ExtremeQTLmapping of germination speed inArabidopsis thaliana

Abstract

Seed germination is a key life history transition for annual plants and partly determines lifetime performance and fitness. Germination speed, the elapsed time for a nondormant seed to germinate, is a poorly understood trait important for plants' competitiveness and fitness in fluctuating environments. Germination speed varied by 30% among 18 Arabidopsis thaliana populations measured, and exhibited weak negative correlation with flowering time and seed weight, with significant genotype effect (P < 0.005). To dissect the genetic architecture of germination speed, we developed the extreme QTL (X-QTL) mapping method in A. thaliana. The method has been shown in yeast to increase QTL mapping power by integrating selective screening and bulk-segregant analysis in a very large mapping population. By pooled genotyping of top 5% of rapid germinants from ~100 000 F3 individuals, three X-QTL regions were identified on chromosomes 1, 3 and 4. All regions were confirmed as QTL regions by sequencing 192 rapid germinants from an independent F3 selection experiment. Positional overlaps were found between X-QTLs and previously identified seed, life history and fitness QTLs. Our method provides a rapid mapping platform in A. thaliana with potentially greater power. One can also relate identified X-QTLs to the A. thaliana physical map, facilitating candidate gene identification.

Genetic dissection of seed oil and protein content and identification of networks associated with oil content in Brassica napus

“…A large number of AGRs were identified rapidly, and significant AGRs with a high Δ (SNP-index) were consistent with the SOC-QTL hotspots, confirming the accuracy of the QTL mapping based on the present map. In addition, we found that highly significant AGRs were subdivided into multiple QTLs (Table S6) rather than being subdivided or narrowed QTLs as previously reported34354849. These results suggested that the present high-density linkage map had sufficiently high resolution to dissect genetic variation in primary mapping populations.…”

Evolutionary and ecological functional genomics, from lab to the wild

“…A method termed as extreme QTL (X‐QTL) mapping was developed in yeast that promised a higher resolution and rapid mapping (Ehrenreich et al ., ). This has been used in mapping seed size (Guo et al ., ), germination features (Yuan et al ., ) salt tolerance (Guo et al ., ; Yuan et al ., ; Figure ) in A. thaliana . X‐QTL mapping continues to hold some promise, although it is likely to be more important for species with high recombination rates.…”

“… An illustrated comparison of selected linkage mapping approaches for finding associations between genotype, phenotype and environment. Stylized and re‐drawn workflow methods for (a) extreme quantitative trait loci (X‐QTL) mapping (Yuan et al ., ,), (b) genome‐wide association study (GWAS; Atwell et al ., ) and (c) nested association mapping (NAM; Buckler et al ., ), which exemplify strengths and weaknesses of these specific linkage mapping approaches. …”

QTG-Finder: a machine-learning based algorithm to prioritize causal genes of quantitative trait loci

“…For literature validation, a separate set of nine casual genes was used for each species. It 392 includes causal genes that have been cloned or indicated by joint linkage-association analysis or 393 indicated by mutant analysis (Chardon et al, 2013;Fan et al, 2016;Fukuoka et al, 2014;Gao et 394 al., 2016;Guo et al, 2015;Hu et al, 2008;Huang et al, 2012;Liu et al, 2017;Motte et al, 395 2014;Oikawa et al, 2015;Qi et al, 2008;Sharma et al, 2005;Yuan et al, 2016;Zeng et al, 396…”