An expanded mammal mitogenome dataset from Southeast Asia

Abstract Southeast (SE) Asia is 1 of the most biodiverse regions in the world, and it holds approximately 20% of all mammal species. Despite this, the majority of SE Asia's genetic diversity is still poorly characterized. The growing interest in using environmental DNA to assess and monitor SE Asian species, in particular threatened mammals—has created the urgent need to expand the available reference database of mitochondrial barcode and complete mitogenome sequences. We have partially addressed this need by generating 72 new mitogenome sequences reconstructed from DNA isolated from a range of historical and modern tissue samples. Approximately 55 gigabases of raw sequence were generated. From this data, we assembled 72 complete mitogenome sequences, with an average depth of coverage of ×102.9 and ×55.2 for modern samples and historical samples, respectively. This dataset represents 52 species, of which 30 species had no previous mitogenome data available. The mitogenomes were geotagged to their sampling location, where known, to display a detailed geographical distribution of the species. Our new database of 52 taxa will strongly enhance the utility of environmental DNA approaches for monitoring mammals in SE Asia as it greatly increases the likelihoods that identification of metabarcoding sequencing reads can be assigned to reference sequences. This magnifies the confidence in species detections and thus allows more robust surveys and monitoring programmes of SE Asia's threatened mammal biodiversity. The extensive collections of historical samples from SE Asia in western and SE Asian museums should serve as additional valuable material to further enrich this reference database.

[1]  Richard Durbin,et al.  Sequence analysis Fast and accurate short read alignment with Burrows – Wheeler transform , 2009 .

[2]  Ning Ma,et al.  BLAST+: architecture and applications , 2009, BMC Bioinformatics.

[3]  Aurélien Ginolhac,et al.  Characterization of ancient and modern genomes by SNP detection and phylogenomic and metagenomic analysis using PALEOMIX , 2014, Nature Protocols.

[4]  Mitogenomics of the Old World monkey tribe Papionini , 2014, BMC Evolutionary Biology.

[5]  O. Gascuel,et al.  SeaView version 4: A multiplatform graphical user interface for sequence alignment and phylogenetic tree building. , 2010, Molecular biology and evolution.

[6]  Robert K. Jansen,et al.  Automatic annotation of organellar genomes with DOGMA , 2004, Bioinform..

[7]  M. Batzer,et al.  Nuclear versus mitochondrial DNA: evidence for hybridization in colobine monkeys , 2011, BMC Evolutionary Biology.

[8]  Mitogenomic phylogeny of the common long-tailed macaque (Macaca fascicularis fascicularis) , 2015, BMC Genomics.

[9]  Marcel Martin Cutadapt removes adapter sequences from high-throughput sequencing reads , 2011 .

[10]  Xun Xu,et al.  SOAPdenovo-Trans: de novo transcriptome assembly with short RNA-Seq reads , 2013, Bioinform..

[11]  K. Katoh,et al.  MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability , 2013, Molecular biology and evolution.

[12]  M. Thomas P. Gilbert,et al.  Screening mammal biodiversity using DNA from leeches , 2012, Current Biology.

[13]  John-James Wilson,et al.  Field calibration of blowfly-derived DNA against traditional methods for assessing mammal diversity in tropical forests. , 2016, Genome.

[14]  Alexandros Stamatakis,et al.  RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies , 2014, Bioinform..

[15]  L. Bachmann,et al.  Reconstructing mitochondrial genomes directly from genomic next-generation sequencing reads—a baiting and iterative mapping approach , 2013, Nucleic acids research.

[16]  V. Radchuk,et al.  Two species of Southeast Asian cats in the genus Catopuma with diverging histories: an island endemic forest specialist and a widespread habitat generalist , 2016, Royal Society Open Science.

[17]  Johanna L A Paijmans,et al.  Analysis of Whole Mitogenomes from Ancient Samples. , 2015, Methods in molecular biology.

[18]  Douglas W. Yu,et al.  iDNA from terrestrial haematophagous leeches as a wildlife surveying and monitoring tool – prospects, pitfalls and avenues to be developed , 2015, Frontiers in Zoology.

[19]  S. Eddy,et al.  tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence. , 1997, Nucleic acids research.

[20]  Paul D. Shaw,et al.  Using Tablet for visual exploration of second-generation sequencing data , 2013, Briefings Bioinform..

[21]  Stinus Lindgreen,et al.  AdapterRemoval: easy cleaning of next-generation sequencing reads , 2012, BMC Research Notes.

[22]  M. DePristo,et al.  The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. , 2010, Genome research.

[23]  Douglas W. Yu,et al.  Environmental DNA for wildlife biology and biodiversity monitoring. , 2014, Trends in ecology & evolution.