Identification and quantification of chimeric sequencing reads in a highly multiplexed RAD-seq protocol.

Highly multiplexed approaches have become common in genomic studies. They have improved the cost-effectiveness of genotyping hundreds of individuals using combinatorially barcoded adapters. These strategies, however, can potentially misassigned reads to incorrect samples. Here, we used a modified quaddRAD protocol to analyse the occurrence of index hopping and PCR chimeras in a series of experiments with up to 100 multiplexed samples per sequencing lane (639 samples in total). We created two types of sequencing libraries: four libraries of type A, where PCRs were run on individual samples before multiplexing, and three libraries of type B, where PCRs were run on pooled samples. We used fixed pairs of inner barcodes to identify chimeric reads. Type B libraries show a higher percentage of misassigned reads (1.15%) than type A libraries (0.65%). We also quantify the commonly undetectable chimeric sequences that occur whenever multiplexed groups of samples with different outer barcodes are sequenced together on a single flow cell. Our results suggest that these types of chimeric sequences represent up to 1.56% and 1.29% of reads in type A and B libraries, respectively. We also show that increasing the number of mismatches allowed for barcode rescue to above 2 dramatically increases the number of recovered chimeric reads. We provide recommendations for developing highly multiplexed RAD-seq protocols and analysing the resulting data to minimize the generation of chimeric sequences, allowing their quantification and a finer control on the number of PCR cycles necessary to generate enough input DNA for library preparation.

Synchronous Seasonality in the Gut Microbiota of Wild Mouse Populations.

The gut microbiome performs many important functions in mammalian hosts, with community composition shaping its functional role. However, the factors that drive individual microbiota variation in wild animals and to what extent these are predictable or idiosyncratic across populations remains poorly understood. Here, we use a multi-population dataset from a common rodent species (the wood mouse, Apodemus sylvaticus), to test whether a consistent "core" gut microbiota is identifiable in this species, and to what extent the predictors of microbiota variation are consistent across populations. Between 2014 and 2018 we used capture-mark-recapture and 16S rRNA profiling to intensively monitor two wild wood mouse populations and their gut microbiota, as well as characterising the microbiota from a laboratory-housed colony of the same species. Although the microbiota was broadly similar at high taxonomic levels, the two wild populations did not share a single bacterial amplicon sequence variant (ASV), despite being only 50km apart. Meanwhile, the laboratory-housed colony shared many ASVs with one of the wild populations from which it is thought to have been founded decades ago. Despite not sharing any ASVs, the two wild populations shared a phylogenetically more similar microbiota than either did with the colony, and the factors predicting compositional variation in each wild population were remarkably similar. We identified a strong and consistent pattern of seasonal microbiota restructuring that occurred at both sites, in all years, and within individual mice. While the microbiota was highly individualised, some seasonal convergence occurred in late winter/early spring. These findings reveal highly repeatable seasonal gut microbiota dynamics in multiple populations of this species, despite different taxa being involved. This provides a platform for future work to understand the drivers and functional implications of such predictable seasonal microbiome restructuring, including whether it might provide the host with adaptive seasonal phenotypic plasticity.