Fungal pathogens associated with crown and root rot in wheat-growing areas of Northern Kyrgyzstan

Göksel ÖZER SENOL YILDIZ MUSTAFA IMREN Abdelfattah DABABAT (2023, [Artículo])

Wheat Diseases Crown and Root Rot CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA TRITICUM WHEAT DISEASES ROOT ROTS PATHOGENICITY

Climate-smart agricultural practices influence the fungal communities and soil properties under major agri-food systems

madhu choudhary ML JAT Parbodh Chander Sharma (2022, [Artículo])

Fungal communities in agricultural soils are assumed to be affected by climate, weather, and anthropogenic activities, and magnitude of their effect depends on the agricultural activities. Therefore, a study was conducted to investigate the impact of the portfolio of management practices on fungal communities and soil physical–chemical properties. The study comprised different climate-smart agriculture (CSA)-based management scenarios (Sc) established on the principles of conservation agriculture (CA), namely, ScI is conventional tillage-based rice–wheat rotation, ScII is partial CA-based rice–wheat–mungbean, ScIII is partial CSA-based rice–wheat–mungbean, ScIV is partial CSA-based maize–wheat–mungbean, and ScV and ScVI are CSA-based scenarios and similar to ScIII and ScIV, respectively, except for fertigation method. All the scenarios were flood irrigated except the ScV and ScVI where water and nitrogen were given through subsurface drip irrigation. Soils of these scenarios were collected from 0 to 15 cm depth and analyzed by Illumina paired-end sequencing of Internal Transcribed Spacer regions (ITS1 and ITS2) for the study of fungal community composition. Analysis of 5 million processed sequences showed a higher Shannon diversity index of 1.47 times and a Simpson index of 1.12 times in maize-based CSA scenarios (ScIV and ScVI) compared with rice-based CSA scenarios (ScIII and ScV). Seven phyla were present in all the scenarios, where Ascomycota was the most abundant phyla and it was followed by Basidiomycota and Zygomycota. Ascomycota was found more abundant in rice-based CSA scenarios as compared to maize-based CSA scenarios. Soil organic carbon and nitrogen were found to be 1.62 and 1.25 times higher in CSA scenarios compared with other scenarios. Bulk density was found highest in farmers' practice (Sc1); however, mean weight diameter and water-stable aggregates were found lowest in ScI. Soil physical, chemical, and biological properties were found better under CSA-based practices, which also increased the wheat grain yield by 12.5% and system yield by 18.8%. These results indicate that bundling/layering of smart agricultural practices over farmers' practices has tremendous effects on soil properties, and hence play an important role in sustaining soil quality/health.

Agriculture Management Fungal Community Diversity Indices Climate-Smart Agricultural Practices CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA AGRICULTURE TILLAGE CLIMATE-SMART AGRICULTURE SOIL ORGANIC CARBON

Production vulnerability to wheat blast disease under climate change

Diego Pequeno Jose Mauricio Fernandes Pawan Singh Willingthon Pavan Kai Sonder Richard Robertson Timothy Joseph Krupnik Olaf Erenstein Senthold Asseng (2024, [Artículo])

Wheat Blast Tropical Regions CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA WHEAT PLANT DISEASES CLIMATE CHANGE PRODUCTION

Occurrence and Distribution of Physiological Races of Exserohilum turcicum in Maize Growing Regions of Mexico

Alexander Loladze Mateo Vargas Hernández amos Alakonya (2022, [Artículo])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA SETOSPHAERIA TURCICA MAIZE FOLIAR DISEASES PHYSIOLOGICAL RACES

Mining alleles for tar spot complex resistance from CIMMYT's maize Germplasm Bank

Martha Willcox Juan Burgueño Daniel Jeffers Zakaria Kehel Rosemary Shrestha Kelly Swarts Edward Buckler Sarah Hearne Charles Chen (2022, [Artículo])

Maize Landraces Maize Genetic Resources Allelic Diversity Rare Alleles Phenotypic Characterization Tropical Maize Phyllachora maydis CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MAIZE LANDRACES GENETIC RESOURCES ALLELES FOLIAR DISEASES CLIMATE CHANGE

Cloning of the broadly effective wheat leaf rust resistance gene Lr42 transferred from Aegilops tauschii

Guifang Lin Hui Chen Bin Tian Sunish Sehgal Jingzhong Xie Philomin Juliana Narinder Singh Sandesh Kumar Shrestha Ravi Singh Harold Trick Jesse Poland Robert Bowden guihua bai bikram gill (2022, [Artículo])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA ALLELES CLONES GENE EXPRESSION GRASSES MUTATION RUSTS WHEAT BASIDIOMYCOTA DISEASE RESISTANCE GENETICS MOLECULAR CLONING PLANT BREEDING PLANT DISEASES

Highlights of the 2023 Southern Africa regional trials coordinated by CIMMYT

Xavier Mhike (2023, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA HYBRIDS SELECTION MAIZE FOLIAR DISEASES DROUGHT STRESS

Phenotyping for Disease Resistance to increase genetic gains

Suresh L.M. (2022, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MAIZE PLANT DISEASES DISEASE RESISTANCE PHENOTYPES

The search for cryptic L-Rhamnosyltransferases on the Sporothrix schenckii genome

Hector M. Mora-Montes Karina García-Gutiérrez Laura Cristina García Carnero Nancy Lozoya-Perez Jorge Humberto Ramírez Prado (2022, [Artículo])

The fungal cell wall is an attractive structure to look for new antifungal drug targets and for understanding the host-fungus interaction. Sporothrix schenckii is one of the main causative agents of both human and animal sporotrichosis and currently is the species most studied of the Sporothrix genus. The cell wall of this organism has been previously analyzed, and rhamnoconjugates are signature molecules found on the surface of both mycelia and yeast-like cells. Similar to other reactions where sugars are covalently linked to other sugars, lipids, or proteins, the rhamnosylation process in this organism is expected to involve glycosyltransferases with the ability to transfer rhamnose from a sugar donor to the acceptor molecule, i.e., rhamnosyltransferases. However, no obvious rhamnosyltransferase has thus far been identified within the S. schenckii proteome or genome. Here, using a Hidden Markov Model profile strategy, we found within the S. schenckii genome five putative genes encoding for rhamnosyltransferases. Expression analyses indicated that only two of them, named RHT1 and RHT2, were significantly expressed in yeast-like cells and during interaction with the host. These two genes were heterologously expressed in Escherichia coli, and the purified recombinant proteins showed rhamnosyltransferase activity, dependent on the presence of UDP-rhamnose as a sugar donor. To the best of our knowledge, this is the first report about rhamnosyltransferases in S. schenckii. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

FUNGAL CELL-WALL GLYCANS RHAMNOCONJUGATES RHAMNOSYLTRANSFERASE BIOLOGÍA Y QUÍMICA CIENCIAS DE LA VIDA BIOLOGÍA VEGETAL (BOTÁNICA) ECOLOGÍA VEGETAL ECOLOGÍA VEGETAL

Using an incomplete block design to allocate lines to environments improves sparse genome-based prediction in plant breeding

Osval Antonio Montesinos-Lopez ABELARDO MONTESINOS LOPEZ RICARDO ACOSTA DIAZ Rajeev Varshney Jose Crossa ALISON BENTLEY (2022, [Artículo])

Genomic selection (GS) is a predictive methodology that trains statistical machine-learning models with a reference population that is used to perform genome-enabled predictions of new lines. In plant breeding, it has the potential to increase the speed and reduce the cost of selection. However, to optimize resources, sparse testing methods have been proposed. A common approach is to guarantee a proportion of nonoverlapping and overlapping lines allocated randomly in locations, that is, lines appearing in some locations but not in all. In this study we propose using incomplete block designs (IBD), principally, for the allocation of lines to locations in such a way that not all lines are observed in all locations. We compare this allocation with a random allocation of lines to locations guaranteeing that the lines are allocated to

the same number of locations as under the IBD design. We implemented this benchmarking on several crop data sets under the Bayesian genomic best linear unbiased predictor (GBLUP) model, finding that allocation under the principle of IBD outperformed random allocation by between 1.4% and 26.5% across locations, traits, and data sets in terms of mean square error. Although a wide range of performance improvements were observed, our results provide evidence that using IBD for the allocation of lines to locations can help improve predictive performance compared with random allocation. This has the potential to be applied to large-scale plant breeding programs.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA Bayes Theorem Genome Inflammatory Bowel Diseases Models, Genetic Plant Breeding