Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “QTL”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records

Dynamic QTL mapping for plant height in the hybrid population of Agropyron Gaertn.

Abstract Plant height (PH) plays a very important role for plant breeding and also serves as a model trait to dynamic development study. The dynamic quantitative trait locus (QTL) analysis for PH of Agropyron Gaertn. was carried out in a cross‐pollination (CP) hybrid population of A. Gaertn. based on the phenotypic data of PH at different developmental stages in four year‐sites and the constructed single‐nucleotide polymorphism (SNP) genetic map. The results showed that 69 QTL and nine major QTL were detected by unconditional QTL mapping. A total of 107 QTL and 13 major QTL were found using conditional QTL mapping. Forty‐seven QTL were detected by two methods. Two unconditional QTL, Qph2‐5 and Qph3‐4, were expressed as major and stable QTL for PH. Four major stable conditional QTL for PH, cQph4‐1 , cQph4‐8, cQph6‐2 and cQph6‐7 , were detected. Two conditional PH QTL, cQph3‐5 and cQPh3‐7 , were identified in four environments over multiple stages. The gene/QTL controlling PH was expressed in a certain spatiotemporal manner. These results could also provide a reference for genetic and breeding research of related plant.

Che, Yonghe↗

QTL × environment interactions underlie ionome divergence in switchgrass

Abstract 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.

59 BASIC BIOLOGICAL SCIENCES↗

Integration of high-density genetic mapping with transcriptome analysis uncovers numerous agronomic QTL and reveals candidate genes for the control of tillering in sorghum

Phenotypes such as branching, photoperiod sensitivity, and height were modified during plant domestication and crop improvement. Here, we perform quantitative trait locus (QTL) mapping of these and other agronomic traits in a recombinant inbred line (RIL) population derived from an interspecific cross between Sorghum propinquum and Sorghum bicolor inbred Tx7000. Using low-coverage Illumina sequencing and a bin-mapping approach, we generated ~1920 bin markers spanning ~875 cM. Phenotyping data were collected and analyzed from two field locations and one greenhouse experiment for six agronomic traits, thereby identifying a total of 30 QTL. Many of these QTL were penetrant across environments and co-mapped with major QTL identified in other studies. Other QTL uncovered new genomic regions associated with these traits, and some of these were environment-specific in their action. To further dissect the genetic underpinnings of tillering, we complemented QTL analysis with transcriptomics, identifying 6189 genes that were differentially expressed during tiller bud elongation. We identified genes such as Dormancy Associated Protein 1 (DRM1) in addition to various transcription factors that are differentially expressed in comparisons of dormant to elongating tiller buds and lie within tillering QTL, suggesting that these genes are key regulators of tiller elongation in sorghum. Our study demonstrates the usefulness of this RIL population in detecting domestication and improvement-associated genes in sorghum, thus providing a valuable resource for genetic investigation and improvement to the sorghum community.

59 BASIC BIOLOGICAL SCIENCES↗

Identification of a QTL region for tomato brown rugose fruit virus resistance in Solanum pimpinellifolium

Abstract Tomato (Solanum lycopersicumL.), one of the most widely grown vegetables in the world, has been seriously impacted in the past decade by the emerging tomato brown rugose fruit virus (ToBRFV). ToBRFV is a seed-borne tobamovirus, with ability to overcome the commonly usedTm-2 2 resistance gene in tomato. The objective of this study was to conduct quantitative trait locus (QTL) mapping and identify single-nucleotide polymorphism (SNP) markers associated with ToBRFV resistance in tomato. Two F 2 populations were used for QTL mapping: One derived from a cross betweenS. pimpinellifoliumUSVL333 (PI 390718) × USVL332 (PI 390717) and another from ‘Moneymaker’ × USVL332 (PI 390717), with population sizes of 195 and 79 plants, respectively. The resistance trait was derived from theS. pimpinellifoliumaccession USVL332 (PI 390717). A major QTL for ToBRFV resistance was identified on chromosome 11 (SL4.0ch11), with the peak located at approximately 46.84 Mbp. This QTL spans a 22-kb interval between 46,825,788 bp and 46,847,421 bp, as determined through both genome-wide association study (GWAS) and QTL linkage mapping. Three SNP markers, SL4.0ch11_46825788, SL4.0ch11_46847421, and SL4.0ch11_46850215, demonstrated the most significant association with high LOD values (LOD = 13 in the Blink model) in GWAS analysis. In this genomic region, two disease resistance gene analogs, Solyc11g062150 (TIR-NBS-LRR resistance protein, Toll-Interleukin receptor) and Solyc11g062180 (disease resistance protein, leucine-rich repeat), were identified, which may serve as candidates for ToBRFV resistance. The QTL identified in this study could be valuable for plant breeders in facilitating tomato breeding with ToBRFV resistance.

Agriculture↗

Identification of a Fusarium ear rot resistance gene in maize by QTL mapping and RNA sequencing

Fusarium ear rot (FER) caused by Fusarium verticillioides is a prevalent maize disease. To comprehensively characterize the genetic basis of the natural variation in FER resistance, a recombinant inbred line (RIL) population was used to map quantitative trait loci (QTL) for FER resistance. A total of 17 QTL were identified by linkage mapping in eight environments. These QTL were located on six chromosomes and explained 3.88–15.62% of the total phenotypic variation. Moreover, qFER1.03 had the strongest effect and accounted for 4.98–15.62% of the phenotypic variation according to analyses of multiple environments involving best linear unbiased predictions. The chromosome segment substitution lines (CSSLs) derived from a cross between Qi319 (donor parent) and Ye478 (recurrent parent) were used to verify the contribution of qFER1.03 to FER resistance. The line CL171, which harbored an introgressed qFER1.03 , was significantly resistant to FER. Further fine mapping of qFER1.03 revealed that the resistance QTL was linked to insertion/deletion markers InDel 8 and InDel 2, with physical distances of 43.55 Mb and 43.76 Mb, respectively. Additionally, qFER1.03 differed from the previous resistance QTL on chromosome 1. There were three annotated genes in this region. On the basis of the RNA-seq data, which revealed the genes differentially expressed between the FER-resistant Qi319 and susceptible Ye478, GRMZM2G017792 (MPK3) was preliminarily identified as a candidate gene in the qFER1.03 region. The Pr-CMV-VIGS system was used to decrease the GRMZM2G017792 expression level in CL171 by 34–57%, which led to a significant decrease in FER resistance. Using RIL and CSSL populations combined with RNA-seq and Pr-CMV-VIGS, the candidate gene can be dissected effectively, which provided important gene resource for breeding FER-resistant varieties.

Xia, Yusheng↗

QTG-Finder2: A Generalized Machine-Learning Algorithm for Prioritizing QTL Causal Genes in Plants

Linkage mapping has been widely used to identify quantitative trait loci (QTL) in many plants and usually requires a time-consuming and labor-intensive fine mapping process to find the causal gene underlying the QTL. Previously, we described QTG-Finder, a machine-learning algorithm to rationally prioritize candidate causal genes in QTLs. Although it showed good performance, QTG-Finder could only be used in Arabidopsis and rice because of the limited number of known causal genes in other species. Here we tested the feasibility of enabling QTG-Finder to work on species that have few or no known causal genes by using orthologs of known causal genes as training set. The model trained with orthologs could recall about 64% of Arabidopsis and 83% of rice causal genes when the top 20% ranked genes were considered, which is similar to the performance of models trained with known causal genes. The average precision was 0.027 for Arabidopsis and 0.029 for rice. We further extended the algorithm to include polymorphisms in conserved non-coding sequences and gene presence/absence variation as additional features. Using this algorithm, QTG-Finder2, we trained and cross-validated Sorghum bicolor and Setaria viridis models. The S. bicolor model was validated by causal genes curated from the literature and could recall 70% of causal genes when the top 20% ranked genes were considered. Furthermore, we applied the S. viridis model and public transcriptome data to prioritize a plant height QTL and identified 13 candidate genes. QTL-Finder2 can accelerate the discovery of causal genes in any plant species and facilitate agricultural trait improvement.

59 BASIC BIOLOGICAL SCIENCES↗

Quantitative trait locus (QTL) mapping and transcriptome profiling identify QTLs and candidate genes associated with heat stress response during reproductive development in Camelina sativa

Camelina sativa (L.) Crantz is a low-input oilseed crop that has great potential in providing sustainable feedstock for biofuels and bioproducts. Climate change is threatening production of camelina with rising global temperatures. Elucidating the genetic response to high temperatures is essential for successful breeding of heat-tolerant camelina varieties. Here, we report a combinatorial approach to identifying candidate genes associated with heat stress by quantitative trait locus (QTL) mapping and comparative transcriptome profiling. A population of recombinant inbred lines (RILs) was grown in a controlled growth chamber under the high-temperature regimes for 14 days beginning at the onset of the reproductive stage. Several traits related to seed production were evaluated at maturity. The QTL analysis identified several regions with co-located traits on chromosomes 8, 10, and 12. Two RILs with contrasting phenotypic responses to heat stress were chosen for gene expression profiling via RNA sequencing. Multiple pathways and genes were found to be strongly affected by heat stress, and many genes expressed differently between the two RILs. Several genes identified within the QTL regions were considered strong candidates that may control heat tolerance during reproduction in camelina. These studies provide resources for future studies that may assist in improving the heat tolerance of camelina.

60 APPLIED LIFE SCIENCES↗

A Pleiotropic Flowering Time QTL Exhibits Gene-by-Environment Interaction for Fitness in a Perennial Grass

Appropriate flowering time is a crucial adaptation impacting fitness in natural plant populations. Although the genetic basis of flowering variation has been extensively studied, its mechanisms in nonmodel organisms and its adaptive value in the field are still poorly understood. Here, we report new insights into the genetic basis of flowering time and its effect on fitness in Panicum hallii, a native perennial grass. Genetic mapping in populations derived from inland and coastal ecotypes identified flowering time quantitative trait loci (QTL) and many exhibited extensive QTL-by-environment interactions. Patterns of segregation within recombinant hybrids provide strong support for directional selection driving ecotypic divergence in flowering time. A major QTL on chromosome 5 (q-FT5) was detected in all experiments. Fine-mapping and expression studies identified a gene with orthology to a rice FLOWERING LOCUS T-like 9 (PhFTL9) as the candidate underlying q-FT5. We used a reciprocal transplant experiment to test for local adaptation and the specific impact of q-FT5 on performance. We did not observe local adaptation in terms of fitness tradeoffs when contrasting ecotypes in home versus away habitats. However, we observed that the coastal allele of q-FT5 conferred a fitness advantage only in its local habitat but not at the inland site. Sequence analyses identified an excess of low-frequency polymorphisms at the PhFTL9 promoter in the inland lineage, suggesting a role for either selection or population expansion on promoter evolution. Together, our findings demonstrate the genetic basis of flowering variation in a perennial grass and provide evidence for conditional neutrality underlying flowering time divergence.

54 ENVIRONMENTAL SCIENCES↗

Longitudinal genome-wide association study reveals early QTL that predict biomass accumulation under cold stress in sorghum

Sorghum bicolor is a promising cellulosic feedstock crop for bioenergy due to its high biomass yields. However, early growth phases of sorghum are sensitive to cold stress, limiting its planting in temperate environments. Cold adaptability is crucial for cultivating bioenergy and grain sorghum at higher latitudes and elevations, or for extending the growing season. Identifying genes and alleles that enhance biomass accumulation under early cold stress can lead to improved sorghum varieties through breeding or genetic engineering. We conducted image-based phenotyping on 369 accessions from the sorghum Bioenergy Association Panel (BAP) in a controlled environment with early cold treatment. The BAP includes diverse accessions with dense genotyping and varied racial, geographical, and phenotypic backgrounds. Daily, non-destructive imaging allowed temporal analysis of growth-related traits and water use efficiency (WUE). A genome-wide association study (GWAS) was performed to identify genomic intervals and genes associated with cold stress response. The GWAS identified transient quantitative trait loci (QTL) strongly associated with growth-related traits, enabling an exploration of the genetic basis of cold stress response at different developmental stages. This analysis of daily growth traits, rather than endpoint traits, revealed early transient QTL predictive of final phenotypes. The study identified both known and novel candidate genes associated with growth-related traits and temporal responses to cold stress. The identified QTL and candidate genes contribute to understanding the genetic mechanisms underlying sorghum's response to cold stress. These findings can inform breeding and genetic engineering strategies to develop sorghum varieties with improved biomass yields and resilience to cold, facilitating earlier planting, extended growing seasons, and cultivation at higher latitudes and elevations.

59 BASIC BIOLOGICAL SCIENCES↗

Correlation and co-localization of QTL for stomatal density, canopy temperature, and productivity with and without drought stress in Setaria

Abstract Mechanistic modeling indicates that stomatal conductance could be reduced to improve water use efficiency (WUE) in C4 crops. Genetic variation in stomatal density and canopy temperature was evaluated in the model C4 genus, Setaria. Recombinant inbred lines (RILs) derived from a Setaria italica×Setaria viridis cross were grown with ample or limiting water supply under field conditions in Illinois. An optical profilometer was used to rapidly assess stomatal patterning, and canopy temperature was measured using infrared imaging. Stomatal density and canopy temperature were positively correlated but both were negatively correlated with total above-ground biomass. These trait relationships suggest a likely interaction between stomatal density and the other drivers of water use such as stomatal size and aperture. Multiple quantitative trait loci (QTL) were identified for stomatal density and canopy temperature, including co-located QTL on chromosomes 5 and 9. The direction of the additive effect of these QTL on chromosome 5 and 9 was in accordance with the positive phenotypic relationship between these two traits. This, along with prior experiments, suggests a common genetic architecture between stomatal patterning and WUE in controlled environments with canopy transpiration and productivity in the field, while highlighting the potential of Setaria as a model to understand the physiology and genetics of WUE in C4 species.

59 BASIC BIOLOGICAL SCIENCES↗

Linkage mapping evidence for a syntenic QTL associated with flowering time in perennial C 4 rhizomatous grasses Miscanthus and switchgrass

Flowering in perennial species is directed via complex signalling pathways that adjust to developmental regulations and environmental cues. Synchronized flowering in certain environments is a prerequisite to commercial seed production, and so the elucidation of the genetic architecture of flowering time in Miscanthus and switchgrass could aid breeding in these underdeveloped species. In this context, we assessed a mapping population in Miscanthus and two ecologically diverse switchgrass mapping populations over 3 years from planting. Multiple flowering time quantitative trait loci (QTL) were identified in both species. Remarkably, the most significant Miscanthus and switchgrass QTL proved to be syntenic, located on linkage groups 4 and 2, with logarithm of odds scores of 17.05 and 21.8 respectively. These QTL regions contained three flowering time transcription factors: Squamosa Promoter-binding protein-Like, MADS-box SEPELLATA2 and gibberellin-responsive bHLH137. The former is emerging as a key component of the age-related flowering time pathway.

54 ENVIRONMENTAL SCIENCES↗

QTL Mapping of Seed Fatty Acid Contents in Camelina sativa Under Heat Stress

Heat stress alters oil quality in oilseed crops, yet its genetic underpinnings in Camelina sativa remain unclear. This study investigated the genetic basis of heat-induced changes in seed fatty acids using a recombinant inbred line (RIL) population derived from a cross between two camelina varieties, Suneson and Pryzeth. Exposure to high temperature during reproductive growth led to increased proportions of saturated (C16:0, C18:0) and monounsaturated (C18:1) fatty acids, whereas polyunsaturated C18:3, total unsaturated fatty acids (UFA) and the PUFA/MUFA ratio were decreased, suggesting an inhibition of the C18:1 → C18:2 → C18:3 desaturation pathway. A high-density linkage map (4981 bins across 20 chromosomes) was built, and 25 QTLs for fatty acids were detected, with hotspots on chromosomes 1, 9, 12, 13, 16, and 20. A major QTL on chromosome 1 (~ 80 cM) explained the largest variance component for PUFA/MUFA under heat. Three desaturase genes (FAD2, FAD7, FAD8) were located within key QTL intervals, nominating them as candidates for modulating unsaturation under elevated temperature. These results provide a genetic basis for fine mapping and functional validation, supporting future molecular and breeding efforts to stabilize oil quality under warming conditions.

Camelina↗

Genetic dissection of natural variation in oilseed traits of camelina by whole‐genome resequencing and QTL mapping

Abstract Camelina [ Camelina sativa (L.) Crantz] is an oilseed crop in the Brassicaceae family that is currently being developed as a source of bioenergy and healthy fatty acids. To facilitate modern breeding efforts through marker‐assisted selection and biotechnology, we evaluated genetic variation among a worldwide collection of 222 camelina accessions. We performed whole‐genome resequencing to obtain single nucleotide polymorphism (SNP) markers and to analyze genomic diversity. We also conducted phenotypic field evaluations in two consecutive seasons for variations in key agronomic traits related to oilseed production such as seed size, oil content (OC), fatty acid composition, and flowering time. We determined the population structure of the camelina accessions using 161,301 SNPs. Further, we identified quantitative trait loci (QTL) and candidate genes controlling the above field‐evaluated traits by genome‐wide association studies (GWAS) complemented with linkage mapping using a recombinant inbred line (RIL) population. Characterization of the natural variation at the genome and phenotypic levels provides valuable resources to camelina genetic studies and crop improvement. The QTL and candidate genes should assist in breeding of advanced camelina varieties that can be integrated into the cropping systems for the production of high yield of oils of desired fatty acid composition.

59 BASIC BIOLOGICAL SCIENCES↗

Integrative path modeling and QTL mapping identify maturity, stem strength, and cell wall composition driving lettuce resistance to Sclerotinia minor

Lettuce ( Lactuca sativa ) is highly vulnerable to Sclerotinia minor , the pathogen causing lettuce drop. Breeding for resistance is the most effective control strategy; however, full resistance has not been achieved, and current partial resistance sources are often linked with undesirable traits, such as early bolting. This study aimed to unravel the genetic basis of partial resistance to S. minor and its relationship with plant maturity (bolting), stem mechanical strength (SMS), and cell wall composition (CWC) using a recombinant inbred line (RIL) population derived from a cross between the susceptible iceberg cv. ‘Salinas’ and the resistant oil-seed accession PI 251246. Field evaluations indicated that resistance was linked to earlier bolting, stronger stems, and higher pentose content. Path analysis demonstrated that earlier-maturing plants exhibited increased resistance through enhanced SMS and modified CWC, particularly with higher xylose and lower arabinose levels. Further analysis indicated a significant relationship between syringyl lignin content and resistance, especially in plants with varying bolting responses. Three key quantitative trait loci (QTLs) on linkage groups (LG) 2, 6, and 7 were consistently associated with resistance, bolting, and SMS. Importantly, residual QTL analysis revealed that the resistance locus on LG7 acted independently of maturity, suggesting a distinct resistance mechanism. Callose synthase emerged as a key candidate gene within the LG7 resistance QTL, located near - but distinct from - genes associated with plant maturity and flowering. These findings provide valuable insights into decoupling resistance from early bolting, suggesting a pathway for breeding lettuce cultivars with improved disease resistance and delayed bolting.

Lactuca↗

Bulk segregant and QTL analysis of maltose metabolism in Saccharomyces eubayanus

This study investigates natural variation in maltose utilization among Saccharomyces eubayanus strains isolated from different tree hosts. An F2 population was generated from a cross between strain QC18 (Quercus-associated) and strain CL467.1 (Nothofagus-associated). Bulk segregant analysis (BSA) was performed on the F2 offspring, and QTL mapping was conducted by whole-genome sequencing of two pools of 30 segregants each, representing the lowest and highest growth in high maltose concentrations. For QTL analysis, the parental strains QC18 and CL467.1 were also sequenced.

evolutionary plasticity↗

QTL analysis of salt tolerance in Sorghum bicolor during whole‐plant growth stages

Abstract To study the salt tolerance genetics of sorghum, 181 recombinant inbred lines (RILs) were used to locate quantitative trait loci (QTLs) underlying salt stress adaptability. Six traits, namely, plant height (PH), stem diameter (SD), total biomass (TB), stem fresh weight (SFW), juice weight (JW) and Brix, were investigated under normal and salt stress conditions in two years. A total of 53 QTLs for the six traits under both conditions and their corresponding salt tolerance index (STI) were detected and phenotypic variation explained (PVE) ranged from 4.16% to 20.42%. Six of the QTLs, qTB6 , qSFW9 , qJW9 , qBrix2 , qBrix10 and qSTI‐Brix9, were the main effect QTLs controlling salt tolerance and had a PVE more than 10%. qSFW9 and qJW9 colocalized in the same marker interval as SB5069‐UGSM18 and had PVEs of 17.70% and 14.20%, respectively, with positive effects from L‐Tian. QTL clusters controlling PH, TB, STI‐TB, SFW and JW were consistently mapped in the marker interval of Xcup19‐SB4177 on chromosome 7. These locations might serve as target sites for marker‐assisted selection (MAS) in improving salt tolerance of sorghum.

Wang, Hailian↗

Identification and mapping of quantitative trait loci for Fusarium head blight resistance in a synthetic hexaploid × hard red spring wheat population

Abstract Fusarium head blight (FHB), caused byFusarium graminearumSchwabe, is one of the most devastating diseases in wheat (Triticum aestivumL.). The synthetic hexaploid wheat line Largo was developed from a cross between the durum wheat [T. turgidumssp.durum(Desf.) Husn.] variety Langdon and theAegilops tauschiiCosson accession PI 268210, and it was previously found to have a moderate level of FHB resistance. This study was conducted to identify quantitative trait loci (QTL) associated with FHB resistance using a population of 188 recombinant inbred lines (RILs) from a cross between Largo and the susceptible wheat line ND495. The RILs were evaluated for Type II resistance in two greenhouse and two field environments. The disease severity and 90K single‐nucleotide polymorphism marker data were used for QTL analysis, which revealed six QTL on chromosomes 1D, 2D, 5B, and 7D. Four QTL (QFhb.rwg‐1D,QFhb.rwg‐5B,QFhb.rwg‐7D.1, andQFhb.rwg‐7D.3) from Largo had minor effects, whereas two QTL (QFhb.rwg‐2DandQFhb.rwg‐7D.2) from ND495 showed large effects on FHB resistance. The result suggested that ND495 may possess suppressor or susceptibility gene(s) suppressing or masking FHB resistance controlled by the resistance QTL. Among these QTL, four coincided with previously reported QTL, includingFhb9, and two (QFhb.rwg‐1DandQFhb.rwg‐7D.1) are likely novel QTL. From the six QTL regions, 10 Kompetitive allele‐specific PCR markers were developed and validated for marker‐assisted selection. The QTL detected from the resistant and susceptible parents enhance our understanding of FHB resistance expression and provide new resources for improving FHB resistance in wheat.

Genetics & Heredity↗

The genetic basis for panicle trait variation in switchgrass ( Panicum virgatum )

Grass species exhibit large diversity in panicle architecture influenced by genes, the environment, and their interaction. The genetic study of panicle architecture in perennial grasses is limited. In this study, we evaluate the genetic basis of panicle architecture including panicle length, primary branching number, and secondary branching number in an outcrossed switchgrass QTL population grown across ten field sites in the central USA through multi-environment mixed QTL analysis. We also evaluate genetic effects in a diversity panel of switchgrass grown at three of the ten field sites using genome-wide association (GWAS) and multivariate adaptive shrinkage. Furthermore, we search for candidate genes underlying panicle traits in both of these independent mapping populations. Overall, 18 QTL were detected in the QTL mapping population for the three panicle traits, and 146 unlinked genomic regions in the diversity panel affected one or more panicle trait. Twelve of the QTL exhibited consistent effects (i.e., no QTL by environment interactions or no QTL × E), and most (four of six) of the effects with QTL × E exhibited site-specific effects. Most (59.3%) significant partially linked diversity panel SNPs had significant effects in all panicle traits and all field sites and showed pervasive pleiotropy and limited environment interactions. Panicle QTL co-localized with significant SNPs found using GWAS, providing additional power to distinguish between true and false associations in the diversity panel.

59 BASIC BIOLOGICAL SCIENCES↗