scholarly journals Genetic architecture modulates diet-induced hepatic mRNA and miRNA expression profiles in Diversity Outbred mice

Genetics ◽  
2021 ◽  
Vol 218 (3) ◽  
Author(s):  
Excel Que ◽  
Kristen L James ◽  
Alisha R Coffey ◽  
Tangi L Smallwood ◽  
Jody Albright ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Mirna Expression ◽  
Quantitative Trait ◽  
Genetic Architecture ◽  
Genetic Regulation ◽  
Phenotypic Variance ◽  
Expression Quantitative Trait Loci ◽  
Diversity Outbred ◽  
Trait Loci ◽  
Outbred Mice

Abstract Genetic approaches in model organisms have consistently demonstrated that molecular traits such as gene expression are under genetic regulation, similar to clinical traits. The resulting expression quantitative trait loci (eQTL) have revolutionized our understanding of genetic regulation and identified numerous candidate genes for clinically relevant traits. More recently, these analyses have been extended to other molecular traits such as protein abundance, metabolite levels, and miRNA expression. Here, we performed global hepatic eQTL and microRNA expression quantitative trait loci (mirQTL) analysis in a population of Diversity Outbred mice fed two different diets. We identified several key features of eQTL and mirQTL, namely differences in the mode of genetic regulation (cis or trans) between mRNA and miRNA. Approximately 50% of mirQTL are regulated by a trans-acting factor, compared to ∼25% of eQTL. We note differences in the heritability of mRNA and miRNA expression and variance explained by each eQTL or mirQTL. In general, cis-acting variants affecting mRNA or miRNA expression explain more phenotypic variance than trans-acting variants. Finally, we investigated the effect of diet on the genetic architecture of eQTL and mirQTL, highlighting the critical effects of environment on both eQTL and mirQTL. Overall, these data underscore the complex genetic regulation of two well-characterized RNA classes (mRNA and miRNA) that have critical roles in the regulation of clinical traits and disease susceptibility

scholarly journals Genetic Architecture Modulates Diet-Induced Hepatic mRNA and miRNA Expression Profiles in Diversity Outbred Mice

Genetics ◽  
2020 ◽  
Vol 216 (1) ◽  
pp. 241-259
Author(s):  
Excel Que ◽  
Kristen L. James ◽  
Alisha R. Coffey ◽  
Tangi L. Smallwood ◽  
Jody Albright ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Mirna Expression ◽  
Quantitative Trait ◽  
Genetic Architecture ◽  
Genetic Regulation ◽  
Phenotypic Variance ◽  
Expression Quantitative Trait Loci ◽  
Diversity Outbred ◽  
Trait Loci ◽  
Outbred Mice

Genetic approaches in model organisms have consistently demonstrated that molecular traits such as gene expression are under genetic regulation, similar to clinical traits. The resulting expression quantitative trait loci (eQTL) have revolutionized our understanding of genetic regulation and identified numerous candidate genes for clinically relevant traits. More recently, these analyses have been extended to other molecular traits such as protein abundance, metabolite levels, and miRNA expression. Here, we performed global hepatic eQTL and microRNA expression quantitative trait loci (mirQTL) analysis in a population of Diversity Outbred mice fed two different diets. We identified several key features of eQTL and mirQTL, namely differences in the mode of genetic regulation (cis or trans) between mRNA and miRNA. Approximately 50% of mirQTL are regulated by a trans-acting factor, compared to ∼25% of eQTL. We note differences in the heritability of mRNA and miRNA expression and variance explained by each eQTL or mirQTL. In general, cis-acting variants affecting mRNA or miRNA expression explain more phenotypic variance than trans-acting variants. Lastly, we investigated the effect of diet on the genetic architecture of eQTL and mirQTL, highlighting the critical effects of environment on both eQTL and mirQTL. Overall, these data underscore the complex genetic regulation of two well-characterized RNA classes (mRNA and miRNA) that have critical roles in the regulation of clinical traits and disease susceptibility.

scholarly journals Integrated Genome-Wide Analysis of MicroRNA Expression Quantitative Trait Loci in Pig Longissimus Dorsi Muscle

2021 ◽  
Vol 12 ◽  
Author(s):  
Kaitlyn R. Daza ◽  
Deborah Velez-Irizarry ◽  
Sebastian Casiró ◽  
Juan P. Steibel ◽  
Nancy E. Raney ◽  
...  
Keyword(s):  
Gene Expression ◽  
Quantitative Trait Loci ◽  
Mirna Expression ◽  
Quantitative Trait ◽  
Complex Traits ◽  
Carcass Composition ◽  
Longissimus Dorsi ◽  
Expression Quantitative Trait Loci ◽  
Genome Wide ◽  
Trait Loci

Determining mechanisms regulating complex traits in pigs is essential to improve the production efficiency of this globally important protein source. MicroRNAs (miRNAs) are a class of non-coding RNAs known to post-transcriptionally regulate gene expression affecting numerous phenotypes, including those important to the pig industry. To facilitate a more comprehensive understanding of the regulatory mechanisms controlling growth, carcass composition, and meat quality phenotypes in pigs, we integrated miRNA and gene expression data from longissimus dorsi muscle samples with genotypic and phenotypic data from the same animals. We identified 23 miRNA expression Quantitative Trait Loci (miR-eQTL) at the genome-wide level and examined their potential effects on these important production phenotypes through miRNA target prediction, correlation, and colocalization analyses. One miR-eQTL miRNA, miR-874, has target genes that colocalize with phenotypic QTL for 12 production traits across the genome including backfat thickness, dressing percentage, muscle pH at 24 h post-mortem, and cook yield. The results of our study reveal genomic regions underlying variation in miRNA expression and identify miRNAs and genes for future validation of their regulatory effects on traits of economic importance to the global pig industry.

Quantitative Trait Loci for Susceptibility to Tapeworm Infection in the Red Flour Beetle

Genetics ◽  
2003 ◽  
Vol 165 (3) ◽  
pp. 1307-1315
Author(s):  
Daibin Zhong ◽  
Aditi Pai ◽  
Guiyun Yan
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Genetic Basis ◽  
Life Cycles ◽  
Red Flour Beetle ◽  
Phenotypic Variance ◽  
Flour Beetle ◽  
Trait Loci ◽  
Host Ecology ◽  
Tapeworm Infection

Abstract Parasites have profound effects on host ecology and evolution, and the effects of parasites on host ecology are often influenced by the magnitude of host susceptibility to parasites. Many parasites have complex life cycles that require intermediate hosts for their transmission, but little is known about the genetic basis of the intermediate host's susceptibility to these parasites. This study examined the genetic basis of susceptibility to a tapeworm (Hymenolepis diminuta) in the red flour beetle (Tribolium castaneum) that serves as an intermediate host in its transmission. Quantitative trait loci (QTL) mapping experiments were conducted with two independent segregating populations using amplified fragment length polymorphism (AFLP) markers and randomly amplified polymorphic DNA (RAPD) markers. A total of five QTL that significantly affected beetle susceptibility were identified in the two reciprocal crosses. Two common QTL on linkage groups 3 and 6 were identified in both crosses with similar effects on the phenotype, and three QTL were unique to each cross. In one cross, the three main QTL accounted for 29% of the total phenotypic variance and digenic epistasis explained 39% of the variance. In the second cross, the four main QTL explained 62% of the variance and digenic epistasis accounted for only 5% of the variance. The actions of these QTL were either overdominance or underdominance. Our results suggest that the polygenic nature of beetle susceptibility to the parasites and epistasis are important genetic mechanisms for the maintenance of variation within or among beetle strains in susceptibility to tapeworm infection.

scholarly journals The Genetic Basis of the Interspecific Differences in Wing Size in Nasonia (Hymenoptera; Pteromalidae): Major Quantitative Trait Loci and Epistasis

Genetics ◽  
2002 ◽  
Vol 161 (2) ◽  
pp. 673-684
Author(s):  
J Gadau ◽  
R E Page ◽  
J H Werren
Keyword(s):  
Quantitative Trait Loci ◽  
Qtl Analysis ◽  
Quantitative Trait ◽  
Wing Length ◽  
Size Difference ◽  
Phenotypic Variance ◽  
Wing Size ◽  
Epistatic Interactions ◽  
Trait Loci ◽  
Wing Width

Abstract There is a 2.5-fold difference in male wing size between two haplodiploid insect species, Nasonia vitripennis and N. giraulti. The haploidy of males facilitated a full genomic screen for quantitative trait loci (QTL) affecting wing size and the detection of epistatic interactions. A QTL analysis of the interspecific wing-size difference revealed QTL with major effects and epistatic interactions among loci affecting the trait. We analyzed 178 hybrid males and initially found two major QTL for wing length, one for wing width, three for a normalized wing-size variable, and five for wing seta density. One QTL for wing width explains 38.1% of the phenotypic variance, and the same QTL explains 22% of the phenotypic variance in normalized wing size. This corresponds to a region previously introgressed from N. giraulti into N. vitripennis that accounts for 44% of the normalized wing-size difference between the species. Significant epistatic interactions were also found that affect wing size and density of setae on the wing. Screening for pairwise epistatic interactions between loci on different linkage groups revealed four additional loci for wing length and four loci for normalized wing size that were not detected in the original QTL analysis. We propose that the evolution of smaller wings in N. vitripennis males is primarily the result of major mutations at few genomic regions and involves epistatic interactions among some loci.

Quantitative Trait Loci Affecting Differences in Floral Morphology Between Two Species of Monkeyflower (Mimulus)

Genetics ◽  
1998 ◽  
Vol 149 (1) ◽  
pp. 367-382 ◽  
Author(s):  
H D Bradshaw ◽  
Kevin G Otto ◽  
Barbara E Frewen ◽  
John K McKay ◽  
Douglas W Schemske
Keyword(s):  
Quantitative Trait Loci ◽  
Reproductive Isolation ◽  
Quantitative Trait ◽  
Floral Morphology ◽  
Cumulative Effect ◽  
Sympatric Species ◽  
Accurate Estimate ◽  
Phenotypic Variance ◽  
Trait Loci ◽  
Morphological Differences

Abstract Conspicuous differences in floral morphology are partly responsible for reproductive isolation between two sympatric species of monkeyflower because of their effect on visitation of the flowers by different pollinators. Mimulus lewisii flowers are visited primarily by bumblebees, whereas M. cardinalis flowers are visited mostly by hummingbirds. The genetic control of 12 morphological differences between the flowers of M. lewisii and M. cardinalis was explored in a large linkage mapping population of F2 plants (n = 465) to provide an accurate estimate of the number and magnitude of effect of quantitative trait loci (QTLs) governing each character. Between one and six QTLs were identified for each trait. Most (9/12) traits appear to be controlled in part by at least one major QTL explaining ≥25% of the total phenotypic variance. This implies that either single genes of individually large effect or linked clusters of genes with a large cumulative effect can play a role in the evolution of reproductive isolation and speciation.

A functional strategy to characterize expression Quantitative Trait Loci

2017 ◽  
Vol 136 (11-12) ◽  
pp. 1477-1487 ◽  
Author(s):  
Elena Grassi ◽  
Elisa Mariella ◽  
Mattia Forneris ◽  
Federico Marotta ◽  
Marika Catapano ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Expression Quantitative Trait Loci ◽  
Functional Strategy ◽  
Trait Loci

scholarly journals Delineamento de experimentos em genética genômica

2007 ◽  
Vol 36 (suppl) ◽  
pp. 211-218 ◽  
Author(s):  
Guilherme Jordão de Magalhães Rosa
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Expression Quantitative Trait Loci ◽  
Trait Loci

Genética genômica é um termo utilizado para representar o estudo de processos genéticos controladores de caracteres fenotípicos de herança complexa, a partir da análise conjunta de informação relativa a fenótipos, estruturas de parentesco, marcadores moleculares e expressão gênica. Estudos de genética genômica são utilizados, por exemplo, para a estimação da herdabilidade de níveis de transcrição, para o mapeamento de locos controladores da expressao gênica (eQTL, do inglês expression Quantitative Trait Loci), e para o estudo de redes regulatórias. Genética genômica geralmente envolve experimentos com microarrays, os quais são ainda bastante caros e trabalhosos, limitando o tamanho amostral e conseqüentemente o poder estatístico de tais estudos. Desta maneira, é essencial que tais experimentos sejam otimizados do ponto de vista do delineamento, a partir de criteriosa escolha das amostras (indivíduos) a serem utilizadas, e do controle rigoroso dos vários fatores que podem afetar as variáveis-resposta de interesse. Outro ponto fundamental na condução de tais experimentos refere-se à marcação das amostras de mRNA com os fluoróforos e ao pareamento das mesmas em cada lâmina de microarray, os quais devem ser cuidadosamente planejados para que não haja confundimento entre estes efeitos e os fatores biológicos de interesse. Nesta apresentação serão discutidas algumas estratégias para o planejamento de estudos de genética genômica, incluindo a seleção de indivíduos objetivando-se a maximização da dissimilaridade genética ou do número de eventos de recombinação, bem como a condução eficiente dos ensaios com microarrays para diferentes objetivos experimentais.

scholarly journals Expression Quantitative Trait Loci for Extreme Host Response to Influenza A in Pre-Collaborative Cross Mice

2012 ◽  
Vol 2 (2) ◽  
pp. 213-221 ◽  
Author(s):  
Daniel Bottomly ◽  
Martin T. Ferris ◽  
Lauri D. Aicher ◽  
Elizabeth Rosenzweig ◽  
Alan Whitmore ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Host Response ◽  
Influenza A ◽  
Collaborative Cross ◽  
Expression Quantitative Trait Loci ◽  
Trait Loci
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