scholarly journals Submergence Tolerance in Rice: Review of Mechanism, Breeding and, Future Prospects

2020 ◽  
Vol 12 (4) ◽  
pp. 1632 ◽  
Author(s):  
Yusuff Oladosu ◽  
Mohd Y. Rafii ◽  
Fatai Arolu ◽  
Samuel Chibuike Chukwu ◽  
Ismaila Muhammad ◽  
...  
Keyword(s):  
Quantitative Trait Locus ◽  
Quantitative Trait ◽  
Association Studies ◽  
Stem Elongation ◽  
Genome Wide Association Studies ◽  
Submergence Tolerance ◽  
Natural Ecosystems ◽  
Rice Varieties ◽  
Affected Plant ◽  
Trait Locus

Flooding or submergence is one of the major environmental stressors affecting many man-made and natural ecosystems worldwide. The increase in the frequency and duration of heavy rainfall due to climate change has negatively affected plant growth and development, which eventually causes the death of plants if it persists for days. Most crops, especially rice, being a semi-aquatic plant, are greatly affected by flooding, leading to yield losses each year. Genetic variability in the plant response to flooding includes the quiescence scheme, which allows underwater endurance of a prolonged period, escape strategy through stem elongation, and alterations in plant architecture and metabolism. Investigating the mechanism for flooding survival in wild species and modern rice has yielded significant insight into developmental, physiological, and molecular strategies for submergence and waterlogging survival. Significant progress in the breeding of submergence tolerant rice varieties has been made during the last decade following the successful identification and mapping of a quantitative trait locus for submergence tolerance, designated as SUBMERGENCE 1 (SUB1) from the FR13A landrace. Using marker-assisted backcrossing, the SUB1 QTL (quantitative trait locus) has been incorporated into many elite varieties within a short time and with high precision as compared with conventional breeding methods. Despite the advancement in submergence tolerance, for future studies, there is a need for practical approaches exploring genome-wide association studies (GWA) and QTL in combination with specific tolerance traits, such as drought, salinity, disease and insect resistance.

scholarly journals Barcoded Bulk QTL mapping reveals highly polygenic and epistatic architecture of complex traits in yeast

2021 ◽  
Author(s):  
Alex N. Nguyen Ba ◽  
Katherine R. Lawrence ◽  
Artur Rego-Costa ◽  
Shreyas Gopalakrishnan ◽  
Daniel Temko ◽  
...  
Keyword(s):  
Quantitative Trait Locus ◽  
Qtl Mapping ◽  
Quantitative Trait ◽  
Complex Traits ◽  
Large Scale ◽  
Genetic Basis ◽  
Association Studies ◽  
Model Organisms ◽  
Genome Wide Association Studies ◽  
Trait Locus

Mapping the genetic basis of complex traits is critical to uncovering the biological mechanisms that underlie disease and other phenotypes. Genome-wide association studies (GWAS) in humans and quantitative trait locus (QTL) mapping in model organisms can now explain much of the observed heritability in many traits, allowing us to predict phenotype from genotype. However, constraints on power due to statistical confounders in large GWAS and smaller sample sizes in QTL studies still limit our ability to resolve numerous small-effect variants, map them to causal genes, identify pleiotropic effects across multiple traits, and infer non-additive interactions between loci (epistasis). Here, we introduce barcoded bulk quantitative trait locus (BB-QTL) mapping, which allows us to construct, genotype, and phenotype 100,000 offspring of a budding yeast cross, two orders of magnitude larger than the previous state of the art. We use this panel to map the genetic basis of eighteen complex traits, finding that the genetic architecture of these traits involves hundreds of small-effect loci densely spaced throughout the genome, many with widespread pleiotropic effects across multiple traits. Epistasis plays a central role, with thousands of interactions that provide insight into genetic networks. By dramatically increasing sample size, BB-QTL mapping demonstrates the potential of natural variants in high-powered QTL studies to reveal the highly polygenic, pleiotropic, and epistatic architecture of complex traits.Significance statementUnderstanding the genetic basis of important phenotypes is a central goal of genetics. However, the highly polygenic architectures of complex traits inferred by large-scale genome-wide association studies (GWAS) in humans stand in contrast to the results of quantitative trait locus (QTL) mapping studies in model organisms. Here, we use a barcoding approach to conduct QTL mapping in budding yeast at a scale two orders of magnitude larger than the previous state of the art. The resulting increase in power reveals the polygenic nature of complex traits in yeast, and offers insight into widespread patterns of pleiotropy and epistasis. Our data and analysis methods offer opportunities for future work in systems biology, and have implications for large-scale GWAS in human populations.

scholarly journals Defining a rat blood pressure quantitative trait locus to a <81.8 kb congenic segment: comprehensive sequencing and renal transcriptome analysis

2010 ◽  
Vol 42A (2) ◽  
pp. 153-161 ◽  
Author(s):  
K. Gopalakrishnan ◽  
J. Saikumar ◽  
C. G. Peters ◽  
S. Kumarasamy ◽  
P. Farms ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Quantitative Trait Locus ◽  
Transcriptome Analysis ◽  
Quantitative Trait ◽  
Congenic Strain ◽  
Association Studies ◽  
Chromosome 9 ◽  
Genome Wide Association Studies ◽  
Congenic Strains ◽  
Trait Locus

Evidence from multiple linkage and genome-wide association studies suggest that human chromosome 2 (HSA2) contains alleles that influence blood pressure (BP). Homologous to a large segment of HSA2 is rat chromosome 9 (RNO9), to which a BP quantitative trait locus (QTL) was previously mapped. The objective of the current study was to further resolve this BP QTL. Eleven congenic strains with introgressed segments spanning <81.8 kb to <1.33 Mb were developed by introgressing genomic segments of RNO9 from the Dahl salt-resistant (R) rat onto the genome of the Dahl salt-sensitive (S) rat and tested for BP. The congenic strain with the shortest introgressed segment spanning <81.8 kb significantly lowered BP of the hypertensive S rat by 25 mmHg and significantly increased its mean survival by 45 days. In contrast, two other congenic strains had increased BP compared with the S. We focused on the <81.8 kb congenic strain, which represents the shortest genomic segment to which a BP QTL has been mapped to date in any species. Sequencing of this entire region in both S and R rats detected 563 variants. The region did not contain any known or predicted rat protein coding genes. Furthermore, a whole genome renal transcriptome analysis between S and the <81.8 kb S.R congenic strain revealed alterations in several critical genes implicated in renal homeostasis. Taken together, our results provide the basis for future studies to examine the relationship between the candidate variants within the QTL region and the renal differentially expressed genes as potential causal mechanisms for BP regulation.

A coordinate descent approach for sparse Bayesian learning in high dimensional QTL mapping and genome-wide association studies

2019 ◽  
Vol 35 (21) ◽  
pp. 4327-4335
Author(s):  
Meiyue Wang ◽  
Shizhong Xu
Keyword(s):  
Quantitative Trait Locus ◽  
Quantitative Trait Locus Mapping ◽  
Bayesian Learning ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Sparse Bayesian Learning ◽  
Genome Wide ◽  
Trait Locus ◽  
Locus Mapping

AbstractMotivationGenomic scanning approaches that detect one locus at a time are subject to many problems in genome-wide association studies and quantitative trait locus mapping. The problems include large matrix inversion, over-conservativeness for tests after Bonferroni correction and difficulty in evaluation of the total genetic contribution to a trait’s variance. Targeting these problems, we take a further step and investigate a multiple locus model that detects all markers simultaneously in a single model.ResultsWe developed a sparse Bayesian learning (SBL) method for quantitative trait locus mapping and genome-wide association studies. This new method adopts a coordinate descent algorithm to estimate parameters (marker effects) by updating one parameter at a time conditional on current values of all other parameters. It uses an L2 type of penalty that allows the method to handle extremely large sample sizes (>100 000). Simulation studies show that SBL often has higher statistical powers and the simulated true loci are often detected with extremely small P-values, indicating that SBL is insensitive to stringent thresholds in significance testing.Availability and implementationAn R package (sbl) is available on the comprehensive R archive network (CRAN) and https://github.com/MeiyueComputBio/sbl/tree/master/R%20packge.Supplementary informationSupplementary data are available at Bioinformatics online.

scholarly journals Integrative Analysis of Omics Data Reveals Regulatory Network of CDK10 in Vitiligo Risk

2021 ◽  
Vol 12 ◽  
Author(s):  
Minglong Cai ◽  
Tao Yuan ◽  
He Huang ◽  
Lan Gui ◽  
Li Zhang ◽  
...  
Keyword(s):  
Quantitative Trait ◽  
Association Studies ◽  
Regulatory Elements ◽  
Functional Genes ◽  
Large Sample Size ◽  
Genome Wide Association Studies ◽  
Omics Data ◽  
Genome Wide ◽  
Trait Locus ◽  
Destruction Of Melanocytes

Vitiligo is a multifactorial polygenic disorder, characterized by acquired depigmented skin and overlying hair resulting from the destruction of melanocytes. Genome-wide association studies (GWASs) of vitiligo have identified approximately 100 genetic variants. However, the identification of functional genes and their regulatory elements remains a challenge. To prioritize putative functional genes and DNAm sites, we performed a Summary data-based Mendelian Randomization (SMR) and heterogeneity in dependent instruments (HEIDI) test to integrate omics summary statistics from GWAS, expression quantitative trait locus (eQTL), and methylation quantitative trait loci (meQTL) analysis of large sample size. By integrating omics data, we identified two newly putative functional genes (SPATA2L and CDK10) associated with vitiligo and further validated CDK10 by qRT-PCR in independent samples. We also identified 17 vitiligo-associated DNA methylation (DNAm) sites in Chr16, of which cg05175606 was significantly associated with the expression of CDK10 and vitiligo. Colocalization analyses detected transcript of CDK10 in the blood and skin colocalizing with cg05175606 at single nucleotide polymorphism (SNP) rs77651727. Our findings revealed that a shared genetic variant rs77651727 alters the cg05175606 as well as up-regulates gene expression of CDK10 and further decreases the risk of vitiligo.

A Quantitative Trait Locus for Body Fat on Chromosome 1q43 in French Canadians: Linkage and Association Studies*

Obesity ◽  
2006 ◽  
Vol 14 (9) ◽  
pp. 1605-1615 ◽  
Author(s):  
Brahim Aissani ◽  
Louis Perusse ◽  
Gilles Lapointe ◽  
Yvon C. Chagnon ◽  
Luigi Bouchard ◽  
...  
Keyword(s):  
Quantitative Trait Locus ◽  
Body Fat ◽  
Quantitative Trait ◽  
Association Studies ◽  
French Canadians ◽  
Trait Locus
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