Project description:This dataset includes mass spectra data for MacNeill et al. 2025, Nectar metabolomes contribute to pollination syndromes. This study primarily focuses on Salvia but includes other species in the order Lamiales as well contrasting nectar and foliar chemical traits of bee and hummingbird pollination syndromes.
2025-04-05 | MSV000097544 | MassIVE
Project description:Genetic basis of floral mechanical isolation between two hummingbird-pollinated plants
Project description:In the present study, we elucidate the molecular and hormonal role of the Six-rowed spike 2 (Vrs2) — a SHORT INTERNODES (SHI) transcriptional regulator during barley inflorescence and shoot development. Here we show that Vrs2 is specifically involved in floral organ patterning and phase duration by maintaining hormonal homeostasis and gradients during normal spike development; but similarly influenced plant stature traits. Furthermore, we establish a first link between the SHI-protein family and sucrose metabolism during organ growth and development, which may have implications for deeper molecular insights into crops' inflorescence and plant architecture. Differential gene expression study between BW-NIL(vrs2.e) vs. Bowman was done on the extracted RNA from immature shoot apices to infer the differences at level of expression at early spike developmental stages (triple mound (TM), glume primordia (GP), stamen primordia (SP), awn primordia (AP)).
Project description:Transcriptome sequencing has become the main methodology for analyzing the relationship between genes and characteristics of interests, particularly those associated with diseases and economic traits. Because of its functional superiority, commercial royal jelly (RJ) and its production are major areas of focus in the field of apiculture. Multiple lines of evidence have demonstrated that many factors affect RJ output by activating or inhibiting various target genes and signaling pathways to augment their efficient replication. The coding sequences made available by the Honey Bee Genome Sequencing Consortium have permitted a pathway-based approach for investigating the development of the hypopharyngeal glands (HGs). In the present study, 3573941, 3562730, 3551541, 3524453, and 3615558 clean reads were obtained from the HGs of five full-sister honey bee samples using Solexa RNA sequencing technology. These reads were then assembled into 18378, 17785, 17065, 17105, and 17995 unigenes, respectively, and aligned to the DFCI Honey Bee Gene Index database. The differentially expressed genes (DEGs) data were also correlated with detailed morphological data for HGs acini. The results identify areas that warrant further study, including those that can be used to improve honey bee breeding techniques and help ensure stable yields of RJ with high quality traits.
2014-05-20 | GSE47136 | GEO
Project description:Role of PMEI in floral architecture
Project description:Mapping the genetic architecture of RNA transcript abundances has potential for revealing molecular mechanisms underlying complex traits like disease. Gene expression microarrays allow monitoring genetic control on a whole transcriptome level, but validity and reproducibility of microarray data is a subject of ongoing scientific debate. Here we demonstrate how combining genetic and gene expression data provide a basis for biologically relevant assessment of the current state of microarray technology. We profile liver samples from a murine F2 intercross population using Agilent microarrays. Tissue profiling in a mouse F2 cross. We analyzed 298 Liver samples.
Project description:Summary Mapping the genetic architecture of RNA transcript abundances has potential for revealing molecular mechanisms underlying complex traits like disease. Gene expression microarrays allow monitoring genetic control on a whole transcriptome level, but validity and reproducibility of microarray data is a subject of ongoing scientific debate. Here we demonstrate how combining genetic and gene expression data provide a basis for biologically relevant assessment of the current state of microarray technology. We profile liver samples from a murine F2 intercross population using Affymetrix microarrays. Tissue profiling in a mouse F2 cross. We analyzed 294 Liver samples.