Dataset Information

Quantifying spatiotemporal variability and noise in absolute microbiota abundances using replicate sampling.

ABSTRACT: Metagenomic sequencing has enabled detailed investigation of diverse microbial communities, but understanding their spatiotemporal variability remains an important challenge. Here, we present decomposition of variance using replicate sampling (DIVERS), a method based on replicate sampling and spike-in sequencing. The method quantifies the contributions of temporal dynamics, spatial sampling variability, and technical noise to the variances and covariances of absolute bacterial abundances. We applied DIVERS to investigate a high-resolution time series of the human gut microbiome and a spatial survey of a soil bacterial community in Manhattan's Central Park. Our analysis showed that in the gut, technical noise dominated the abundance variability for nearly half of the detected taxa. DIVERS also revealed substantial spatial heterogeneity of gut microbiota, and high temporal covariances of taxa within the Bacteroidetes phylum. In the soil community, spatial variability primarily contributed to abundance fluctuations at short time scales (weeks), while temporal variability dominated at longer time scales (several months).

SUBMITTER: Ji BW

PROVIDER: S-EPMC7219825 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Quantifying spatiotemporal variability and noise in absolute microbiota abundances using replicate sampling.

Ji Brian W BW Sheth Ravi U RU Dixit Purushottam D PD Huang Yiming Y Kaufman Andrew A Wang Harris H HH Vitkup Dennis D

Nature methods 20190715 8

Metagenomic sequencing has enabled detailed investigation of diverse microbial communities, but understanding their spatiotemporal variability remains an important challenge. Here, we present decomposition of variance using replicate sampling (DIVERS), a method based on replicate sampling and spike-in sequencing. The method quantifies the contributions of temporal dynamics, spatial sampling variability, and technical noise to the variances and covariances of absolute bacterial abundances. We app ...[more]

PMID: 31308552

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Project description:Anthropogenic noise is a widespread and growing form of sensory pollution associated with the expansion of human infrastructure. One specific source of constant and intense noise is that produced by compressors used for the extraction and transportation of natural gas. Terrestrial arthropods play a central role in many ecosystems, and given that numerous species rely upon airborne sounds and substrate-borne vibrations in their life histories, we predicted that increased background sound levels or the presence of compressor noise would influence their distributions. In the second largest natural gas field in the United States (San Juan Basin, New Mexico, USA), we assessed differences in the abundances of terrestrial arthropod families and community structure as a function of compressor noise and background sound level. Using pitfall traps, we simultaneously sampled five sites adjacent to well pads that possessed operating compressors, and five alternate, quieter well pad sites that lacked compressors, but were otherwise similar. We found a negative association between sites with compressor noise or higher levels of background sound and the abundance of five arthropod families and one genus, a positive relationship between loud sites and the abundance of one family, and no relationship between noise level or compressor presence and abundance for six families and two genera. Despite these changes, we found no evidence of community turnover as a function of background sound level or site type (compressor and noncompressor). Our results indicate that anthropogenic noise differentially affects the abundances of some arthropod families. These preliminary findings point to a need to determine the direct and indirect mechanisms driving these observed responses. Given the diverse and important ecological functions provided by arthropods, changes in abundances could have ecological implications. Therefore, we recommend the consideration of arthropods in the environmental assessment of noise-producing infrastructure.

Project description:Background: RNA-seq is revolutionizing the way we study transcriptomes. mRNA can be surveyed without prior knowledge of gene transcripts. Alternative splicing of transcript isoforms and the identification of previously unknown exons are being reported. Initial reports of differences in exon usage, and splicing between samples as well as quantitative differences among samples are beginning to surface. Biological variation has been reported to be larger than technical variation. In addition, technical variation has been reported to be in line with expectations due to random sampling. However, strategies for dealing with technical variation will differ depending on the magnitude. The size of technical variance, and the role of sampling are examined in this manuscript. Results: Independent Solexa/Illumina experiments containing technical replicates are analyzed. When coverage is low, large disagreements between technical replicates are apparent. Exon detection between technical replicates is highly variable when the coverage is less than 5 reads per nucleotide and estimates of gene expression are more likely to disagree when coverage is low. Although large disagreements in the estimates of expression are observed at all levels of coverage. Conclusions: Technical variability is too high to ignore. Technical variability results in inconsistent detection of exons at low levels of coverage. Further, the estimate of the relative abundance of a transcript can substantially disagree, even when coverage levels are high. This may be due to the low sampling fraction and if so, it will persist as an issue needing to be addressed in experimental design even as the next wave of technology produces larger numbers of reads. We provide practical recommendations for dealing with the technical variability, without dramatic cost increases. Three independent samples of D. simulans male heads were collected with each sample representing a unique pool of biological material. Each sample was prepared according to manufacturer's instructions and then the same library was run on two lanes of a Solexa/Illumina flow cell, resulting in two technical replicates for each biological replicate, runs were 36 base-pair paired end.

Project description:Background: RNA-seq is revolutionizing the way we study transcriptomes. mRNA can be surveyed without prior knowledge of gene transcripts. Alternative splicing of transcript isoforms and the identification of previously unknown exons are being reported. Initial reports of differences in exon usage, and splicing between samples as well as quantitative differences among samples are beginning to surface. Biological variation has been reported to be larger than technical variation. In addition, technical variation has been reported to be in line with expectations due to random sampling. However, strategies for dealing with technical variation will differ depending on the magnitude. The size of technical variance, and the role of sampling are examined in this manuscript. Results: Independent Solexa/Illumina experiments containing technical replicates are analyzed. When coverage is low, large disagreements between technical replicates are apparent. Exon detection between technical replicates is highly variable when the coverage is less than 5 reads per nucleotide and estimates of gene expression are more likely to disagree when coverage is low. Although large disagreements in the estimates of expression are observed at all levels of coverage. Conclusions: Technical variability is too high to ignore. Technical variability results in inconsistent detection of exons at low levels of coverage. Further, the estimate of the relative abundance of a transcript can substantially disagree, even when coverage levels are high. This may be due to the low sampling fraction and if so, it will persist as an issue needing to be addressed in experimental design even as the next wave of technology produces larger numbers of reads. We provide practical recommendations for dealing with the technical variability, without dramatic cost increases. Three independent samples of D. melanogaster female heads were collected with each sample representing a unique pool of biological material. Each sample was prepared according to manufacturer's instructions and then the same library was run on two lanes of a Solexa/Illumina flow cell, resulting in two technical replicates for each biological replicate, runs were 36 base-pair paired end.

Dataset Information

Quantifying spatiotemporal variability and noise in absolute microbiota abundances using replicate sampling.

Publications

Quantifying spatiotemporal variability and noise in absolute microbiota abundances using replicate sampling.

Similar Datasets

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