Quantitative trait loci detection of E dwardsiella tarda resistance in Japanese flounder Paralichthys olivaceus using bulked segregant analysis

In recent years, Edwardsiella tarda has become one of the most deadly pathogens of Japanese fl ounder( Paralichthys olivaceus), causing serious annual losses in commercial production. In contrast to the rapid advances in the aquaculture of P. o livaceus, the study of E. tarda resistance-related markers has lagged behind, hindering the development of a disease-resistant strain. Thus, a marker-trait association analysis was initiated, combining bulked segregant analysis(BSA) and quantitative trait loci(QTL) mapping. Based on 180 microsatellite loci across all chromosomes, 106 individuals from the F1333(♀: F0768 ×♂: F0915)(Nomenclature rule: F+year+family number) were used to detect simple sequence repeats(SSRs) and QTLs associated with E. tarda resistance. After a genomic scan, three markers(Scaffold 404-21589, Scaffold 404-21594 and Scaffold 270-13812) from the same linkage group(LG)-1 exhibited a signifi cant difference between DNA, pooled/bulked from the resistant and susceptible groups( P <0.001). Therefore, 106 individuals were genotyped using all the SSR markers in LG1 by single marker analysis. Two different analytical models were then employed to detect SSR markers with different levels of signifi cance in LG1, where 17 and 18 SSR markers were identifi ed, respectively. Each model found three resistance-related QTLs by composite interval mapping(CIM). These six QTLs, designated q E1–6, explained 16.0%–89.5% of the phenotypic variance. Two of the QTLs, q E-2 and q E-4, were located at the 66.7 c M region, which was considered a major candidate region for E. tarda resistance. This study will provide valuable data for further investigations of E. tarda resistance genes and facilitate the selective breeding of disease-resistant Japanese fl ounder in the future.

Identification of quantitative trait loci and epistasis for root characteristics and root exudations in maize (Zea mays L.) under deficient phosphorus

The phosphorus uptake （PU） in above-ground parts of plant, root characteristics and root exudations as well as the quantitative trait loci （QTLs） associated with these characteristics were determined for a F2：3 population derived from the cross of two contrasting maize （Zea mays L.） genotypes, 082 and Yel07. A total of 241 F2：3 families were evaluated in replicated trials under deficient phosphorus conditions in 2007 at two sites （Kaixian County and Southwest University, Chongqing, P. R. China）. The results show pleiotropy and close linkage among QTLs. Four common regions in different environments were in bnlg100- bnlg1268b （bins 1.02） for QTL of H＋, bnlg1268a-umc1290a （bins 1.09） for QTL of AP （acid phospbatase activity）, dupssrl5- P 1MT/a （bins 6.06） for QTLs of PU （phosphorus uptake） and RW （root weight）, and P IM3/d-P1M3/g （bins9.04） for QTLs of PU and AP. These QTLs are non-environment or minor QTLs x environment. By epistatic analysis, three main QTLs and eighteen QTLs x QTLs interactions were detected for the seven measured characteristics. These QTLs may affect trait expression by epistatic interaction with the other loci, and make a substantial contribution to phosphorus utilization efficiency, which should be considered when breeding maize varieties with high P efficiency. Two regions were detected in dupssrl 5- P1MT/a （bins 6.06） for QTL of RW and P1M3/d- P 1M3/g （bins 9.04） for QTL of PU and AP. They were detected in two different environments and by two methods of QTL analysis, which were useful for marker-assisted selection.

QTL analysis for some quantitative traits in bread wheat

Quantitative trait loci (QTL) analysis was conducted in bread wheat for 14 important traits utilizing data from four different mapping populations involving different approaches of QTL analysis. Analysis for grain protein content (GPC) sug- gested that the major part of genetic variation for this trait is due to environmental interactions. In contrast, pre-harvest sprouting tolerance (PHST) was controlled mainly by main effect QTL (M-QTL) with very little genetic variation due to environmental interactions; a major QTL for PHST was detected on chromosome arm 3AL. For grain weight, one QTL each was detected on chromosome arms 1AS, 2BS and 7AS. QTL for 4 growth related traits taken together detected by different methods ranged from 37 to 40; nine QTL that were detected by single-locus as well as two-locus analyses were all M-QTL. Similarly, single-locus and two-locus QTL analyses for seven yield and yield contributing traits in two populations respectively allowed detection of 25 and 50 QTL by composite interval mapping (CIM), 16 and 25 QTL by multiple-trait composite interval mapping (MCIM) and 38 and 37 QTL by two-locus analyses. These studies should prove useful in QTL cloning and wheat improvement through marker aided selection.

Methods for Population-Based eQTL Analysis in Human Genetics

Gene expression is a critical process in biological system that is influenced and modulated by many factors including genetic variation. Expression Quantitative Trait Loci（e QTL） analysis provides a powerful way to understand how genetic variants affect gene expression. For genome wide e QTL analysis, the number of genetic variants and that of genes are large and thus the search space is tremendous. Therefore, e QTL analysis brings about computational and statistical challenges. In this paper, we provide a comprehensive review of recent advances in methods for e QTL analysis in population-based studies. We first present traditional pairwise association methods, which are widely used in human genetics. To account for expression heterogeneity, we investigate the methods for correcting confounding factors. Next, we discuss newly developed statistical learning methods including Lasso-based models. In the conclusion, we provide an overview of future method development in analyzing e QTL associations. Although we focus on human genetics in this review, the methods are applicable to many other organisms.