Institution
Nanjing Agricultural University
Education•Nanjing, China•
About: Nanjing Agricultural University is a education organization based out in Nanjing, China. It is known for research contribution in the topics: Gene & Population. The organization has 31656 authors who have published 27306 publications receiving 546544 citations. The organization is also known as: Nánjīng nóngyè dàxué.
Topics: Gene, Population, Quantitative trait locus, Biology, Chemistry
Papers published on a yearly basis
Papers
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Daniel J. Klionsky1, Fábio Camargo Abdalla2, Hagai Abeliovich3, Robert T. Abraham4 +1284 more•Institutions (463)
TL;DR: These guidelines are presented for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes.
Abstract: In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. A key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process vs. those that measure flux through the autophagy pathway (i.e., the complete process); thus, a block in macroautophagy that results in autophagosome accumulation needs to be differentiated from stimuli that result in increased autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field.
4,316 citations
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TL;DR: This review aims to compare and contrast the different HCoVs with regard to epidemiology and pathogenesis, in addition to the virus evolution and recombination events which have, on occasion, resulted in outbreaks amongst humans.
2,268 citations
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TL;DR: This study identifies ∼3.6 million SNPs by sequencing 517 rice landraces and constructed a high-density haplotype map of the rice genome using a novel data-imputation method, demonstrating that an approach integrating second-generation genome sequencing and GWAS can be used as a powerful complementary strategy to classical biparental cross-mapping for dissecting complex traits in rice.
Abstract: Uncovering the genetic basis of agronomic traits in crop landraces that have adapted to various agro-climatic conditions is important to world food security. Here we have identified ∼ 3.6 million SNPs by sequencing 517 rice landraces and constructed a high-density haplotype map of the rice genome using a novel data-imputation method. We performed genome-wide association studies (GWAS) for 14 agronomic traits in the population of Oryza sativa indica subspecies. The loci identified through GWAS explained ∼ 36% of the phenotypic variance, on average. The peak signals at six loci were tied closely to previously identified genes. This study provides a fundamental resource for rice genetics research and breeding, and demonstrates that an approach integrating second-generation genome sequencing and GWAS can be used as a powerful complementary strategy to classical biparental cross-mapping for dissecting complex traits in rice.
1,718 citations
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University of Florida1, University of Bonn2, Institut national de la recherche agronomique3, Blaise Pascal University4, Stanford University5, Prince of Songkla University6, Agricultural Research Service7, University of Arizona8, International Maize and Wheat Improvement Center9, Kansas State University10, International Water Management Institute11, Washington State University12, Michigan State University13, CGIAR14, University of Leeds15, Counterintelligence Field Activity16, Spanish National Research Council17, University of Tübingen18, University of Guelph19, University of Maryland, College Park20, Texas A&M University21, Aarhus University22, Potsdam Institute for Climate Impact Research23, Indian Agricultural Research Institute24, Goddard Institute for Space Studies25, Rothamsted Research26, University of Hohenheim27, Wageningen University and Research Centre28, Chinese Academy of Sciences29, Commonwealth Scientific and Industrial Research Organisation30, China Agricultural University31, Nanjing Agricultural University32
TL;DR: The authors systematically tested 30 different wheat crop models of the Agricultural Model Intercomparison and Improvement Project against field experiments in which growing season mean temperatures ranged from 15 degrees C to 32 degrees C, including experiments with artificial heating.
Abstract: Crop models are essential tools for assessing the threat of climate change to local and global food production(1). Present models used to predict wheat grain yield are highly uncertain when simulating how crops respond to temperature(2). Here we systematically tested 30 different wheat crop models of the Agricultural Model Intercomparison and Improvement Project against field experiments in which growing season mean temperatures ranged from 15 degrees C to 32 degrees C, including experiments with artificial heating. Many models simulated yields well, but were less accurate at higher temperatures. The model ensemble median was consistently more accurate in simulating the crop temperature response than any single model, regardless of the input information used. Extrapolating the model ensemble temperature response indicates that warming is already slowing yield gains at a majority of wheat-growing locations. Global wheat production is estimated to fall by 6% for each degrees C of further temperature increase and become more variable over space and time.
1,461 citations
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Peking University1, Nanjing Agricultural University2, Stanford University3, Chinese Academy of Sciences4, University of Sassari5, Commissariat à l'énergie atomique et aux énergies alternatives6, Institut national de la recherche agronomique7, University of Chicago8, University of Bonn9, University of Antwerp10, International Rice Research Institute11, Potsdam Institute for Climate Impact Research12, Goddard Institute for Space Studies13, University of Florida14
TL;DR: Investigating the impacts of temperature on yields of the four crops by compiling extensive published results from four analytical methods consistently showed negative temperature impacts on crop yield at the global scale, generally underpinned by similar impacts at country and site scales.
Abstract: Wheat, rice, maize, and soybean provide two-thirds of human caloric intake. Assessing the impact of global temperature increase on production of these crops is therefore critical to maintaining global food supply, but different studies have yielded different results. Here, we investigated the impacts of temperature on yields of the four crops by compiling extensive published results from four analytical methods: global grid-based and local point-based models, statistical regressions, and field-warming experiments. Results from the different methods consistently showed negative temperature impacts on crop yield at the global scale, generally underpinned by similar impacts at country and site scales. Without CO2 fertilization, effective adaptation, and genetic improvement, each degree-Celsius increase in global mean temperature would, on average, reduce global yields of wheat by 6.0%, rice by 3.2%, maize by 7.4%, and soybean by 3.1%. Results are highly heterogeneous across crops and geographical areas, with some positive impact estimates. Multimethod analyses improved the confidence in assessments of future climate impacts on global major crops and suggest crop- and region-specific adaptation strategies to ensure food security for an increasing world population.
1,442 citations
Authors
Showing all 31871 results
Name | H-index | Papers | Citations |
---|---|---|---|
Pete Smith | 156 | 2464 | 138819 |
Jian Li | 133 | 2863 | 87131 |
Yves Van de Peer | 115 | 494 | 61479 |
Ary A. Hoffmann | 113 | 907 | 55354 |
Chunhai Fan | 112 | 702 | 51735 |
Fang-Jie Zhao | 107 | 372 | 39328 |
Qi Li | 102 | 1563 | 46762 |
Zhigang Chen | 96 | 783 | 40892 |
Stephen Joseph | 95 | 485 | 45357 |
Feng Chen | 95 | 2138 | 53881 |
Sergey Shabala | 86 | 435 | 26083 |
Hauke Smidt | 84 | 400 | 23609 |
Jie Tian | 83 | 1238 | 31825 |
Tom Beeckman | 82 | 228 | 23573 |
Yang Zhang | 75 | 442 | 41275 |