Common methods for fecal sample storage in field studies yield consistent signatures of individual identity in microbiome sequencing data, bioRxiv, 2016-02-05

Field studies of wild vertebrates are frequently associated with extensive collections of banked fecal samples, which are often collected from known individuals and sometimes also sampled longitudinally across time. Such collections represent unique resources for understanding ecological, behavioral, and phylogenetic effects on the gut microbiome, especially for species of particular conservation concern. However, we do not understand whether sample storage methods confound the ability to investigate interindividual variation in gut microbiome profiles. This uncertainty arises in part because comparisons across storage methods to date generally include only a few (≤5) individuals, or analyze pooled samples. Here, we used n=52 samples from 13 rhesus macaque individuals to compare immediate freezing, the gold standard of preservation, to three methods commonly used in vertebrate field studies storage in ethanol, lyophilization following ethanol storage, and storage in RNAlater. We found that the signature of individual identity consistently outweighed storage effects alpha diversity and beta diversity measures were significantly correlated across methods, and while samples often clustered by donor, they never clustered by storage method. Provided that all analyzed samples are stored the same way, banked fecal samples therefore appear highly suitable for investigating variation in gut microbiota. Our results open the door to a much-expanded perspective on variation in the gut microbiome across species and ecological contexts.

biorxiv genomics 0-100-users 2016

Comparative Analysis of Single-Cell RNA Sequencing Methods, bioRxiv, 2016-01-14

AbstractBackgroundSingle-cell RNA sequencing (scRNA-seq) offers exciting possibilities to address biological and medical questions, but a systematic comparison of recently developed protocols is still lacking.ResultsWe generated data from 447 mouse embryonic stem cells using Drop-seq, SCRB-seq, Smart-seq (on Fluidigm C1) and Smart-seq2 and analyzed existing data from 35 mouse embryonic stem cells prepared with CEL-seq. We find that Smart-seq2 is the most sensitive method as it detects the most genes per cell and across cells. However, it shows more amplification noise than CEL-seq, Drop-seq and SCRB-seq as it cannot use unique molecular identifiers (UMIs). We use simulations to model how the observed combinations of sensitivity and amplification noise affects detection of differentially expressed genes and find that SCRB-seq reaches 80% power with the fewest number of cells. When considering cost-efficiency at different sequencing depths at 80% power, we find that Drop-seq is preferable when quantifying transcriptomes of a large numbers of cells with low sequencing depth, SCRB-seq is preferable when quantifying transcriptomes of fewer cells and Smart-seq2 is preferable when annotating andor quantifying transcriptomes of fewer cells as long one can use in-house produced transposase.ConclusionsOur analyses allows an informed choice among five prominent scRNA-seq protocols and provides a solid framework for benchmarking future improvements in scRNA-seq methodologies.

biorxiv genomics 0-100-users 2016

No evidence for extensive horizontal gene transfer in the genome of the tardigrade Hypsibius dujardini, bioRxiv, 2015-12-02

AbstractTardigrades are meiofaunal ecdysozoans that are key to understanding the origins of Arthropoda. Many species of Tardigrada can survive extreme conditions through cryptobiosis. In a recent paper (Boothby TC et al (2015) Evidence for extensive horizontal gene transfer from the draft genome of a tardigrade. Proc Natl Acad Sci USA 11215976-15981) the authors concluded that the tardigrade Hypsibius dujardini had an unprecedented proportion (17%) of genes originating through functional horizontal gene transfer (fHGT), and speculated that fHGT was likely formative in the evolution of cryptobiosis. We independently sequenced the genome of H. dujardini. As expected from whole-organism DNA sampling, our raw data contained reads from non-target genomes. Filtering using metagenomics approaches generated a draft H. dujardini genome assembly of 135 Mb with superior assembly metrics to the previously published assembly. Additional microbial contamination likely remains. We found no support for extensive fHGT. Among 23,021 gene predictions we identified 0.2% strong candidates for fHGT from bacteria, and 0.2% strong candidates for fHGT from non-metazoan eukaryotes. Cross-comparison of assemblies showed that the overwhelming majority of HGT candidates in the Boothby et al. genome derived from contaminants. We conclude that fHGT into H. dujardini accounts for at most 1-2% of genes and that the proposal that one sixth of tardigrade genes originate from functional HGT events is an artefact of undetected contamination.

biorxiv genomics 200-500-users 2015

 

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