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Biology subjects

Fidan, F. R.

Publications and source records attributed to Fidan, F. R..

3 recordsLinked to original sources

Investigating DNA methylation changes associated with food production using paleogenomes

AO_SCPLOWBSTRACTC_SCPLOWThe Neolithic transition introduced major diet and lifestyle changes to human populations across continents. Beyond well-documented bioarchaeological and genetic effects, whether these changes also had molecular-level epigenetic repercussions in past human populations has been an open question. In fact, methylation signatures can be inferred from UDG-treated ancient DNA through postmortem damage patterns, but with low signal-to-noise ratios; it is thus unclear whether published paleogenomes would provide the necessary resolution to discover systematic effects of lifestyle and diet shifts. To address this we compiled UDG-treated shotgun genomes of 13 pre-Neolithic hunter-gatherer (HGs) and 21 Neolithic farmer (NFs) individuals from West and North Eurasia, published by six different laboratories and with coverage c.1x-58x (median=9x). We used epiPALEOMIX and a Monte Carlo normalization scheme to estimate methylation levels per genome. Our paleomethylome dataset showed expected genome-wide methylation patterns such as CpG island hypomethylation. However, analysing the data using various approaches did not yield any systematic signals for subsistence type, genetic sex, or tissue effects. Comparing the HG-NF methylation differences in our dataset with methylation differences between hunter-gatherers vs. farmers in modern-day Central Africa also did not yield consistent results. Meanwhile, paleomethylome profiles did cluster strongly by their laboratories of origin. Our results mark the importance of minimizing technical noise for capturing subtle biological signals from paleomethylomes.

evolutionary biology↗

The first complete genome of the extinct European wild ass (Equus hemionus hydruntinus)

We present paleogenomes of three morphologically-unidentified Anatolian equids dating to the 1st millennium BCE, sequenced to coverages of 0.6-6.4X. Mitochondrial DNA haplotypes of the Anatolian individuals clustered with those of Equus hydruntinus (or Equus hemionus hydruntinus), the extinct European wild ass. The Anatolian wild ass whole genome profiles fall outside the genomic diversity of other extant and past Asiatic wild ass (E.hemionus) lineages. These observations strongly suggest that the three Anatolian wild asses represent E.hydruntinus, making them the latest recorded survivors of this lineage, about a millennium later than the latest observations in the zooarchaeological record. Comparative genomic analyses suggest that E.hydruntinus was a sister clade to all ancient and present-day E.hemionus lineages, representing an early split. We also find indication of gene flow between hydruntines and Middle Eastern wild asses. Analyses of genome-wide heterozygosity and runs of homozygosity reveal that the Anatolian wild ass population had severely lost genetic diversity by the mid-1st millennium BCE, a likely omen of its eventual demise.

genomics↗

SWAMPy: Simulating SARS-CoV-2 Wastewater Amplicon Metagenomes with Python

MotivationTracking SARS-CoV-2 variants through genomic sequencing has been an important part of the global response to the pandemic. As well as whole-genome sequencing of clinical samples, this surveillance effort has been aided by amplicon sequencing of wastewater samples, which proved effective in real case studies. Because of its relevance to public healthcare decisions, testing and benchmarking wastewater sequencing analysis methods is also crucial, which necessitates a simulator. Although metagenomic simulators exist, none are fit for the purpose of simulating the metagenomes produced through amplicon sequencing of wastewater. ResultsOur new simulation tool, SWAMPy (Simulating SARS-CoV-2 Wastewater Amplicon Metagenomes with Python), is intended to provide realistic simulated SARS-CoV-2 wastewater sequencing datasets with which other programs that rely on this type of data can be evaluated and improved. AvailabilityThe code for this project is available at https://github.com/goldman-gp-ebi/SWAMPy It can be installed on any Unix-based operating system and is available under the GPL-v3 license.

bioinformatics↗