Mapping Bias Overestimates Reference Allele Frequencies at the HLA Genes in the 1000 Genomes Project Phase I Data.

Next-generation sequencing (NGS) technologies have become the standard for data generation in studies of population genomics, as the 1000 Genomes Project (1000G). However, these techniques are known to be problematic when applied to highly polymorphic genomic regions, such as the human leukocyte antigen (HLA) genes. Because accurate genotype calls and allele frequency estimations are crucial to population genomics analyses, it is important to assess the reliability of NGS data. Here, we evaluate the reliability of genotype calls and allele frequency estimates of the single-nucleotide polymorphisms (SNPs) reported by 1000G (phase I) at five HLA genes (HLA-A, -B, -C, -DRB1, and -DQB1). We take advantage of the availability of HLA Sanger sequencing of 930 of the 1092 1000G samples and use this as a gold standard to benchmark the 1000G data. We document that 18.6% of SNP genotype calls in HLA genes are incorrect and that allele frequencies are estimated with an error greater than ±0.1 at approximately 25% of the SNPs in HLA genes. We found a bias toward overestimation of reference allele frequency for the 1000G data, indicating mapping bias is an important cause of error in frequency estimation in this dataset. We provide a list of sites that have poor allele frequency estimates and discuss the outcomes of including those sites in different kinds of analyses. Because the HLA region is the most polymorphic in the human genome, our results provide insights into the challenges of using of NGS data at other genomic regions of high diversity

7th Drug hypersensitivity meeting: part two

No abstract availabl

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time, and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space. While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes, vast areas of the tropics remain understudied. In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity, but it remains among the least known forests in America and is often underrepresented in biodiversity databases. To worsen this situation, human-induced modifications 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, 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

Composição química do bagaço de cana-de-açúcar amonizado com diferentes doses de uréia e soja grão

The objective of this work was to evaluate the effect of the different levels of urea and ground whole soybean as a urease source on the chemical composition of the ammoniated sugarcane bagasse. Four levels of urea (2%, 4%, 6% e 8% DM) and three levels of ground whole soybean (0%; 2% e 4%, DM) were added to sugarcane bagasse stored during 52 days in plastic bags (50 L). We analyzed the levels of DM, CP, NDF, ADF, cellulose, hemicellulose and lignin. Was used a complete randomized design with three replicates for treatments. The gradual increase of the urea levels in the process of amonização of sugarcane bagasse implied in reduction of NDF, ADF, cellulose, hemicellulose and lignin, and increase of CP. However, the levels of DM were not affected by different levals of urea and whole soybean used in different treatments, differing only in the DM of in nature sugarcane bagasse. The use of ground whole soybean, as source of urease, in the amonização of sugarcane bagasse, was efficient in the reduction of the levels of NDObjetivou-se com este trabalho avaliar o efeito de diferentes doses de uréia e soja grão moída, como fonte de urease, sobre a composição quími- ca do bagaço de cana-de-açúcar amonizado. Utilizaram-se quatro doses de uréia (2, 4, 6 e 8% MS) e três doses de soja grão moída (0; 2 e 4% MS) no bagaço de cana-de-açúcar armazenado por um período de 52 dias, em sacos de polietileno com capacidade de 50 litros. Foram analisados os teores de MS, PB, FDN, FDA, hemicelulose, celulose e lignina. Foi utilizado delineamento experimental inteiramente casualizado com três repetições por tratamento. O aumento das doses de uréia no processo de amonização do bagaço de cana-de- açúcar implicou em redução dos teores de FDN, FDA, celulose, hemicelulose e lignina, e aumento dos teores de PB. Todavia, os teores de MS não foram afetados pelas diferentes doses de uréia e soja grão moída utilizadas nos tratamentos, diferindo apenas da MS do bagaço de cana in natura. A utilização da soja grão moída, como fonte de urease, na amonização do bagaço de cana-de-açúcar, foi eficiente na redução dos níveis de FDN apenas para as doses de 2 e 4% de uréia

Variabilidade espacial de propriedades dendrométricas do eucalipto e de atributos físicos de um Latossolo Vermelho

Este trabalho teve como objetivo analisar a variabilidade espacial de atributos de eucalipto (Eucalyptus urophylla S.T. Blake) e atributos físicos de um Latossolo Vermelho distrófico em Selvíria (MS). A área de estudo possui cerca de 1,98 ha e as amostras de planta e solo foram coletadas em uma grade de amostragem contendo 122 pontos sendo: 84 pontos com espaçamento regular de 15 m e 38 pontos com espaçamento regular de 5 m. Os atributos de planta e solo analisados foram: perímetro na altura do peito, altura da planta, volume de madeira, resistência do solo à penetração e o teor de água no solo. Os atributos das plantas de eucalipto apresentaram moderada variabilidade espacial, ao passo que os atributos do solo apresentaram variabilidade moderada (RP3) e forte (RP1). O modelo exponencial foi o que mais se adequou para os ajustes dos atributos de planta e solo estudados. A correlação linear simples mostrou haver baixa correlação entre os atributos de Eucalyptus urophylla e os atributos físicos do solo