Transcriptome Sequencing Analysis Provides Insights Into the Response to Fusarium oxysporum in Lilium pumilum.

Lily basal rot, caused by Fusarium oxysporum f. sp. lilii, is one of the most serious diseases of lily. Although the lily germplasm which is resistant to F. oxysporum has been used in disease-resistant breeding, few studies on its molecular mechanism of disease resistance have been reported. To comprehensively study the mechanism of resistance to F. oxysporum, transcriptome sequencings of root tissues from Lilium pumilum inoculated with F. oxysporum or sterile water for 6, 12, or 24 h were performed. A total of 50 GB of data were obtained from the transcriptome sequencings of the 6 L. pumilum samples, and 217 098 Unigenes were obtained after the de novo assembly, of which 38.36% Unigenes were annotated. The sequencing results showed that the numbers of differentially expressed genes at 6, 12, and 24 h after inoculation compared with the control were 111, 254, and 2500, respectively. The functional enrichment analysis of the differentially expressed genes showed that several pathways were involved in responses of L. pumilum, mainly including starch and sucrose metabolism, glycolysis/gluconeogenesis, phenylpropanoid biosynthesis, plant hormone signal transduction, flavonoid biosynthesis, vitamin B6 (VB6) biosynthesis, acid biosynthesis, proteasome, and ribosome. Transcription factor analysis revealed that the WRKY and ERF families played important roles in responses of L. pumilum to F. oxysporum. The results of this study elucidate the molecular responses to F. oxysporum in lily and lay a theoretical foundation for improving lily breeding and strategies for lily basal rot resistance.

Characterization of Conserved and Novel microRNAs in Lilium lancifolium Thunb. by High-Throughput Sequencing.

MicroRNAs (miRNAs) are among the class of noncoding small RNA molecules and play a crucial role in post-transcriptional regulation in plants. Although Lilium is one of the most popular ornamental flowers worldwide, however, there is no report on miRNAs identification. In the present study, therefore, miRNAs and their targets were identified from flower, leaf, bulblet and bulb of Lilium lancifolium Thunb. by high-throughput sequencing and bioinformatics analysis. In this study, a total of 38 conserved miRNAs belonging to 17 miRNA families and 44 novel miRNAs were identified. In total, 366 target genes for conserved miRNAs and 415 target genes for novel miRNAs were predicted. The majority of the target genes for conserved miRNAs were transcriptional factors and novel miRNAs targeted mainly protein coding genes. A total of 53 cleavage sites belonging to 6 conserved miRNAs families and 14 novel miRNAs were identified using degradome sequencing. Twenty-three miRNAs were randomly selected, then, their credibility was confirmed using northern blot or stem-loop qRT-PCR. The results from qRT-PCR analysis showed the expression pattern of 4 LL-miRNAs was opposite to their targets. Therefore, our finding provides an important basis to understand the biological functions of miRNAs in Lilium.

Determining spatio-temporal distribution of bee forage species of Al-Baha region based on ground inventorying supported with GIS applications and Remote Sensed Satellite Image analysis.

In arid zones, the shortage of bee forage is critical and usually compels beekeepers to move their colonies in search of better forages. Identifying and mapping the spatiotemporal distribution of the bee forages over given area is important for better management of bee colonies. In this study honey bee plants in the target areas were inventoried following, ground inventory work supported with GIS applications. The study was conducted on 85 large plots of 50 × 50 m each. At each plot, data on species name, height, base diameter, crown height, crown diameter has been taken for each plant with their respective geographical positions. The data were stored, and processed using Trimble GPS supported with ArcGIS10 software program. The data were used to estimate the relative frequency, density, abundance and species diversity, species important value index and apicultural value of the species. In addition, Remotely Sensed Satellite Image of the area was obtained and processed using Hopfield Artificial Neural Network techniques. During the study, 182 species from 49 plant families were identified as bee forages of the target area. From the total number of species; shrubs, herbs and trees were accounting for 61%, 27.67%, and 11.53% respectively. Of which Ziziphus spina-christi, Acacia tortilis, Acacia origina, Acacia asak, Lavandula dentata, and Hypoestes forskaolii were the major nectar source plants of the area in their degree of importance. The average vegetation cover values of the study areas were low (<30%) with low Shannon's species diversity indices (H') of 0.5-1.52 for different sites. Based on the eco-climatological factors and the variations in their flowering period, these major bee forage species were found to form eight distinct spatiotemporal categories which allow beekeepers to migrate their colonies to exploit the resources at different seasons and place. The Remote Sensed Satellite Image analysis confirmed the spatial distribution of the bee forage resources as determined by the ground inventory work. An integrated approach, combining the ground inventory work with GIS and satellite image processing techniques could be an important tool for characterizing and mapping the available bee forage resources leading to their efficient and sustainable utilization.

Natural and within-farmland biodiversity enhances crop productivity.

Ongoing expansion of large-scale agriculture critically threatens natural habitats and the pollination services they offer. Creating patches with high plant diversity within farmland is commonly suggested as a measure to benefit pollinators. However, farmers rarely adopt such practice, instead removing naturally occurring plants (weeds). By combining pollinator exclusion experiments with analysis of honeybee behaviour and flower-visitation webs, we found that the presence of weeds allowed pollinators to persist within sunflower fields, maximizing the benefits of the remaining patches of natural habitat to productivity of this large-scale crop. Weed diversity increased flower visitor diversity, hence ameliorating the measured negative effects of isolation from natural habitat. Although honeybees were the most abundant visitors, diversity of flower visitors enhanced honeybee movement, being the main factor influencing productivity. Conservation of natural patches combined with promoting flowering plants within crops can maximize productivity and, therefore, reduce the need for cropland expansion, contributing towards sustainable agriculture.