Dissecting quantitative trait variation in the resequencing era: complementarity of bi-parental, multi-parental and association panels

Abstract

Quantitative trait loci (QTL) have been identified using traditional linkage mapping and positional cloning identified several QTLs. However linkage mapping is limited to the analysis of traits differing between two lines and the impact of the genetic background on QTL effect has been underlined. Genome-wide association studies (GWAs) were proposed to circumvent these limitations. In tomato, we have shown that GWAs is possible, using the admixed nature of cherry tomato genomes that reduces the impact of population structure. Nevertheless, GWAs success might be limited due to the low decay of linkage disequilibrium, which varies along the genome in this species. Multi-parent advanced generation intercross (MAGIC) populations offer an alternative to traditional linkage and GWAs by increasing the precision of QTL mapping. We have developed a MAGIC population by crossing eight tomato lines whose genomes were resequenced. We showed the potential of the MAGIC population when coupled with whole genome sequencing to detect candidate single nucleotide polymorphisms (SNPs) underlying the QTLs. QTLs for fruit quality traits were mapped and related to the variations detected at the genome sequence and expression levels. The advantages and limitations of the three types of population, in the context of the available genome sequence and resequencing facilities, are discussed.

Association mapping reveals the genetic architecture of tomato response to water deficit: focus on major fruit quality traits

“…Ten QTLs co-localized with loci identified in the RILs (Albert et al , 2016, control and drought conditions) and/or in the three tomato population analyzed by Pascual et al (2016) (RIL, GWA, and MAGIC, control conditions) but for which no candidate gene was proposed until now, while six were present in genomic regions where, to the best of our knowledge, no QTLs for related traits were mapped thus far. In the intervals of four of them, controlling vitamin C and fructose content in a drought-specific manner (‘ VitCDM.Avi_1.1 ’, ‘ FructoseDM.Avi_4.1 ’, and ‘ FructoseDM.Avi_10.1 ’), three genes coding for ‘ chaperone proteins dnaJ ’ were identified (Solyc01g105340, Solyc04g009770, and Solyc10g078560; Table 4).…”

“…With the availability of a high-throughput genotyping assay, this classification can be considered in crop species via conventional linkage mapping (Malosetti et al , 2007; Verbyla et al , 2014) as well as genome-wide association studies (GWASs) (Korte et al , 2012; Saïdou et al , 2014). A GWAS has the advantage over linkage mapping that it allows exploration of the genetic diversity and the numerous recombination events present in germplasm collections and may lead to higher resolution mapping if the LD (linkage disequilibrium) is low enough in the population (Brachi et al , 2010; Korte and Farlow, 2013; El-Soda et al , 2015; Pascual et al , 2016). …”

Model-Assisted Estimation of the Genetic Variability in Physiological Parameters Related to Tomato Fruit Growth under Contrasted Water Conditions

“…QTLs detected for nuM and axis 2 (related to sugar active uptake) did not colocalize with any QTL identified in Albert et al (2016). However, QTL for soluble solid content were identified in this genomic region in other tomato populations (Pascual et al, 2016). Finally, the QTLs for lp and lx on top of chromosome 8 colocalized with QTLs for flowering time (Flw, specific to WD condition), fruit pH (specific to WD condition), vitamin C content in fruit on a fresh weight and on a dry weight basis (WD specific and constitutive, respectively) and yield (with changing effect according to the watering regime).…”

“…When distributions were skewed, the best corrections for normality were applied: LOG10(nuM); $\sqrt{tstar}$; LOG10(lp1); LOG10(lx); LOG10(lx1); 1/rxp. The QTL detection was performed as presented in Albert et al (2016) using the genetic map developed by Pascual et al (2016) which included 501 SNP markers covering 80% of the tomato genome. Briefly, the simple interval parametric mapping model (Lander and Botstein, 1989) based on the EM algorithm method implemented in the R/QTL package (Broman et al, 2003) was used.…”

Genetics and Genomics of Cultivated Eggplants and Wild Relatives

“…However, RILs carry on average 50% of the wild parent, which in most cases are unsuitable for commercial breeding programs without a pre-breeding pipeline in place. An alternative to the backcross method is to develop multi-parental populations, such as multi-parent advanced generation inter-cross (MAGIC), which consist of multi-parent RIL populations (Cavanagh et al, 2008;Pascual et al, 2016 One of the main challenges to the development and use of introgressiomics populations is linkage drag, based on reduced recombination at introgressed fragments (Tanksley and Nelson, 1996;Wendler et al, 2015). The use of molecular markers allows selecting individuals carrying recombined introgressed fragments (Alkeesh et al, 2013).…”