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.     

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.     

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.

     

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 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.     

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 fruit-related traits in pepper (Capsicum annuum)

QTL analysis of pepper fruit characters was performed in an F₃ population derived from a cross between two Capsicum annuum genotypes, the bell-type cultivar Maor and the Indian small-fruited line Perennial. RFLP, AFLP^®1, RAPD and morphological markers (a total of 177) were used to construct a comparative pepper-tomato genetic map for this cross, and 14 quantitatively inherited traits were evaluated in 180 F₃ families. A total of 55 QTL were identified by interval analysis using LOD 3.0 as the threshold for QTL detection. QTL for several traits including fruit diameter and weight, pericarp thickness and pedicel diameter were often located in similar chromosomal regions, thus reflecting high genetic correlations among these traits. A major QTL that accounts for more than 60% of the phenotypic variation for fruit shape (ratio of fruit length to fruit diameter) was detected in chromosome 3. This chromosome also contained QTL for most of the traits scored in the population. Markers in linkage groups 2, 3, 8 and 10 were associated with QTL for multiple traits, thereby suggesting their importance as loci that control developmental processes in pepper. Several QTL in pepper appeared to correspond to positions in tomato for loci controlling the same traits, suggesting the hypothesis that these QTL may be orthologous in the two species.     

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.     

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.     

QTL mapping for nitrogen-use efficiency and nitrogen-deficiency tolerance traits in rice

Plant and Soil - The improvement of nitrogen-deficiency tolerance (NDT) and nitrogen-use efficiency (NUE) traits is an important objective of many rice breeding programs. A better understanding of...     

QTL mapping for traits associated with stress neuroendocrine reactivity in rats

In the present study we searched for quantitative trait loci (QTLs) that affect neuroendocrine stress responses in a 20-min restraint stress paradigm using Brown–Norway (BN) and Wistar–Kyoto–Hyperactive (WKHA) rats. These strains differed in their hypothalamic–pituitary–adrenal axis (plasma ACTH and corticosterone levels, thymus, and adrenal weights) and in their renin–angiotensin–aldosterone system reactivity (plasma renin activity, aldosterone concentration). We performed a whole-genome scan on a F₂ progeny derived from a WKHA × BN intercross, which led to the identification of several QTLs linked to plasma renin activity (Sr6, Sr8, Sr11, and Sr12 on chromosomes RNO2, 3, 19, and 8, respectively), plasma aldosterone concentration (Sr7 and Sr9 on RNO2 and 5, respectively), and thymus weight (Sr10, Sr13, and Srl4 on RNO5, 10, and 16, respectively). The type 1b angiotensin II receptor gene (Agtrlb) maps within the confidence intervals of QTLs on RNO2 linked to plasma renin activity (Sr6, highly significant; LOD = 5.0) and to plasma aldosterone level (Sr7, suggestive; LOD = 2.0). In vitro studies of angiotensin II–induced release of aldosterone by adrenal glomerulosa cells revealed a lower receptor potency (log EC₅₀ = −8.16 ± 0.11 M) and efficiency (E_max = 453.3 ± 25.9 pg/3 × 10⁴ cells/24 h) in BN than in WKHA (log EC₅₀ = −10.66 ± 0.18 M; E_max = 573.1 ± 15.3 pg/3 × 10⁴ cells/24 h). Moreover, differences in Agtr1b mRNA abundance and sequence reinforce the putative role of the Agtr1b gene in the differential plasma renin stress reactivity between the two rat strains.     

QTL mapping for sexually dimorphic fitness-related traits in wild bighorn sheep

Dissecting the genetic architecture of fitness-related traits in wild populations is key to understanding evolution and the mechanisms maintaining adaptive genetic variation. We took advantage of a recently developed genetic linkage map and phenotypic information from wild pedigreed individuals from Ram Mountain, Alberta, Canada, to study the genetic architecture of ecologically important traits (horn volume, length, base circumference and body mass) in bighorn sheep. In addition to estimating sex-specific and cross-sex quantitative genetic parameters, we tested for the presence of quantitative trait loci (QTLs), colocalization of QTLs between bighorn sheep and domestic sheep, and sex × QTL interactions. All traits showed significant additive genetic variance and genetic correlations tended to be positive. Linkage analysis based on 241 microsatellite loci typed in 310 pedigreed animals resulted in no significant and five suggestive QTLs (four for horn dimension on chromosomes 1, 18 and 23, and one for body mass on chromosome 26) using genome-wide significance thresholds (Logarithm of odds (LOD) >3.31 and >1.88, respectively). We also confirmed the presence of a horn dimension QTL in bighorn sheep at the only position known to contain a similar QTL in domestic sheep (on chromosome 10 near the horns locus; nominal P<0.01) and highlighted a number of regions potentially containing weight-related QTLs in both species. As expected for sexually dimorphic traits involved in male-male combat, loci with sex-specific effects were detected. This study lays the foundation for future work on adaptive genetic variation and the evolutionary dynamics of sexually dimorphic traits in bighorn sheep.     

QTL mapping for yield and yield contributing traits in two mapping populations of bread wheat

In bread wheat, single-locus and two-locus QTL analyses were conducted for seven yield and yield contributing traits using two different mapping populations (P I and P II). Single-locus QTL analyses involved composite interval mapping (CIM) for individual traits and multiple-trait composite interval mapping (MCIM) for correlated yield traits to detect the pleiotropic QTLs. Two-locus analyses were conducted to detect main effect QTLs (M-QTLs), epistatic QTLs (E-QTLs) and QTL × environment interactions (QE and QQE). Only a solitary QTL for spikelets per spike was common between the above two populations. HomoeoQTLs were also detected, suggesting the presence of triplicate QTLs in bread wheat. Relatively fewer QTLs were detected in P I than in P II. This may be partly due to low density of marker loci on P I framework map (173) than in P II (521) and partly due to more divergent parents used for developing P II. Six QTLs were important which were pleiotropic/coincident involving more than one trait and were also consistent over environments. These QTLs could be utilized efficiently for marker assisted selection (MAS).