Genetic mapping of quantitative trait loci controlling fruit size and shape in papaya

Papaya (Carica papaya L.) is a pan-tropical tree that bears fruit exhibiting a wide range of size and shape. Depending on variety and environment, papaya fruit may weigh from 0.2 kg up to 10 kg. Papaya fruit shape is a sex-linked trait ranging from spherical to ovate, cylindrical or pyriform. An F2 mapping population, produced from a cross between the Thai variety Khaek Dum, bearing 1.2 kg, red-fleshed fruit, and variety 2H94, a Hawaii Solo type bearing a 0.2 kg, yellow-fleshed fruit, was used to identify quantitative trait loci (QTLs) that influence papaya fruit characters including weight, diameter, length and shape. Fruit phenotype data, collected from two subpopulations planted in successive growing seasons, showed striking differences by year indicating significant genotype × environment interactions. Fourteen QTL with phenotypic effects ranging from 5 to 23% were identified across six linkage groups (LGs) with clusters of two or more QTL on LGs 02, 03, 07 and 09. These loci contain homologs to the tomato fruit QTL ovate, sun and fw2.2 regulating fruit size and shape. The papaya fruit QTL provide a starting point for dissecting the genetic pathways leading to extreme fruit size and shape and may prove useful for papaya breeders attempting to tailor new varieties to specific consumer markets.     

Dynamic QTL analysis of linolenic acid content in different developmental stages of soybean seed

Linolenic acid (LN) in soybean (Glycine max L. Merr.) seed mainly contributes to the undesirable odors and flavors commonly associated with poor oil quality. LN deposition at various stages of soybean seed development had not been reported by 2010. The objects of this study were (1) to identify and measure quantitative trait loci (QTL) underlying LN content and (2) to estimate the QTL effects expressed from earlier seed developmental stages to drying seed of soybean. One hundred and twenty-five F_5:8 and F_5:9 recombinant inbred lines derived from the cross of soybean cultivars ‘Hefeng 25’ and ‘Dongnong L5’ were used for the identification of QTL underlying LN content from the 37 day (D) to 86D stages after flowering, at Harbin in 2008 and 2009. QTL × Environment interactions (QE) effects were evaluated using a mixed genetic model (Zhu in J Zhejiang Univ (Natural Science) 33:327–335, 1999). Twelve unconditional QTL and 12 conditional QTL associated with LN content were identified at different developmental stages. Most of the QTL explained <10% of phenotypic variation of LN content. Unconditional QTL QLNF-1, QLNC2-1, QLND1b-1, QLNA2-1 and QLNH-1 influenced LN content across different development stages and environments. Conditional QTL QLNF-1, QLNC2-1 and QLNH-1 were identified in multiple developmental stages and environments. Conditional and unconditional QTL clustered in neighboring intervals on linkage groups A2, C2 and D1b. Ten QTL with conditional additive main effects (a) and/or conditional additive × environment interaction effects (ae) at specific developmental stage were identified on nine linkage groups. Of them, six QTL only possessed additive main effects and seven QTL had significant ae effects in different developmental stages. A total of 13 epistatic pairwise QTL were identified by conditional mapping in different developmental stages. Two pairs of QTL only showed aa effects and five pairs of QTL only showed aae effects at different developmental stages. QTL with aa effects, as well as their environmental interaction effects, appeared to vary at different developmental stages.     

QTL and association analysis for skin and fibre pigmentation in sheep provides evidence of a major causative mutation and epistatic effects

The pursuits of white features and white fleeces free of pigmented fibre have been important selection objectives for many sheep breeds. The cause and inheritance of non‐white colour patterns in sheep has been studied since the early 19th century. Discovery of genetic causes, especially those which predispose pigmentation in white sheep, may lead to more accurate selection tools for improved apparel wool. This article describes an extended QTL study for 13 skin and fibre pigmentation traits in sheep. A total of 19 highly significant, 10 significant and seven suggestive QTL were identified in a QTL mapping experiment using an Awassi × Merino × Merino backcross sheep population. All QTL on chromosome 2 exceeded a LOD score of greater than 4 (range 4.4–30.1), giving very strong support for a major gene for pigmentation on this chromosome. Evidence of epistatic interactions was found for QTL for four traits on chromosomes 2 and 19. The ovine TYRP1 gene on OAR 2 was sequenced as a strong positional candidate gene. A highly significant association (P < 0.01) of grandparental haplotypes across nine segregating SNP/microsatellite markers including one non‐synonymous SNP with pigmentation traits could be shown. Up to 47% of the observed variation in pigmentation was accounted for by models using TYRP1 haplotypes and 83% for models with interactions between two QTL probabilities, offering scope for marker‐assisted selection for these traits.     

Mapping of quantitative trait loci for kernel row number in maize across seven environments

Genetic factors controlling quantitative inheritance of grain yield and its components have been intensively investigated during recent decades using diverse populations in maize (Zea mays L.). Notwithstanding this, quantitative trait loci (QTL) for kernel row number (KRN) with large and consistent effect have not been identified. In this study, a linkage map of 150 simple sequence repeat (SSR) loci was constructed by using a population of 500 F2 individuals derived from a cross between elite inbreds Ye478 and Dan340. The linkage map spanned a total of 1478 cM with an average interval of 10.0 cM. A total of 397 F2:3 lines were evaluated across seven diverse environments for mapping QTL for KRN. Some QTL for grain yield and its components had previously been confirmed with this population across environments. A total of 13 QTL for KRN were identified, with each QTL explaining from 3.0 to 17.9% of phenotypic variance. The gene action for KRN was mainly additive to partial dominance. A large-effect QTL (qkrn7) with partial dominance effect accounting for 17.9% of the phenotypic variation for KRN was identified on chromosome 7 near marker umc1865 with consistent gene effect across seven diverse environments. This study has laid a foundation for map-based cloning of this major QTL and for developing molecular markers for marker-assisted selection of high KRN.     

Maternal environment affects the genetic basis of seed dormancy in Arabidopsis thaliana

The genetic basis of seed dormancy, a key life history trait important for adaptive evolution in plant populations, has yet been studied only using seeds produced under controlled conditions in greenhouse environments. However, dormancy is strongly affected by maternal environmental conditions, and interactions between seed genotype and maternal environment have been reported. Consequently, the genetic basis of dormancy of seeds produced under natural field conditions remains unclear. We examined the effect of maternal environment on the genetic architecture of seed dormancy using a recombinant inbred line (RIL) population derived from a cross between two locally adapted populations of Arabidopsis thaliana from Italy and Sweden. We mapped quantitative trait loci (QTL) for dormancy of seeds produced in the greenhouse and at the native field sites of the parental genotypes. The Italian genotype produced seeds with stronger dormancy at fruit maturation than did the Swedish genotype in all three environments, and the maternal field environments induced higher dormancy levels compared to the greenhouse environment in both genotypes. Across the three maternal environments, a total of nine dormancy QTL were detected, three of which were only detected among seeds matured in the field, and six of which showed significant QTL × maternal environment interactions. One QTL had a large effect on dormancy across all three environments and colocalized with the candidate gene DOG1. Our results demonstrate the importance of studying the genetic basis of putatively adaptive traits under relevant conditions.     

Extreme QTL mapping of germination speed in Arabidopsis thaliana

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.     

QTL Analysis for Root Protein in a Backcross Family of Cassava Derived from Manihot esculenta ssp flabellifolia

Root protein content of elite cassava is very low, largely due to breeder’s selection for other agronomic traits mainly fresh weight yield and disease resistance. Increased protein content in the root of cassava will improve its usefulness as a more complete food source in the developing world. An inter-specific F₁ hybrid CW 198 - 11 was earlier developed at International Center for Tropical Agriculture (CIAT), Cali, Colombia by genetic crosses of OW 230 - 1 (FLA 441 - 5) and CW 30–65 (an inter-specific hybrid between an improved cassava variety SG 427 - 87 and an accession of Manihot esculenta ssp flabellifolia (MESCFLAX – 80)). The inter-specific cross was ‘backcrossed’, in the sense of another cross to cassava (MTAI – 8) to generate a B₁P₂ family with 225 progenies in which major quantitative trait loci (QTL) for root protein in the backcross population of cassava were identified. A linkage map from the female parent of the backcross population was used for QTL detection. A total of three QTL (protg.7, protg.13 and protg.23) controlling protein were identified in three different environments. One QTL was expressed across all three environments. These results demonstrated high broad sense heritability of 61.6% for protein over 2 years, in two different locations. The individual effects of alleles at these QTL explained from 15% to 25% of the phenotypic variance. The consistency of QTL controlling protein across environments reveals their potential for use in marker-assisted recurrent selection.     

QTL analysis for capsaicinoid content in Capsicum

Pungency or “heat” found in Capsicum fruit results from the biosynthesis and accumulation of alkaloid compounds known as capsaicinoids in the dissepiment, placental tissue adjacent to the seeds. Pepper cultivars differ with respect to their level of pungency because of quantitative and qualitative variation in capsaicinoid content. We analyzed the segregation of three capsaicinoids: capsaicin, dihydrocapsaicin and nordihydrocapsaicin in an inter-specific cross between a mildly pungent Capsicum annuum ‘NuMex RNaky’ and the wild, highly pungent C. frutescens accession BG2814-6. F₃ families were analyzed in three trials in California and in Israel and a dense molecular map was constructed comprised mostly of loci defined by simple sequence repeat (SSR) markers. Six QTL controlling capsaicinoid content were detected on three chromosomes. One gene from the capsaicinoid biosynthetic pathway, BCAT, and one random fruit EST, 3A2, co-localized with QTL detected in this study on chromosomes 3 and 4. Because one confounding factor in quantitative determination of capsaicinoid is fruit size, fruit weight measurements were taken in two trials. Two QTL controlling fruit weight were detected, however, they did not co-localize with QTL detected for capsaicinoid content. The major contribution to the phenotypic variation of capsaicinoid content (24–42% of the total variation) was attributed to a digenic interaction between a main-effect QTL, cap7.1, and a marker located on chromosome 2 that did not have a main effect on the trait. A second QTL, cap7.2 is likely to correspond to the QTL, cap, identified in a previous study as having pronounced influence on capsaicinoid content.     

Pyramiding QTL for multiple lateral branching in cucumber using inbred backcross lines

Multiple lateral branching (MLB) is a quantitatively inherited trait associated with yield in cucumber (Cucumis sativus L.; 2n = 2x = 14). Although quantitative trait loci (QTL) have been identified for MLB and QTL-marker associations have been verified by marker-assisted selection, the individual effects of these QTL have not been characterized. To test the effects of pyramiding QTL for MLB, molecular genotyping was utilized to create two sets (standard- and little-leaf types) of inbred backcross (IBC) lines possessing various numbers of QTL that promote branching. These IBC lines were evaluated for lateral branch number in two Wisconsin environments at three plant densities. Highly significant differences in the number of primary lateral branches were detected between spacings, leaf types, and lines, but not between locations. Lateral branch number decreased at higher plant densities in all genotypes, while genotype by environment and QTL by environment interactions were marginally non-significant. As the number of QTL increased among IBC lines, the number of branches did not generally change in the little-leaf lines, but decreased in the standard-leaf lines, demonstrating an epistatic effect related to genetic background during lateral branch development. The genomic location with the greatest effect on MLB was confirmed as the QTL that was previously mapped near the little-leaf locus (ll), while the addition of one specific QTL consistently decreased the number of lateral branches in standard-leaf lines. Although pyramiding QTL for MLB did not uniformly increase the number of lateral branches, pyramiding QTL in IBC lines allowed further characterization of individual QTL involved in MLB. Our results, coupled with those of previous studies indicate that lateral branch development in cucumber is determined by growing environment (i.e., plant spacing), genetic background, and QTL composition.     

Genetic analysis of adult plant,quantitative resistance to stripe rust in wheat cultivar ‘Stephens’ in multi-environment trials

The wheat (Triticum aestivum L.) cultivar ‘Stephens’ has been grown commercially in the USA Pacific Northwest for 30 years. The durable resistance of ‘Stephens’ to stripe rust (Puccinia striiformis f. sp. tritici) was believed to be due to a combination of seedling and adult plant resistance genes. Multilocation field trials, diversity array technology (DArT), and simple sequence repeat (SSR) markers were used to identify quantitative trait loci (QTL) for resistance. Recombinant inbred lines were assessed for stripe rust response in eight locations/years, five in 2008 and three in 2009. The data from Mt. Vernon, WA, differed from all other environments, and composite interval mapping (CIM) identified three QTL, QYrst.orr-1AL, QYrst.orr-4BS, and QYrpl.orr-6AL, which accounted for 12, 11, and 6% of the phenotypic variance, respectively. CIM across the remaining six environments identified four main QTL. Two QTL, QYrst.orr-2BS.2 and QYrst.orr-7AS, were detected in five of six environments and explained 11 and 15% of the phenotypic variance, respectively. Two other QTL, QYrst.orr-2AS and QYrpl.orr-4BL, were detected across four and three of six environments, and explained 19 and 9% of the phenotypic variance, respectively. The susceptible parent ‘Platte’ contributed QYrpl.orr-4BL and QYrpl.orr-6AL, with the remaining QTL originating from ‘Stephens’. For each environment, additional minor QTL were detected, each accounting for 6–10% of the phenotypic variance. Different QTL with moderate effects were identified in both ‘Stephens’ and ‘Platte’. Significant QTL × environment interactions were evident, suggesting that specificity to plant stage, pathogen genotype, and/or temperature was important.     

Fruit size QTL analysis of an F<Subscript>1</Subscript> population derived from a cross between a domesticated sweet cherry cultivar and a wild forest sweet cherry

Maximizing fruit size is critical for profitable sweet cherry (Prunus avium L.) production. Yet, despite its importance, little is known about the genetic control of fruit size. The objective of this study was to identify quantitative trait loci (QTLs) for fruit size and two essential components of fruit size, mesocarp cell number and size. This study utilized a double pseudo-testcross population derived from reciprocal crosses between a sweet cherry cultivar with ~8 g fruit, “Emperor Francis” (EF), and a wild forest sweet cherry selection with ~2 g fruit, “New York 54” (NY). A total of 190 F₁ progeny previously utilized for the construction of the linkage maps were evaluated in 2006 and 2007 for fruit weight, length, and diameter; mesocarp cell number and length; and pit length and diameter. In 2008, a subset of this population was again evaluated for fruit weight. Correlation analysis revealed that the three fruit size traits were highly correlated with each other, and mesocarp cell number, not cell length, was correlated with fruit size. Three QTLs were identified for each fruit size trait, and one QTL was identified for mesocarp cell number. Fruit size QTLs were found on linkage group 2 on the EF map (EF 2) and linkage groups 2 and 6 on the NY map (NY 2 and NY 6). On EF 2, the cell number QTL clustered with the fruit size QTL, suggesting that the underlying basis of the fruit size increase associated with this QTL was an increase in mesocarp cell number. On NY 6, pit length and diameter QTLs clustered with those for fruit size, suggesting that the underlying morphological basis of this fruit size QTL is the difference in pit size.     

QTL in mega-environments: I. Universal and specific seed yield QTL detected in a population derived from a cross of high-yielding adapted × high-yielding exotic soybean lines

Modern soybean [(Glycine max (L.) Merrill] breeding programs rely primarily on the use of elite × elite line crosses to develop high-yielding cultivars. Favorable alleles for traits of interest have been found in exotic germplasm but the successful introduction of such alleles has been hampered by the lack of adaptation of the exotic parent to local mega-environment and difficulties in identifying superior progeny from elite × exotic crosses. The objective of this study was to use a population derived from a cross between an adapted and an exotic elite line to understand the genetic causes underlying adaptation to two mega-environments (China and Canada). A cross between a high-yielding Canadian cultivar ‘OAC Millennium’ and an elite Chinese cultivar ‘Heinong 38’ was performed to develop a recombinant inbred line (RIL) population. The RIL population was evaluated in China and Canada in multiple environments from 2004 to 2006. Significant variation for seed yield was observed among the RILs in both the Chinese and Canadian environment. Individual RILs performed differently between the Chinese and Canadian environments suggesting differential adaptation to intercontinental mega-environments. Seven seed yield quantitative trait loci (QTL) were identified of which five were mega-environment universal QTL (linked to markers Satt100, Satt162, Satt277, Sat_126, and the interval of Satt139-Sat_042) and two were mega-environment-specific QTL (at marker intervals, Satt194-SOYGPA and Satt259-Satt576). Seed yield QTL located near Satt277 has been confirmed and new QTL have been identified explaining between 9 and 37% of the phenotypic variation in seed yield. The QTL located near Satt100 explained the greatest amount of variation ranging from 18 to 37% per environment. Broad sense heritability ranged from 89 to 64% among environments. Epistatic effects have been identified in both mega-environments with pairs of markers explaining between 9 and 14% of the phenotypic variation in seed yield. An improved understanding of the type of QTL action as either universal or mega-environment-specific QTL as well as their interaction may facilitate the development of strategies to introgress specific high-yielding alleles from Chinese to North American germplasm and vice versa to sustain efforts in breeding of high-yielding soybean cultivars.     

A QTL for rice grain yield in aerobic environments with large effects in three genetic backgrounds

A large-effect QTL associated with grain yield in aerobic environments was identified in three genetic backgrounds, Apo/²*Swarna, Apo/²*IR72, and Vandana/²*IR72, using bulk-segregant analysis (BSA). Apo and Vandana are drought-tolerant aerobic-adapted varieties, while Swarna and IR72 are important lowland rice varieties grown on millions of hectares in Asia but perform poorly in aerobic conditions. Two closely linked rice microsatellite (RM) markers, RM510 and RM19367, located on chromosome 6, were found to be associated with yield under aerobic soil conditions in all three backgrounds. The QTL linked to this marker, qDTY6.1 (DTY, grain yield under drought), was mapped to a 2.2 cM region between RM19367 and RM3805 at a peak LOD score of 32 in the Apo/²*Swarna population. The effect of qDTY6.1 was tested in a total of 20 hydrological environments over a period of five seasons and in five populations in the three genetic backgrounds. In the Apo/²*Swarna population, qDTY6.1 had a large effect on grain yield under favorable aerobic (R ² ≤ 66%) and irrigated lowland (R ² < 39%) conditions but not under drought stress; Apo contributed the favorable allele in all the conditions where an effect was observed. In the Apo/IR72 cross, Apo contributed the favorable allele in almost all the aerobic environments in RIL and BC₁-derived populations. In the Vandana/IR72 RIL and BC₁-derived populations, qDTY6.1 had a strong effect on yield in aerobic drought stress, aerobic non-stress, and irrigated lowland conditions; the Vandana allele was favorable in aerobic environments and the IR72 allele was favorable in irrigated lowland environments. We conclude that qDTY6.1 is a large-effect QTL for rice grain yield under aerobic environments and could potentially be used in molecular breeding of rice for aerobic environments.     

Identification and stability of QTLs for fruit quality traits in apple

Breeding for fruit quality traits is complex due to the polygenic (quantitative) nature of the genetic control of these traits. Therefore, to improve the speed and efficiency of genotype selection, attention in recent years has focused on the identification of quantitative trait loci (QTLs) and molecular markers associated with these QTLs. However, despite the huge potential of molecular markers in breeding programmes, their implementation in practice has been limited by the lack of information on the stability of QTLs across different environments and within different genetic backgrounds. Here, we present the results from a comprehensive analysis of the inheritance of fruit quality traits within a population derived from a cross between the apple cultivars ‘Telamon’ and ‘Braeburn’ over two successive seasons. A total of 74 different QTLs were identified for all the major fruit physiological traits including fruit height, diameter, weight and stiffness, flesh firmness, rate of flesh browning, acidity, the oBrix content and harvest date. Seventeen of these QTLs were ‘major’ QTLs, accounting for over 20% of the observed population variance of the trait. However, only one third (26) of the identified QTLs were stable over both harvest years, and of these year-stable QTLs only one was a major QTL. A direct comparison with published QTL results obtained using other populations (King et al., Theor Appl Genet 102:1227–1235, 2001; Liebhard et al., Plant Mol Biol 52:511–526, 2003) is difficult because the linkage maps do not share a sufficient number of common markers and due to differences in the trait evaluation protocols. Nonetheless, our results suggest that for the six fruit quality traits which were measured in all populations, nine out of a total of 45 QTLs were common or stable across all population × environments combinations. These results are discussed in the framework of the development and application of molecular markers for fruit quality trait improvement.     

Genome mapping of kernel characteristics in hard red spring wheat breeding lines

Kernel characteristics, particularly kernel weight, kernel size, and grain protein content, are important components of grain yield and quality in wheat. Development of high performing wheat cultivars, with high grain yield and quality, is a major focus in wheat breeding programs worldwide. Here, we report chromosome regions harboring genes that influence kernel weight, kernel diameter, kernel size distribution, grain protein content, and grain yield in hard red spring wheat breeding lines adapted to the Upper Midwest region of the United States. A genetic linkage map composed of 531 SSR and DArT marker loci spanned a distance of 2,505 cM, covering all 21 chromosomes of wheat. Stable QTL clusters influencing kernel weight, kernel diameter, and kernel size distribution were identified on chromosomes 2A, 5B, and 7A. Phenotypic variation explained by individual QTL at these clusters varied from 5 to 20% depending on the trait. A QTL region on chromosome 2B confers an undesirable pleiotropic effect or a repulsion linkage between grain yield (LOD = 6.7; R ² = 18%) and grain protein content (LOD = 6.2; R ² = 13.3%). However, several grain protein and grain yield QTL independent of each other were also identified. Because some of the QTL identified in this study were consistent across environments, DNA markers will provide an opportunity for increasing the frequency of desirable alleles through marker-assisted selection.     

Identification and characterization of large-effect quantitative trait loci for grain yield under lowland drought stress in rice using bulk-segregant analysis

An F_4:5 population of 490 recombinant inbred lines (RILs) from the cross Apo/^2*Swarna was used to detect quantitative trait loci (QTL) with large effects on grain yield under drought stress using bulk-segregant analysis (BSA). Swarna is an important rainfed lowland rice variety grown on millions of hectares in Asia, but is highly susceptible to drought and aerobic soil conditions. Apo is an aerobic-adapted variety with moderate tolerance to drought. Two rice microsatellite (RM) markers, RM324, and RM416, located on chromosomes 2 and 3, respectively, were shown via BSA to be strongly associated with yield under lowland drought stress. The effects of these QTL were tested in a total of eight hydrological environments over a period of 3 years. The QTL linked to RM416 (DTY _3.1 ) had a large effect on grain yield under severe lowland drought stress, explaining about 31% of genetic variance for the trait (P < 0.0001). It also explained considerable variance for yield under mild stress in lowland conditions and aerobic environments. To our knowledge this is the first reported QTL that has a large effect on yield in both lowland drought and aerobic environments. The QTL linked to RM324 (DTY _2.1 ) had a highly significant effect on grain yield in lowland drought stress (R ² = 13–16%) and in two aerobic trials. The effect of these QTL on grain yield was verified to be not mainly due to phenology differences. Effects of DTY _3.1 on yield under stress have been observed in several other rice mapping populations studied at IRRI. Results of this study indicate that BSA is an effective method of identifying QTL alleles with large effects on rice yield under severe drought stress. The Apo alleles for these large-effect QTL for grain yield under drought and aerobic conditions may be immediately exploited in marker-assisted-breeding to improve the drought tolerance of Swarna.     

Detection and verification of malting quality QTLs using wild barley introgression lines

A malting quality quantitative trait locus (QTL) study was conducted using a set of 39 wild barley introgression lines (hereafter abbreviated with S42ILs). Each S42IL harbors a single marker-defined chromosomal segment from the wild barley accession ‘ISR 42-8’ (Hordeum vulgare ssp. spontaneum) within the genetic background of the elite spring barley cultivar ‘Scarlett’ (Hordeum vulgare ssp. vulgare). The aim of the study was (1) to verify genetic effects previously identified in the advanced backcross population S42, (2) to detect new QTLs, and (3) to identify S42ILs exhibiting multiple QTL effects. For this, grain samples from field tests in three different environments were subjected to micro malting. Subsequently, a line × phenotype association study was performed with the S42ILs in order to localize putative QTL effects. A QTL was accepted if the trait value of a particular S42IL was significantly (P < 0.05) different from the recurrent parent as a control, either across all tested environments or in a particular environment. For eight malting quality traits, altogether 40 QTLs were localized, among which 35 QTLs (87.5%) were stable across all environments. Six QTLs (15.0%) revealed a trait improving wild barley effect. Out of 36 QTLs detected in a previous advanced backcross QTL study with the parent BC₂DH population S42, 18 QTLs (50.0%) could be verified with the S42IL set. For the quality parameters α-amylase activity and Hartong 45°C, all QTLs assessed in population S42 were verified by S42ILs. In addition, eight new QTL effects and 17 QTLs affecting two newly investigated traits were localized. Two QTL clusters harboring simultaneous effects on eight and six traits, respectively, were mapped to chromosomes 1H and 4H. In future, fine-mapping of these QTL regions will be conducted in order to shed further light on the genetic basis of the most interesting QTLs.     

QTL mapping and GWAS reveal candidate genes controlling capsaicinoid content in Capsicum

Capsaicinoids are unique compounds produced only in peppers (Capsicum spp.). Several studies using classical quantitative trait loci (QTLs) mapping and genomewide association studies (GWAS) have identified QTLs controlling capsaicinoid content in peppers; however, neither the QTLs common to each population nor the candidate genes underlying them have been identified due to the limitations of each approach used. Here, we performed QTL mapping and GWAS for capsaicinoid content in peppers using two recombinant inbred line (RIL) populations and one GWAS population. Whole‐genome resequencing and genotyping by sequencing (GBS) were used to construct high‐density single nucleotide polymorphism (SNP) maps. Five QTL regions on chromosomes 1, 2, 3, 4 and 10 were commonly identified in both RIL populations over multiple locations and years. Furthermore, a total of 109 610 SNPs derived from two GBS libraries were used to analyse the GWAS population consisting of 208 C. annuum‐clade accessions. A total of 69 QTL regions were identified from the GWAS, 10 of which were co‐located with the QTLs identified from the two biparental populations. Within these regions, we were able to identify five candidate genes known to be involved in capsaicinoid biosynthesis. Our results demonstrate that QTL mapping and GBS‐GWAS represent a powerful combined approach for the identification of loci controlling complex traits.     

Analysis of the genetic architecture of maize kernel size traits by combined linkage and association mapping

Kernel size‐related traits are the most direct traits correlating with grain yield. The genetic basis of three kernel traits of maize, kernel length (KL), kernel width (KW) and kernel thickness (KT), was investigated in an association panel and a biparental population. A total of 21 single nucleotide polymorphisms (SNPs) were detected to be most significantly (P < 2.25 × 10^?6) associated with these three traits in the association panel under four environments. Furthermore, 50 quantitative trait loci (QTL) controlling these traits were detected in seven environments in the intermated B73 × Mo17 (IBM) Syn10 doubled haploid (DH) population, of which eight were repetitively identified in at least three environments. Combining the two mapping populations revealed that 56 SNPs (P < 1 × 10^?3) fell within 18 of the QTL confidence intervals. According to the top significant SNPs, stable‐effect SNPs and the co‐localized SNPs by association analysis and linkage mapping, a total of 73 candidate genes were identified, regulating seed development. Additionally, seven miRNAs were found to situate within the linkage disequilibrium (LD) regions of the co‐localized SNPs, of which zma‐miR164e was demonstrated to cleave the mRNAs of Arabidopsis CUC1, CUC2 and NAC6 in vitro. Overexpression of zma‐miR164e resulted in the down‐regulation of these genes above and the failure of seed formation in Arabidopsis pods, with the increased branch number. These findings provide insights into the mechanism of seed development and the improvement of molecular marker‐assisted selection (MAS) for high‐yield breeding in maize.