AFLP/SSR mapping of resistance genes to Alectra vogelii in cowpea (Vigna unguiculata l. Walp)

The parasite weed Alectra vogelii (Benth) causes significant yield reduction of cowpea in Africa. To find and map the resistance gene to A. vogelii in cowpea, a F2 population from a cross involving a resistant parent IT81D-994 and a susceptible TVX3236 was screened. Amplified fragment length polymorphism (AFLP) in combination with Single Sequence Repeat (SSR) analysis was used to identify markers that may be linked to the gene Rav3 conferring resistance to A. vogelii in the cowpea cultivar IT81D-994. The analysis of F2 individuals scored for resistance showedthat a single dominant gene conditioned A. vogelii resistance in IT81D-994 with a probability of 30 to 50%. Sixty-six AFLP/SSR markers were identified. Using MAPMAKER, four linkage groups were found. The first group showed 33 markers linked to the susceptible gene. The closest identified marker was 21.4 centimorgans away from the susceptible gene. The primer combination that showed the closest linkage was 809ACG8 (E-ACG 8 + UBC-809). The second group indicated 4 markers linked together while the third and the fourth groups showed 2 markers linkedtogether respectively. No markers were found linked to the resistance gene Rav3 conferring the resistance in the cultivated cowpea cultivar IT81D-994.La plante parasite Alectra vogelii (Benth) provoque une réduction significative du rendement de niébé en Afrique. Pour repérer et cartographier le gène de résistance à A. vogelii, une population F2 issue d’un croisement impliquant le cultivar résistant IT81D-994 et le cultivar sensible TVX3236 a été criblée. La technique Amplified fragment length polymorphism (AFLP) en combinaison avec des Séquences Simples Répétés (SSR) a été utilisée pour identifier les marqueurs qui seraient liés au gène Rav3 qui confère la résistance à A. vogelii chez le cultivar de niébé IT81D- 994. L’analyse des individus F2 montrant une résistance indique qu’un seul gène dominant conditionne la résistance à A. vogelii chez IT81D-994 avec une probabilité de 30 à 50 %. Soixante six marqueurs AFLP/SSR ont été identifiés. A l’aide de MAPMAKER, 4 groupes de liaison ont été trouvés. Le premier groupe montre 33 marqueurs liés au gène sensible. Le marqueur le plus proche identifié est à 21.4 centimorgans du gène sensible. La combinaison d’amorces ayant des liaisons les plus proches était 809ACG8 (E-ACG 8 + UBC-809). Le secondgroupe montre 4 marqueurs liés ensemble tandis que le troisième et le quatrième groupe montrent 2 marqueurs liés entre eux respectivement. Aucun marqueur n’a été trouvé lié au gène Rav3 qui confère la résistance au cultivar de niébé cultivé IT81D-994.Key words: Parasite, weeds, legumes, molecular marker

Strategies for Broadening Participation of Underrepresented Minority Students in STEM

poster abstractThe Louis Stokes Midwest Center of Excellence (LSMCE) was created in 2012 to communicate evidence-based program effectiveness garnered from the Louis Stokes Alliances for Minority Participation (LSAMP) consortium to a broader audience. The goal of LSMCE is to serve as a national hub of information for scholars to access data, models, and funding opportunities in broadening the participation of underrepresented minority (URM) students in Science, Technology, Engineering, and Mathematics (STEM). The Center is comprised of three lead institutions: Chicago State University, Indiana University-Purdue University Indianapolis and Department of Energy-Argonne National Laboratory. The Center outcomes are: 1) development of the cLSMCE information hub to provide consistent online resources and sustained initiatives to showcase best practices in STEM teaching/learning, information dissemination and outreach; 2) faculty engagement in establishing programs, obtaining support and promoting growth across institutions; 3) student development skill-building webinars and workshops; 4) annual conferences providing LSMCE partners and LSAMP community members the opportunity to network and learn/share successful program models, celebrate student success, and be a forum for junior researchers to present in a supportive environment; and 5) partnering with key industry and corporate organizations to provide students access to internships, as well as, sponsorship of LSMCE initiatives and awards. The Center is currently in the fourth year of a five year grant and has recruited twenty Midwestern non-LSAMP schools. It has collaborated with them in developing strategies to improve their URM students’ performance, persistence and graduation in STEM degree programs. The Center also affords a professional platform for their faculty and students to participate in STEM activities

Spatio-temporal expression patterns of Arabidopsis thaliana and Medicago truncatula defensin-like genes

Plant genomes contain several hundred defensin-like (DEFL) genes that encode short cysteine-rich proteins resembling defensins, which are well known antimicrobial polypeptides. Little is known about the expression patterns or functions of many DEFLs because most were discovered recently and hence are not well represented on standard microarrays. We designed a custom Affymetrix chip consisting of probe sets for 317 and 684 DEFLs from Arabidopsis thaliana and Medicago truncatula, respectively for cataloging DEFL expression in a variety of plant organs at different developmental stages and during symbiotic and pathogenic associations. The microarray analysis provided evidence for the transcription of 71% and 90% of the DEFLs identified in Arabidopsis and Medicago, respectively, including many of the recently annotated DEFL genes that previously lacked expression information. Both model plants contain a subset of DEFLs specifically expressed in seeds or fruits. A few DEFLs, including some plant defensins, were significantly up-regulated in Arabidopsis leaves inoculated with Alternaria brassicicola or Pseudomonas syringae pathogens. Among these, some were dependent on jasmonic acid signaling or were associated with specific types of immune responses. There were notable differences in DEFL gene expression patterns between Arabidopsis and Medicago, as the majority of Arabidopsis DEFLs were expressed in inflorescences, while only a few exhibited root-enhanced expression. By contrast, Medicago DEFLs were most prominently expressed in nitrogen-fixing root nodules. Thus, our data document salient differences in DEFL temporal and spatial expression between Arabidopsis and Medicago, suggesting distinct signaling routes and distinct roles for these proteins in the two plant species

Do NERICA rice cultivars express resistance to Striga hermonthica (Del.) Benth. and Striga asiatica (L.) Kuntze under field conditions?

The parasitic weeds Striga asiatica and Striga hermonthica cause high yield losses in rain-fed upland rice in Africa. Two resistance classes (pre- and post-attachment) and several resistant genotypes have been identified among NERICA (New Rice for Africa) cultivars under laboratory conditions (in vitro) previously. However, little is known about expression of this resistance under field conditions. Here we investigated (1) whether resistance exhibited under controlled conditions would express under representative Striga-infested field conditions, and (2) whether NERICA cultivars would achieve relatively good grain yields under Striga-infested conditions. Twenty-five rice cultivars, including all 18 upland NERICA cultivars, were screened in S. asiatica-infested (in Tanzania) and S. hermonthica-infested (in Kenya) fields during two seasons. Additionally, a selection of cultivars was tested in vitro, in mini-rhizotron systems. For the first time, resistance observed under controlled conditions was confirmed in the field for NERICA-2, -5, -10 and -17 (against S. asiatica) and NERICA-1 to -5, -10, -12, -13 and -17 (against S. hermonthica). Despite high Striga-infestation levels, yields of around 1.8 t ha−1 were obtained with NERICA-1, -9 and -10 (in the S. asiatica-infested field) and around 1.4 t ha−1 with NERICA-3, -4, -8, -12 and -13 (in the S. hermonthica-infested field). In addition, potential levels of tolerance were identified in vitro, in NERICA-1, -17 and -9 (S. asiatica) and in NERICA-1, -17 and -10 (S. hermonthica). These findings are highly relevant to rice agronomists and breeders and molecular geneticists working on Striga resistance. In addition, cultivars combining broad-spectrum resistance with good grain yields in Striga-infested fields can be recommended to rice farmers in Striga-prone areas

Parasitic weed incidence and related economic losses in rice in Africa

Parasitic weeds pose increasing threats to rain-fed rice production in Africa. Most important species are Striga asiatica, S. aspera and S. hermonthica in rain-fed uplands, and Rhamphicarpa fistulosa in rain-fed lowlands. Information on the regional spread and economic importance of parasitic weeds in cereal production systems is scant. This article presents the first multi-species, multi-country, single-crop impact assessment of parasitic weeds in Africa. A systematic search of public international and national herbaria and the scientific literature was conducted to collect all available data on the regional distribution, incidences and related yield losses of the most important parasitic weeds in rice. Herbaria specimens were geo-referenced and these coordinates were overlapped with rain-fed rice areas. Probabilistic diffusion waves of parasitic weeds were generated to derive most likely incidence values. Estimates from this spatial analysis were then combined with secondary data from the literature into a stochastic impact assessment model to generate a confidence interval of the likely economic impact per country and for sub-Saharan Africa as a whole. Rhamphicarpa fistulosa occurs in at least 36 African countries, 28 of which produce rice in rain-fed lowlands where this species thrives. Striga hermonthica is found in at least 32 countries, Striga asiatica in at least 44 and S. aspera in at least 17. A total of 50 countries have at least one of these three species of Striga, 31 of which produce rice in the rain-fed uplands where these species can be encountered. An estimated 1.34 million ha of rain-fed rice is infested with at least one species of a parasitic weed in Africa. Our stochastic model estimates that annual economic losses inflicted by all parasitic weeds exceeds, with 95% certainty, a minimum value of US $111 million and most likely reaches roughly US$200 million and increases by US $30 million annually. To reverse this trend and support small-holder rice farmers in Africa with effective, sustainable and affordable solutions for control, targeted investments in research, development and capacity building are required. The top-10 priority countries where such investments would probably have the highest return are Nigeria, Guinea, Mali, Côte d’Ivoire, Cameroon, Tanzania, Madagascar, Uganda, Sierra Leone and Burkina Faso

Identification of Reference Genes for Quantitative Gene Expression Studies in a Non-Model Tree Pistachio (Pistacia vera L.).

The tree species, Pistacia vera (P. vera) is an important commercial product that is salt-tolerant and long-lived, with a possible lifespan of over one thousand years. Gene expression analysis is an efficient method to explore the possible regulatory mechanisms underlying these characteristics. Therefore, having the most suitable set of reference genes is required for transcript level normalization under different conditions in P. vera. In the present study, we selected eight widely used reference genes, ACT, EF1α, α-TUB, β-TUB, GAPDH, CYP2, UBQ10, and 18S rRNA. Using qRT-PCR their expression was assessed in 54 different samples of three cultivars of P. vera. The samples were collected from different organs under various abiotic treatments (cold, drought, and salt) across three time points. Several statistical programs (geNorm, NormFinder, and BestKeeper) were applied to estimate the expression stability of candidate reference genes. Results obtained from the statistical analysis were then exposed to Rank aggregation package to generate a consensus gene rank. Based on our results, EF1α was found to be the superior reference gene in all samples under all abiotic treatments. In addition to EF1α, ACT and β-TUB were the second best reference genes for gene expression analysis in leaf and root. We recommended β-TUB as the second most stable gene for samples under the cold and drought treatments, while ACT holds the same position in samples analyzed under salt treatment. This report will benefit future research on the expression profiling of P. vera and other members of the Anacardiaceae family

The use of cross species SSR primers to study genetic diversity of okra from Burkina Faso

Sixteen pairs of primers designed to amplify SSR regions of Medicago truncatula were used to amplify genomic DNA samples of 20 different okra accessions collected from different regions Burkina Faso.These primers amplified a number of fragments that range from 1-16 with the sizes of 396-506 bp. Each accession was scored for the presence or absence of the bands and phylogenetic analysis of thesedata clustered the 20 accessions into five different groups. Two okra accessions were distinctly different from other 18, based on the molecular marker as well as on morphological features of theirfruits. One of the primers, MT-27 amplified a unique 440 bp PCR product in these 2 okra accessions. This PCR product was sequenced and based on the sequence information, sequence specific primerswere designed to PCR amplify the genomic DNA of all the okra accessions. This pair of primer amplified PCR products only in the two okra accessions where the amplification of the PCR productswas seen with MT-27 primers. Our data indicate that cross species SSR primer developed for Medicago truncatula can also be used to analyze genetic diversity in unrelated species, like Okra

List of the selected widely used reference genes.

<p>List of the selected widely used reference genes.</p

Candidate reference genes rank in term of their expression stability as computed by BestKeeper.

<p>Candidate reference genes rank in term of their expression stability as computed by BestKeeper.</p