Dataset Information

Genetic mapping of a pollinator preference trait: Nectar volume in sunflower (Helianthus annuus L.).

ABSTRACT: Although high pollinator visitation is crucial to ensure the yields of pollinator-dependent crops, the quantitative trait loci (QTL) controlling nectar volume in sunflower (Helianthus annuus L.), a pollinator preference trait, have yet to be identified. To address this, a recombinant inbred line mapping population, derived from lines with contrasting nectar volume, was used to identify loci responsible for the phenotype. As a result, linkage mapping and QTL analysis discovered major loci on chromosomes 2 and 16 that are associated with variation in nectar volume in sunflower. Increased nectar volume is also associated with increased sugars and total energy available per floret. The regions on chromosomes 2 and 16 associated with the nectar phenotype exhibit indications of chromosome structural variation, such that the phenotype is associated with rearrangements affecting regions containing hundreds of genes. Candidate genes underlying QTL on chromosomes 9 and 16 are homologous to genes with nectary function in Arabidopsis. These results have implications for sunflower breeding, to enhance pollination efficiency in sunflower, as well as current and future studies on sunflower evolution.

SUBMITTER: Barstow AC

PROVIDER: S-EPMC9806390 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Genetic mapping of a pollinator preference trait: Nectar volume in sunflower (<i>Helianthus annuus</i> L.).

Barstow Ashley C AC Prasifka Jarrad R JR Attia Ziv Z Kane Nolan C NC Hulke Brent S BS

Frontiers in plant science 20221219

Although high pollinator visitation is crucial to ensure the yields of pollinator-dependent crops, the quantitative trait loci (QTL) controlling nectar volume in sunflower (<i>Helianthus annuus</i> L.), a pollinator preference trait, have yet to be identified. To address this, a recombinant inbred line mapping population, derived from lines with contrasting nectar volume, was used to identify loci responsible for the phenotype. As a result, linkage mapping and QTL analysis discovered major loci ...[more]

PMID: 36600919

Similar Datasets

Project description:Background: Respiratory allergy triggered by pollen allergens is increasing at an alarming rate worldwide. Sunflower pollen is thought to be an important source of inhalant allergens. Present study aims to identify the prevalence of sunflower pollinosis among the Indian allergic population and characterizes the pollen allergens using immuno-proteomic tools. Methodology: Clinico-immunological tests were performed to understand the prevalence of sensitivity towards sunflower pollen among the atopic population. Sera from selected sunflower positive patients were used as probe to detect the IgE-reactive proteins from the one and two dimensionally separated proteome of sunflower pollen. The antigenic nature of the sugar moiety of the glycoprotein allergens was studied by meta-periodate modification of IgE-immunoblot. Finally, these allergens were identified by mass-spectrometry (MALDI TOF/TOF and LC ESI qTOF). MASCOT searching was performed against NCBInr database. However, Helianthus annuus genome is not fully sequenced and partially annotated. So in case of low confidence (p> 0.05) protein identification, searching was performed against EST library of Helianthus annuus. Results: Prevalence of sunflower pollen allergy was observed among 21% of the atopic population and associated with elevated level of specific IgE and histamine in the sera of these patients. Immunoscreening of sunflower pollen proteome with patient serum detected seven IgE-reactive proteins with varying molecular weight and pI. Hierarchical clustering of 2D-immunoblot data highlighted three allergens characterized by a more frequent immuno-reactivity and increased levels of IgE antibodies in the sera of susceptible patients. These allergens were considered as the major allergens of sunflower pollen and were found to have their glycan moiety critical for inducing IgE response. Homology driven search of MS/MS data of these IgE-reactive proteins identified seven previously unreported allergens from sunflower pollen. Three major allergenic proteins were identified as two non-isoformic pectate lyases and a cystein protease. Conclusion: Novelty of the present report is the identification of a panel of seven sunflower pollen allergens for the first time at immuno-biochemical and proteomic level, which substantiated the clinical evidence of sunflower allergy. Further purification and recombinant expression of these allergens will improve component-resolved diagnosis and therapy of pollen allergy.

Project description:Drought is a major agricultural challenge that is expected to worsen with climate change. A better understanding of drought responses has the potential to inform efforts to breed more tolerant plants. We assessed leaf trait variation and covariation in cultivated sunflower (Helianthus annuus L.) in response to water limitation. Plants were grown under four levels of water availability and assessed for environmentally induced plasticity in leaf stomatal and vein traits as well as biomass (performance indicator), mass fractions, leaf area, leaf mass per area, and chlorophyll content. Overall, biomass declined in response to stress; these changes were accompanied by responses in leaf-level traits including decreased leaf area and stomatal size, and increased stomatal and vein density. The magnitude of trait responses increased with stress severity and relative plasticity of smaller-scale leaf anatomical traits was less than that of larger-scale traits related to construction and growth. Across treatments, where phenotypic plasticity was observed, stomatal density was negatively correlated with stomatal size and positively correlated with minor vein density, but the correlations did not hold up within treatments. Four leaf traits previously shown to reflect major axes of variation in a large sunflower diversity panel under well-watered conditions (i.e. stomatal density, stomatal pore length, vein density, and leaf mass per area) predicted a surprisingly large amount of the variation in biomass across treatments, but trait associations with biomass differed within treatments. Additionally, the importance of these traits in predicting variation in biomass is mediated, at least in part, through leaf size. Our results demonstrate the importance of leaf anatomical traits in mediating drought responses in sunflower, and highlight the role that phenotypic plasticity and multi-trait phenotypes can play in predicting productivity under complex abiotic stresses like drought.

Dataset Information

Genetic mapping of a pollinator preference trait: Nectar volume in sunflower (Helianthus annuus L.).

Publications

Genetic mapping of a pollinator preference trait: Nectar volume in sunflower (<i>Helianthus annuus</i> L.).

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets