The R2R3-MYB Transcription Factor Gene Family in Maize

MYB proteins comprise a large family of plant transcription factors, members of which perform a variety of functions in plant biological processes. To date, no genome-wide characterization of this gene family has been conducted in maize (Zea mays). In the present study, we performed a comprehensive computational analysis, to yield a complete overview of the R2R3-MYB gene family in maize, including the phylogeny, expression patterns, and also its structural and functional characteristics. The MYB gene structure in maize and Arabidopsis were highly conserved, indicating that they were originally compact in size. Subgroup-specific conserved motifs outside the MYB domain may reflect functional conservation. The genome distribution strongly supports the hypothesis that segmental and tandem duplication contribute to the expansion of maize MYB genes. We also performed an updated and comprehensive classification of the R2R3-MYB gene families in maize and other plant species. The result revealed that the functions were conserved between maize MYB genes and their putative orthologs, demonstrating the origin and evolutionary diversification of plant MYB genes. Species-specific groups/subgroups may evolve or be lost during evolution, resulting in functional divergence. Expression profile study indicated that maize R2R3-MYB genes exhibit a variety of expression patterns, suggesting diverse functions. Furthermore, computational prediction potential targets of maize microRNAs (miRNAs) revealed that miR159, miR319, and miR160 may be implicated in regulating maize R2R3-MYB genes, suggesting roles of these miRNAs in post-transcriptional regulation and transcription networks. Our comparative analysis of R2R3-MYB genes in maize confirm and extend the sequence and functional characteristics of this gene family, and will facilitate future functional analysis of the MYB gene family in maize

Should Easier Access to International Credit Replace Foreign Aid?

We examine the interaction between foreign aid and binding borrowing constraint for a recipient country. We also analyze how these two instruments affect economic growth via non-linear relationships. First of all, we develop a two-country, two-period trade-theoretic model to develop testable hypotheses and then we use dynamic panel analysis to test those hypotheses empirically. Our main findings are that: (i) better access to international credit for a recipient country reduces the amount of foreign aid it receives, and (ii) there is a critical level of international financial transfer, and the marginal effect of foreign aid is larger than that of loans if and only if the transfer (loans or foreign aid) is below this critical level

A Further Step into the ELGH and TLGH for Spain and Italy

Nowadays many developing countries focus on economic policies for promoting international tourism and exports expansion as a potential source of economic growth of the country. However, the understanding of the relationship between exports and economic growth is still ongoing. When treating the relationship between tourism and economic growth, considering tourism as a non-traditional export few studies have been published to date. This paper has the objective to assess if exports and tourism have really promoted growth by means of the export-led growth hypothesis (ELGH) and the tourism-led growth hypothesis (TLGH). The cases under analysis are Spain and Italy, two of the most important countries worldwide regarding the expansion of tourism. Cointegration techniques and the multivariate Granger causality test are applied. Results reveal that exports cause economic growth in the long-term for both countries, whilst only for Spain tourism appears as a factor which influences economic growth in the lon-run

Modelling tourism and travel using tourism satellite accounts and tourism policy and forecasting models

SIGLEAvailable from British Library Document Supply Centre-DSC:3597.12575(2001/4) / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Using the panel cointegration approach to analyse the determinants of tourism demand in South Africa

Estimating tourism demand has become a challenge among researchers, as identification of key determinants is important for policymakers at a time when tourism has become the world's largest industry. Using a theoretical framework based on the gravity model, this paper models inbound tourism demand for South Africa to estimate price and income sensitivities as well as the impact of other important factors that affect tourist flows, such as the location of markets and socio-political factors. Given the non-stationary but cointegrated nature of the panel data, panel cointegration estimation techniques are employed. The results show that tourists are sensitive to price changes in South Africa and also to tourism price changes in competing destinations. The level of development, tourism infrastructure, distance (or transportation costs), common border and language are also found to affect arrivals. The results also indicate the need to conduct estimation by regional groupings for a better understanding of different markets