed a simple and practical method for predicting multiple-trait segregation in an F1 progeny population. This method uses breeding values of parental genotypes and an additive genetic (co)variance matrix calculated by the best linear unbiased prediction method to construct a model for trait segregation in F1 progeny. To confirm the validity of our proposed method, we calculated the breeding values and additive genetic (co)variances based on phenotypic records on nine fruit-quality traits in 2122 genotypes, and constructed a trait segregation model. Subsequently, we applied the trait segregation model to all pairs of the 2122 genotypes (i.e., 2,252,503 combinations), and predicted the most promising combinations and evaluated their probabilities of producing superior genotypes exceeding the nine fruit-quality traits of satsuma mandarin (Citrus unshiu Marcow.) or 'Shiranuhi' ('Kiyomi' × 'Nakano No. 3' ponkan), two popular citrus cultivars in Japan. We consider these results to be useful not only for selecting good parental combinations for fruit quality or other important traits but also for determining the scale of breeding programs required to achieve specific breeding goals.
| S-EPMC6095598 | biostudies-literature
Project description:Key messageA breeding strategy combining genomic with one-stage phenotypic selection maximizes annual selection gain for net merit. Choice of the selection index strongly affects the selection gain expected in individual traits. Selection indices using genomic information have been proposed in crop-specific scenarios. Routine use of genomic selection (GS) for simultaneous improvement of multiple traits requires information about the impact of the available economic and logistic resources and genetic properties (variances, trait correlations, and prediction accuracies) of the breeding population on the expected selection gain. We extended the R package "selectiongain" from single trait to index selection to optimize and compare breeding strategies for simultaneous improvement of two traits. We focused on the expected annual selection gain (ΔGa) for traits differing in their genetic correlation, economic weights, variance components, and prediction accuracies of GS. For all scenarios considered, breeding strategy GSrapid (one-stage GS followed by one-stage phenotypic selection) achieved higher ΔGa than classical two-stage phenotypic selection, regardless of the index chosen to combine the two traits and the prediction accuracy of GS. The Smith-Hazel or base index delivered higher ΔGa for net merit and individual traits compared to selection by independent culling levels, whereas the restricted index led to lower ΔGa in net merit and divergent results for selection gain of individual traits. The differences among the indices depended strongly on the correlation of traits, their variance components, and economic weights, underpinning the importance of choosing the selection indices according to the goal of the breeding program. We demonstrate our theoretical derivations and extensions of the R package "selectiongain" with an example from hybrid wheat by designing indices to simultaneously improve grain yield and grain protein content or sedimentation volume.
| S-EPMC8580912 | biostudies-literature
Project description:One of the biggest challenges to a more widespread utilization of natural fibers from flax and other fiber plants is to obtain a better understanding of the different factors underlying the observed variability in fiber quality. To do this, we measured fiber morphometric parameters from seven different flax varieties (4 spring fiber, 2 winter fiber and 1 winter oil) and undertook Partial Least-Squares Discriminant Analysis (sPLS-DA) of transcriptomic data obtained from the same varieties in an attempt to identify high-information molecular markers. The calculation of Pearson correlation coefficients identified 5 putative gene-markers strongly correlated with morphometric features. Proteomic analysis on the two varieties showing the most discriminant and significant differences regarding to morphometrics identified an additional 4 protein-markers. The majority of the obtained markers are involved in lipid metabolism and the senescence process. Further comparative analysis of the obtained expression data with fiber mechanical measurements (strength, maximum force, area) obtained after field-retting for all 7 varieties allowed us to identify 4 highly-correlated putative molecular markers for the mechanical parameters. Three genes, connected directly or indirectly to cell wall metabolism (Expansin-related protein 3 precursor, beta-glucosidase and ascorbate peroxidase), and one gene coding an enzyme that catalyzes the oxidative decarboxylation of L-malate (NADP-malic enzyme 3). Based on our results, we hypothesize that a reduced number of RNA and protein functional markers can be used to more accurately monitor and/or predict fiber yield and quality properties in different flax varieties, thereby contributing to an Agriculture 4.0 for this economically-important species.
2023-07-18 | PXD039389 | Pride
Project description:Plant architecture is a critical trait in fruit crops that can significantly influence yield, pruning, planting density and harvesting. Most of the existing varieties of olive are traditional and their architecture is poorly suited for modern growing and harvesting systems. This study focuses on the identification of candidate genes involved in determining plant architecture in olive that could help in selecting phenotypes adapted to modern cultivation practices. We previously developed the first microarray for olive, as a means to discover candidate genes involved in relevant agronomical traits. The microarray has already been applied to identify candidates genes involved in regulating juvenile to adult transition in the shoot apex of seedlings. In the present study, made in the framework of an olive breeding program, varieties displaying differences in architecture and pooled seedlings grouped by their architecture-related phenotypes, were analysed using microarray analysis of meristematic tissue. We identify 2,258 differentially expressed genes potentially involved in determining plant architecture. Varieties with opposite architecture phenotypes and individuals from segregating progenies displaying extreme architecture features, constitute our key to linking phenotype to expression. We analyze some of the genes with potentially interesting functional annotation using quantitative RT-PCR assays, in the reference varieties and individual seedlings. Arabidopsis mutants in putative orthologs of some of the candidate genes show altered architecture, indicating functional conservation between the two species and supporting both, the biological relevance of the results, and the potential of the identified genes as markers for assisted breeding for olive varieties suited for high density orchards.
2016-02-15 | GSE60284 | GEO