J. Craig Venter Institute

About: J. Craig Venter Institute is a nonprofit organization based out in La Jolla, California, United States. It is known for research contribution in the topics: Genome & Gene. The organization has 1268 authors who have published 2300 publications receiving 304083 citations. The organization is also known as: JCVI & The Institute for Genomic Research.

Evolutionary trends in host physiology outweigh dietary niche in structuring primate gut microbiomes.

Abstract: Over the past decade several studies have reported that the gut microbiomes of mammals with similar dietary niches exhibit similar compositional and functional traits. However, these studies rely heavily on samples from captive individuals and often confound host phylogeny, gut morphology, and diet. To more explicitly test the influence of host dietary niche on the mammalian gut microbiome we use 16S rRNA gene amplicon sequencing and shotgun metagenomics to compare the gut microbiota of 18 species of wild non-human primates classified as either folivores or closely related non-folivores, evenly distributed throughout the primate order and representing a range of gut morphological specializations. While folivory results in some convergent microbial traits, collectively we show that the influence of host phylogeny on both gut microbial composition and function is much stronger than that of host dietary niche. This pattern does not result from differences in host geographic location or actual dietary intake at the time of sampling, but instead appears to result from differences in host physiology. These findings indicate that mammalian gut microbiome plasticity in response to dietary shifts over both the lifespan of an individual host and the evolutionary history of a given host species is constrained by host physiological evolution. Therefore, the gut microbiome cannot be considered separately from host physiology when describing host nutritional strategies and the emergence of host dietary niches.

Genomic sequencing of uncultured microorganisms from single cells

Abstract: Sequencing DNA from single cells has opened new windows onto the microbial world. It is becoming routine to sequence bacterial species directly from environmental samples or clinical specimens without the need to develop cultivation methods. Recent technical improvements often allow nearly complete genome assembly from these otherwise inaccessible species. New bioinformatics methods are also improving genome assembly from single cells. The use of single-cell sequencing in combination with metagenomic analysis is also emerging as a powerful new strategy to analyse bacterial communities. Here, the technical developments that have enabled single-cell sequencing, as well as some of the most exciting applications of this approach from the past few years, are reviewed.

Complex mtDNA constitutes an approximate 620-kb insertion on Arabidopsis thaliana chromosome 2: Implication of potential sequencing errors caused by large-unit repeats

Abstract: Previously conducted sequence analysis of Arabidopsis thaliana (ecotype Columbia-0) reported an insertion of 270-kb mtDNA into the pericentric region on the short arm of chromosome 2. DNA fiber-based fluorescence in situ hybridization analyses reveal that the mtDNA insert is 618 ± 42 kb, ≈2.3 times greater than that determined by contig assembly and sequencing analysis. Portions of the mitochondrial genome previously believed to be absent were identified within the insert. Sections of the mtDNA are repeated throughout the insert. The cytological data illustrate that DNA contig assembly by using bacterial artificial chromosomes tends to produce a minimal clone path by skipping over duplicated regions, thereby resulting in sequencing errors. We demonstrate that fiber-fluorescence in situ hybridization is a powerful technique to analyze large repetitive regions in the higher eukaryotic genomes and is a valuable complement to ongoing large genome sequencing projects.

A probabilistic method for identifying start codons in bacterial genomes.

Abstract: As the pace of genome sequencing has accelerated, the need for highly accurate gene prediction systems has grown. Computational systems for identifying genes in prokaryotic genomes have sensitivities of 98-99% or higher (Delcher et al., Nucleic Acids Res., 27, 4636-4641, 1999). These accuracy figures are calculated by comparing the locations of verified stop codons to the predictions. Determining the accuracy of start codon prediction is more problematic, however, due to the relatively small number of start sites that have been confirmed by independent, non-computational methods. Nonetheless, the accuracy of gene finders at predicting the exact gene boundaries at both the 5' and 3' ends of genes is of critical importance for microbial genome annotation, especially in light of the important signaling information that is sometimes found on the 5' end of a protein coding region. In this paper we propose a probabilistic method to improve the accuracy of gene identification systems at finding precise translation start sites. The new system, RBSfinder, is tested on a validated set of genes from Escherichia coli, for which it improves the accuracy of start site locations predicted by computational gene finding systems from the range 67-77% to 90% correct.