scholarly journals Improving Flooding Tolerance of Crop Plants

Agronomy ◽  
2018 ◽  
Vol 8 (9) ◽  
pp. 160 ◽  
Author(s):  
Angelika Mustroph
Keyword(s):  
Crop Plants ◽  
Flooding Tolerance ◽  
Waterlogging Tolerance ◽  
Aerenchyma Formation ◽  
Crop Resistance ◽  
Genome Wide ◽  
Anatomical Adaptations ◽  
Trait Locus ◽  
Heavy Rainfall Events ◽  
Gwa Studies

A major problem of climate change is the increasing duration and frequency of heavy rainfall events. This leads to soil flooding that negatively affects plant growth, eventually leading to death of plants if the flooding persists for several days. Most crop plants are very sensitive to flooding, and dramatic yield losses occur due to flooding each year. This review summarizes recent progress and approaches to enhance crop resistance to flooding. Most experiments have been done on maize, barley, and soybean. Work on other crops such as wheat and rape has only started. The most promising traits that might enhance crop flooding tolerance are anatomical adaptations such as aerenchyma formation, the formation of a barrier against radial oxygen loss, and the growth of adventitious roots. Metabolic adaptations might be able to improve waterlogging tolerance as well, but more studies are needed in this direction. Reasonable approaches for future studies are quantitative trait locus (QTL) analyses or genome-wide association (GWA) studies in combination with specific tolerance traits that can be easily assessed. The usage of flooding-tolerant relatives or ancestral cultivars of the crop of interest in these experiments might enhance the chances of finding useful tolerance traits to be used in breeding.

scholarly journals Increasing flooding tolerance in rice: combining tolerance of submergence and of stagnant flooding

2019 ◽  
Vol 124 (7) ◽  
pp. 1199-1209 ◽  
Author(s):  
Yoichiro Kato ◽  
Bertrand C Y Collard ◽  
Endang M Septiningsih ◽  
Abdelbagi M Ismail
Keyword(s):  
Shoot Elongation ◽  
Yield Reduction ◽  
Flooding Tolerance ◽  
Wet Season ◽  
Lodging Resistance ◽  
Aerenchyma Formation ◽  
Flooding Stress ◽  
Rice Ecosystems ◽  
Trait Locus

Abstract Background and Aims Rice ecosystems in the tropical coastal areas are subject to two types of flooding stress: transient complete submergence and long-term water stagnation (stagnant flooding). Here, we aimed to dissect the mechanisms for stagnant flooding tolerance of rice genotypes carrying SUB1, a quantitative trait locus for submergence tolerance. Methods We screened 80 elite genotypes under stagnant flooding stress in the lowland rice fields in the wet and dry seasons, and examined the tolerance mechanisms of promising genotypes for the two following seasons. Key results Yield reduction under stagnant flooding averaged 48 % in the dry season and 89 % in the wet season. Elite genotypes carrying SUB1 showed 49 % lower yield than those without SUB1 under stagnant flooding, with no differences under shallow water conditions. However, we identified a few high-yielding Sub1 genotypes that were as tolerant of stagnant flooding as a reference genotype that lacked SUB1. These genotypes had intermediate stature with more shoot elongation in response to rising water than a moderately tolerant Sub1 reference variety, resulting in greater canopy expansion and higher yield. It was important to increase lodging resistance, since plant height >140 cm increased lodging under stagnant flooding. The culm diameter was closely associated with culm strength; reduced aerenchyma formation and increased lignin accumulation in the culm should increase lodging resistance. Conclusions The study demonstrated a successful combination of submergence and stagnant flooding tolerance in a rice breeding programme, and identified elite Sub1 genotypes that also tolerate stagnant flooding. Our results will support genetic improvement of Sub1 varieties for stagnant flooding tolerance.

scholarly journals Epigenome-Wide Study Identified Methylation Sites Associated with the Risk of Obesity

Nutrients ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1984
Author(s):  
Majid Nikpay ◽  
Sepehr Ravati ◽  
Robert Dent ◽  
Ruth McPherson
Keyword(s):  
Quantitative Trait Locus ◽  
Quantitative Trait ◽  
Rare Variants ◽  
Genome Wide ◽  
A Genome ◽  
Genome Wide Search ◽  
Risk Snps ◽  
Trait Locus ◽  
Genomic Regions ◽  
Eqtl Data

Here, we performed a genome-wide search for methylation sites that contribute to the risk of obesity. We integrated methylation quantitative trait locus (mQTL) data with BMI GWAS information through a SNP-based multiomics approach to identify genomic regions where mQTLs for a methylation site co-localize with obesity risk SNPs. We then tested whether the identified site contributed to BMI through Mendelian randomization. We identified multiple methylation sites causally contributing to the risk of obesity. We validated these findings through a replication stage. By integrating expression quantitative trait locus (eQTL) data, we noted that lower methylation at cg21178254 site upstream of CCNL1 contributes to obesity by increasing the expression of this gene. Higher methylation at cg02814054 increases the risk of obesity by lowering the expression of MAST3, whereas lower methylation at cg06028605 contributes to obesity by decreasing the expression of SLC5A11. Finally, we noted that rare variants within 2p23.3 impact obesity by making the cg01884057 site more susceptible to methylation, which consequently lowers the expression of POMC, ADCY3 and DNAJC27. In this study, we identify methylation sites associated with the risk of obesity and reveal the mechanism whereby a number of these sites exert their effects. This study provides a framework to perform an omics-wide association study for a phenotype and to understand the mechanism whereby a rare variant causes a disease.

scholarly journals Identification and Functional Analysis of ThADH1 and ThADH4 Genes Involved in Tolerance to Waterlogging Stress in Taxodium hybrid ‘Zhongshanshan 406’

Genes ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 225
Author(s):  
Lei Xuan ◽  
Jianfeng Hua ◽  
Fan Zhang ◽  
Zhiquan Wang ◽  
Xiaoxiao Pei ◽  
...  
Keyword(s):  
Ethanol Metabolism ◽  
Flooding Tolerance ◽  
Transcriptome Data ◽  
Low Oxygen ◽  
Anaerobic Conditions ◽  
Waterlogging Tolerance ◽  
Waterlogging Stress ◽  
Adh Genes ◽  
Oxygen Conditions ◽  
Stems And Leaves

The Taxodium hybrid ‘Zhongshanshan 406’ (T. hybrid ‘Zhongshanshan 406’) [Taxodium mucronatum Tenore × Taxodium distichum (L.). Rich] has an outstanding advantage in flooding tolerance and thus has been widely used in wetland afforestation in China. Alcohol dehydrogenase genes (ADHs) played key roles in ethanol metabolism to maintain energy supply for plants in low-oxygen conditions. Two ADH genes were isolated and characterized—ThADH1 and ThADH4 (GenBank ID: AWL83216 and AWL83217—basing on the transcriptome data of T. hybrid ‘Zhongshanshan 406’ grown under waterlogging stress. Then the functions of these two genes were investigated through transient expression and overexpression. The results showed that the ThADH1 and ThADH4 proteins both fall under ADH III subfamily. ThADH1 was localized in the cytoplasm and nucleus, whereas ThADH4 was only localized in the cytoplasm. The expression of the two genes was stimulated by waterlogging and the expression level in roots was significantly higher than those in stems and leaves. The respective overexpression of ThADH1 and ThADH4 in Populus caused the opposite phenotype, while waterlogging tolerance of the two transgenic Populus significantly improved. Collectively, these results indicated that genes ThADH1 and ThADH4 were involved in the tolerance and adaptation to anaerobic conditions in T. hybrid ‘Zhongshanshan 406’.

scholarly journals Genome-wide Scan of IQ Finds Significant Linkage to a Quantitative Trait Locus on 2q

2005 ◽  
Vol 36 (1) ◽  
pp. 45-55 ◽  
Author(s):  
M. Luciano ◽  
M. J. Wright ◽  
D. L. Duffy ◽  
M. A. Wainwright ◽  
G. Zhu ◽  
...  
Keyword(s):  
Quantitative Trait Locus ◽  
Quantitative Trait ◽  
Genome Wide ◽  
Trait Locus ◽  
Significant Linkage ◽  
Genome Wide Scan

scholarly journals A Robust Rerank Approach for Feature Selection and Its Application to Pooling-Based GWA Studies

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Jia-Rou Liu ◽  
Po-Hsiu Kuo ◽  
Hung Hung
Keyword(s):  
Characteristic Curve ◽  
Real Data ◽  
Tuning Parameter ◽  
Practical Implementation ◽  
Tuning Parameters ◽  
Genome Wide ◽  
Feature Based ◽  
The Difference ◽  
Gwa Studies ◽  
Selection Of

Large-p-small-ndatasets are commonly encountered in modern biomedical studies. To detect the difference between two groups, conventional methods would fail to apply due to the instability in estimating variances int-test and a high proportion of tied values in AUC (area under the receiver operating characteristic curve) estimates. The significance analysis of microarrays (SAM) may also not be satisfactory, since its performance is sensitive to the tuning parameter, and its selection is not straightforward. In this work, we propose a robust rerank approach to overcome the above-mentioned diffculties. In particular, we obtain a rank-based statistic for each feature based on the concept of “rank-over-variable.” Techniques of “random subset” and “rerank” are then iteratively applied to rank features, and the leading features will be selected for further studies. The proposed re-rank approach is especially applicable for large-p-small-ndatasets. Moreover, it is insensitive to the selection of tuning parameters, which is an appealing property for practical implementation. Simulation studies and real data analysis of pooling-based genome wide association (GWA) studies demonstrate the usefulness of our method.

scholarly journals Independent genome-wide scans identify a chromosome 18 quantitative-trait locus influencing dyslexia

10.1038/ng792 ◽  
2001 ◽  
Vol 30 (1) ◽  
pp. 86-91 ◽  
Author(s):  
Simon E. Fisher ◽  
Clyde Francks ◽  
Angela J. Marlow ◽  
I. Laurence MacPhie ◽  
Dianne F. Newbury ◽  
...  
Keyword(s):  
Quantitative Trait Locus ◽  
Quantitative Trait ◽  
Chromosome 18 ◽  
Genome Wide ◽  
Trait Locus

scholarly journals Prioritization and Evaluation of Flooding Tolerance Genes in Soybean [Glycine max (L.) Merr.]

2021 ◽  
Vol 11 ◽  
Author(s):  
Mu-Chien Lai ◽  
Zheng-Yuan Lai ◽  
Li-Hsin Jhan ◽  
Ya-Syuan Lai ◽  
Chung-Feng Kao
Keyword(s):  
Glycine Max ◽  
Genome Wide Association Study ◽  
Meta Analysis ◽  
Soybean Seeds ◽  
Flooding Tolerance ◽  
Big Data Mining ◽  
Genome Wide ◽  
Glycine Max L ◽  
Mapping Gene ◽  
Selection Of

Soybean [Glycine max (L.) Merr.] is one of the most important legume crops abundant in edible protein and oil in the world. In recent years there has been increasingly more drastic weather caused by climate change, with flooding, drought, and unevenly distributed rainfall gradually increasing in terms of the frequency and intensity worldwide. Severe flooding has caused extensive losses to soybean production and there is an urgent need to breed strong soybean seeds with high flooding tolerance. The present study demonstrates bioinformatics big data mining and integration, meta-analysis, gene mapping, gene prioritization, and systems biology for identifying prioritized genes of flooding tolerance in soybean. A total of 83 flooding tolerance genes (FTgenes), according to the appropriate cut-off point, were prioritized from 36,705 test genes collected from multidimensional genomic features linking to soybean flooding tolerance. Several validation results using independent samples from SoyNet, genome-wide association study, SoyBase, GO database, and transcriptome databases all exhibited excellent agreement, suggesting these 83 FTgenes were significantly superior to others. These results provide valuable information and contribution to research on the varieties selection of soybean.

scholarly journals Evidence for GRN as part of a neuroinflammatory mechanism connecting common neurodegenerative diseases

2020 ◽  
Author(s):  
Mike A. Nalls ◽  
Cornelis Blauwendraat ◽  
Lana Sargent ◽  
Dan Vitale ◽  
Hampton Leonard ◽  
...  
Keyword(s):  
Amyotrophic Lateral Sclerosis ◽  
Neurodegenerative Diseases ◽  
Genetic Risk ◽  
Association Studies ◽  
Molecular Data ◽  
Genome Wide Association Studies ◽  
Data Types ◽  
Genome Wide ◽  
Trait Locus ◽  
Lateral Sclerosis

SUMMARYBackgroundPrevious research using genome wide association studies (GWAS) has identified variants that may contribute to lifetime risk of multiple neurodegenerative diseases. However, whether there are common mechanisms that link neurodegenerative diseases is uncertain. Here, we focus on one gene, GRN, encoding progranulin, and the potential mechanistic interplay between genetic risk, gene expression in the brain and inflammation across multiple common neurodegenerative diseases.MethodsWe utilized GWAS, expression quantitative trait locus (eQTL) mapping and Bayesian colocalization analyses to evaluate potential causal and mechanistic inferences. We integrate various molecular data types from public resources to infer disease connectivity and shared mechanisms using a data driven process.FindingseQTL analyses combined with GWAS identified significant functional associations between increasing genetic risk in the GRN region and decreased expression of the gene in Parkinson’s, Alzheimer’s and amyotrophic lateral sclerosis. Additionally, colocalization analyses show a connection between blood based inflammatory biomarkers relating to platelets and GRN expression in the frontal cortex.InterpretationGRN expression mediates neuroinflammation function related to general neurodegeneration. This analysis suggests shared mechanisms for Parkinson’s, Alzheimer’s and amyotrophic lateral sclerosis.FundingNational Institute on Aging, National Institute of Neurological Disorders and Stroke, and the Michael J. Fox Foundation.

Identification of aerenchyma formation-related QTL in barley that can be effective in breeding for waterlogging tolerance

2016 ◽  
Vol 129 (6) ◽  
pp. 1167-1177 ◽  
Author(s):  
Xuechen Zhang ◽  
Gaofeng Zhou ◽  
Sergey Shabala ◽  
Anthony Koutoulis ◽  
Lana Shabala ◽  
...  
Keyword(s):  
Waterlogging Tolerance ◽  
Aerenchyma Formation
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