scholarly journals Genetic mapping and identification of a QTL determining tolerance to freezing stress in Fragaria vesca L.

2021 ◽  
Author(s):  
Jahn Davik ◽  
Robert C. Wilson ◽  
Relindis G. Njah ◽  
Paul E. Grini ◽  
Stephen K. Randall ◽  
...  
Keyword(s):  
Low Temperature ◽  
Differential Expression ◽  
Freezing Tolerance ◽  
Quantitative Trait ◽  
Mapping Population ◽  
Differential Expression Analysis ◽  
Interval Mapping ◽  
Freezing Stress ◽  
Transcript Accumulation ◽  
Irreversible Damage

AbstractExtreme cold and frost cause significant stress to plants which can potentially be lethal. Low temperature freezing stress can cause significant and irreversible damage to plant cells and can induce physiological and metabolic changes that impact on growth and development. Low temperatures cause physiological responses including winter dormancy and autumn cold hardening in strawberry (Fragaria) species, and some diploid F. vesca accessions have been shown to have adapted to low-temperature stresses. To study the genetics of freezing tolerance, a F. vesca mapping population of 142 seedlings segregating for differential responses to freezing stress was raised. The progeny was mapped using ‘Genotyping-by-Sequencing’ and a linkage map of 2,918 markers at 851 loci was resolved. The mapping population was phenotyped for freezing tolerance response under controlled and replicated laboratory conditions and subsequent quantitative trait loci analysis using interval mapping revealed a single significant quantitative trait locus on Fvb2 in the physical interval 10.6 Mb and 15.73 Mb on the F. vesca v4.0 genome sequence. This physical interval contained 896 predicted genes, several of which had putative roles associated with tolerance to abiotic stresses including freezing. Differential expression analysis of the 896 QTL-associated gene predictions in the leaves and crowns from ‘Alta’ and ‘NCGR1363’ parental genotypes revealed genotype-specific changes in transcript accumulation in response to low temperature treatment as well as expression differences between genotypes prior to treatment for many of the genes. The putative roles, and significant interparental differential expression levels of several of the genes reported here identified them as good candidates for the control of the effects of freezing tolerance at the QTL identified in this investigation and the possible role of these candidate genes in response to freezing stress is discussed.

scholarly journals Quantitative trait loci and candidate genes associated with freezing tolerance of winter triticale (× Triticosecale Wittmack)

2021 ◽  
Author(s):  
I. Wąsek ◽  
M. Dyda ◽  
G. Gołębiowska ◽  
M. Tyrka ◽  
M. Rapacz ◽  
...  
Keyword(s):  
Chlorophyll Fluorescence ◽  
Quantitative Trait Loci ◽  
Freezing Tolerance ◽  
Quantitative Trait ◽  
Electrolyte Leakage ◽  
Interval Mapping ◽  
Single Marker Analysis ◽  
Chlorophyll Fluorescence Parameters ◽  
Fluorescence Parameters ◽  
Trait Loci

Abstract Freezing tolerance of triticale is a major trait contributing to its winter hardiness. The identification of genomic regions — quantitative trait loci (QTL) and molecular markers associated with freezing tolerance in winter hexaploid triticale — was the aim of this study. For that purpose, a new genetic linkage map was developed for the population of 92 doubled haploid lines derived from ‘Hewo’ × ‘Magnat’ F1 hybrid. Those lines, together with parents were subjected to freezing tolerance test three times during two winter seasons. Plants were grown and cold-hardened under natural fall/winter conditions and then subjected to freezing in controlled conditions. Freezing tolerance was assessed as the plants recovery (REC), the electrolyte leakage (EL) from leaves and chlorophyll fluorescence parameters (JIP) after freezing. Three consistent QTL for several fluorescence parameters, electrolyte leakage, and the percentage of the survived plants were identified with composite interval mapping (CIM) and single marker analysis (SMA). The first locus Qfr.hm-7A.1 explained 9% of variation of both electrolyte leakage and plants recovery after freezing. Two QTL explaining up to 12% of variation in plants recovery and shared by selected chlorophyll fluorescence parameters were found on 4R and 5R chromosomes. Finally, main locus Qchl.hm-5A.1 was detected for chlorophyll fluorescence parameters that explained up to 19.6% of phenotypic variation. The co-located QTL on chromosomes 7A.1, 4R and 5R, clearly indicated physiological and genetic relationship of the plant survival after freezing with the ability to maintain optimal photochemical activity of the photosystem II and preservation of the cell membranes integrity. The genes located in silico within the identified QTL include those encoding BTR1-like protein, transmembrane helix proteins like potassium channel, and phosphoric ester hydrolase involved in response to osmotic stress as well as proteins involved in the regulation of the gene expression, chloroplast RNA processing, and pyrimidine salvage pathway. Additionally, our results confirm that the JIP test is a valuable tool to evaluate freezing tolerance of triticale under unstable winter environments.

Quantitative Trait Loci and Epistasis for Crown Freezing Tolerance in the ‘Kanota’ × ‘Ogle’ Hexaploid Oat Mapping Population

Crop Science ◽  
2008 ◽  
Vol 48 (1) ◽  
pp. 149-157 ◽  
Author(s):  
David R. Wooten ◽  
David P. Livingston ◽  
James B. Holland ◽  
David S. Marshall ◽  
J. Paul Murphy
Keyword(s):  
Quantitative Trait Loci ◽  
Freezing Tolerance ◽  
Quantitative Trait ◽  
Mapping Population ◽  
Trait Loci

scholarly journals Changes in Ethylene, ABA and Sugars Regulate Freezing Tolerance under Low-Temperature Waterlogging in Lolium perenne

2021 ◽  
Vol 22 (13) ◽  
pp. 6700
Author(s):  
Barbara Jurczyk ◽  
Ewa Pociecha ◽  
Franciszek Janowiak ◽  
Michał Dziurka ◽  
Izabela Kościk ◽  
...  
Keyword(s):  
Low Temperature ◽  
Lolium Perenne ◽  
Freezing Tolerance ◽  
Tolerance Test ◽  
Cold Climate ◽  
Leaf Water Content ◽  
Test Plant ◽  
Transcript Accumulation ◽  
Glucose Signaling ◽  
Main Component

Plant overwintering may be affected in the future by climate change. Low-temperature waterlogging, associated with a predicted increase in rainfall during autumn and winter, can affect freezing tolerance, which is the main component of winter hardiness. The aim of this study was to elucidate the mechanism of change in freezing tolerance caused by low-temperature waterlogging in Lolium perenne, a cool-season grass that is well adapted to a cold climate. The work included: (i) a freezing tolerance test (plant regrowth after freezing); (ii) analysis of plant phytohormones production (abscisic acid [ABA] content and ethylene emission); (iii) measurement of leaf water content and stomatal conductance; (iv) carbohydrate analysis; and (v) analysis of Aco1, ABF2, and FT1 transcript accumulation. Freezing tolerance may be improved as a result of cold waterlogging. The mechanism of this change is reliant on multifaceted actions of phytohormones and carbohydrates, whereas ethylene may counteract ABA signaling. The regulation of senescence processes triggered by concerted action of phytohormones and glucose signaling may be an essential component of this mechanism.

scholarly journals Quantitative Trait Loci and Candidate Genes associated with Freezing Tolerance of Winter Triticale (×Triticosecale Wittmack)

2021 ◽  
Author(s):  
Iwona Wąsek ◽  
Mateusz Dyda ◽  
Gabriela Julia Golebiowska ◽  
Mirosław Tyrka ◽  
Marcin Rapacz ◽  
...  
Keyword(s):  
Chlorophyll Fluorescence ◽  
Freezing Tolerance ◽  
Quantitative Trait ◽  
Electrolyte Leakage ◽  
Transmembrane Helix ◽  
Interval Mapping ◽  
Tolerance Test ◽  
Single Marker Analysis ◽  
Chlorophyll Fluorescence Parameters ◽  
Fluorescence Parameters

Abstract Freezing tolerance of triticale is a major trait contributing to its winter hardiness. The identification of genomic regions – quantitative trait loci (QTLs) and molecular markers associated with freezing tolerance in winter hexaploid triticale was the aim of this study. For that purpose a new genetic linkage map was developed for the population of 92 doubled haploid lines derived from ‘Hewo’ × ‘Magnat’ F1 hybrid. Those lines, together with parents were subjected to freezing tolerance test three times during two winter seasons. Plants were grown and cold-hardened under natural fall/winter conditions and then subjected to freezing in controlled conditions. Freezing tolerance was assessed as the plants recovery (REC), the electrolyte leakage (EL) and chlorophyll fluorescence parameters (JIP) after freezing. Three consistent QTLs for several fluorescence parameters, electrolyte leakage and the percentage of the survived plants were identified with composite interval mapping (CIM) and single marker analysis (SMA). The first locus Qfr.hm-7A.1 explained 9 % of variation of both electrolyte leakage and plants recovery after freezing. Two QTLs explaining up to 12 % of variation in plants recovery and shared by selected chlorophyll fluorescence parameters were found on 4R and 5R chromosomes. Finally, main locus Qchl.hm-5A.1 was detected for chlorophyll fluorescence parameters that explained up to 19.6 % of phenotypic variation. The common QTLs located on chromosomes 7A.1, 4R and 5R, clearly indicated physiological and genetic relationship of the plant survival after freezing with the ability to maintain optimal photochemical activity of the photosystem II and preservation of the cell membranes integrity. The genes located in silico in the identified QTLs include those encoding transmembrane helix proteins like potassium channel and phosphoric ester hydrolase involved in response to osmotic stress as well as proteins involved in the regulation of the gene expression, chloroplast RNA processing and pyrimidine salvage pathway. Additionally, our results confirm that the JIP test is a valuable tool to evaluate freezing tolerance of triticale under unstable winter environments.

scholarly journals On the Differences Between Maximum Likelihood and Regression Interval Mapping in the Analysis of Quantitative Trait Loci

Genetics ◽  
2000 ◽  
Vol 156 (2) ◽  
pp. 855-865 ◽  
Author(s):  
Chen-Hung Kao
Keyword(s):  
Quantitative Trait Loci ◽  
Maximum Likelihood ◽  
Qtl Mapping ◽  
Quantitative Trait ◽  
Mean Squared Error ◽  
Interval Mapping ◽  
Size Difference ◽  
Ratio Test ◽  
Trait Loci ◽  
Variance Explained

AbstractThe differences between maximum-likelihood (ML) and regression (REG) interval mapping in the analysis of quantitative trait loci (QTL) are investigated analytically and numerically by simulation. The analytical investigation is based on the comparison of the solution sets of the ML and REG methods in the estimation of QTL parameters. Their differences are found to relate to the similarity between the conditional posterior and conditional probabilities of QTL genotypes and depend on several factors, such as the proportion of variance explained by QTL, relative QTL position in an interval, interval size, difference between the sizes of QTL, epistasis, and linkage between QTL. The differences in mean squared error (MSE) of the estimates, likelihood-ratio test (LRT) statistics in testing parameters, and power of QTL detection between the two methods become larger as (1) the proportion of variance explained by QTL becomes higher, (2) the QTL locations are positioned toward the middle of intervals, (3) the QTL are located in wider marker intervals, (4) epistasis between QTL is stronger, (5) the difference between QTL effects becomes larger, and (6) the positions of QTL get closer in QTL mapping. The REG method is biased in the estimation of the proportion of variance explained by QTL, and it may have a serious problem in detecting closely linked QTL when compared to the ML method. In general, the differences between the two methods may be minor, but can be significant when QTL interact or are closely linked. The ML method tends to be more powerful and to give estimates with smaller MSEs and larger LRT statistics. This implies that ML interval mapping can be more accurate, precise, and powerful than REG interval mapping. The REG method is faster in computation, especially when the number of QTL considered in the model is large. Recognizing the factors affecting the differences between REG and ML interval mapping can help an efficient strategy, using both methods in QTL mapping to be outlined.

scholarly journals Expression profiling of ileal mucosa in asthma reveals upregulation of innate immunity and genes characteristic of Paneth and goblet cells

2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Jan K. Nowak ◽  
Marzena Dworacka ◽  
Nazgul Gubaj ◽  
Arystan Dossimov ◽  
Zhumabek Dossimov ◽  
...  
Keyword(s):  
Crohn’S Disease ◽  
Crohn's Disease ◽  
Differential Expression ◽  
Expression Profiles ◽  
Differential Expression Analysis ◽  
Goblet Cells ◽  
Ileal Mucosa ◽  
Significant Differential Expression ◽  
Immune Genes ◽  
Asthma Patients

Abstract Background The expression profiles of the intestinal mucosa have not been comprehensively investigated in asthma. We aimed to explore this in the Correlated Expression and Disease Association Research (CEDAR) patient cohort. Methods Differential expression analysis of ileal, transverse colon, and rectal biopsies were supplemented by a comparison of transcriptomes from platelets and leukocytes subsets, including CD4+, CD8+, CD14+, CD15+, and CD19+ cells. Asthma patients (n = 15) and controls (n = 15) had similar age (p = 0.967), body mass index (p = 0.870), similar numbers of females (80%) and smoking rates (13.3%). Results Significant differential expression was found in the ileum alone, and not in any other cell/tissue types. More genes were found to be overexpressed (1,150) than under-expressed (380). The most overexpressed genes included Fc Fragment of IgG Binding Protein (FCGBP, logFC = 3.01, pFDR = 0.015), Mucin 2 (MUC2, logFC = 2.78, pFDR = 0.015), and Alpha 1B Defensin (DEFA1B, logFC = 2.73, pFDR = 0.024). Gene ontology implicated the immune system, including interleukins 4 and 13, as well as antimicrobial peptides in this overexpression. There was concordance of gene over- (STAT1, XBP1) and underexpression (NELF, RARA) in asthma and Crohn’s disease ileum when our results were compared to another dataset (p = 3.66 × 10–7). Conclusion Ileal mucosa in asthma exhibits a specific transcriptomic profile, which includes the overexpression of innate immune genes, mostly characteristic of Paneth and goblet cells, in addition to other changes that may resemble Crohn’s disease.

scholarly journals Best practices on the differential expression analysis of multi-species RNA-seq

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Matthew Chung ◽  
Vincent M. Bruno ◽  
David A. Rasko ◽  
Christina A. Cuomo ◽  
José F. Muñoz ◽  
...  
Keyword(s):  
Best Practices ◽  
Differential Expression ◽  
Expression Analysis ◽  
Differential Expression Analysis ◽  
Single Species ◽  
Rna Seq ◽  
Species Analysis ◽  
Differential Gene ◽  
Multiple Species ◽  
Downstream Analysis

AbstractAdvances in transcriptome sequencing allow for simultaneous interrogation of differentially expressed genes from multiple species originating from a single RNA sample, termed dual or multi-species transcriptomics. Compared to single-species differential expression analysis, the design of multi-species differential expression experiments must account for the relative abundances of each organism of interest within the sample, often requiring enrichment methods and yielding differences in total read counts across samples. The analysis of multi-species transcriptomics datasets requires modifications to the alignment, quantification, and downstream analysis steps compared to the single-species analysis pipelines. We describe best practices for multi-species transcriptomics and differential gene expression.

scholarly journals Identification of Prognostic RBPs in Osteosarcoma

2021 ◽  
Vol 20 ◽  
pp. 153303382110049
Author(s):  
Bei Li ◽  
Long Fang ◽  
Baolong Wang ◽  
Zengkun Yang ◽  
Tingbao Zhao
Keyword(s):  
Regression Analysis ◽  
Prognostic Factors ◽  
Differential Expression ◽  
Ribosome Biogenesis ◽  
Rna Binding ◽  
Cox Regression ◽  
Rna Binding Proteins ◽  
Malignant Tumors ◽  
Differential Expression Analysis ◽  
Cox Regression Analysis

Osteosarcoma often occurs in children and adolescents and causes poor prognosis. The role of RNA-binding proteins (RBPs) in malignant tumors has been elucidated in recent years. Our study aims to identify key RBPs in osteosarcoma that could be prognostic factors and treatment targets. GSE33382 dataset was downloaded from Gene Expression Omnibus (GEO) database. RBPs extraction and differential expression analysis was performed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed to explore the biological function of differential expression RBPs. Moreover, we constructed Protein-protein interaction (PPI) network and obtained key modules. Key RBPs were identified by univariate Cox regression analysis and multiple stepwise Cox regression analysis combined with the clinical information from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. Risk score model was generated and validated by GSE16091 dataset. A total of 38 differential expression RBPs was identified. Go and KEGG results indicated these RBPs were significantly involved in ribosome biogenesis and mRNA surveillance pathway. COX regression analysis showed DDX24, DDX21, WARS and IGF2BP2 could be prognostic factors in osteosarcoma. Spearman’s correlation analysis suggested that WARS might be important in osteosarcoma immune infiltration. In conclusion, DDX24, DDX21, WARS and IGF2BP2 might play key role in osteosarcoma, which could be therapuetic targets for osteosarcoma treatment.

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