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. Key words: Coffea, cDNA, EST, transcriptome.Projeto Genoma Brasileiro Café: recursos genômicos baseados em ESTs: 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...

BackgroundMeat and egg-type chickens have been selected for several generations for different traits. Artificial and natural selection for different phenotypes can change frequency of genetic variants, leaving particular genomic footprints throghtout the genome. Thus, the aims of this study were to sequence 28 chickens from two Brazilian lines (meat and white egg-type) and use this information to characterize genome-wide genetic variations, identify putative regions under selection using Fst method, and find putative pathways under selection.ResultsA total of 13.93 million SNPs and 1.36 million INDELs were identified, with more variants detected from the broiler (meat-type) line. Although most were located in non-coding regions, we identified 7255 intolerant non-synonymous SNPs, 512 stopgain/loss SNPs, 1381 frameshift and 1094 non-frameshift INDELs that may alter protein functions. Genes harboring intolerant non-synonymous SNPs affected metabolic pathways related mainly to reproduction and endocrine systems in the white-egg layer line, and lipid metabolism and metabolic diseases in the broiler line. Fst analysis in sliding windows, using SNPs and INDELs separately, identified over 300 putative regions of selection overlapping with more than 250 genes. For the first time in chicken, INDEL variants were considered for selection signature analysis, showing high level of correlation in results between SNP and INDEL data. The putative regions of selection signatures revealed interesting candidate genes and pathways related to important phenotypic traits in chicken, such as lipid metabolism, growth, reproduction, and cardiac development.ConclusionsIn this study, Fst method was applied to identify high confidence putative regions under selection, providing novel insights into selection footprints that can help elucidate the functional mechanisms underlying different phenotypic traits relevant to meat and egg-type chicken lines. In addition, we generated a large catalog of line-specific and common genetic variants from a Brazilian broiler and a white egg layer line that can be used for genomic studies involving association analysis with phenotypes of economic interest to the poultry industry.Electronic supplementary materialThe online version of this article (10.1186/s12864-018-4444-0) contains supplementary material, which is available to authorized users.

The high numbers of COVID-19 cases and deaths in Brazil have made Latin America an epicentre of the pandemic. SARS-CoV-2 established sustained transmission in Brazil early in the pandemic, but important gaps remain in our understanding of virus transmission dynamics at a national scale. We use 17,135 near-complete genomes sampled from 27 Brazilian states and bordering country Paraguay. From March to November 2020, we detected co-circulation of multiple viral lineages that were linked to multiple importations (predominantly from Europe). After November 2020, we detected large, local transmission clusters within the country. In the absence of effective restriction measures, the epidemic progressed, and in January 2021 there was emergence and onward spread, both within and abroad, of variants of concern and variants under monitoring, including Gamma (P.1) and Zeta (P.2). We also characterized a genomic overview of the epidemic in Paraguay and detected evidence of importation of SARS-CoV-2 ancestor lineages and variants of concern from Brazil. Our findings show that genomic surveillance in Brazil enabled assessment of the real-time spread of emerging SARS-CoV-2 variants.

The current COVID-19 pandemic demands massive testing by Real-time RT-PCR (Reverse Transcription Polymerase Chain Reaction), which is considered the gold standard diagnostic test for the detection of the SARS-CoV-2 virus. However, the virus continues to evolve with mutations that lead to phenotypic alterations as higher transmissibility, pathogenicity or vaccine evasion. Another big issue are mutations in the annealing sites of primers and probes of RT-PCR diagnostic kits leading to false-negative results. Therefore, here we identify mutations in the N (Nucleocapsid) gene that affects the use of the GeneFinder COVID-19 Plus RealAmp Kit. We sequenced SARS-CoV-2 genomes from 17 positive samples with no N gene detection but with RDRP (RNA-dependent RNA polymerase) and E (Envelope) genes detection, and observed a set of three different mutations affecting the N detection: a deletion of 18 nucleotides (Del28877-28894), a substitution of GGG to AAC (28881-28883) and a frameshift mutation caused by deletion (Del28877-28878). The last one cause a deletion of six AAs (amino acids) located in the central intrinsic disorder region at protein level. We also found this mutation in 99 of the 14,346 sequenced samples by the Sao Paulo state Network for Pandemic Alert of Emerging SARS-CoV-2 variants, demonstrating the circulation of the mutation in Sao Paulo, Brazil. Continuous monitoring and characterization of mutations affecting the annealing sites of primers and probes by genomic surveillance programs are necessary to maintain the effectiveness of the diagnosis of COVID-19.