bioRxivGenomicsPreprint
High coverage genome sequencing and identification of genomic variants in Bengal tiger (Panthera tigris tigris)
Patlolla Anuradha ReddyiD, Harish KothandaramaniD, P. V. Parvati Sai AruniD, Anil Challagandla, Dushyant Singh BagheliD
- Citations
- 2
Abstract
Bengal tiger (Panthera tigris tigris), one of six extant tiger subspecies, occurs solely in the Indian subcontinent. Although endangered and threatened by various extinction risks, this is the most populous tiger subspecies with the highest genetic diversity and strongest chance of survival in the wild. Availability of high quality genomic information on this animal will help us understand its ability to adapt to different habitats and environmental changes, in addition to comparative studies with other subspecies. Here we report high coverage sequencing of the Bengal tiger genome and its mapping to the Amur tiger genome in order to discover single nucleotide to large structural variants. A total of 345 Gb, roughly equivalent to 144X coverage of the genome, was generated from 1,149,381,669 raw read pairs. Further, 990,060,729 clean read pairs, again equivalent to 115X coverage, were retained from the raw read data and considered for comparative analysis with the Amur tiger genome. This alignment showed that 97.35% of the bases mapped at 5X depth, 97.26% at 10X and 90.44% at 50X depth. We identified a total of 3,601,882 single nucleotide variants, 948 structural variants, 56,649 copy number variants and 1,760,347 simple sequence repeats. We report the first high coverage genome sequence of Bengal tiger with an overview of its genomic variants when compared to the Amur tiger genome. Of the several variants identified, we further have to assess and validate variants potentially associated with the ability of the animal to adapt to environmental changes, disease susceptibility and other important biological phenomena.
- assay: whole-genome sequencing
- research focus: variant calling
- research focus: genome assembly
- research focus: database / resource
- approach: statistical model
- approach: experimental assay
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