scholarly journals Genome-wide analyses reveal the role of noncoding variation in complex traits during rice domestication

2019 ◽  
Vol 5 (12) ◽  
pp. eaax3619 ◽  
Author(s):  
X. M. Zheng ◽  
J. Chen ◽  
H. B. Pang ◽  
S. Liu ◽  
Q. Gao ◽  
...  
Keyword(s):  
Complex Traits ◽  
Starch Content ◽  
Noncoding Rnas ◽  
Rice Grains ◽  
Population Analyses ◽  
Genome Wide ◽  
Functional Consequences ◽  
Selection For ◽  
Rice Domestication

Genomes carry millions of noncoding variants, and identifying the tiny fraction with functional consequences is a major challenge for genomics. We assessed the role of selection on long noncoding RNAs (lncRNAs) for domestication-related changes in rice grains. Among 3363 lncRNA transcripts identified in early developing panicles, 95% of those with differential expression (329 lncRNAs) between Oryza sativa ssp. japonica and wild rice were significantly down-regulated in the domestication event. Joint genome and transcriptome analyses reveal that directional selection on lncRNAs altered the expression of energy metabolism genes during domestication. Transgenic experiments and population analyses with three focal lncRNAs illustrate that selection on these loci led to increased starch content and grain weight. Together, our findings indicate that genome-wide selection for lncRNA down-regulation was an important mechanism for the emergence of rice domestication traits.

scholarly journals Genome-Wide Identification and Characterization of Long Noncoding RNAs Involved in Chinese Wheat Mosaic Virus Infection of Nicotiana benthamiana

Biology ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 232
Author(s):  
Weiran Zheng ◽  
Haichao Hu ◽  
Qisen Lu ◽  
Peng Jin ◽  
Linna Cai ◽  
...  
Keyword(s):  
Virus Infection ◽  
Mosaic Virus ◽  
Nicotiana Benthamiana ◽  
Noncoding Rnas ◽  
Long Noncoding Rnas ◽  
Differentially Expressed ◽  
Genome Wide ◽  
Chinese Wheat

Recent studies have shown that a large number of long noncoding RNAs (lncRNAs) can regulate various biological processes in animals and plants. Although lncRNAs have been identified in many plants, they have not been reported in the model plant Nicotiana benthamiana. Particularly, the role of lncRNAs in plant virus infection remains unknown. In this study, we identified lncRNAs in N. benthamiana response to Chinese wheat mosaic virus (CWMV) infection by RNA sequencing. A total of 1175 lncRNAs, including 65 differentially expressed lncRNAs, were identified during CWMV infection. We then analyzed the functions of some of these differentially expressed lncRNAs. Interestingly, one differentially expressed lncRNA, XLOC_006393, was found to participate in CWMV infection as a precursor to microRNAs in N. benthamiana. These results suggest that lncRNAs play an important role in the regulatory network of N. benthamiana in response to CWMV infection.

Genome-wide association study of the resistant starch content in rice grains

2017 ◽  
Vol 69 (7-8) ◽  
pp. 1600343 ◽  
Author(s):  
Jinsong Bao ◽  
Xin Zhou ◽  
Feifei Xu ◽  
Qiang He ◽  
Yong-Jin Park
Keyword(s):  
Association Study ◽  
Resistant Starch ◽  
Genome Wide Association Study ◽  
Starch Content ◽  
Genome Wide Association ◽  
Rice Grains ◽  
Genome Wide

scholarly journals Genotypes and Phenotypes: A Search for Influential Genes in Diabetic Retinopathy

2020 ◽  
Vol 21 (8) ◽  
pp. 2712
Author(s):  
Andrea P. Cabrera ◽  
Rushi N. Mankad ◽  
Lauren Marek ◽  
Ryan Das ◽  
Sampath Rangasamy ◽  
...  
Keyword(s):  
Diabetic Retinopathy ◽  
Complex Traits ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Metabolic Dysfunction ◽  
Duration Of Diabetes ◽  
Gene Environment ◽  
Genome Wide ◽  
Novel Biomarkers

Although gene–environment interactions are known to play an important role in the inheritance of complex traits, it is still unknown how a genotype and the environmental factors result in an observable phenotype. Understanding this complex interaction in the pathogenesis of diabetic retinopathy (DR) remains a big challenge as DR appears to be a disease with heterogenous phenotypes with multifactorial influence. In this review, we examine the natural history and risk factors related to DR, emphasizing distinct clinical phenotypes and their natural course in retinopathy. Although there is strong evidence that duration of diabetes and metabolic factors play a key role in the pathogenesis of DR, accumulating new clinical studies reveal that this disease can develop independently of duration of diabetes and metabolic dysfunction. More recently, studies have emphasized the role of genetic factors in DR. However, linkage analyses, candidate gene studies, and genome-wide association studies (GWAS) have not produced any statistically significant results. Our recently initiated genomics study, the Diabetic Retinopathy Genomics (DRGen) Study, aims to examine the contribution of rare and common variants in the development DR, and how they can contribute to clinical phenotype, rate of progression, and response to available therapies. Our preliminary findings reveal a novel set of genetic variants associated with proangiogenic and inflammatory pathways that may contribute to DR pathogenesis. Further investigation of these variants is necessary and may lead to development of novel biomarkers and new therapeutic targets in DR.

scholarly journals The role of gene expression on human sexual dimorphism: too early to call

2020 ◽  
Author(s):  
Eleonora Porcu ◽  
Annique Claringbould ◽  
Kaido Lepik ◽  
Tom G. Richardson ◽  
Federico A. Santoni ◽  
...  
Keyword(s):  
Sexual Dimorphism ◽  
Complex Traits ◽  
Causal Effect ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
A Genome ◽  
Specific Trait ◽  
Trait Associations

AbstractThe genetic underpinning of sexual dimorphism is very poorly understood. The prevalence of many diseases differs between men and women, which could be in part caused by sex-specific genetic effects. Nevertheless, only a few published genome-wide association studies (GWAS) were performed separately in each sex. The reported enrichment of expression quantitative trait loci (eQTLs) among GWAS–associated SNPs suggests a potential role of sex-specific eQTLs in the sex-specific genetic mechanism underlying complex traits.To explore this scenario, we performed a genome-wide analysis of sex-specific whole blood RNA-seq eQTLs from 3,447 individuals. Among 9 million SNP-gene pairs showing sex-combined associations, we found 18 genes with significant sex-specific cis-eQTLs (FDR 5%). Our phenome-wide association study of the 18 top sex-specific eQTLs on >700 traits unraveled that these eQTLs do not systematically translate into detectable sex-specific trait-associations. Power analyses using real eQTL- and causal effect sizes showed that millions of samples would be necessary to observe sex-specific trait associations that are fully driven by sex-specific cis-eQTLs. Compensatory effects may further hamper their detection. In line with this observation, we confirmed that the sex-specific trait-associations detected so far are not driven by sex-specific cis-eQTLs.

scholarly journals Optimizing the power to identify the genetic basis of complex traits with Evolve and Resequence studies

2019 ◽  
Author(s):  
Christos Vlachos ◽  
Robert Kofler
Keyword(s):  
Complex Traits ◽  
Quantitative Traits ◽  
Genetic Basis ◽  
Optimal Selection ◽  
Selection Regime ◽  
Higher Power ◽  
Powerful Approach ◽  
Selection For ◽  
Generation Sequencing

AbstractEvolve and Resequence (E&R) studies are frequently used to dissect the genetic basis of quantitative traits. By subjecting a population to truncating selection for several generations and estimating the allele frequency differences between selected and non-selected populations using Next Generation Sequencing, the loci contributing to the selected trait may be identified. The role of different parameters, such as, the population size or the number of replicate populations have been examined in previous works. However, the influence of the selection regime, i.e. the strength of truncating selection during the experiment, remains little explored. Using whole genome, individual based forward simulations of E&R studies, we found that the power to identify the causative alleles may be maximized by gradually increasing the strength of truncating selection during the experiment. Notably, such an optimal selection regime comes at no or little additional cost in terms of sequencing effort and experimental time. Interestingly, we also found that a selection regime which optimizes the power to identify the causative loci is not necessarily identical to a regime that maximizes the phenotypic response. Finally, our simulations suggest that an E&R study with an optimized selection regime may have a higher power to identify the genetic basis of quantitative traits than a GWAS, highlighting that E&R is a powerful approach for finding the loci underlying complex traits.

scholarly journals Long Noncoding RNAs and Their Therapeutic Promise in Diabetic Nephropathy

Nephron ◽  
2021 ◽  
pp. 1-11
Author(s):  
Juan D. Coellar ◽  
Jianyin Long ◽  
Farhad R. Danesh
Keyword(s):  
Diabetic Nephropathy ◽  
Large Scale ◽  
Kidney Diseases ◽  
Noncoding Rnas ◽  
Therapeutic Targets ◽  
Long Noncoding Rnas ◽  
Biological Processes ◽  
Aberrant Expression ◽  
Genome Wide

Recent advances in large-scale RNA sequencing and genome-wide profiling projects have unraveled a heterogeneous group of RNAs, collectively known as long noncoding RNAs (lncRNAs), which play central roles in many diverse biological processes. Importantly, an association between aberrant expression of lncRNAs and diverse human pathologies has been reported, including in a variety of kidney diseases. These observations have raised the possibility that lncRNAs may represent unexploited potential therapeutic targets for kidney diseases. Several important questions regarding the functionality of lncRNAs and their impact in kidney diseases, however, remain to be carefully addressed. Here, we provide an overview of the main functions and mechanisms of actions of lncRNAs, and their promise as therapeutic targets in kidney diseases, emphasizing on the role of some of the best-characterized lncRNAs implicated in the pathogenesis and progression of diabetic nephropathy.

scholarly journals Integrating gene expression with summary association statistics to identify susceptibility genes for 30 complex traits

2016 ◽  
Author(s):  
Nicholas Mancuso ◽  
Huwenbo Shi ◽  
Pagé Goddard ◽  
Gleb Kichaev ◽  
Alexander Gusev ◽  
...  
Keyword(s):  
Gene Expression ◽  
Genetic Correlation ◽  
Complex Traits ◽  
Association Studies ◽  
Susceptibility Genes ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Causal Variants

AbstractAlthough genome-wide association studies (GWASs) have identified thousands of risk loci for many complex traits and diseases, the causal variants and genes at these loci remain largely unknown. We leverage recently introduced methods to integrate gene expression measurements from 45 expression panels with summary GWAS data to perform 30 transcriptome-wide association studies (TWASs). We identify 1,196 susceptibility genes whose expression is associated with these traits; of these, 168 reside more than 0.5Mb away from any previously reported GWAS significant variant, thus providing new risk loci. Second, we find 43 pairs of traits with significant genetic correlation at the level of predicted expression; of these, 8 are not found through genetic correlation at the SNP level. Third, we use bi-directional regression to find evidence for BMI causally influencing triglyceride levels, and triglyceride levels causally influencing LDL. Taken together, our results provide insights into the role of expression to susceptibility of complex traits and diseases.

The Genomics ofOryzaSpecies Provides Insights into Rice Domestication and Heterosis

2019 ◽  
Vol 70 (1) ◽  
pp. 639-665 ◽  
Author(s):  
Erwang Chen ◽  
Xuehui Huang ◽  
Zhixi Tian ◽  
Rod A. Wing ◽  
Bin Han
Keyword(s):  
Complex Traits ◽  
Oryza Rufipogon ◽  
Oryza Species ◽  
Oryza Glaberrima ◽  
Cultivated Rice ◽  
African Rice ◽  
Genome Wide ◽  
Genome Variations ◽  
Genomic Studies ◽  
Rice Domestication

Here, we review recent progress in genetic and genomic studies of the diversity of Oryza species. In recent years, unlocking the genetic diversity of Oryza species has provided insights into the genomics of rice domestication, heterosis, and complex traits. Genome sequencing and analysis of numerous wild rice ( Oryza rufipogon) and Asian cultivated rice ( Oryza sativa) accessions have enabled the identification of genome-wide signatures of rice domestication and the unlocking of the origin of Asian cultivated rice. Moreover, similar studies on genome variations of African rice ( Oryza glaberrima) cultivars and their closely related wild progenitor Oryza barthii accessions have provided strong evidence to support a theory of independent domestication in African rice. Integrated genomic approaches have efficiently investigated many heterotic loci in hybrid rice underlying yield heterosis advantages and revealed the genomic architecture of rice heterosis. We conclude that in-depth unlocking of genetic variations among Oryza species will further enhance rice breeding.

scholarly journals Genome-Wide Association Mapping of Mixed Linkage (1,3;1,4)-β-Glucan and Starch Contents in Rice Whole Grain

2021 ◽  
Vol 12 ◽  
Author(s):  
Rahele Panahabadi ◽  
Asadollah Ahmadikhah ◽  
Lauren S. McKee ◽  
Pär K. Ingvarsson ◽  
Naser Farrokhi
Keyword(s):  
Genome Wide Association Study ◽  
Starch Content ◽  
Economic Value ◽  
Industrial Applications ◽  
Genome Wide Association ◽  
Whole Grain ◽  
Rice Grains ◽  
Genome Wide ◽  
Grain Starch ◽  
Key Factor

The glucan content of rice is a key factor defining its nutritional and economic value. Starch and its derivatives have many industrial applications such as in fuel and material production. Non-starch glucans such as (1,3;1,4)-β-D-glucan (mixed-linkage β-glucan, MLG) have many benefits in human health, including lowering cholesterol, boosting the immune system, and modulating the gut microbiome. In this study, the genetic variability of MLG and starch contents were analyzed in rice (Oryza sativa L.) whole grain, by performing a new quantitative analysis of the polysaccharide content of rice grains. The 197 rice accessions investigated had an average MLG content of 252 μg/mg, which was negatively correlated with the grain starch content. A new genome-wide association study revealed seven significant quantitative trait loci (QTLs) associated with the MLG content and two QTLs associated with the starch content in rice whole grain. Novel genes associated with the MLG content were a hexose transporter and anthocyanidin 5,3-O-glucosyltransferase. Also, the novel gene associated with the starch content was a nodulin-like domain. The data pave the way for a better understanding of the genes involved in determining both MLG and starch contents in rice grains and should facilitate future plant breeding programs.

scholarly journals A robust method to estimate regional polygenic correlation identifies heterogeneity in the shared heritability between complex traits

2017 ◽  
Author(s):  
Guillaume Paré ◽  
Shihong Mao ◽  
Wei Q. Deng
Keyword(s):  
Complex Traits ◽  
Potential Role ◽  
Hdl Cholesterol ◽  
Polygenic Effect ◽  
Genome Wide ◽  
Novel Method ◽  
Artery Disease ◽  
Genomic Regions ◽  
Epidemiological Association

AbstractBackgroundComplex traits can share a substantial proportion of their polygenic heritability. However, genome-wide polygenic correlations between pairs of traits can mask heterogeneity in their shared polygenic effects across loci. We propose a novel method (WML-RPC) to evaluate polygenic correlation between two complex traits in small genomic regions using summary association statistics. Our method tests for evidence that the polygenic effect at a given region affects two traits concurrently.ResultsWe show through simulations that our method is well calibrated, powerful and more robust to misspecification of linkage disequilibrium than other methods under a polygenic model. As small genomic regions are more likely to harbour specific genetic effects, our method is ideal to identify heterogeneity in shared polygenic correlation across regions. We illustrate the usefulness of our method by addressing two questions related to cardio-metabolic traits. First, we explored how regional polygenic correlation can inform on the strong epidemiological association between HDL cholesterol and coronary artery disease (CAD), suggesting a key role for triglycerides metabolism. Second, we investigated the potential role of PPARγ activators in the prevention of CAD.ConclusionsOur results provide a compelling argument that shared heritability between complex traits is highly heterogeneous across loci.

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