Biology subjects

Guschanski, K.

Publications and source records attributed to Guschanski, K..

23 records · Page 2Linked to original sources

bioRxiv2019

Estimates of genetic load in small populations suggest extensive purging of deleterious alleles

It is commonly thought that declining populations will experience negative genetic consequences as a result of increased inbreeding. Here we estimated the average deleteriousness of derived alleles in a range of mammals and found that species with historically small population size and low genetic diversity often have lower genetic load than species with large population sizes. This is likely the result of genetic purging - the more efficient removal of partially deleterious recessive alleles from inbred populations. Our findings suggest that genetic purging occurs over long evolutionary time frames, and therefore rapid population declines are likely to dis-proportionally increase mutational load in species with high diversity, as they carry many deleterious alleles that can reach fixation before genetic purging can remove them.

genomics↗

bioRxiv2019

The genome of the endangered dryas monkey provides new insights into the evolutionary history of the vervets

Genomic data can be a powerful tool for inferring ecology, behaviour and conservation needs of highly elusive species, particularly when other sources of information are hard to come by. Here we focus on the Dryas monkey (Cercopithecus dryas), an endangered primate endemic to the Congo Basin with cryptic behaviour and possibly less than 250 remaining individuals. Using whole genome sequencing data we show that the Dryas monkey represents a sister lineage to the vervets (Chlorocebus sp.) and has diverged from them around 1.4 million years ago with additional bi-directional gene flow [~]750,000 - [~]500,000 years ago that has likely involved the crossing of the Congo River. Together with evidence of gene flow across the Congo River in bonobos and okapis, our results suggest that the fluvial topology of the Congo River might have been more dynamic than previously recognised. Despite the presence of several homozygous loss-of-function mutations in genes associated with sperm mobility and immunity, we find high genetic diversity and low levels of inbreeding and genetic load in the studied Dryas monkey individual. This suggests that the current population carries sufficient genetic variability for long-term survival and might be larger than currently recognised. We thus provide an example of how genomic data can directly improve our understanding of highly elusive species.

genomics↗

bioRxiv2019

Dental calculus as a tool to study the evolution of the oral microbiome in mammals

Animals and their associated microbiomes share a long evolutionary history, influenced by a complex interplay between extrinsic environmental and intrinsic host factors. However, we know little about microbiome responses to long-lasting environmental and host-centred processes, which require studying microbiome changes through time. Here, we apply a temporal metagenomics approach to dental calculus, the calcified oral microbial biofilm. We establish dental calculus as a valuable tool for the study of host microbiome evolution by characterising the taxonomic and functional composition of the oral microbiome in a variety of wild mammals. We detect oral pathogens in individuals with evidence of oral disease, assemble near-complete bacterial genomes from historical specimens, characterise antibiotic resistance genes even before the advent of industrial antibiotic production, reconstruct components of the host diet and recover host genetic profiles. Our work demonstrates how dental calculus can be used in the future to study the evolution of oral microbiomes and pathogens, and the impact of anthropogenic changes on wildlife and the environment.

evolutionary biology↗

bioRxiv2018

Characterising the microbiome from host shotgun sequencing data: bacterial and diatom community dynamics derived from killer whale skin

Recent exploration into the interactions and relationship between hosts and their microbiota has revealed a connection between many aspects of the hosts biology, health and associated microorganisms. Whereas amplicon sequencing has traditionally been used to characterise the microbiome, the increasing number of published population genomics datasets offer an underexploited opportunity to study microbial profiles from the host shotgun sequencing data. Here, we use sequence data originally generated from killer whale Orcinus orca skin biopsies for population genomics, to characterise the skin microbiome and investigate how host social and geographic factors influence the microbial community composition. Having identified 845 microbial taxa from 2.4 million reads that did not map to the killer whale reference genome, we found that both ecotypic and geographic factors influence community composition of killer whale skin microbiomes. Furthermore, we uncovered key taxa that drive the microbiome community composition and showed that they are embedded in unique networks, one of which is tentatively linked to diatom presence and poor skin condition. Community composition differed between Antarctic killer whales with and without diatom coverage, suggesting that the previously reported episodic migrations of Antarctic killer whales to warmer waters associated with skin turnover may control the effects of potentially pathogenic bacteria such as Tenacibaculum dicentrarchi. Our work demonstrates the feasibility of microbiome studies from host shotgun sequencing data and highlights the importance of metagenomics in understanding the relationship between host and microbial ecology.

evolutionary biology↗

bioRxiv2017

Low rate of index hopping on the Illumina HiSeq X platform

The high-throughput capacities of the Illumina sequencing platforms and possibility to label samples individually have encouraged a wide use of sample multiplexing. However, this practice results in read misassignment (usually <1%) across samples sequenced on the same lane. Alarmingly high rates of read misassignment of up to 10% were reported for the latest generation of lllumina sequencing machines. This potentially calls into question previously generated results and may make future use of the newest generation of platforms prohibitive. In this study we rely on barcodes, short sequences that are directly ligated to both ends of the DNA insert, which allows us to quantify the amount of index hopping. Correcting for multiple sources of noise, we identify on average only 0.470% of reads containing a hopped index. Multiplexing of samples on this platform is therefore unlikely to cause markedly different results to those obtained from older platforms.

bioinformatics↗