**3.3. Genetic distances and altitude**

sequencing ready reaction kit (Applied Biosystems, Darmstadt, Germany) in an automatic sequencer (ABI-PRISM 3730 genetic analyzer, Applied Biosystems, Foster City, California, United states of America). PCR for the sequencing was performed in an automatic sequencer with a total reaction volume of approximately 5 μL containing 3 μL genomic DNA (10 ng/μL),

conditions were as follows: initial denaturation for 2 min at 95°C, 25 cycles of denaturation at 95°C for 10 s, and annealing at 51°C for 10 s. The final extension step was followed by a 190 s extension at 60°C. The PCR sequencing products were subsequently stored at 12°C until use.

The sequences were arranged for multiple comparisons using Clustal Omega [32] and were aligned using ClustalW and BLAST [33]. These results were compared with other sequences obtained from GenBank. The reference sequences for tree construction were taken from the maternal lineages of each tree: haplogroup A (AF039578), haplogroup B (AF039577, AY582801, and AY091487), haplogroup E (AY091490, AJ238300). The diversity parameters, including the haplotype diversity, nucleotide diversity and average number of nucleotide differences, were estimated using DnaSP (Sequence Polymorphism Software) 5.10.01 [34]. *GST*, *FST*, *Nm*, AMOVA test, and neutrality tests were estimated using Arlequin version 3.5.1.2 [35]. To identify differences between the geographic regions using the AMOVA program, four groups were established. The

clustering tree, and genetic distance were assessed using MEGA version 6.0 [36]. We sketched the network and mismatched distribution graphs using the median-joining method implemented in

Based on the reference sequences from GenBank accession numbers (AY091487, AY091490, AJ238300, AF039578, AF039577, AY582801), all of the sequences were aligned with 1274 comparative sites, and 350 haplotypes were obtained from the 642 sequenced individuals. The length of the sequences obtained from the 636 individuals varied considerably, between 1031 and 1259 bp, although the majority were between 1180 and 1183 bp [29]. A total of 196 variable sites were obtained from the sequences, including 63 singleton variable sites and 133 parsimony-informative variable sites. There were 158 transitions and 38 transversions within the 196 variable sites, among which 15 sites had both transitions and transversions. Transition mutations were caused by observed substitutions. The variability of the number of 75 bp tandem repeat motifs [38] caused the observed variation in the length of the mtDNA D-loop sequences of the Tibetan sheep, with the exception of the insertion or deletion of several nucleotide sites. Whole haplotypes' nucleotide composition was 32.96% A, 29.71% T, 22.89% C, 14.44% G, 62.67% A+T, and 37.33% G+C, and the A+T were more common than the G+C haplotype substantially, showing an AT bias [29]. The largest haplogroup A consisted of 490 individuals and 259 haplotypes; the next largest haplogroup B and haplogroup C consisted of 145 individuals

the NETWORK version 4.6.1.2 software to assess the haplotype relationships [37].

**3.1. Polymorphic site and sequencing analysis of the complete control region**

O. The sequencing

, ME phylogenetic haplotype and

1 μL (3 pM) of each sequencing primer, 0.5 μL BigDye, and 0.5 μL ddH2

phylogenetic and molecular evolutionary relationships, *Dxy*, *Da*

**2.3. Data analysis**

138 Mitochondrial DNA - New Insights

**3. Results**

We test whether genetic distances between populations can be explained by absolute differences between altitudes for the 15 Tibetan sheep populations. Graphically, for the focal population of LZ, **Figure 1** plots the genetic distance between population LZ and each of the remaining populations as a function of the absolute difference in altitudes. Genetic distance tends to decrease with absolute difference in altitudes, as estimated by the Pearson correlation coefficient (r = −0.4136, two tailed P = 0.063, square root of 0.1711 indicated in **Figure 1**). This tendency is observed in 10 among the 15 sheep populations, but is never statistically significant at P < 0.05 (see **Table 1**). It is strongest (most negative) for high altitude populations and weakest (most positive) for populations living at low altitudes. This association between altitude and Pearson correlation coefficients obtained between genetic distances and absolute differences in altitudes (**Table 1**) has itself r = −0.65, one tailed P = 0.0044.

#### **3.4. Genetic differentiation**

To examine the genetic differentiation between the 15 Tibetan sheep populations, we calculated *FST* and *GST*. We also calculated *Nm*, *Dxy*, and *Da* among the 15 studied Tibetan sheep

Tibetan sheep populations. No *FST* values were larger than 0.25 [39], indicating that there was no significant genetic differentiation among the whole Tibetan sheep populations. The decreasing sequence of *FST* values among Tibetan sheep were 14 MX, 13 GD and JZ, 12 QK,

Phylogenetic Evolution and Phylogeography of Tibetan Sheep Based on mtDNA D-Loop Sequences

http://dx.doi.org/10.5772/intechopen.76583

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The distribution of the 15 Tibetan sheep populations varied according to their *FST* values (*P* < 0.05, or *P* < 0.01). The *GST* values ranged from 0.01 to 0.05 in Liu et al. [29]. The *GST* value between the LKZ and LZ was the smallest, and the *GST* value was the largest (JZ and AW, MX and AW, respectively). The mean *GST* was 0.02, which indicates that most of the genetic diversity occurred within populations and that 1.76% of the total population differentiation came from inter-population comparisons, whereas the remaining 98.24% came from differences among individuals within each population. Thus, the gene divergence between the populations was very low. Variation observed among and within the 15 Tibetan sheep populations

Liu et al. present the 15 Tibetan sheep populations' *Nm* of the sequence values and haplotype values [29]. The *Nm* of sequences ranged from −731.04 to 495.66, demonstrating that gene exchange was either extremely frequent or extremely rare. The sequence value between GN and QK was the smallest, and MX and QL was the largest. The mean *Nm* of the sequences was −9.40, implying a relationship with distance relatively. The *Nm* of the haplotype values ranged from 5.04 to 177.66. Notably, the value between QL and GJ was 35.24 times greater than the *Nm* between JZ and AW. The *Nm* of the haplotype values between JZ and AW was the smallest, and the *Nm* of the haplotype values between GJ and QL was the greatest. The mean haplotype *Nm* was 22.59, failed to indicate that gene flow occurred between the populations in the past time.

[29]. The *Dxy* value between JZ and AW was the largest, and the *Dxy* value between LKZ and

number of net nucleotide substitutions per site between populations of the 15 Tibetan sheep

We test whether genetic differentiation between populations can be explained by altitude. Graphically, for the focal population of GD, **Figure 2** plots genetic differentiation between GZ and each of the remaining populations as a function of the absolute value of the difference between their altitudes. Genetic differentiation tends to increase with altitude (r = 0.4315, one-tailed P = 0.062) (square root of 0.1862 indicated in **Figure 2**). Analyses similar to those in **Figure 2** showed that genetic differentiation increases with absolute differences in altitude, specifically for nine populations ((significance at P < 0.05 indicated by \*) QL\*, TJ\*, QH\*, MX\*, GJ, QK\*, GN\*, DM, and LKZ) and decreases for the remaining five populations

This association between genetic differentiation and absolute difference between altitudes is most positive for populations at high altitudes and most negative for those at low altitudes. This association between altitude and Pearson correlation coefficients obtained between genetic differentiations and absolute differences in altitudes (**Table 1**) has itself r = −0.75,

values were from 0.01 to 0.03. The mean *Da*

values among the 15 Tibetan sheep populations

was 0.02. Similarly, the

10 GB and GN and TJ, 9 GJ and HB and QH, 7 QL, 4 LKZ and LZ, 3 DM, and 1 AW.

indicate lack of differentiation among geographic populations.

Liu et al. provided the data of the *Dxy* and *Da*

**3.5. Genetic differentiation and altitude**

populations was highest JZ and LZ and lowest TJ and AW.

(GB,HB, JZ, LZ, and AW), mainly GB\* and HB\* (**Table 1**).

LZ was the smallest. The *Da*

one-tailed P = 0.0011.

**Figure 1.** Genetic distance and absolute difference between altitudes for population LZ.

populations [29]. The estimated pairwise *FST* values are from Liu et al. [29]. The *FST* values ranged from −0.05 to 0.24. DM and LKZ had the closest pairwise *FST* value among the 15 Tibetan sheep populations and AW were more distantly related to JZ, compared with other


**Table 1.** Altitude and Pearson correlation coefficients between absolute differences in altitude and each genetic distance and genetic differentiation between 15 Tibetan sheep populations.

Tibetan sheep populations. No *FST* values were larger than 0.25 [39], indicating that there was no significant genetic differentiation among the whole Tibetan sheep populations. The decreasing sequence of *FST* values among Tibetan sheep were 14 MX, 13 GD and JZ, 12 QK, 10 GB and GN and TJ, 9 GJ and HB and QH, 7 QL, 4 LKZ and LZ, 3 DM, and 1 AW.

The distribution of the 15 Tibetan sheep populations varied according to their *FST* values (*P* < 0.05, or *P* < 0.01). The *GST* values ranged from 0.01 to 0.05 in Liu et al. [29]. The *GST* value between the LKZ and LZ was the smallest, and the *GST* value was the largest (JZ and AW, MX and AW, respectively). The mean *GST* was 0.02, which indicates that most of the genetic diversity occurred within populations and that 1.76% of the total population differentiation came from inter-population comparisons, whereas the remaining 98.24% came from differences among individuals within each population. Thus, the gene divergence between the populations was very low. Variation observed among and within the 15 Tibetan sheep populations indicate lack of differentiation among geographic populations.

Liu et al. present the 15 Tibetan sheep populations' *Nm* of the sequence values and haplotype values [29]. The *Nm* of sequences ranged from −731.04 to 495.66, demonstrating that gene exchange was either extremely frequent or extremely rare. The sequence value between GN and QK was the smallest, and MX and QL was the largest. The mean *Nm* of the sequences was −9.40, implying a relationship with distance relatively. The *Nm* of the haplotype values ranged from 5.04 to 177.66. Notably, the value between QL and GJ was 35.24 times greater than the *Nm* between JZ and AW. The *Nm* of the haplotype values between JZ and AW was the smallest, and the *Nm* of the haplotype values between GJ and QL was the greatest. The mean haplotype *Nm* was 22.59, failed to indicate that gene flow occurred between the populations in the past time.

Liu et al. provided the data of the *Dxy* and *Da* values among the 15 Tibetan sheep populations [29]. The *Dxy* value between JZ and AW was the largest, and the *Dxy* value between LKZ and LZ was the smallest. The *Da* values were from 0.01 to 0.03. The mean *Da* was 0.02. Similarly, the number of net nucleotide substitutions per site between populations of the 15 Tibetan sheep populations was highest JZ and LZ and lowest TJ and AW.
