Challenges facing sustainable protein production: Opportunities for cereals

OnlinePublRising demands for protein across the world are likely to increase livestock production, as meat provides ∼40% of dietary protein. This will come at significant environmental expense; therefore, a shift towards plant-based protein sources would provide major benefits. While legumes provide substantial plant-based proteins, cereals are the major constituents of global foods with wheat alone accounting for 15-20% of the required protein intake. Improving protein content in wheat is limited by phenotyping challenges, lack of genetic potential of modern germplasms, negative yield trade-off, and the environmental cost of nitrogen fertilisers. Presenting wheat as a case study, we discuss how increasing protein content in cereals through a revised breeding strategy combined with robust phenotyping can ensure a sustainable protein supply while minimising the environmental impact of nitrogen fertiliser.Luqman B. Safdar, M. John Foulkes, Friedrich H. Kleiner, Iain R. Searle, Rahul A. Bhosale, Ian D. Fisk, Scott A. Bode

Updated guidelines for gene nomenclature in wheat

The last decade has seen a proliferation in genomic resources for wheat, including reference- and pan-genome assemblies with gene annotations, which provide new opportunities to detect, characterise, and describe genes that influence traits of interest. The expansion of genetic information has supported growth of the wheat research community and catalysed strong interest in the genes that control agronomically important traits, such as yield, pathogen resistance, grain quality, and abiotic stress tolerance. To accommodate these developments, we present an updated set of guidelines for gene nomenclature in wheat. These guidelines can be used to describe loci identified based on morphological or phenotypic features or to name genes based on sequence information, such as similarity to genes characterised in other species or the biochemical properties of the encoded protein. The updated guidelines provide a flexible system that is not overly prescriptive but provides structure and a common framework for naming genes in wheat, which may be extended to related cereal species. We propose these guidelines be used henceforth by the wheat research community to facilitate integration of data from independent studies and allow broader and more efficient use of text and data mining approaches, which will ultimately help further accelerate wheat research and breeding.EEA PergaminoFil: Boden, S. A. University of Adelaide. Waite Research Institute. School of Agriculture, Food and Wine; AustraliaFil: McIntosh, R .A. University of Sydney. School of Life and Environmental Sciences. Plant Breeding Institute; AustraliaFil: Uauy, C. Norwich Research Park. John Innes Centre; Reino UnidoFil: Krattinger, S. G. King Abdullah University of Science and Technology. Biological and Environmental Science and Engineering Division. Plant Science Program; Arabia SauditaFil: Krattinger, S. G. The Wheat Initiative; AlemaniaFil: Dubcovsky, J. University of California. Department of Plant Science; Estados UnidosFil: Dubcovsky, J. The Wheat Initiative; AlemaniaFil: Rogers, W.J. Universidad Nacional del Centro de La Provincia de Buenos Aires. Facultad de Agronomía (CIISAS, CIC-BIOLAB AZUL, CONICET-INBIOTEC, CRESCA). Departamento de Biología Aplicada; ArgentinaFil: Rogers, W.J. The Wheat Initiative; AlemaniaFIL: Xia, X. C. Chinese Academy of Agricultural Sciences. National Wheat Improvement Centre. Institute of Crop Science; ChinaFil: Badaeva, E. D. Russian Academy of Sciences. N.I. Vavilov Institute of General Genetics; RusiaFil: Bentley, A. R. International Maize and Wheat Improvement Center (CIMMYT); MéxicoFil: Bentley, A. R. The Wheat Initiative; AlemaniaFil: Brown-Guedira, G. North Carolina State University. USDA-ARS Plant Science Research; Estados UnidosFil: Brown-Guedira, G. The Wheat Initiative; AlemaniaFil: González, Fernanda G. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Pergamino. Sección Ecofisiología; ArgentinaFil: González, Fernanda G. Centro de Investigaciones y Transferencia del Noroeste de la Provincia de Buenos Aires (CITNOBA, CONICET-UNNOBA-UNSADA); ArgentinaFil: González, Fernanda G. The Wheat Initiative; AlemaniaFil: Zhang, Y. Fudan University. School of Life Sciences. Institute of Plant Biology. Collaborative Innovation Center of Genetics and Development. State Key Laboratory of Genetic Engineering; Chin

The Gould's Belt Distances Survey (GOBELINS). III. The Distance to the Serpens/Aquila Molecular Complex

Interstellar matter and star formatio

Updated guidelines for gene nomenclature in wheat.

Here, we provide an updated set of guidelines for naming genes in wheat that has been endorsed by the wheat research community. The last decade has seen a proliferation in genomic resources for wheat, including reference- and pan-genome assemblies with gene annotations, which provide new opportunities to detect, characterise, and describe genes that influence traits of interest. The expansion of genetic information has supported growth of the wheat research community and catalysed strong interest in the genes that control agronomically important traits, such as yield, pathogen resistance, grain quality, and abiotic stress tolerance. To accommodate these developments, we present an updated set of guidelines for gene nomenclature in wheat. These guidelines can be used to describe loci identified based on morphological or phenotypic features or to name genes based on sequence information, such as similarity to genes characterised in other species or the biochemical properties of the encoded protein. The updated guidelines provide a flexible system that is not overly prescriptive but provides structure and a common framework for naming genes in wheat, which may be extended to related cereal species. We propose these guidelines be used henceforth by the wheat research community to facilitate integration of data from independent studies and allow broader and more efficient use of text and data mining approaches, which will ultimately help further accelerate wheat research and breeding.S. A. Boden, R. A. McIntosh, C. Uauy, S. G. Krattinger, J. Dubcovsky, W. J. Rogers, X. C. Xia, E. D. Badaeva, A. R. Bentley, G. Brown, Guedira, M. Caccamo, L. Cattivelli, P. Chhuneja, J. Cockram, B. Contreras, Moreira, S. Dreisigacker, D. Edwards, F. G. González, C. Guzmán, T. M. Ikeda, I. Karsai, S. Nasuda, C. Pozniak, R. Prins, T. Z. Sen, P. Silva, H. Simkova, Y. Zhang, the Wheat Initiativ

Bio-mimetic subwavelength surface for near-zero reflection sunrise to sunset

We present a study of antireflective schemes and their operation over a full day. We compare simulation results for single and double layer antireflective coatings with biomimetic moth-eye structures, taking into account the full range of wavelengths and incident angles experienced by fixed solar cells from sunrise to sunset. We show that solar cells incorporating antireflective moth-eye arrays could produce up to 12% more energy than those employing single layer antireflective coatings