Ancient genomics

The past decade has witnessed a revolution in ancient DNA (aDNA) research. Although the field's focus was previously limited to mitochondrial DNA and a few nuclear markers, whole genome sequences from the deep past can now be retrieved. This breakthrough is tightly connected to the massive sequence throughput of next generation sequencing platforms and the ability to target short and degraded DNA molecules. Many ancient specimens previously unsuitable for DNA analyses because of extensive degradation can now successfully be used as source materials. Additionally, the analytical power obtained by increasing the number of sequence reads to billions effectively means that contamination issues that have haunted aDNA research for decades, particularly in human studies, can now be efficiently and confidently quantified. At present, whole genomes have been sequenced from ancient anatomically modern humans, archaic hominins, ancient pathogens and megafaunal species. Those have revealed important functional and phenotypic information, as well as unexpected adaptation, migration and admixture patterns. As such, the field of aDNA has entered the new era of genomics and has provided valuable information when testing specific hypotheses related to the past.No Full Tex

Snakemake rna-seq template

<p><strong>RNA-seq analysis with Snakemake</strong></p> <p><a href="https://snakemake.readthedocs.io/en/stable/">Snakemake</a> is a workflow manager system for</p> <p>creating reproducible and scalable pipelines.</p> <p> </p> <p>This repository allows you to perform a <em>*RNA-seq analysis*</em>, from raw reads to differential expression and is customised</p> <p>from <a href="https://github.com/snakemake-workflows/rna-seq-star-deseq2">this template </a>by <strong>Johannes Köster</strong>.</p> <p>Reads can be supplied either as <strong>single-end</strong> or <strong>paired-end</strong> and optionally with technical replicates.</p> <p>Sequencing files from technical replicates are merged at the mapping step</p> <p>See full description there https://gitlab.lcsb.uni.lu/aurelien.ginolhac/snakemake-rna-seq</p&gt

Snakemake rna-seq template

<p><strong>RNA-seq analysis with Snakemake</strong></p><p><a href="https://snakemake.readthedocs.io/en/stable/">Snakemake</a> is a workflow manager system for</p><p>creating reproducible and scalable pipelines.</p><p> </p><p>This repository allows you to perform a <i>*RNA-seq analysis*</i>, from raw reads to differential expression and is customised</p><p>from <a href="https://github.com/snakemake-workflows/rna-seq-star-deseq2">this template </a>by <strong>Johannes Köster</strong>.</p><p>Reads can be supplied either as <strong>single-end</strong> or <strong>paired-end</strong> and optionally with technical replicates.</p><p>Sequencing files from technical replicates are merged at the mapping step</p><p>See full description there <a href="https://gitlab.lcsb.uni.lu/aurelien.ginolhac/snakemake-rna-seq">https://gitlab.lcsb.uni.lu/aurelien.ginolhac/snakemake-rna-seq</a></p&gt

Snakemake rna-seq template

<p><strong>RNA-seq analysis with Snakemake</strong></p><p><a href="https://snakemake.readthedocs.io/en/stable/">Snakemake</a> is a workflow manager system for</p><p>creating reproducible and scalable pipelines.</p><p> </p><p>This repository allows you to perform a <i>*RNA-seq analysis*</i>, from raw reads to differential expression and is customised</p><p>from <a href="https://github.com/snakemake-workflows/rna-seq-star-deseq2">this template </a>by <strong>Johannes Köster</strong>.</p><p>Reads can be supplied either as <strong>single-end</strong> or <strong>paired-end</strong> and optionally with technical replicates.</p><p>Sequencing files from technical replicates are merged at the mapping step</p><p>See full description there <a href="https://gitlab.lcsb.uni.lu/aurelien.ginolhac/snakemake-rna-seq">https://gitlab.lcsb.uni.lu/aurelien.ginolhac/snakemake-rna-seq</a></p&gt

Improving ancient DNA read mapping against modern reference genomes

Abstract Background Next-Generation Sequencing has revolutionized our approach to ancient DNA (aDNA) research, by providing complete genomic sequences of ancient individuals and extinct species. However, the recovery of genetic material from long-dead organisms is still complicated by a number of issues, including post-mortem DNA damage and high levels of environmental contamination. Together with error profiles specific to the type of sequencing platforms used, these specificities could limit our ability to map sequencing reads against modern reference genomes and therefore limit our ability to identify endogenous ancient reads, reducing the efficiency of shotgun sequencing aDNA. Results In this study, we compare different computational methods for improving the accuracy and sensitivity of aDNA sequence identification, based on shotgun sequencing reads recovered from Pleistocene horse extracts using Illumina GAIIx and Helicos Heliscope platforms. We show that the performance of the Burrows Wheeler Aligner (BWA), that has been developed for mapping of undamaged sequencing reads using platforms with low rates of indel-types of sequencing errors, can be employed at acceptable run-times by modifying default parameters in a platform-specific manner. We also examine if trimming likely damaged positions at read ends can increase the recovery of genuine aDNA fragments and if accurate identification of human contamination can be achieved using a strategy previously suggested based on best hit filtering. We show that combining our different mapping and filtering approaches can increase the number of high-quality endogenous hits recovered by up to 33%. Conclusions We have shown that Illumina and Helicos sequences recovered from aDNA extracts could not be aligned to modern reference genomes with the same efficiency unless mapping parameters are optimized for the specific types of errors generated by these platforms and by post-mortem DNA damage. Our findings have important implications for future aDNA research, as we define mapping guidelines that improve our ability to identify genuine aDNA sequences, which in turn could improve the genotyping accuracy of ancient specimens. Our framework provides a significant improvement to the standard procedures used for characterizing ancient genomes, which is challenged by contamination and often low amounts of DNA material.</p