RESUMO

Wild emmer (Triticum turgidum ssp. dicoccoides) genotypes were studied for their high-nutritional value and good tolerance to various types of stress; for this reason, several QTL (quantitative trait loci) studies have been conducted to find favorable alleles to be introgressed into modern wheat cultivars. Given the complexity of the QTL nature, their interaction with the environment, and other QTLs, a small number of genotypes have been used in wheat breeding programs. Meta-QTL (MQTL) analysis helps to simplify the existing QTL information, identifying stable genomic regions and possible candidate genes for further allele introgression. The study aimed to identify stable QTL regions across different environmental conditions and genetic backgrounds using the QTL information of the past 14 years for different traits in wild emmer based upon 17 independent studies. A total of 41 traits were classified as quality traits (16), mineral composition traits (11), abiotic-related traits (13), and disease-related traits (1). The analysis revealed 852 QTLs distributed across all 14 chromosomes of wild emmer, with an average of 61 QTLs per chromosome. Quality traits had the highest number of QTLs (35%), followed by mineral content (33%), abiotic-related traits (28%), and disease-related traits (4%). Grain protein content (GPC) and thousand kernel weight (TKW) were associated with most of the QTLs detected. A total of 43 MQTLs were identified, simplifying the information, and reducing the average confidence interval (CI) from 22.6 to 4.78 cM. These MQTLs were associated with multiple traits across different categories. Nine candidate genes were identified for several stable MQTLs, potentially contributing to traits such as quality, mineral content, and abiotic stress resistance. These genes play essential roles in various plant processes, such as carbohydrate metabolism, nitrogen assimilation, cell wall biogenesis, and cell wall extensibility. Overall, this study underscores the importance of considering MQTL analysis in wheat breeding programs, as it identifies stable genomic regions associated with multiple traits, offering potential solutions for improving wheat varieties under diverse environmental conditions.

RESUMO

Abiotic stress strongly affects yield-related traits in durum wheat, in particular drought is one of the main environmental factors that have effect on grain yield and plant architecture. In order to obtain new genotypes well adapted to stress conditions, the highest number of desirable traits needs to be combined in the same genotype. In this context, hundreds of quantitative trait loci (QTL) have been identified for yield-related traits in different genetic backgrounds and environments. Meta-QTL (MQTL) analysis is a useful approach to combine data sets and for creating consensus positions for the QTL detected in independent studies for the reliability of their location and effects. MQTL analysis is a useful method to dissect the genetic architecture of complex traits, which provide an extensive allelic coverage, a higher mapping resolution and allow the identification of putative molecular markers useful for marker-assisted selection (MAS). In the present study, a complete and comprehensive MQTL analysis was carried out to identify genomic regions associated with grain-yield related traits in durum wheat under different water regimes. A total of 724 QTL on all 14 chromosomes (genomes A and B) were collected for the 19 yield-related traits selected, of which 468 were reported under rainfed conditions, and 256 under irrigated conditions. Out of the 590 QTL projected on the consensus map, 421 were grouped into 76 MQTL associated with yield components under both irrigated and rainfed conditions, 12 genomic regions containing stable MQTL on all chromosomes except 1A, 4A, 5A, and 6B. Candidate genes associated to MQTL were identified and an in-silico expression analysis was carried out for 15 genes selected among those that were differentially expressed under drought. These results can be used to increase durum wheat grain yields under different water regimes and to obtain new genotypes adapted to climate change.

RESUMO

The Mexican tetra, Astyanax mexicanus, is a unique model system consisting of cave-adapted and surface-dwelling morphotypes that diverged >1 million years (My) ago. This remarkable natural experiment has enabled powerful genetic analyses of cave adaptation. Here, we describe the application of next-generation sequencing technology to the creation of a high-density linkage map. Our map comprises more than 2200 markers populating 25 linkage groups constructed from genotypic data generated from a single genotyping-by-sequencing project. We leveraged emergent genomic and transcriptomic resources to anchor hundreds of anonymous Astyanax markers to the genome of the zebrafish (Danio rerio), the most closely related model organism to our study species. This facilitated the identification of 784 distinct connections between our linkage map and the Danio rerio genome, highlighting several regions of conserved genomic architecture between the two species despite ~150 My of divergence. Using a Mendelian cave-associated trait as a proof-of-principle, we successfully recovered the genomic position of the albinism locus near the gene Oca2. Further, our map successfully informed the positions of unplaced Astyanax genomic scaffolds within particular linkage groups. This ability to identify the relative location, orientation, and linear order of unaligned genomic scaffolds will facilitate ongoing efforts to improve on the current early draft and assemble future versions of the Astyanax physical genome. Moreover, this improved linkage map will enable higher-resolution genetic analyses and catalyze the discovery of the genetic basis for cave-associated phenotypes.

Assuntos

RESUMO

Numerous selective breeding experiments have been performed with rodents, in an attempt to understand the genetic basis for innate differences in preference for alcohol consumption. Quantitative trait locus (QTL) analysis has been used to determine regions of the genome that are associated with the behavioral difference in alcohol preference/consumption. Recent work suggests that differences in gene expression represent a major genetic basis for complex traits. Therefore, the QTLs are likely to harbor regulatory regions (eQTLs) for the differentially expressed genes that are associated with the trait. In this study, we examined brain gene expression differences over generations of selection of the third replicate lines of high and low alcohol-preferring (HAP3 and LAP3) mice, and determined regions of the genome that control the expression of these differentially expressed genes (de eQTLs). We also determined eQTL regions (rv eQTLs) for genes that showed a decrease in variance of expression levels over the course of selection. We postulated that de eQTLs that overlap with rv eQTLs, and also with phenotypic QTLs, represent genomic regions that are affected by the process of selection. These overlapping regions controlled the expression of candidate genes (that displayed differential expression and reduced variance of expression) for the predisposition to differences in alcohol consumption by the HAP3/LAP3 mice.

Assuntos

RESUMO

Most traits of interest in plant breeding show quantitative inheritance, which complicate the breeding process since phenotypic performances only partially reflects the genetic values of individuals. The genetic variation of a quantitative trait is assumed to be controlled by the collective effects of quantitative trait loci (QTLs), epistasis (interaction between QTLs), the environment, and interaction between QTL and environment. Exploiting molecular markers in breeding involve finding a subset of markers associated with one or more QTLs that regulate the expression of complex traits. Many QTL mapping studies conducted in the last two decades identified QTLs that generally explained a significant proportion of the phenotypic variance, and therefore, gave rise to an optimistic assessment of the prospects of markers assisted selection. Linkage analysis and association mapping are the two most commonly used methods for QTL mapping. This review provides an overview of the two QTL mapping methods, including mapping population type and size, phenotypic evaluation of the population, molecular profiling of either the entire or a subset of the population, marker-trait association analysis using different statistical methods and software as well as the future prospects of using markers in crop improvement.

Assuntos