Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Temporal expression of eight Phakopsora pachyrhizi effector candidate genes and subcellular localization of the encoded proteins in Nicotiana benthamiana

Durante a sua interação com a soja, o fungo Phakopsora pachyrhizi secreta e transloca para a célula vegetal várias proteínas efetoras com função de suprimir as respostas de defesa e/ou favorecer o seu parasitismo. Por meio da análise do transcritoma da interação soja- Phakopsora pachyrhizi vários genes que codificam proteínas candidatas a efetoras já foram identificados, mas a função da maioria dessas proteínas na patogênese ainda é desconhecida. Desta forma, o objetivo do presente estudo foi caracterizar genes candidatos a efetores de P. pachyrhizi, analisando a sua expressão temporal durante a infecção e localização subcelular das proteínas codificadas. Para isso, candidatos a efetores obtidos a partir de estudos de proteômica e transcritômica foram analisados e oito genes (EC3318, EC23, CSEP07, CSEP09, RTP1, HESP-C49, PHPA_29 e PHPA_43) foram selecionados, com base na expressão durante a infecção, presença de sequência codificadora do peptídeo sinal de secreção e alta identidade com genes que codificam proteínas efetoras de outras espécies de fungos causadores de ferrugens. Os genes selecionados apresentaram diferentes padrões de expressão, mas a maioria apresentou pico de expressão 24 horas após a inoculação, momento de início de formação dos haustórios do patógeno. As proteínas fusionadas a GFP foram expressas em folhas de Nicotiana benthamiana juntamente com proteínas marcadoras de compartimentos subcelulares e observadas em microscópio confocal de varredura a laser. A proteína EC23 se localizou exclusivamente no citoplasma, enquanto as proteínas EC3318, CSEP07, CSEP09, Hesp-C49, PHPA_29 e PHPA_43 se localizaram no citoplasma e no núcleo. O padrão de expressão dos genes e a localização subcelular das proteínas codificadas são condizentes com um provável papel efetor durante a patogênese em soja.During its interaction with soybeans, the fungus Phakopsora pachyrhizi secretes and translocates several effector proteins into the plant cell to suppress defense responses and/or to facilitate its parasitism. Through transcriptome analysis of the interaction between P.pachyrhizi and soybean, several candidate genes encoding putative effector proteins have been identified, but the function of the majority of these proteins in pathogenesis is still unknown. The objective of this study was to characterize P. pachyrhizi effector candidate genes, analyzing their temporal expression during infection and investigating the possible subcellular targets of the encoded proteins. Effector candidates sequences obtained from transcriptomics studies were analyzed and eight genes (EC3318, EC23, CSEP07, CSEP09, RTP1, HESP-C49, PHPA_29 and PHPA_43) were selected based on their expression during infection, presence of sequence encoding signal peptide for secretion and high identity with genes that encode effector proteins in others rust fungi. Different expression patterns were observed but most of the genes showed expression peaks 24 hours after the inoculation, stage in which the haustoria formation begins. GFP-fused proteins were expressed in Nicotiana benthamiana leaves together with fluorescence-tagged proteins that are markers of subcellular compartments. The EC23 protein was located exclusively in the cytoplasm, while EC3318, CSEP07, CSEP09, HEPEP-C49, PHPA_29 and PHPA_43 located in the cytoplasm and also in the cell nucleus, The gene expression pattern and the subcellular localization of the encoded proteins strongly indicate that the selected genes encode P. pachyrhizi effectors

Genomic studies in Phakopsora pachyrhizi and in its hyperparasite Simplicillium lanosoniveum

Phakopsora pachyrhizi and P. meibomiae are the etiological agents of Asian soybean rust (ASR) and American soybean rust, respectively. Asian soybean rust is the most important fungal disease of soybean in Brazil and the use of genetic resistance is one of the methods of control recommended for the ASR management. Currently, seven loci containing dominant genes that confer resistance to Phakopsora pachyrhizi (Rpp) were identified, but the complementary avirulence genes of the pathogen have not yet been cloned and characterized. The P. pachyrhizi genome complexity, the absence of sexual reproduction, the obligate biotrophy, and the absence of transformation protocols limit the gene mapping and functional studies with this fungus. Recent advances in the DNA sequencing technologies and tools for genome assembly opened new possibilities to study genome structure, organization, and function for complex genomes such as the P. pachyrhizi one, avoiding difficulties posed by the fungus’ biology. In addition, the assembly of complete genomes and comparative analysis allow the identification and characterization of complex loci and evolutionary processes related to pathogenicity, virulence, and hyperparasitism. Although the hyperparasitism of P. pachyrhizi by Simplicillium lanosoniveum has already been very well documented from a microscopic point of view, associated genes, and molecular mechanisms are still unknown. Therefore, in this study, genomic analyses were used to: a) Identification of P. pachyrhizi candidate avirulence genes corresponding to resistance genes Rpp1b (Avr1) and Rpp5 (Avr5); b) Characterization of the genetic and genomic structure of the Mating-type system in Phakopsora sp., P. meibomiae, and P. pachyrhizi; and c) Assembly and annotation of S. lanosoniveum genome and identification of molecular mechanisms possibly associated with hyperparasitism of P. pachyrhizi. Two candidate genes for Avr1 and four Avr5 of P. pachyrhizi predicted to encode secreted proteins were identified. The mating-type system in the Phakopsora species that were analyzed is heterothallic, possibly tetrapolar, and one hormone receptor protein with an atypical structure was identified in P. pachyrhizi. The genome of the mycoparasite S. lanosoniveum was sequenced and chromosome-level assembly was obtained. The annotation of the S. lanosoniveum genome revealed enzymes and secondary metabolites unique to this species that may be related to its parasitism on P. pachyrhizi. The genetic and genomic resources developed create new perspectives for cloning and characterization of avirulence genes of P. pachyrhizi, genes of S. lanosoniveum that encode specific enzymes and secondary metabolites, and also expand the understanding of the importance of sexual reproduction in the reproductive biology of P. pachyrhizi. Keywords: Avirulence genes. Mating-type. Comparative genomics. Genetic control. Biological control. Rpp1b. Rpp5.Phakopsora pachyrhizi e P. meibomiae são os agentes causais da ferrugem asiática e americana em leguminosas, respectivamente. A ferrugem é a principal doença fúngica da soja no Brasil e a utilização de variedades resistentes é uma das medidas recomendadas para o seu manejo integrado. Sete locos que contém genes dominantes que conferem resistência a P. pachyrhizi já foram identificados, mas nenhum gene de avirulência correspondente do patógeno foi clonado e caracterizado até o momento. A complexidade do genoma de P. pachyrhizi, a ausência de reprodução sexuada funcional e de protocolos de transformação, associados ao parasitismo obrigatório, limitam os estudos de mapeamento genético e a identificação e análise funcional de genes neste patógeno. Os avanços recentes nas tecnologias de sequenciamento de DNA e de algoritmos de montagem de genomas abriram novas possibilidades de estudo da estrutura, organização e função de genomas complexos como o de P. pachyrhizi, permitindo contornar alguns dos entraves relacionados à biologia do fungo. Além disso, a obtenção de genomas completos e análises comparativas permitem identificar e caracterizar locos complexos e processos evolutivos relacionados a patogenicidade, virulência e hiperparasitismo. Embora o hiperparasitismo de P. pachyrhizi por Simplicillium lanosoniveum já tenha sido muito bem documentado do ponto de vista microscópico, ainda não se conhece os genes e mecanismos moleculares associados. Portanto, neste estudo foram utilizadas ferramentas de análise genômica para: a) Identificar candidatos a genes de avirulência de P. pachyrhizi correspondentes aos genes de resistência Rpp1b (Avr1) e Rpp5 (Avr5); b) Caracterizar a estrutura genética e genômica do sistema Mating-type em Phakopsora sp., P. meibomiae e P. pachyrhizi; e c) Montar e anotar o genoma do micoparasita S. lanosoniveum e identificar mecanismos moleculares possivelmente associados ao hiperparasitismo em P. pachyrhizi. Foram identificados seis genes candidatos a Avr1 e Avr5 de P. pachyrhizi preditos como codificadores de proteínas secretadas. O sistema de mating-type nas espécies de Phakopsora analisadas é heterotálico, possivelmente tetrapolar, sendo identificada a sequência codificadora de uma proteína receptora de hormônios com estrutura atípica em P. pachyrhizi. O genoma do micoparasita S. lanosoniveum foi sequenciado e montado em nível cromossômico. A anotação do seu genoma revelou enzimas e metabólitos secundários únicos desta espécie que podem estar relacionados ao seu parasitismo em P. pachyrhizi. Os resultados obtidos nessa tese abrem novas perspectivas para a clonagem e caracterização de genes de avirulência de P. pachyrhizi, genes que codificam enzimas e metabólitos secundários específicos de S. lanosoniveum, além de ampliar a compreensão da importância da reprodução sexuada na biologia reprodutiva de P. pachyrhizi. Palavras-chave: Genes de avirulência. Mating-type. Genômica comparativa. Controle genético. Controle biológico. Rpp1b. Rpp5.Conselho Nacional de Desenvolvimento Científico e Tecnológic

The soybean rust pathogen Phakopsora pachyrhizi displays transposable element proliferation that correlates with broad host-range adaptation on legumes

ABSTRACTAsian soybean rust, caused by Phakopsora pachyrhizi, is one of the world’s most economically damaging agricultural diseases. Despite P. pachyrhizi’s impact, the exceptional size and complexity of its genome prevented generation of an accurate genome assembly. We simultaneously sequenced three P. pachyrhizi genomes uncovering a genome up to 1.25 Gb comprising two haplotypes with a transposable element (TE) content of ~93%. The proliferation of TEs within the genome occurred in several bursts and correlates with the radiation and speciation of the legumes. We present data of clear de-repression of TEs that mirrors expression of virulence-related candidate effectors. We can see a unique expansion in amino acid metabolism for this fungus. Our data shows that TEs play a dominant role in P. pachyrhizi’s genome and have a key impact on various processes such as host range adaptation, stress responses and genetic plasticity of the genome

Major proliferation of transposable elements shaped the genome of the soybean rust pathogen Phakopsora pachyrhizi

Asian soybean rust caused by Phakopsora pachyrhizi is an important plant pathogen, but an accurate genome assembly for this fungus has been lacking. This study sequenced three independent P. pachyrhizi isolates and generated reference quality assemblies and genome annotations, representing a critical step for further in-depth studies of this pathogen and the development of new methods of control

NEOTROPICAL CARNIVORES: a data set on carnivore distribution in the Neotropics

Mammalian carnivores are considered a key group in maintaining ecological health and can indicate potential ecological integrity in landscapes where they occur. Carnivores also hold high conservation value and their habitat requirements can guide management and conservation plans. The order Carnivora has 84 species from 8 families in the Neotropical region: Canidae; Felidae; Mephitidae; Mustelidae; Otariidae; Phocidae; Procyonidae; and Ursidae. Herein, we include published and unpublished data on native terrestrial Neotropical carnivores (Canidae; Felidae; Mephitidae; Mustelidae; Procyonidae; and Ursidae). NEOTROPICAL CARNIVORES is a publicly available data set that includes 99,605 data entries from 35,511 unique georeferenced coordinates. Detection/non-detection and quantitative data were obtained from 1818 to 2018 by researchers, governmental agencies, non-governmental organizations, and private consultants. Data were collected using several methods including camera trapping, museum collections, roadkill, line transect, and opportunistic records. Literature (peer-reviewed and grey literature) from Portuguese, Spanish and English were incorporated in this compilation. Most of the data set consists of detection data entries (n = 79,343; 79.7%) but also includes non-detection data (n = 20,262; 20.3%). Of those, 43.3% also include count data (n = 43,151). The information available in NEOTROPICAL CARNIVORES will contribute to macroecological, ecological, and conservation questions in multiple spatio-temporal perspectives. As carnivores play key roles in trophic interactions, a better understanding of their distribution and habitat requirements are essential to establish conservation management plans and safeguard the future ecological health of Neotropical ecosystems. Our data paper, combined with other large-scale data sets, has great potential to clarify species distribution and related ecological processes within the Neotropics. There are no copyright restrictions and no restriction for using data from this data paper, as long as the data paper is cited as the source of the information used. We also request that users inform us of how they intend to use the data