Advantages of continuous genotype values over genotype classes for GWAS in higher polyploids: a comparative study in hexaploid chrysanthemum

Background: Association studies are an essential part of modern plant breeding, but are limited for polyploid crops. The increased number of possible genotype classes complicates the differentiation between them. Available methods are limited with respect to the ploidy level or data producing technologies. While genotype classification is an established noise reduction step in diploids, it gains complexity with increasing ploidy levels. Eventually, the errors produced by misclassifications exceed the benefits of genotype classes. Alternatively, continuous genotype values can be used for association analysis in higher polyploids. We associated continuous genotypes to three different traits and compared the results to the output of the genotype caller SuperMASSA. Linear, Bayesian and partial least squares regression were applied, to determine if the use of continuous genotypes is limited to a specific method. A disease, a flowering and a growth trait with h(2) of 0.51, 0.78 and 0.91 were associated with a hexaploid chrysanthemum genotypes. The data set consisted of 55,825 probes and 228 samples. Results: We were able to detect associating probes using continuous genotypes for multiple traits, using different regression methods. The identified probe sets were overlapping, but not identical between the methods. Baysian regression was the most restrictive method, resulting in ten probes for one trait and none for the others. Linear and partial least squares regression led to numerous associating probes. Association based on genotype classes resulted in similar values, but missed several significant probes. A simulation study was used to successfully validate the number of associating markers. Conclusions: Association of various phenotypic traits with continuous genotypes is successful with both uni- and multivariate regression methods. Genotype calling does not improve the association and shows no advantages in this study. Instead, use of continuous genotypes simplifies the analysis, saves computational time and results more potential markers

Integrating gene expression and GO classification for PCA by preclustering

Contains fulltext : 83407.pdf (publisher's version ) (Open Access)10 p

PERGOLA: fast and deterministic linkage mapping of polyploids

Background: A large share of agriculturally and horticulturally important plant species are polyploid. Linkage maps are used to locate associations between genes and traits by breeders and geneticists. Linkage map creation for polyploid species is not supported by standard tools. We want to overcome this limitation and validate our results with simulation studies. Results: We developed PERGOLA, a deterministic and heuristic method that addresses this problem. We show that it creates correct linkage groups, marker orders and distances for simulated and real datasets. We compare it to existing tools and demonstrate that it overcomes limitations in ploidy and outperforms them in computational time and mapping accuracy. We represent linkage maps as dendrograms and show that this has advantages in the comparison of different maps. Conclusions: PERGOLA can be used successfully to calculate linkage maps for diploid and polyploid species and outperforms existing tools

Meiotic recombination profiling of interspecific hybrid F1 tomato pollen by linked read sequencing

Genome wide screening of pooled pollen samples from a single interspecific F1 hybrid obtained from a cross between tomato, Solanum lycopersicum and its wild relative, Solanum pimpinellifolium using linked read sequencing of the haploid nuclei, allowed profiling of the crossover (CO) and gene conversion (GC) landscape. We observed a striking overlap between cold regions of CO in the male gametes and our previously established F6 recombinant inbred lines (RILs) population. COs were overrepresented in non‐coding regions in the gene promoter and 5′UTR regions of genes. Poly‐A/T and AT rich motifs were found enriched in 1 kb promoter regions flanking the CO sites. Non‐crossover associated allelic and ectopic GCs were detected in most chromosomes, confirming that besides CO, GC represents also a source for genetic diversity and genome plasticity in tomato. Furthermore, we identified processed break junctions pointing at the involvement of both homology directed and non‐homology directed repair pathways, suggesting a recombination machinery in tomato that is more complex than currently anticipated

Genome-wide mRNA expression analysis of hepatic adaptation to high-fat diets reveals switch from an inflammatory to steatotic transcriptional program

Background: Excessive exposure to dietary fats is an important factor in the initiation of obesity and metabolic syndrome associated pathologies. The cellular processes associated with the onset and progression of diet-induced metabolic syndrome are insufficiently understood. Principal Findings: To identify the mechanisms underlying the pathological changes associated with short and long-term exposure to excess dietary fat, hepatic gene expression of ApoE3Leiden mice fed chow and two types of high-fat (HF) diets was monitored using microarrays during a 16-week period. A functional characterization of 1663 HF-responsive genes reveals perturbations in lipid, cholesterol and oxidative metabolism, immune and inflammatory responses and stress-related pathways. The major changes in gene expression take place during the early (day 3) and late (week 12) phases of HF feeding. This is also associated with characteristic opposite regulation of many HF-affected pathways between these two phases. The most prominent switch occurs in the expression of inflammatory/immune pathways (early activation, late repression) and lipogenic/adipogenic pathways (early repression, late activation). Transcriptional network analysis identifies NF-κB, NEMO, Akt, PPARγ and SREBP1 as the key controllers of these processes and suggests that direct regulatory interactions between these factors may govern the transition from early (stressed, inflammatory) to late (pathological, steatotic) hepatic adaptation to HF feeding. This transition observed by hepatic gene expression analysis is confirmed by expression of inflammatory proteins in plasma and the late increase in hepatic triglyceride content. In addition, the genes most predictive of fat accumulation in liver during 16-week high-fat feeding period are uncovered by regression analysis of hepatic gene expression and triglyceride levels. Conclusions: The transition from an inflammatory to a steatotic transcriptional program, possibly driven by the reciprocal activation of NF-κB and PPARγ regulators, emerges as the principal signature of the hepatic adaptation to excess dietary fat. These findings may be of essential interest for devising new strategies aiming to prevent the progression of high-fat diet induced pathologies. © 2009 Radonjic et al