Howard Hughes Medical Institute

About: Howard Hughes Medical Institute is a nonprofit organization based out in Chevy Chase, Maryland, United States. It is known for research contribution in the topics: Gene & RNA. The organization has 20371 authors who have published 34677 publications receiving 5247143 citations. The organization is also known as: HHMI & hhmi.org.

Lattice Light Sheet Microscopy: Imaging Molecules to Embryos at High Spatiotemporal Resolution

Abstract: Although fluorescence microscopy provides a crucial window into the physiology of living specimens, many biological processes are too fragile, are too small, or occur too rapidly to see clearly with existing tools. We crafted ultrathin light sheets from two-dimensional optical lattices that allowed us to image three-dimensional (3D) dynamics for hundreds of volumes, often at subsecond intervals, at the diffraction limit and beyond. We applied this to systems spanning four orders of magnitude in space and time, including the diffusion of single transcription factor molecules in stem cell spheroids, the dynamic instability of mitotic microtubules, the immunological synapse, neutrophil motility in a 3D matrix, and embryogenesis in Caenorhabditis elegans and Drosophila melanogaster. The results provide a visceral reminder of the beauty and the complexity of living systems.

Diet drives convergence in gut microbiome functions across mammalian phylogeny and within humans

Abstract: Coevolution of mammals and their gut microbiota has profoundly affected their radiation into myriad habitats. We used shotgun sequencing of microbial community DNA and targeted sequencing of bacterial 16S ribosomal RNA genes to gain an understanding of how microbial communities adapt to extremes of diet. We sampled fecal DNA from 33 mammalian species and 18 humans who kept detailed diet records, and we found that the adaptation of the microbiota to diet is similar across different mammalian lineages. Functional repertoires of microbiome genes, such as those encoding carbohydrate-active enzymes and proteases, can be predicted from bacterial species assemblages. These results illustrate the value of characterizing vertebrate gut microbiomes to understand host evolutionary histories at a supraorganismal level.

Mutations in the hepatocyte nuclear factor-1α gene in maturity-onset diabetes of the young (MODY3)

Abstract: The disease non-insulin-dependent (type 2) diabetes mellitus (NIDDM) is characterized by abnormally high blood glucose resulting from a relative deficiency of insulin. It affects about 2% of the world's population and treatment of diabetes and its complications are an increasing health-care burden. Genetic factors are important in the aetiology of NIDDM, and linkage studies are starting to localize some of the genes that influence the development of this disorder. Maturity-onset diabetes of the young (MODY), a single-gene disorder responsible for 2-5% of NIDDM, is characterized by autosomal dominant inheritance and an age of onset of 25 years or younger. MODY genes have been localized to chromosomes 7, 12 and 20 (refs 5, 7, 8) and clinical studies indicate that mutations in these genes are associated with abnormal patterns of glucose-stimulated insulin secretion. The gene on chromosome 7 (MODY2) encodes the glycolytic enzyme glucokinases which plays a key role in generating the metabolic signal for insulin secretion and in integrating hepatic glucose uptake. Here we show that subjects with the MODY3-form of NIDDM have mutations in the gene encoding hepatocyte nuclear factor-1alpha (HNF-1alpha, which is encoded by the gene TCF1). HNF-1alpha is a transcription factor that helps in the tissue-specific regulation of the expression of several liver genes and also functions as a weak transactivator of the rat insulin-I gene.

Long noncoding RNAs: past, present, and future.

Abstract: Long noncoding RNAs (lncRNAs) have gained widespread attention in recent years as a potentially new and crucial layer of biological regulation. lncRNAs of all kinds have been implicated in a range of developmental processes and diseases, but knowledge of the mechanisms by which they act is still surprisingly limited, and claims that almost the entirety of the mammalian genome is transcribed into functional noncoding transcripts remain controversial. At the same time, a small number of well-studied lncRNAs have given us important clues about the biology of these molecules, and a few key functional and mechanistic themes have begun to emerge, although the robustness of these models and classification schemes remains to be seen. Here, we review the current state of knowledge of the lncRNA field, discussing what is known about the genomic contexts, biological functions, and mechanisms of action of lncRNAs. We also reflect on how the recent interest in lncRNAs is deeply rooted in biology’s longstanding concern with the evolution and function of genomes.

Selecting a Maximally Informative Set of Single-Nucleotide Polymorphisms for Association Analyses Using Linkage Disequilibrium

Abstract: Common genetic polymorphisms may explain a portion of the heritable risk for common diseases. Within candidate genes, the number of common polymorphisms is finite, but direct assay of all existing common polymorphism is inefficient, because genotypes at many of these sites are strongly correlated. Thus, it is not necessary to assay all common variants if the patterns of allelic association between common variants can be described. We have developed an algorithm to select the maximally informative set of common single-nucleotide polymorphisms (tagSNPs) to assay in candidate-gene association studies, such that all known common polymorphisms either are directly assayed or exceed a threshold level of association with a tagSNP. The algorithm is based on the r2 linkage disequilibrium (LD) statistic, because r2 is directly related to statistical power to detect disease associations with unassayed sites. We show that, at a relatively stringent r2 threshold (r2>0.8), the LD-selected tagSNPs resolve >80% of all haplotypes across a set of 100 candidate genes, regardless of recombination, and tag specific haplotypes and clades of related haplotypes in nonrecombinant regions. Thus, if the patterns of common variation are described for a candidate gene, analysis of the tagSNP set can comprehensively interrogate for main effects from common functional variation. We demonstrate that, although common variation tends to be shared between populations, tagSNPs should be selected separately for populations with different ancestries.