AIMS_delta

Genotypes for AIMs, delta values, outlier block detection, and population-specificit

Sample_Information

Sample information and genome-wide ancestry estimate

ImmigrantPopulation

ImmigrantPopulatio

Hypoxia Adaptations in the Grey Wolf (<i>Canis lupus chanco</i>) from Qinghai-Tibet Plateau

<div><p>The Tibetan grey wolf (<i>Canis lupus chanco</i>) occupies habitats on the Qinghai-Tibet Plateau, a high altitude (>3000 m) environment where low oxygen tension exerts unique selection pressure on individuals to adapt to hypoxic conditions. To identify genes involved in hypoxia adaptation, we generated complete genome sequences of nine Chinese wolves from high and low altitude populations at an average coverage of 25× coverage. We found that, beginning about 55,000 years ago, the highland Tibetan grey wolf suffered a more substantial population decline than lowland wolves. Positively selected hypoxia-related genes in highland wolves are enriched in the HIF signaling pathway (<i>P</i> = 1.57E-6), ATP binding (<i>P</i> = 5.62E-5), and response to an oxygen-containing compound (<i>P</i>≤5.30E-4). Of these positively selected hypoxia-related genes, three genes (<i>EPAS1</i>, <i>ANGPT1</i>, and <i>RYR2</i>) had at least one specific fixed non-synonymous SNP in highland wolves based on the nine genome data. Our re-sequencing studies on a large panel of individuals showed a frequency difference greater than 58% between highland and lowland wolves for these specific fixed non-synonymous SNPs and a high degree of LD surrounding the three genes, which imply strong selection. Past studies have shown that <i>EPAS1</i> and <i>ANGPT1</i> are important in the response to hypoxic stress, and <i>RYR2</i> is involved in heart function. These three genes also exhibited significant signals of natural selection in high altitude human populations, which suggest similar evolutionary constraints on natural selection in wolves and humans of the Qinghai-Tibet Plateau.</p></div

Top: Partial alignments of <i>ANGPT1</i> (left) and <i>RYR2</i> (right) amino acid sequences.

<p>The sequences with more than 15% gaps or less than 60% identity with lowland ortholog sequences were filtered out. Dots (.) represent residues identical to lowland wolves' sequence. The mutation S214T in <i>RYR2</i> and M201V in <i>ANGPT1</i> in highland wolves were denoted with arrows. Where highland showed the wolves from Tibet and Qinghai and lowland showed the wolves from Xinjiang and Inner Mongolia. Bottom: Genotypes plots of three hypoxic genes (top) and LD patterns (triangle plot, bottom). These genotypes derive from Sanger sequencing of 35 wolves and were encoded as homozygous reference (ref), heterozygote (het), and homozygous alternative (alt). Red regions represent a high degree of LD. I: intron; N: non-synonymous; S: synonymous.</p

Population structure from genome data (excluding highly linked SNPs with r²>0.2).

<p>A: Structure assignments based on complete genome data from nine Chinese wolves. B: Principle component analysis of complete genome data from nine Chinese wolves. Xinjiang, XJ: XJ24, XJ30; Inner Mongolia, IM: IM06, IM07; Tibet, TI: TI09, TI32; Qinghai, QH: QH11, QH16. See table S1 and the text for abbreviations and localities.</p

Selection candidates involved in the HIF pathway that were found to show evidence of positive selection in highland wolves.

<p>Solid lines indicate a direct relationship between enzymes and metabolites. Dashed lines indicate that more than one step is involved in the process. The genes outlined in black boxes were under selection and those indicated in gray boxes were provided for reference. See <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004466#s3" target="_blank">discussion</a> of interactions in the text.</p

Genomic regions with strong selective sweep signals in Tibet wolves.

<p>The three hypoxia-related genes (<i>EPAS1</i>, <i>RYR2</i>, and <i>ANGPT1</i>) which each include at least one fixed non-synonymous SNP in highland wolves are highlighted. (A) Distribution of <i>θ</i>_π ratios (<i>θ</i>^high_π/<i>θ</i>^low_π) and F_ST values calculated in 100-kb sliding windows in 20-kb steps. Data points in red (corresponding to the 5% empirical <i>θ</i>_π ratio distribution, where <i>θ</i>_π ratio is 5.311, and the 5% empirical F_ST distribution, where F_ST is 0.259) are regions under selection in highland wolves. (B) Genome-wide distribution of F_ST and Δπ along autosomes 1–38 (chromosomes are separated by color). Each dot represents 100 Kb genome regions. A dashed horizontal line indicates the top 5% level (F_ST>0.259; Pi>5.311) used for extracting outliers, where another dashed horizontal line F_ST>0.489 shows the top 1% level. (C) The genotypes observed in 9 full-genome data around <i>EPAS1</i>, <i>RYR2</i>, and <i>ANGPT1</i>. Every plot includes a gene region (top) and genotypes around the region (below). The y-axis denotes individuals: 1—RKWL <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004466#pgen.1004466-Freedman1" target="_blank">[21]</a>, 2-IM06, 3-IM07, 4-XJ24, 5-XJ30, 6-QH11, 7-QH16, 8-TI09, and 9-TI32. See table S1 and the text for abbreviations and localities. The x-axis denotes the locations on genome.</p

The number of nonsynonymous SNPs that might affect protein function based on SIFT [24], MAPP [25], and PolyPhen2 [26].

<p>These SNPs genotypes differ at the 5% level between highland and lowland wolves.</p

Geographical distribution of the sampled 35 Chinese wolves in this study.

<p>The average altitudes are also shown on the map.</p