Genome-wide association mapping of yield components and drought tolerance-related traits in cotton

Drought causes serious yield losses in cotton production throughout the world. Association mapping allows identification and localization of the genes controlling drought-related traits which will be helpful in cotton breeding. In the present study, genetic diversity analysis and association mapping of yield and drought traits were performed on a panel of 99 upland cotton genotypes using 177 SSR (simple sequence repeat) markers. Yield parameters and drought tolerance-related traits were evaluated for two seasons under two watering regimes: water-stressed and well-watered. The traits included seed cotton yield (SCY), lint yield (LY), lint percentage (LP), water-use efficiency (WUE), yield potential (YP), yield reduction (YR), yield index (YI), drought sensitivity index (DSI), stress tolerance index (STI), harmonic mean (HM), and geometric mean productivity (GMP). The genotypes with the least change in seed cotton yield under drought stress were Zeta 2, Delcerro, Nazilli 87, and DAK 66/3 which were also the most water-use efficient cultivars. The average genetic diversity of the panel was 0.38. The linkage disequilibrium decayed relatively rapidly at 20–30 cM (r²?≥?0.5). We identified 30 different SSR markers associated with the traits. Fifteen and 23 SSR markers were linked to the traits under well-watered and water-stress conditions, respectively. To our knowledge, most of these quantitative yield and drought tolerance-associated loci were newly identified. The genetic diversity and association mapping results should facilitate the development of drought-tolerant cotton lines with high yield in molecular breeding programs.     

Mapping QTL controlling maize deep-seeding tolerance-related traits and confirmation of a major QTL for mesocotyl length

Deep-seeding tolerant seeds can emerge from deep soil where the moisture is suitable for seed germination. Breeding deep-seeding tolerant cultivars is becoming increasingly important in arid and semi-arid regions. To dissect the quantitative trait loci (QTL) controlling deep-seeding tolerance traits, we selected a tolerant maize inbred line 3681-4 and crossed it with the elite inbred line-X178 to generate an F₂ population and the derivative F_2:3 families. A molecular linkage map composed of 179 molecular markers was constructed, and 25 QTL were detected including 10 QTL for sowing at 10 cm depth and 15 QTL for sowing at 20 cm depth. The QTL analysis results confirmed that deep-seeding tolerance was mainly caused by mesocotyl elongation and also revealed considerable overlap among QTL for different traits. To confirm a major QTL on chromosome 10 for mesocotyl length measured at 20 cm depth, we selected and self-pollinated a BC₃F₂ plant that was heterozygous at the markers around the target QTL and homozygous at other QTL to generate a BC₃F₃ population. We found that this QTL explained more phenotypic variance in the BC₃F₃ population than that in the F₂ population, which laid the foundation for fine mapping and NIL (near-isogenic line) construction.     

Multi-trait QTL mapping in barley using multivariate regression

Many studies of QTL locations record several different traits on the same population, but most analyses look at this information on a trait-by-trait basis. In this paper we show how the regression approach to QTL mapping of Haley & Knott (1992) may be extended to a multi-trait analysis via multivariate regression, easily programmed in statistical packages. A procedure for identifying QTL locations using forward selection and bootstrapping is proposed. The method is applied to examine the locations for QTLs for six yield characters (the number of fertile stems, the grain number of the main stem, the main stem grain weight, the single plant yield, the plot yield and the thousand grain weight) in a doubled haploid population of spring barley. Several chromosomal locations with effects on more than one trait are found. The method is also suitable for examining a single trait measured in different years or environments, and is used here to examine data on heading date, a highly heritable trait, and plot yield, a trait with moderate heritability and showing QTL-environment interactions.     

QTL mapping under truncation selection in homozygous lines derived from biparental crosses

In plant breeding, a large number of progenies that will be discarded later in the breeding process must be phenotyped and marker genotyped for conducting QTL analysis. In many cases, phenotypic preselection of lines could be useful. However, in QTL analyses even moderate preselection can have a significant effect on the power of QTL detection and estimation of effects of the target traits. In this study, we provide exact formulas for quantifying the change of allele frequencies within marker classes, expectations of marker contrasts and the variance of the marker contrasts under truncation selection, for the general case of two QTL affecting the target trait and a correlated trait. We focused on homozygous lines derived at random from biparental crosses. The effects of linkage between the marker and the QTL under selection as well as the effect of selection on a correlated trait can be quantified with the given formulas. Theoretical results clearly show that depending on the magnitude of QTL effects, high selection intensities can lead to a dramatic reduction in power of QTL detection and that approximations based on the infinitesimal model deviate substantially from exact solutions. The presented formulas are valuable for choosing appropriate selection intensity when performing QTL mapping experiments on the data on phenotypically preselected traits and enable the calculation and bias correction of the effects of QTL under selection. Application of our theory to experimental data revealed that selection-induced bias of QTL effects can be successfully corrected.     

Fine mapping a domestication-related QTL for spike-related traits in a synthetic wheat

QTL analysis using a BC5F2:3 mapping population derived from a cross between Am3, a synthetic hexaploid wheat as a donor parent, and Laizhou953, a Chinese winter wheat cultivar as a recurrent parent, showed that variation at the microsatellite locus Xgwm113 on chromosome 4B was associated with variation in grain number per spike (GN), spike length (SL), and spikelet number per spike (SPI). The Qgn.caas-4B, Qsl.caas-4B, and Qspi.caas-4B were responsible for 16.6%-35.6%, 18.0%-32.3%, and 23.7%-25.9% of the phenotypic variation present in two environments, respectively. Segregation for GN fit a Mendelian monogenic ratio. A subpopulation consisting of 497 plants was used to map the QTL to a 1.2?cM interval between Xgwm113 and Xgwm857. The three spike traits, GN, SL, and SPI, were correlated and were thus probably under the pleiotropic control of the QTL. The Am3 allele had a reduction effect on all three spike traits. Evidence for positive selective history on SSR locus Xgwm113 was supported using Ewens-Watterson's statistic test on a germplasm panel of wild and landrace entries, suggesting that this genomic region may contain genes under selection during wheat domestication.     

On the use of mathematically-derived traits in QTL mapping

Mathematically-derived traits from two or more component traits, either by addition, subtraction, multiplication, or division, have been frequently used in genetics and breeding. When used in quantitative trait locus (QTL) mapping, derived traits sometimes show discrepancy with QTL identified for the component traits. We used three QTL distributions and three genetic effects models, and an actual maize mapping population, to investigate the efficiency of using derived traits in QTL mapping, and to understand the genetic and biological basis of derived-only QTL, i.e., QTL identified for a derived trait but not for any component trait. Results indicated that the detection power of the four putative QTL was consistently greater than 90% for component traits in simulated populations, each consisting of 200 recombinant inbred lines. Lower detection power and higher false discovery rate (FDR) were observed when derived traits were used. In an actual maize population, simulations were designed based on the observed QTL distributions and effects. When derived traits were used, QTL detected for both component and derived traits had comparable power, but those detected for component traits but not for derived traits had low detection power. The FDR from subtraction and division in the maize population were higher than the FDR from addition and multiplication. The use of derived traits increased the gene number, caused higher-order gene interactions than observed in component traits, and possibly complicated the linkage relationship between QTL as well. The increased complexity of the genetic architecture with derived traits may be responsible for the reduced detection power and the increased FDR. Derived-only QTL identified in practical genetic populations can be explained either as minor QTL that are not significant in QTL mapping of component traits, or as false positives.     

橡胶树与胶乳产量相关性状的QTL定位

对橡胶树株产干胶等与胶乳产量相关性状进行了QTL分析。以热研88-13×IAN873杂交授粉子代F1群体为材料,测定其株产干胶、干胶含量、乳管列数、乳管个数和乳管大小等与橡胶树胶乳产量相关的性状,利用FsQtlMap 1.0软件,复合区间作图法(CIM,composite interval mapping),以已构建的SSR连锁图谱为基础进行QTL分析。结果显示,各性状偏度和峰度符合正态分布,除乳管大小外,各性状的平均值和方差有较大变化;株产干胶的变异系数最大,各因子的变异系数顺序为株产干胶>乳管个数>乳管列数>乳管大小>干胶含量;LOD阈值大于2.5,检测到与株产干胶相关的QTL 5个,分别可解释71.3%、69.1%、68.3%、64.4%和62.9%的群体变异,与乳管大小相关的QTL 3个,分别可解释84.5%、81.3%和15.4%的群体变异,未检测到与其他性状相关的QTL。     

Genes mapping to boron tolerance QTL in barley identified by suppression subtractive hybridization

Boron tolerance is a quantitative trait controlled by multiple genes. Suppression subtractive hybridization was carried out on root cDNA from bulked boron tolerant and intolerant doubled haploid barley lines grown under moderate boron stress to identify genes associated with boron tolerance. One hundred and eleven clones representing known proteins were found to be up‐regulated in the tolerant bulk upon boron stress. Nine clones were genetically mapped to previously reported boron tolerance QTL. These include a clone identical to the boron transporter gene Bot1 and a clone coding for a bromo‐adjacent homology domain‐containing protein, mapping to the 6H boron tolerance locus and co‐segregating with reduced boron intake in a Clipper × Sahara‐3771 mapping population. A third clone mapping to the 2H QTL region encoding an S‐adenosylmethionine decarboxylase precursor was found to provide tolerance to high boron by heterologous expression. Yeast cells expressing Sahara SAMDC were able to grow on 15 mm boron solid media and maintained cellular boron concentrations at 13% lower than control cells expressing empty vector. The data suggest that an antioxidative response mechanism involving polyamines and the ascorbate–glutathione pathway in Sahara barley may provide an advantage in tolerating high soil concentrations of boron.     

Using QTL mapping to investigate the relationships between abiotic stress tolerance (drought and salinity) and agronomic and physiological traits

Background

Drought and salinity are two major abiotic stresses that severely limit barley production worldwide. Physiological and genetic complexity of these tolerance traits has significantly slowed the progress of developing stress-tolerant cultivars. Marker-assisted selection (MAS) may potentially overcome this problem. In the current research, seventy two double haploid (DH) lines from a cross between TX9425 (a Chinese landrace variety with superior drought and salinity tolerance) and a sensitive variety, Franklin were used to identify quantitative trait loci (QTL) for drought and salinity tolerance, based on a range of developmental and physiological traits.

Results

Two QTL for drought tolerance (leaf wilting under drought stress) and one QTL for salinity tolerance (plant survival under salt stress) were identified from this population. The QTL on 2H for drought tolerance determined 42% of phenotypic variation, based on three independent experiments. This QTL was closely linked with a gene controlling ear emergency. The QTL on 5H for drought tolerance was less affected by agronomic traits and can be effectively used in breeding programs. A candidate gene for this QTL on 5H was identified based on the draft barley genome sequence. The QTL for proline accumulation, under both drought and salinity stresses, were located on different positions to those for drought and salinity tolerance, indicating no relationship with plant tolerance to either of these stresses.

Conclusions

Using QTL mapping, the relationships between QTL for agronomic and physiological traits and plant drought and salinity tolerance were studied. A new QTL for drought tolerance which was not linked to any of the studied traits was identified. This QTL can be effectively used in breeding programs. It was also shown that proline accumulation under stresses was not necessarily linked with drought or salinity tolerance based on methods of phenotyping used in this experiment. The use of proline content in breeding programs can also be limited by the accuracy of phenotyping.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1243-8) contains supplementary material, which is available to authorized users.     

QTL mapping of root traits in phosphorus-deficient soils reveals important genomic regions for improving NDVI and grain yield in barley

Key message

Major QTLs for root rhizosheath size are not correlated with grain yield or yield response to phosphorus. Important QTLs were found to improve phosphorus efficiency.

Abstract

Root traits are important for phosphorus (P) acquisition, but they are often difficult to characterize and their breeding values are seldom assessed under field conditions. This has shed doubts on using seedling-based criteria of root traits to select and breed for P efficiency. Eight root traits were assessed under controlled conditions in a barley doubled-haploid population in soils differing in P levels. The population was also phenotyped for grain yield, normalized difference vegetation index (NDVI), grain P uptake and P utilization efficiency at maturity (PutE_GY) under field conditions. Several quantitative traits loci (QTLs) from the root screening and the field trials were co-incident. QTLs for root rhizosheath size and root diameter explained the highest phenotypic variation in comparison to QTLs for other root traits. Shared QTLs were found between root diameter and grain yield, and total root length and PutE_GY. A common major QTL for rhizosheath size and NDVI was mapped to the HvMATE gene marker on chromosome 4H. Collocations between major QTLs for NDVI and grain yield were detected on chromosomes 6H and 7H. When results from BIP and MET were combined, QTLs detected for grain yield were also those QTLs found for NDVI. QTLs qGY5H, qGY6H and qGY7Hb on 7H were robust QTLs in improving P efficiency. A selection of multiple loci may be needed to optimize the breeding outcomes due to the QTL x Environment interaction. We suggest that rhizosheath size alone is not a reliable trait to predict P efficiency or grain yield.

     

QTL mapping and epistasis analysis of brace root traits in maize

Root architecture is a major factor influencing root lodging, which limits greater yield stability at high planting density. Total brace root tier number (TBRTN) and effective brace root tier number (EBRTN) are the two most important root architecture traits influencing root lodging. However, the genetic mechanisms that underlie these traits remain poorly understood. In this study, quantitative trait loci (QTL) for TBRTN and EBRTN were mapped using a set of 201 recombinant inbred lines (RILs) and 278 immortalized F2 (IF2) populations derived from these RILs, which were evaluated in three environments. Ten QTL in the RILs and 15 QTL in the IF2 population were detected. In the two populations, we identified two coincident major QTL for TBRTN and a single identical major QTL for EBRTN. The QTL for TBRTN showed the largest additive effect, accounting for 16.36 and 17.88% of the phenotypic variance in the RILs and IF2 population, respectively. Additional epistatic effects were identified for all the maize chromosomes, except for chromosome 4. Most epistatic effects involved pairs of loci that were on different chromosomes. At the same time, we found loci that interacted simultaneously with several other loci to affect expression of the traits, which was particularly evident in the IF2 population. For example, qTAR1-2 interacted simultaneously with qTAR2-1, qTAR3-1, qTAR5-1, and qITAR8-2 to affect the expression of TBRTN. Therefore, a complex network controlling the traits was found in maize. These results provide useful information for understanding the molecular mechanisms controlling root architecture.     

Genetic dissection of floral traits in anemone-type chrysanthemum by QTL mapping

Brassica oleracea comprises several important subspecies, including cabbage, broccoli, cauliflower, Chinese kale, and kohlrabi. The petal color of Chinese kale is mostly white and sometimes yellow. To explore the genetic basis of petal color variation in Chinese kale, F₂ and BC₁ (backcross) populations were constructed from the cross of two inbred lines, 2114 (yellow petal) and 2116 (white petal). Genetic analysis of the F₂ and BC₁ populations demonstrated that yellow petal color was controlled by a single recessive nuclear gene, termed cpc-2. Insertion-deletion (InDel) markers, designed based on the parental resequencing data, were used to map cpc-2. The fine mapping results indicated that the cpc-2 gene was located in a 569-kb interval on chromosome C03 flanked by InDel markers ZB636 and ZB692, with genetic distances of 0.3 cM and 0.6 cM, respectively. By analyzing the nucleotide variations and annotations of the genes in this interval, a CCD4 family gene was predicted to be a candidate for cpc-2 and renamed BoCCD4.2. In addition, insertion of the CACTA-like transposable element (TE3) interrupted the function of the BoCCD4 gene, which may have resulted in the loss of function of BoCCD4 and the petal color transition from white to yellow. The TE3 insertion in the BoCCD4 gene was also present in 63 cabbage inbred lines among 159 accessions, which revealed that the TE3-type null allele of BoCCD4 formed before the divergence of the two subspecies cabbage and Chinese kale and that Chinese kale evolved much earlier than cabbage. This study lays the foundation for cloning BoCCD4.2 and revealing the molecular mechanism underlying petal color formation in Chinese kale.

     

QTL mapping of complex binary traits in an advanced intercross line

An advanced intercross line (AIL) is an easier and more cost-effective approach compared to recombinant inbred lines for fine mapping of quantitative trait loci (QTL) identified by F(2) designs. In an AIL, a complex binary trait can be mapped through analysis of either continuously distributed proxy traits for the liability of the binary trait or the liability itself, the latter presenting the greater statistical challenge. In another work, we successfully applied both approaches in an AIL to fine map previously identified QTL underlying anatomical parameters of the cardiac inter-atrial septum including patent foramen ovale. Here, we describe the statistical methods that we used to analyse complex binary traits in our AIL design. This is achieved using a likelihood-based method, with the expectation-maximisation algorithm allowing use of standard logistic regression methods for model fitting.     

QTL mapping of domestication-related traits in soybean (Glycine max)

BACKGROUND AND AIMS: Understanding the genetic basis underlying domestication-related traits (DRTs) is important in order to use wild germplasm efficiently for improving yield, stress tolerance and quality of crops. This study was conducted to characterize the genetic basis of DRTs in soybean (Glycine max) using quantitative trait locus (QTL) mapping. METHODS: A population of 96 recombinant inbred lines derived from a cultivated (ssp. max) x wild (ssp. soja) cross was used for mapping and QTL analysis. Nine DRTs were examined in 2004 and 2005. A linkage map was constructed with 282 markers by the Kosambi function, and the QTL was detected by composite interval mapping. KEY RESULTS: The early flowering and determinate habit derived from the max parent were each controlled by one major QTL, corresponding to the major genes for maturity (e1) and determinate habit (dt1), respectively. There were only one or two significant QTLs for twinning habit, pod dehiscence, seed weight and hard seededness, which each accounted for approx. 20-50 % of the total variance. A comparison with the QTLs detected previously indicated that in pod dehiscence and hard seededness, at least one major QTL was common across different crosses, whereas no such consistent QTL existed for seed weight. CONCLUSIONS: Most of the DRTs in soybeans were conditioned by one or two major QTLs and a number of genotype-dependent minor QTLs. The common major QTLs identified in pod dehiscence and hard seededness may have been key loci in the domestication of soybean. The evolutionary changes toward larger seed may have occurred through the accumulation of minor changes at many QTLs. Since the major QTLs for DRTs were scattered across only six of the 20 linkage groups, and since the QTLs were not clustered, introgression of useful genes from wild to cultivated soybeans can be carried out without large obstacles.     

Association mapping of resistance to Puccinia hordei in Australian barley breeding germplasm

Key message

“To find stable resistance using association mapping tools, QTL with major and minor effects on leaf rust reactions were identified in barley breeding lines by assessing seedlings and adult plants.”

Abstract

Three hundred and sixty (360) elite barley (Hordeum vulgare L.) breeding lines from the Northern Region Barley Breeding Program in Australia were genotyped with 3,244 polymorphic diversity arrays technology markers and the results used to map quantitative trait loci (QTL) conferring a reaction to leaf rust (Puccinia hordei Otth). The F_3:5 (Stage 2) lines were derived or sourced from different geographic origins or hubs of international barley breeding ventures representing two breeding cycles (2009 and 2011 trials) and were evaluated across eight environments for infection type at both seedling and adult plant stages. Association mapping was performed using mean scores for disease reaction, accounting for family effects using the eigenvalues from a matrix of genotype correlations. In this study, 15 QTL were detected; 5 QTL co-located with catalogued leaf rust resistance genes (Rph1, Rph3/19, Rph8/14/15, Rph20, Rph21), 6 QTL aligned with previously reported genomic regions and 4 QTL (3 on chromosome 1H and 1 on 7H) were novel. The adult plant resistance gene Rph20 was identified across the majority of environments and pathotypes. The QTL detected in this study offer opportunities for breeding for more durable resistance to leaf rust through pyramiding multiple genomic regions via marker-assisted selection.