Quantitative Trait Locus Mapping Approach Research Articles

Pan-cancer analysis of promoter activity quantitative trait loci.

Altered promoter activity has been generally observed in diverse biological processes, including tumorigenesis. Accumulating evidence suggests that employing a quantitative trait locus mapping approach is effective in comprehending the genetic basis of promoter activity. By utilizing genotype data from The Cancer Genome Atlas and calculating corresponding promoter activity values using proActiv, we systematically evaluated the impact of genetic variants on promoter activity and identified >1.0 million promoter activity quantitative trait loci (paQTLs) as both cis- and trans-acting. Additionally, leveraging data from the genome-wide association study (GWAS) catalog, we discovered >1.3 million paQTLs that overlap with known GWAS linkage disequilibrium regions. Remarkably, ∼9324 paQTLs exhibited significant associations with patient prognosis. Moreover, investigating the impact of promoter activity on >1000 imputed antitumor therapy responses among pan-cancer patients revealed >43000 million significant associations. Furthermore, ∼25000 significant associations were identified between promoter activity and immune cell abundance. Finally, a user-friendly data portal, Pancan-paQTL (https://www.hbpding.com/PancanPaQTL/), was constructed for users to browse, search and download data of interest. Pancan-paQTL serves as a comprehensive multidimensional database, enabling functional and clinical investigations into genetic variants associated with promoter activity, drug responses and immune infiltration across multiple cancer types.

Characterization and Molecular Mapping of a Gene Conferring High-Temperature Adult-Plant Resistance to Stripe Rust Originally from Aegilops ventricosa.

Wheat near-isogenic line AvSYr17NIL carrying Yr17, originally from Aegilops ventricosa for all-stage resistance to Puccinia striiformis f. sp. tritici, also shows nonrace-specific, high-temperature adult-plant (HTAP) resistance to the stripe rust pathogen. To separate and identify the HTAP resistance gene, seeds of AvSYr17NIL were treated with ethyl methanesulfonate. Mutant lines with only HTAP resistance were obtained, and one of the lines, M1225, was crossed with the susceptible recurrent parent Avocet S (AvS). Field responses of the F2 plants and F3 lines, together with the parents, were recorded at the adult-plant stage in Pullman and Mount Vernon, WA under natural P. striiformis f. sp. tritici infection. The parents and the F4 population were phenotyped with a Yr17-virulent P. striiformis f. sp. tritici race in the adult-plant stage under the high-temperature profile in the greenhouse. The phenotypic results were confirmed by testing the F5 population in the field under natural P. striiformis f. sp. tritici infection. The F2 data indicated a single recessive gene, temporarily named YrM1225, for HTAP resistance. The F4 lines were genotyped with Kompetitive allele-specific PCR markers converted from single-nucleotide polymorphism markers polymorphic between M1225 and AvS. The HTAP resistance gene was mapped on the short arm of chromosome 2A in an interval of 7.5 centimorgans using both linkage and quantitative trait locus mapping approaches. The separation of the HTAP resistance gene from Yr17 should improve the understanding and utilization of the different types of resistance.

Relieving the Phenotyping Bottleneck for Grape Bunch Architecture in Grapevine Breeding Research: Implementation of a 3D-Based Phenotyping Approach for Quantitative Trait Locus Mapping

In viticulture, winemakers and the industry demand grape bunches that have a reduced degree of bunch compactness. The major aspect is that a loose bunch compactness reduces the risk of severe Botrytis bunch-rot infections. Grapevine breeders focus hereby on several bunch-architecture-related traits. For specific breeding approaches and breeding-research-related topics, such as Quantitative Trait Locus (QTL) analysis or molecular marker development, the exact and objective phenotyping of such traits is mandatory. In this study, a precise and high-throughput 3D phenotyping pipeline was applied to screen 1514 genotypes from three mapping populations with different genetic backgrounds to investigate its applicability for QTL mapping approaches. In the first step, the phenotypic data of one population containing 150 genotypes were collected and analyzed with the 3D phenotyping pipeline. Additionally, corresponding reference data were obtained. Phenotypic values and results of a QTL analysis were compared with each other. Strongly positive correlations up to r = 0.93 between 3D and reference measurements could be detected for several traits. The ten-times-faster 3D phenotyping pipeline revealed 20, and the reference phenotyping methods revealed 22 QTLs. Eighteen of these QTLs were consistent between both procedures. In the next step, screening was extended to four different mapping populations across several seasons. In total, up to 1500 genotypes were screened during one season (>5000 grape bunches in total). The data analysis revealed significant differences across years and populations. Three bunch-architecture traits, including total berry volume, bunch width, and berry diameter, explained the highest amount of variability in the phenotypic data. A QTL analysis was performed on the phenotypic data of the involved populations to identify comparative genetic loci for bunch-architecture traits. Between 20 and 26 stable and reproducible QTLs for the investigated populations were detected. A common QTL for berry diameter could be identified for all populations. Our results strongly conclude that this locus is co-located on chromosome 17 when mapped to the grapevine reference genome. The results show that the implementation of the 3D phenotyping platform allows for precise and extended screenings of different, genetic diverse mapping populations and thus opens up the possibility to uncover the genomic architecture of this highly complex quantitative grapevine trait.

Fine mapping and candidate gene analysis of flesh browning in pear (Pyrus L.)

Flesh browning significantly affects the quality of fresh pear and causes great waste and commercial losses of pear products. However, the inheritance of genetic factors controlling flesh browning in pear remains largely unknown. In this study, a mapping population from a cross between the browning cultivar ‘Mantianhong’ and the nonbrowning cultivar ‘Hongxiangsu’ was utilized. The browning degree of pear flesh was evaluated in successive years in 2020 and 2021, and the results fit a normal distribution. Using the QTL mapping approach, the major quantitative trait loci (QTL) associated with pear browning were identified on chromosome 2 (Chr 2), with a minor QTL on chromosome 17 (Chr 17). The QTL on Chr 2 showed a high confidence level (LOD >10). In 2020, the interval length of the QTL was 48.301 cM, from 43.476 cM (LOD = 4.0) to 91.768 cM (LOD = 10.58), and contained 72 markers. The peak LOD value was 15.06, the percentage of total phenotypic variance explained was 49.98%, and the contribution rate was 65.6%. In 2021, the interval length of the QTL was 49.292 cM, from 43.476 cM (LOD = 4.68) to 92.768 cM (LOD = 6.32), and contained 76 markers. The peak LOD value was 13.77, the percentage of total phenotypic variance explained was 86.84%, and the contribution rate was 38.6%. To further delineate the QTL interval on Chr 2, 93 indel markers were designed for analysis, and 21 pairs showed polymorphism in the progeny. A total of 41 candidate genes were identified within the fine mapping QTL range on Chr 2. To further identify the candidate genes controlling flesh browning in pear, RNA-seq analysis was performed using three browning individuals and three nonbrowning individuals at three different times after cutting. The results showed that there were three candidate genes on Chr 2 and one candidate genes on Chr 17, and the expression levels of these four genes were analyzed. Gene expression analyses suggested that Pear_GLEAN_10026026 (acyl-activating enzyme 1, peroxisomal) and Pear_GLEAN_10026027 (protein stritosidine synthase-like 5-like) may be involved in the regulation of pear flesh browning. Taken together, these findings will facilitate marker-assisted breeding for flesh browning in pear and provide a foundation for mining genes related to flesh browning.

Fine mapping of qDB.A03, a QTL for rapeseed branching, and identification of the candidate gene.

Increasing the yield of rapeseed is required to meet the rapidly expanding demand for both edible vegetable oil and biofuel. Branching, an important determinant of yield potential in rapeseed, is controlled by a series of quantitative trait loci (QTLs). To explore the genetic mechanism regulating the natural variation of branching, a BC1F1 population derived from a cross between dense branching 2 (dense branching line) and L72 (normal branching line) was used to map QTL conferring branching in rapeseed. A major QTL, qDB.A03, for branching-related traits was identified by the BeadChip Array assisted bulked segregation analysis method, which was subsequently validated by the classical QTL mapping approach, and fine mapped to the 256kb region. This interval contains 56 annotated or predicted genes, 8 of which are candidates for controlling the branching trait. Comparative and expression analysis revealed four promising candidate genes for qDB.A03. Fine mapping and identification of the candidate genes for qDB.A03 represents the first step toward unraveling the genetical and molecular mechanisms controlling branching in rapeseed.

The evolution of larger size in high-altitude Drosophila melanogaster has a variable genetic architecture.

Important uncertainties persist regarding the genetic architecture of adaptive trait evolution in natural populations, including the number of genetic variants involved, whether they are drawn from standing genetic variation, and whether directional selection drives them to complete fixation. Here, we take advantage of a unique natural population of Drosophila melanogaster from the Ethiopian highlands, which has evolved larger body size than any other known population of this species. We apply a bulk segregant quantitative trait locus mapping approach to 4 unique crosses between highland Ethiopian and lowland Zambian populations for both thorax length and wing length. Results indicated a persistently variable genetic basis for these evolved traits (with largely distinct sets of quantitative trait loci for each cross), and at least a moderately polygenic architecture with relatively strong effects present. We complemented these mapping experiments with population genetic analyses of quantitative trait locus regions and gene ontology enrichment analysis, generating strong hypotheses for specific genes and functional processes that may have contributed to these adaptive trait changes. Finally, we find that the genetic architectures indicated by our quantitative trait locus mapping results for size traits mirror those from similar experiments on other recently evolved traits in this species. Collectively, these studies suggest a recurring pattern of polygenic adaptation in this species, in which causative variants do not approach fixation and moderately strong effect loci are present.

Whole Exome-Sequencing of Pooled Genomic DNA Samples to Detect Quantitative Trait Loci in Esotropia and Exotropia of Strabismus in Japanese.

Background: Esotropia and exotropia are two major phenotypes of comitant strabismus. It remains controversial whether esotropia and exotropia would share common genetic backgrounds. In this study, we used a quantitative trait locus (QTL)-sequencing pipeline for diploid plants to screen for susceptibility loci of strabismus in whole exome sequencing of pooled genomic DNAs of individuals. Methods: Pooled genomic DNA (2.5 ng each) of 20 individuals in three groups, Japanese patients with esotropia and exotropia, and normal members in the families, was sequenced twice after exome capture, and the first and second sets of data in each group were combined to increase the read depth. The SNP index, as the ratio of variant genotype reads to all reads, and Δ(SNP index) values, as the difference of SNP index between two groups, were calculated by sliding window analysis with a 4 Mb window size and 10 kb slide size. The rows of 200 “N”s were inserted as a putative 200-b spacer between every adjoining locus to depict Δ(SNP index) plots on each chromosome. SNP positions with depth < 20 as well as SNP positions with SNP index of <0.3 were excluded. Results: After the exclusion of SNPs, 12,242 SNPs in esotropia/normal group and 12,108 SNPs in exotropia/normal group remained. The patterns of the Δ(SNP index) plots on each chromosome appeared different between esotropia/normal group and exotropia/normal group. When the consecutive groups of SNPs on each chromosome were set at three patterns: SNPs in each cytogenetic band, 50 consecutive sliding SNPs, and SNPs in 4 Mb window size with 10 kb slide size, p values (Wilcoxon signed rank test) and Q values (false discovery rate) in a few loci as Manhattan plots showed significant differences in comparison between the Δ(SNP index) in the esotropia/normal group and exotropia/normal group. Conclusions: The pooled DNA sequencing and QTL mapping approach for plants could provide overview of genetic background on each chromosome and would suggest different genetic backgrounds for two major phenotypes of comitant strabismus, esotropia and exotropia.

How to Detect QTLs in the Plant Circadian Clock.

One of the most powerful methods to identify loci controlling complex quantitative traits has been the quantitative trait locus (QTL) mapping. The QTL mapping approach has proven immensely useful to improve our understanding of key pathways such as flowering time, growth, and disease resistance. Since major circadian clock parameters such as period, phase, and amplitude are quantitative in nature, the QTL mapping approach could also be used to study the complex genetic architecture of the circadian clock. Here, we describe a simple QTL mapping method to identify components controlling clock parameters in natural populations of Arabidopsis thaliana.

A forward genetics approach integrating genome-wide association study and expression quantitative trait locus mapping to dissect leaf development in maize (Zea mays).

SUMMARYThe characterization of the genetic basis of maize (Zea mays) leaf development may support breeding efforts to obtain plants with higher vigor and productivity. In this study, a mapping panel of 197 biparental and multiparental maize recombinant inbred lines (RILs) was analyzed for multiple leaf traits at the seedling stage. RNA sequencing was used to estimate the transcription levels of 29 573 gene models in RILs and to derive 373 769 single nucleotide polymorphisms (SNPs), and a forward genetics approach combining these data was used to pinpoint candidate genes involved in leaf development. First, leaf traits were correlated with gene expression levels to identify transcript–trait correlations. Then, leaf traits were associated with SNPs in a genome‐wide association (GWA) study. An expression quantitative trait locus mapping approach was followed to associate SNPs with gene expression levels, prioritizing candidate genes identified based on transcript–trait correlations and GWAs. Finally, a network analysis was conducted to cluster all transcripts in 38 co‐expression modules. By integrating forward genetics approaches, we identified 25 candidate genes highly enriched for specific functional categories, providing evidence supporting the role of vacuolar proton pumps, cell wall effectors, and vesicular traffic controllers in leaf growth. These results tackle the complexity of leaf trait determination and may support precision breeding in maize.

QTL × environment interactions underlie ionome divergence in switchgrass.

Ionomics measures elemental concentrations in biological organisms and provides a snapshot of physiology under different conditions. In this study, we evaluate genetic variation of the ionome in outbred, perennial switchgrass in three environments across the species’ native range, and explore patterns of genotype-by-environment interactions. We grew 725 clonally replicated genotypes of a large full sib family from a four-way linkage mapping population, created from deeply diverged upland and lowland switchgrass ecotypes, at three common gardens. Concentrations of 18 mineral elements were determined in whole post-anthesis tillers using ion coupled plasma mass spectrometry (ICP-MS). These measurements were used to identify quantitative trait loci (QTL) with and without QTL-by-environment interactions (QTLxE) using a multi-environment QTL mapping approach. We found that element concentrations varied significantly both within and between switchgrass ecotypes, and GxE was present at both the trait and QTL level. Concentrations of 14 of the 18 elements were under some genetic control, and 77 QTL were detected for these elements. Seventy-four percent of QTL colocalized multiple elements, half of QTL exhibited significant QTLxE, and roughly equal numbers of QTL had significant differences in magnitude and sign of their effects across environments. The switchgrass ionome is under moderate genetic control and by loci with highly variable effects across environments.

A combined BSA-Seq and linkage mapping approach identifies genomic regions associated with Phytophthora root and crown rot resistance in squash

Two QTL mapping approaches were used to identify a total of six QTL associated with Phytophthora root and crown rot resistance in a biparental squash population. Phytophthora root and crown rot, caused by the soilborne oomycete pathogen Phytophthora capsici, leads to severe yield losses in squash (Cucurbita pepo). To identify quantitative trait loci (QTL) involved in resistance to this disease, we crossed a partially resistant squash breeding line with a susceptible zucchini cultivar and evaluated over 13,000 F2 seedlings in a greenhouse screen. Bulked segregant analysis with whole genome resequencing (BSA-Seq) resulted in the identification of five genomic regions-on chromosomes 4, 5, 8, 12, and 16-featuring significant allele frequency differentiation between susceptible and resistant bulks in each of two independent replicates. In addition, we conducted linkage mapping using a population of 176 F3 families derived from individually genotyped F2 individuals. Variation in disease severity among these families was best explained by a four-QTL model, comprising the same loci identified via BSA-Seq on chromosomes 4, 5, and 8 as well as an additional locus on chromosome 19, for a combined total of six QTL identified between both methods. Loci, whether those identified by BSA-Seq or linkage mapping, were of small-to-moderate effect, collectively accounting for 28-35% and individually for 2-10% of the phenotypic variance explained. However, a multiple linear regression model using one marker in each BSA-Seq QTL could predict F2:3 disease severity with only a slight drop in cross-validation accuracy compared to genomic prediction models using genome-wide markers. These results suggest that marker-assisted selection could be a suitable approach for improving Phytophthora crown and root rot resistance in squash.

Frontiers in Dissecting and Managing Brassica Diseases: From Reference-Based RGA Candidate Identification to Building Pan-RGAomes.

The Brassica genus contains abundant economically important vegetable and oilseed crops, which are under threat of diseases caused by fungal, bacterial and viral pathogens. Resistance gene analogues (RGAs) are associated with quantitative and qualitative disease resistance and the identification of candidate RGAs associated with disease resistance is crucial for understanding the mechanism and management of diseases through breeding. The availability of Brassica genome assemblies has greatly facilitated reference-based quantitative trait loci (QTL) mapping for disease resistance. In addition, pangenomes, which characterise both core and variable genes, have been constructed for B. rapa, B. oleracea and B. napus. Genome-wide characterisation of RGAs using conserved domains and motifs in reference genomes and pangenomes reveals their clustered arrangements and presence of structural variations. Here, we comprehensively review RGA identification in important Brassica genome and pangenome assemblies. Comparison of the RGAs in QTL between resistant and susceptible individuals allows for efficient identification of candidate disease resistance genes. However, the reference-based QTL mapping and RGA candidate identification approach is restricted by the under-represented RGA diversity characterised in the limited number of Brassica assemblies. The species-wide repertoire of RGAs make up the pan-resistance gene analogue genome (pan-RGAome). Building a pan-RGAome, through either whole genome resequencing or resistance gene enrichment sequencing, would effectively capture RGA diversity, greatly expanding breeding resources that can be utilised for crop improvement.

Quantitative Trait Loci (QTL) Mapping.

Quantitative trait loci (QTL) are genetic regions that influence phenotypic variation of a complex trait, often through genetic interactions with each other and the environment. These are commonly identified through a statistical genetic analysis known as QTL mapping. Here, I present a step-by-step, practical approach to QTL mapping along with a sample data file. I focus on methods commonly used and discoveries that have been made in fishes, and utilize a multiple QTL mapping (MQM) approach in the free software package R/qtl.

QTL mapping and genome-wide association study reveal two novel loci associated with green flesh color in cucumber

BackgroundGreen flesh color, resulting from the accumulation of chlorophyll, is one of the most important commercial traits for the fruits. The genetic network regulating green flesh formation has been studied in tomato, melon and watermelon. However, little is known about the inheritance and molecular basis of green flesh in cucumber. This study sought to determine the main genomic regions associated with green flesh. Three F2 and two BC1 populations derived from the 9110Gt (cultivated cucumber, green flesh color) and PI183967 (wild cucumber, white flesh color) were used for the green flesh genetic analysis. Two F2 populations of them were further employed to do the map construction and quantitative trait loci (QTL) study. Also, a core cucumber germplasms population was used to do the GWAS analysis.ResultsWe identified three indexes, flesh color (FC), flesh extract color (FEC) and flesh chlorophyll content (FCC) in three environments. Genetic analysis indicated that green flesh color in 9110Gt is controlled by a major-effect QTL. We developed two genetic maps with 192 and 174 microsatellite markers respectively. Two novel inversions in Chr1 were identified between cultivated and wild cucumbers. The major-effect QTL, qgf5.1, was identified using FC, FEC and FCC index in all different environments used. In addition, the same qgf5.1, together with qgf3.1, was identified via GWAS. Further investigation of two candidate regions using pairwise LD correlations, combined with genetic diversity of qgf5.1 in natural populations, it was found that Csa5G021320 is the candidate gene of qgf5.1. Geographical distribution revealed that green flesh color formation could be due to the high latitude, which has longer day time to produce the photosynthesis and chlorophyll synthesis during cucumber domestication and evolution.ConclusionsWe first reported the cucumber green flesh color is a quantitative trait. We detected two novel loci qgf5.1 and qgf3.1, which regulate the green flesh formation in cucumber. The QTL mapping and GWAS approaches identified several candidate genes for further validation using functional genomics or forward genetics approaches. Findings from the present study provide a new insight into the genetic control of green flesh in cucumber.

Parental DNA Methylation States Are Associated with Heterosis in Epigenetic Hybrids.

Despite the importance and wide exploitation of heterosis in commercial crop breeding, the molecular mechanisms behind this phenomenon are not completely understood. Recent studies have implicated changes in DNA methylation and small RNAs in hybrid performance; however, it remains unclear whether epigenetic changes are a cause or a consequence of heterosis. Here, we analyze a large panel of over 500 Arabidopsis (Arabidopsis thaliana) epigenetic hybrid plants (epiHybrids), which we derived from near-isogenic but epigenetically divergent parents. This proof-of-principle experimental system allowed us to quantify the contribution of parental methylation differences to heterosis. We measured traits such as leaf area, growth rate, flowering time, main stem branching, rosette branching, and final plant height and observed several strong positive and negative heterotic phenotypes among the epiHybrids. Using an epigenetic quantitative trait locus mapping approach, we were able to identify specific differentially methylated regions in the parental genomes that are associated with hybrid performance. Sequencing of methylomes, transcriptomes, and genomes of selected parent-epiHybrid combinations further showed that these parental differentially methylated regions most likely mediate the remodeling of methylation and transcriptional states at specific loci in the hybrids. Taken together, our data suggest that locus-specific epigenetic divergence between the parental lines can directly or indirectly trigger heterosis in Arabidopsis hybrids independent of genetic changes. These results add to a growing body of evidence that points to epigenetic factors as one of the key determinants of hybrid performance.

Quantitative trait locus mapping of Populus bark features and stem diameter

BackgroundBark plays important roles in photosynthate transport and storage, along with physical and chemical protection. Bark texture varies extensively among species, from smooth to fissured to deeply furrowed, but its genetic control is unknown. This study sought to determine the main genomic regions associated with natural variation in bark features and stem diameter. Quantitative trait loci (QTL) were mapped using an interspecific pseudo-backcross pedigree (Populus trichocarpa x P. deltoides and P. deltoides) for bark texture, bark thickness and diameter collected across three years, two sites and three biological replicates per site.ResultsQTL specific to bark texture were highly reproducible in shared intervals across sites, years and replicates. Significant positive correlations and co-localization between trait QTL suggest pleiotropic regulators or closely linked genes. A list of candidate genes with related putative function, location close to QTL maxima and with the highest expression level in the phloem, xylem and cambium was identified.ConclusionCandidate genes for bark texture included an ortholog of Arabidopsis ANAC104 (PopNAC128), which plays a role in lignified fiber cell and ray development, as well as Pinin and Fasciclin (PopFLA) genes with a role in cell adhesion, cell shape and migration. The results presented in this study provide a basis for future genomic characterization of genes found within the QTL for bark texture, bark thickness and diameter in order to better understand stem and bark development in Populus and other woody perennial plants. The QTL mapping approach identified a list of prime candidate genes for further validation using functional genomics or forward genetics approaches.

Molecular Dissection of a Genomic Region Governing Root Traits Associated with Drought Tolerance Employing a Combinatorial Approach of QTL Mapping and RNA-seq in Rice

Drought is considered as one of the major obstacles for progressive yield enhancement and stability in rice, especially in rain-fed conditions. Being a complex trait, drought is regulated by numerous quantitative trait loci (QTL), of which, however, very few underlying genes have been cloned. In the present investigation, we made an attempt to uncover the candidate gene(s) behind a major QTL, rdw8.1 governing drought tolerance traits viz., root dry weight and root length. The targeted QTL has been delimited to 366.75 kb from 10.17 Mb by QTL mapping in BC1F2 population. Further, the targeted region was delineated employing next-generation sequencing based RNA-seq. Based on the QTL mapping and RNA-seq approaches, the plausible candidate gene underlying the QTL region was identified as a wound inducible protein (LOC_Os08g08090). This gene can be of potential value to enhance the drought tolerance of the elite rice varieties through molecular breeding.

Genetic Mapping of Anaerobic Germination-Associated QTLs Controlling Coleoptile Elongation in Rice.

BackgroundIncreasing numbers of rice farmers are adopting direct-seeding methods to save on costs associated with labor and transplanting. Successful seedling establishment in flooded conditions requires rapid coleoptile growth to ensure access to oxygen near the water surface. It is important that the natural variations in coleoptile growth of submerged rice plants are identified.ResultsColeoptile responses of submerged plants at the germination stage were analyzed in diverse rice accessions and recombinant inbred lines. Several genomic regions identified from a genome-wide association analysis were significantly associated with anaerobic germination, with many that corresponded to published quantitative trait locus (QTL) intervals. In the recombinant inbred line population derived from a cross between japonica and indica varieties, only one unique and strong signal explaining about 27 % of the phenotypic variation was detected. Distinct haplotypes associated with variations in coleoptile length were identified in diverse germplasm.ConclusionsWe demonstrated the value of combining genome-wide association analysis and biparental QTL mapping approaches to identify chromosomal regions regulating coleoptile elongation in submerged rice plants. The significant genomic regions detected in this study are potential candidates for incorporation into elite cultivars to improve seedling survival during anaerobic germination. Future studies that map the QTLs and investigate the effects and functions of candidate genes may lead to new rice varieties that can be used in direct-seeding systems.Electronic supplementary materialThe online version of this article (doi:10.1186/s12284-015-0072-3) contains supplementary material, which is available to authorized users.

QTL detection for growth and form traits in three full-sib pedigrees of Pinus elliottii var. elliottii × P. caribaea var. hondurensis hybrids

Quantitative trait locus (QTL) analysis was conducted on three full-sib Pinus elliottii var. elliottii × P. caribaea var. hondurensis (PEE × PCH) hybrid families to identify genomic regions affecting two growth traits, height (Ht) and DBH at age 5, and seven morphological (“form”) traits. The QTL detection population consisted of family A containing 122 progeny, which was related to the validation population family B (n = 66) via a common PEE parent, but unrelated to the second validation population, family C (n = 107). Using a double pseudo-testcross QTL mapping approach, quantitative trait loci (QTLs) had been identified in the detection population for Ht, DBH, and three form traits. One QTL for Ht05 was validated in the shared common PEE lineage. For two other form traits, QTLs were validated by identifying QTLs that co-located to the same genomic regions in both validation populations. Two QTL, for another form trait and DBH05 were not identified in the original detection population but occurred in both validation populations. The QTL positions detected in this study provide a resource to identify form-trait loci using the Pinus genome or expressed sequence tag (EST) sequences, which may be useful for future association studies.

Identification of single nucleotide polymorphism markers associated with bacterial cold water disease resistance and spleen size in rainbow trout

Bacterial cold water disease (BCWD) is one of the frequent causes of elevated mortality in salmonid aquaculture. Previously, we identified and validated microsatellites on chromosome Omy19 associated with QTL (quantitative trait loci) for BCWD resistance and spleen size in rainbow trout. Recently, SNPs (single nucleotide polymorphism) have become the markers of choice for genetic analyses in rainbow trout as they are highly abundant, cost-effective and are amenable for high throughput genotyping. The objective of this study was to identify SNP markers associated with BCWD resistance and spleen size using both genome-wide association studies (GWAS) and linkage-based QTL mapping approaches. A total of 298 offspring from the two half-sib families used in our previous study to validate the significant BCWD QTL on chromosome Omy19 were genotyped with RAD-seq (restriction-site-associated DNA sequencing), and 7,849 informative SNPs were identified. Based on GWAS, 18 SNPs associated with BCWD resistance and 20 SNPs associated with spleen size were identified. Linkage-based QTL mapping revealed three significant QTL for BCWD resistance. In addition to the previously validated dam-derived QTL on chromosome Omy19, two significant BCWD QTL derived from the sires were identified on chromosomes Omy8 and Omy25, respectively. A sire-derived significant QTL for spleen size on chromosome Omy2 was detected. The SNP markers reported in this study will facilitate fine mapping to identify positional candidate genes for BCWD resistance in rainbow trout.