Epigenetic events underlying somatic cell reprogramming

Although differentiated cells normally retain cell-type-specific gene expression patterns throughout their lifetime, cell identity can sometimes be modified or reversed in vivo by transdifferentiation, or experimentally through cell fusion or by nuclear transfer. Several studies have illustrated the importance of chromatin remodelling, DNA demethylation and dominant transcriptional factor expression for changes in lineage identity. Here the epigenetic mechanisms required to “reset” genome function were investigated using experimental heterokaryons. To examine the epigenetic changes that are required for the dominant conversion of lymphocytes to muscle, I generated stable heterokaryons between human B-lymphocytes and mouse C2C12 myotubes. I show that lymphocyte nuclei adopt an architecture resembling that of muscle and initiate the expression of musclespecific genes in the same temporal order as developing muscle. The establishment of this novel gene expression program is coordinated with the shutdown of several lymphocyte-associated genes. Interestingly, inhibition of histone deacetylase (HDAC) activity during reprogramming selectively blocks the silencing of lymphocyte-specific genes but does not prevent the establishment of muscle-specific gene expression. In order to reprogram somatic cells to pluripotency, I fused human Blymphocytes and mouse embryonic stem (ES) cells. The conversion of human cells is initiated rapidly, occurring in heterokaryons before nuclear fusion. Reprogramming of human lymphocytes by mouse ES cells elicits the expression of a human ES-specific gene expression profile in which endogenous hSSEA4, hFgf receptors and ligands are expressed while factors that are characteristic of mouse ES cells, such as Bmp4 and Lif receptor are not. Using genetically engineered mouse ES cells I demonstrate that successful reprogramming requires the expression of Oct4, but importantly, does not require Sox2, a factor implicated as critical for the induction of pluripotency. Following reprogramming, mOct4 becomes dispensable for maintaining the multi-potent state of hybrid cells. Finally, I have examined the reprogramming potential of embryonic germ (EG), embryonic carcinoma (EC) and ES cells deficient for the Polycomb repressive complex 2 (PRC2) proteins Eed, Suz12 and Ezh2. While EC and EG cells share the ability to reprogram human lymphocytes with ES cells, the lack of Polycomb proteins abolishes reprogramming. Thus, the repressive chromatin mark (H3K27 methylation) catalysed by PRC2 play a crucial role in keeping ES cells with full reprogramming capacity. Collectively my results underscore the importance of chromatin events during cell fate reprogramming

MAMMALS IN PORTUGAL : A data set of terrestrial, volant, and marine mammal occurrences in P ortugal

Mammals are threatened worldwide, with 26% of all species being includedin the IUCN threatened categories. This overall pattern is primarily associatedwith habitat loss or degradation, and human persecution for terrestrial mam-mals, and pollution, open net fishing, climate change, and prey depletion formarine mammals. Mammals play a key role in maintaining ecosystems func-tionality and resilience, and therefore information on their distribution is cru-cial to delineate and support conservation actions. MAMMALS INPORTUGAL is a publicly available data set compiling unpublishedgeoreferenced occurrence records of 92 terrestrial, volant, and marine mam-mals in mainland Portugal and archipelagos of the Azores and Madeira thatincludes 105,026 data entries between 1873 and 2021 (72% of the data occur-ring in 2000 and 2021). The methods used to collect the data were: live obser-vations/captures (43%), sign surveys (35%), camera trapping (16%),bioacoustics surveys (4%) and radiotracking, and inquiries that represent lessthan 1% of the records. The data set includes 13 types of records: (1) burrowsjsoil moundsjtunnel, (2) capture, (3) colony, (4) dead animaljhairjskullsjjaws, (5) genetic confirmation, (6) inquiries, (7) observation of live animal (8),observation in shelters, (9) photo trappingjvideo, (10) predators dietjpelletsjpine cones/nuts, (11) scatjtrackjditch, (12) telemetry and (13) vocalizationjecholocation. The spatial uncertainty of most records ranges between 0 and100 m (76%). Rodentia (n=31,573) has the highest number of records followedby Chiroptera (n=18,857), Carnivora (n=18,594), Lagomorpha (n=17,496),Cetartiodactyla (n=11,568) and Eulipotyphla (n=7008). The data setincludes records of species classified by the IUCN as threatened(e.g.,Oryctolagus cuniculus[n=12,159],Monachus monachus[n=1,512],andLynx pardinus[n=197]). We believe that this data set may stimulate thepublication of other European countries data sets that would certainly contrib-ute to ecology and conservation-related research, and therefore assisting onthe development of more accurate and tailored conservation managementstrategies for each species. There are no copyright restrictions; please cite thisdata paper when the data are used in publications.info: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 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

Mammals in Portugal: a data set of terrestrial, volant, and marine mammal occurrences in Portugal

Mammals are threatened worldwide, with ~26% of all species being included in the IUCN threatened categories. This overall pattern is primarily associated with habitat loss or degradation, and human persecution for terrestrial mammals, and pollution, open net fishing, climate change, and prey depletion for marine mammals. Mammals play a key role in maintaining ecosystems functionality and resilience, and therefore information on their distribution is crucial to delineate and support conservation actions. MAMMALS IN PORTUGAL is a publicly available data set compiling unpublished georeferenced occurrence records of 92 terrestrial, volant, and marine mammals in mainland Portugal and archipelagos of the Azores and Madeira that includes 105,026 data entries between 1873 and 2021 (72% of the data occurring in 2000 and 2021). The methods used to collect the data were: live observations/captures (43%), sign surveys (35%), camera trapping (16%), bioacoustics surveys (4%) and radiotracking, and inquiries that represent less than 1% of the records. The data set includes 13 types of records: (1) burrows | soil mounds | tunnel, (2) capture, (3) colony, (4) dead animal | hair | skulls | jaws, (5) genetic confirmation, (6) inquiries, (7) observation of live animal (8), observation in shelters, (9) photo trapping | video, (10) predators diet | pellets | pine cones/nuts, (11) scat | track | ditch, (12) telemetry and (13) vocalization | echolocation. The spatial uncertainty of most records ranges between 0 and 100 m (76%). Rodentia (n =31,573) has the highest number of records followed by Chiroptera (n = 18,857), Carnivora (n = 18,594), Lagomorpha (n = 17,496), Cetartiodactyla (n = 11,568) and Eulipotyphla (n = 7008). The data set includes records of species classified by the IUCN as threatened (e.g., Oryctolagus cuniculus [n = 12,159], Monachus monachus [n = 1,512], and Lynx pardinus [n = 197]). We believe that this data set may stimulate the publication of other European countries data sets that would certainly contribute to ecology and conservation-related research, and therefore assisting on the development of more accurate and tailored conservation management strategies for each species. There are no copyright restrictions; please cite this data paper when the data are used in publications

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

ABSTRACT PROCEEDINGS OF INTERNATIONAL CONFERENCE ON TOURISM AND SOCIAL SUPPORT TECHNOLOGIES INNOVATION AND LOCAL DEVELOPMENT

info:eu-repo/semantics/publishedVersio

Brazilian coffee genome project: an EST-based genomic resource

O café é um dos principais produtos agrícolas, sendo considerado o segundo item em importância do comércio internacional de commodities. O gênero Coffea pertence à família Rubiaceae que também inclui outras plantas importantes. Este gênero contém aproximadamente 100 espécies, mas a produção comercial é baseada somente em duas espécies, Coffea arabica e Coffea canephora, que representam aproximadamente 70 % e 30 % do mercado total de café, respectivamente. O Projeto Genoma Café Brasileiro foi desenvolvido com o objetivo de disponibilizar os modernos recursos da genômica à comunidade científica e aos diferentes segmentos da cadeia produtiva do café. Para isso, foram seqüenciados 214.964 clones escolhidos aleatoriamente de 37 bibliotecas de cDNA de C. arabica, C. canephora e C. racemosa representando estádios específicos do desenvolvimento de células e de tecidos do cafeeiro, resultando em 130.792, 12.381 e 10.566 seqüências de cada espécie, respectivamente, após processo de trimagem. Os ESTs foram agrupados em 17.982 contigs e em 32.155 singletons. A comparação destas seqüências pelo programa BLAST revelou que 22 % não tiveram nenhuma similaridade significativa às seqüências no banco de dados do National Center for Biotechnology Information (de função conhecida ou desconhecida). A base de dados de ESTs do cafeeiro resultou na identificação de cerca de 33.000 unigenes diferentes. Os resultados de anotação das seqüências foram armazenados em base de dados online em http://www.lge.ibi.unicamp.br/cafe. Os recursos desenvolvidos por este projeto disponibilizam ferramentas genéticas e genômicas que podem ser decisivas para a sustentabilidade, a competitividade e a futura viabilidade da agroindústria cafeeira nos mercados interno e externo.Coffee is one of the most valuable agricultural commodities and ranks second on international trade exchanges. The genus Coffea belongs to the Rubiaceae family which includes other important plants. The genus contains about 100 species but commercial production is based only on two species, Coffea arabica and Coffea canephora that represent about 70 % and 30 % of the total coffee market, respectively. The Brazilian Coffee Genome Project was designed with the objective of making modern genomics resources available to the coffee scientific community, working on different aspects of the coffee production chain. We have single-pass sequenced a total of 214,964 randomly picked clones from 37 cDNA libraries of C. arabica, C. canephora and C. racemosa, representing specific stages of cells and plant development that after trimming resulted in 130,792, 12,381 and 10,566 sequences for each species, respectively. The ESTs clustered into 17,982 clusters and 32,155 singletons. Blast analysis of these sequences revealed that 22 % had no significant matches to sequences in the National Center for Biotechnology Information database (of known or unknown function). The generated coffee EST database resulted in the identification of close to 33,000 different unigenes. Annotated sequencing results have been stored in an online database at http://www.lge.ibi.unicamp.br/cafe. Resources developed in this project provide genetic and genomic tools that may hold the key to the sustainability, competitiveness and future viability of the coffee industry in local and international markets