Chromosomal mapping of rDNAs and H3 histone sequences in the grasshopper rhammatocerus brasiliensis (acrididae, gomphocerinae): extensive chromosomal dispersion and co-localization of 5S rDNA/H3 histone clusters in the A complement and B chromosome

<p>Abstract</p> <p>Background</p> <p>Supernumerary B chromosomes occur in addition to standard karyotype and have been described in about 15% of eukaryotes, being the repetitive DNAs the major component of these chromosomes, including in some cases the presence of multigene families. To advance in the understanding of chromosomal organization of multigene families and B chromosome structure and evolution, the distribution of rRNA and H3 histone genes were analyzed in the standard karyotype and B chromosome of three populations of the grasshopper <it>Rhammatocerus brasiliensis</it>.</p> <p>Results</p> <p>The location of major rDNA was coincident with the previous analysis for this species. On the other hand, the 5S rDNA mapped in almost all chromosomes of the standard complement (except in the pair 11) and in the B chromosome, showing a distinct result from other populations previously analyzed. Besides the spreading of 5S rDNA in the genome of <it>R. brasiliensis </it>it was also observed multiple sites for H3 histone genes, being located in the same chromosomal regions of 5S rDNAs, including the presence of the H3 gene in the B chromosome.</p> <p>Conclusions</p> <p>Due to the intense spreading of 5S rRNA and H3 histone genes in the genome of <it>R. brasiliensis</it>, their chromosomal distribution was not informative in the clarification of the origin of B elements. Our results indicate a linked organization for the 5S rRNA and H3 histone multigene families investigated in <it>R. brasiliensis</it>, reinforcing previous data concerning the association of both genes in some insect groups. The present findings contribute to understanding the organization/evolution of multigene families in the insect genomes.</p

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