Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2012 Jan 1.
Published in final edited form as: Forensic Sci Int Genet. 2010 Feb 25;5(1):33–42. doi: 10.1016/j.fsigen.2010.01.013

Feline Non-repetitive Mitochondrial DNA Control Region Database for Forensic Evidence

R A Grahn 1, J D Kurushima 1, N C Billings 1, JC Grahn 1, J L Halverson 2, E Hammer 1, CK Ho 1, T J Kun 3, JK Levy 4, M J Lipinski 1, JM Mwenda 5, H Ozpinar 6, RK Schuster 7, SJ Shoorijeh 8, C R Tarditi 1,2, NE Waly 9, E J Wictum 2, L A Lyons 1
PMCID: PMC2921450  NIHMSID: NIHMS184595  PMID: 20457082

Abstract

The domestic cat is the one of the most popular pets throughout the world. A by-product of owning, interacting with, or being in a household with a cat is the transfer of shed fur to clothing or personal objects. As trace evidence, transferred cat fur is a relatively untapped resource for forensic scientists. Both phenotypic and genotypic characteristics can be obtained from cat fur, but databases for neither aspect exist. Because cats incessantly groom, cat fur may have nucleated cells, not only in the hair bulb, but also as epithelial cells on the hair shaft deposited during the grooming process, thereby generally providing material for DNA profiling. To effectively exploit cat hair as a resource, representative databases must be established. This study evaluates 402 bp of the mtDNA control region (CR) from 1,394 cats, including cats from 25 distinct worldwide populations and 26 breeds. Eighty-three percent of the cats are represented by 12 major mitotypes. An additional 8.0% are clearly derived from the major mitotypes. Unique sequences were found in 7.5% of the cats. The overall genetic diversity for this data set was 0.8813 ± 0.0046 with a random match probability of 11.8%. This region of the cat mtDNA has discriminatory power suitable for forensic application worldwide.

Keywords: Forensic science, domestic cat, mtDNA, mitochondria, d-loop, control region

1. Introduction

The increasing popularity of the domestic cat (Felis catus) as a household pet has unknowingly fostered the distribution of potential crime scene evidence across millions of households. Cat fur obtained from a crime scene has the potential to link perpetrators, accomplices, witnesses, and victims. Cats are fastidious groomers, and shed fur can have sufficient genetic material for trace forensic studies [1–5], allowing potential analysis of both standard short tandem repeat (STR) profiles and mtDNA regions. The first DNA analysis of cat fur in a criminal investigation occurred in 1996 in a Canadian murder case, Beamish vs. Her Majesty’s Court, P.E.I. [3]. Investigators linked the perpetrator to the crime scene by STR identification of a single cat hair found in the pocket of a discarded jacket. Despite this early success, cat fur has had limited use as evidence in forensic applications. This may result from the limited value of shed epithelial cells with respect to the successful typing of nuclear markers. While not as informative in discriminating individuals as microsatellite-based panels, the higher copy number of mtDNA in trace biological evidence and greater stability renders mtDNA a desirable tool for hair forensic analysis [6].

Studies of DNA variation in diverse and worldwide populations support the selection of standardized markers and typing systems for the forensic community. Several data sets and microsatellite-based DNA marker panels have been developed for the cat [4, 7–9], but similar data sets for mtDNA are still lacking. The complete DNA sequence of cat mtDNA is published and accessible in GenBank (Accession no. U20753) [10]. Several studies have evaluated mtDNA genes to identify felid species-specific markers [11–22], however, less is known about individual domestic cat variation at the mtDNA level. Mitochondrial DNA has been investigated from an evolutionary point of view, including the analysis of many mtDNA gene polymorphisms [12–13, 23–24], however, regions of analysis are not consistent between studies and the regions previously examined are sometimes difficult to apply to forensic science.

In respect to individual identification in forensic applications, 167 cats (purebred = 86, random bred = 81) across 945 – 1105 bases of the mtDNA control region (CR) (Reference sequence U20753: 16287 – 475) have been analyzed [2]. The described size differences in this region resulted from a tandem repeat, which was subject to a high degree of heteroplasmy. However, the sequence data from these cats are not currently available in a public database. A Japanese research team evaluated the genetic diversity of both the Cytochrome b gene and a 350 base pair (bp) fragment of the mtDNA CR (ref seq positions 16315 – 16664) in domestic cats from Japan [25]. A random sampling of 50 individuals from the Tsushima Islands was evaluated and 10 mitotypes were identified. Polymorphic sites were 2.4 times greater and sequence differences were 1.8 times greater for the CR than Cytochrome b [25]. This sampling is currently the only publicly available data set for the CR of the domestic cat.

Recently, an analysis of a 402 bp region of the domestic cat mtDNA CR in 174 random bred cats from the United States further demonstrated that this mtDNA segment could be useful for forensic applications [26], however mtDNA mitotypes and mitotype distributions from extensive geographical locations, within the United States and in foreign countries, were not determined. The mtDNA CR sequence from the USA study overlaps with the work of previous work [2], although the amplified sequence omits the tandem repeat section in order to reduce concerns of heteroplasmy. In the current study, a reference database for the feline mtDNA CR is further developed. This database of feline mtDNA CR incorporates 1,394 cats, including the sequences generated by both previous studies and an additional 1219 cats obtained from discrete populations from sites throughout the world. This work also includes previous breed data and expands both the number of individuals per breed as well as the number of breeds evaluated (N = 26). The goal of this study is to present a mtDNA CR database and document the nucleotide variation that define the universal mitotypes of domestic cats from the United States and abroad.

2. Materials and Methods

2.1. Populations and sample collection

This study extends 174 cat mtDNA CR sequences previously published [26] with an additional 1219 cats (Table 1 and Table 2), generating a database of 1394 samples, consisting of 1,027 random bred cats, 364 cats representing fancy breeds and three control samples/sequences. A subset of the cats (Southern California) was discussed previously [2]. Random bred samples were collected from 17 distinct geographic locations for an STR study [27], 15 locations are represented in this sample set (for this study the Kenyan samples were divided into a mainland population-Kenya and island population-Lamu/Pate, and Egyptian samples were divided into 3 additional regions – Assuit, Luxor and Abu Simbel. Additionally, samples from four US populations (Orange County, CA, Davis, CA, Alachua County, FL and Clay County, MO), one Eastern Mediterranean location (Lebanon), one site along the Indian Ocean trade route (India) and three sites in the Middle East (Dubai, Iran and Iraq) were collected. Breed samples were collected from cat shows at locations across the United States or were submitted by owners. Two PCR positive controls included a commercial cell line, CCL-94 (ATCC, Manassas, VA) and a laboratory control cat, Fcat-4406.

Table 1.

Mitotype Distribution Among Random Bred Cats

Mitotypes
Group Location # A A1 A1a A2 A3 A4 A5 A6 A6a A6b A7 A8 A9 B B1 B2 B3 B4 B5 B6 C C1 C2 C3 C4 C5 D D1 D2 D3 D4 D5 E E1 F G G1 H I J K L OL1 OL2 OL3 U
United States California (n) 133 22 1 5 1 35 1 24 1 8 1 6 2 6 2 7 1 10
California (s) 99 19 3 25 1 26 1 8 2 4 3 1 6
Florida 50 9 19 11 1 2 1 2 1 1 3
Hawaii 59 19 2 17 7 1 2 3 8
Missouri 24 4 7 4 2 2 2 1 1 1
New York 100 33 26 1 1 13 5 4 5 3 1 1 4 1 2
Texas 28 5 9 1 5 1 4 3
Europe Germany 21 4 1 2 1 1 12
Italy 23 1 1 2 2 2 1 1 13
Tunisia 14 3 3 4 1 3
Eastern Mediterranean Egypt 130 30 1 2 1 2 2 4 39 2 7 3 8 13 2 1 6 2 5
Israel 45 16 2 5 5 6 1 2 1 6 1
Lebanon 2 2
Turkey 56 13 2 1 3 1 15 1 1 6 8 1 1 3
Iran/Iraq Iran 65 8 1 2 28 2 1 7 6 1 6 3
Iraq 7 1 5 1
Indian Ocean Trade Route Dubai 10 6 4
India 29 4 15 2 2 4 2
Kenya 35 4 6 3 8 3 2 9
Lamu/Pate 17 3 5 4 1 4
Sri Lanka 24 13 1 3 4 2 1
East Asia China 12 2 1 8 1
Korea 20 3 2 12 3
Taiwan 12 6 1 1 1 2 1
Vietnam 12 7 1 2 1 1
Subtotal 1027 229 4 2 2 2 0 0 3 10 3 3 0 3 179 2 0 0 4 2 2 126 7 0 1 1 2 139 5 1 4 4 8 53 6 46 24 0 24 8 14 18 13 0 3 2 68
Tarditi et al mitotype 2 1 11 9 3 4 8 7 6 12 5 14 10 13 16–33
Open in a new tab

Table 2.

Mitotype Distribution Among Fancy Breed Cats

Mitotypes
Breed # A A1 A1a A2 A3 A4 A5 A6 A6a A6b A7 A8 A9 B B1 B2 B3 B4 B5 B6 C C1 C2 C3 C4 C5 D D1 D2 D3 D4 D5 E E1 F G G1 H I J K L OL1 OL2 OL3 U
Abyssinian 21 6 1 12 1 1
American Shorthair 9 4 1 2 2
Birman 23 14 2 1 1 1 1 3
British Shorthair 23 2 4 1 13 2 1
Burmese 18 1 7 2 1 5 1 1
Chartreux 12 3 5 3 1
Cornish Rex 11 3 5 1 1 1
Egyptian Mau 11 6 5
Exotic Shorthair 11 1 3 1 2 1 3
Havana Brown 4 1 1 1 1
Japanese Bobtail 14 2 1 8 3
Korat 19 12 1 3 2 1
Maine Coon 14 3 1 1 1 1 1 4 1 1
Manx 12 2 1 1 4 1 3
Norwegian Forest Cat 10 1 3 1 5
Persian 17 4 4 4 1 1 3
Ragdoll 13 1 3 2 2 1 2 1 1
Russian Blue 11 4 1 1 3 1 1
Scottish Fold 13 6 1 1 5
Siamese 25 11 9 1 2 1 1
Siberian 12 7 4 1
Singapura 9 2 6 1
Sokoke 7 3 1 1 2
Sphynx 14 4 1 4 2 3
Turkish Angora 15 3 3 4 1 2 1 1
Turkish Van 16 1 2 10 2 1
CCL-94 1 1
U20753 (Lopez et al) 1 1
Fcat-4406 1 1
   Subtotal 367 93 0 0 0 0 3 2 2 0 0 0 2 0 68 3 3 2 0 1 0 59 0 4 1 3 0 30 0 1 0 0 2 9 0 8 9 2 1 11 1 2 2 7 0 0 36
 Fancy + Random Bred 1394 322 4 2 2 2 3 2 5 10 3 3 2 3 247 5 3 2 4 3 2 185 7 4 2 4 2 169 5 2 4 4 10 62 6 54 33 2 25 19 15 20 15 7 3 2 104
Tarditi et al mitotype 2 1 11 9 3 4 8 7 6 12 5 14 10 13 16–33
Open in a new tab

Feline samples for DNA isolation were collected by various techniques including, EDTA anti-coagulated whole blood via venipuncture, gonadal tissues collected during routine castrations and hysterectomies, and buccal samples obtained with cytological brushes or cotton swabs. DNA was isolated from tissues, peripheral white blood cells, and buccal swabs using the Qiagen DNeasy Tissue extraction kit following manufacturer’s specifications (Qiagen Inc, Valencia CA). The relatedness of the random bred cats is unknown. However, during collection, only one individual from an obvious litter was sampled. Breed assignments of six Siamese, three Persian, one Maine Coon, and one Manx were reported by owners and not supported by pedigrees. Breed cats with available pedigrees (90.5%) had no grandparents in common.

2.2. mtDNA CR amplification and analyses

The partial CR (positions 16814 – 206) from the published full mtDNA genome of the cat (GenBank Accession No: U20753) was analyzed by direct sequencing. Mitochondrial DNA sequences were generated in three laboratories: QuestGen Forensics, the UC Davis Veterinary Genetics Laboratory Forensic Unit, and the UC Davis Lyons’ Feline Genetics Research Laboratory.

The domestic cat mtDNA CR was amplified using PCR primers JHmtF3 -gatagtgcttaatcgtgc and JHmtR3 - gtcctgtggaacaatagg, which correspond with the published feline mtDNA CR sequence (Genbank no. U20753 and NC_001700) to bp 16760 – 16776 and bp 240 −223, respectively. The 3’ nucleotide of the reverse primer is different from the published sequence, which is an adenine. These primers amplify a 492 bp region, including the primers. The mtDNA CR was amplified from extracted total DNA. Each 30 µL reaction contained 2 – 30 ng (5 µL) of DNA, 2.0 mM MgCl2, 1X PCR buffer (Denville, Saint-Laurent, Canada) with 0.05% bovine serum albumin, 1.25 mM dNTPs (Denville, Saint-Laurent, Canada), 0.2 mM of each primer (Operon, Huntsville, AL) and 1 unit of Taq polymerase (Abgene, Rochester, New York). Each reaction was amplified under the following cycling conditions in a MJ Research DNA engine (MJ Research, Waltham MA): 94°C for 3 min initial denaturation, followed by 35 cycles of 45 s at 94°C, 30 s at 58°C and 45 s at 72°C. The PCR cycling was followed by a final extension for 10 min at 72°C. PCR products were stored at 4°C.

PCR amplification products, 5 µL, were size separated for 1 hr at 95V on 2% TAE agarose gels. Products were photo-documented on an Alpha imager (Alpha Innotek Corp, San Leandro, CA). Products were prepared for sequencing using ExoSap-IT exonuclease clean-up (USB Cleveland, OH) according to the manufacturer’s specifications.

Purified PCR product was used for sequencing reaction according to the manufacturer’s specifications. Each reaction contained 50 ng of amplified DNA, 1X sequencing buffer, 1 µL of BigDye v3.1 (Applied Biosystems, Foster City, CA) and 0.4 µM of either the forward or reverse amplification primer in a 15 µL reaction. Each reaction was amplified on a GeneAmp PCR system 9700 DNA according to the manufacturers specifications with cycles increased from 30 to 40. Unincorporated, labeled nucleotide, were removed from the reaction using Sephadex G-50 (Sigma-Aldrich, St. Louis, MO) in a 96-well plate. Sequencing product, approximately 12 µL, was combined with 10 µl of Hi-DI formamide (Applied Biosystems, Foster City, CA) and denatured for 3 min at 95°C. Products were separated on an ABI 3730 DNA Analyzer. Sequences were aligned using Sequencher analysis software v4.1 (Gene Codes Corporation, Ann Arbor, MI).

Sequences were aligned using Sequencher 4.0™ software (Gene Codes Corporation, Ann Arbor, MI). Sequencing data were assembled into contigs and consensus sequences were generated. Sequences were aligned using the Megalign component of Lasergene (DNAStar, Madison Wisconsin) and variable nucleotide positions were identified.

Once nucleotide variants were identified in all the sequences, a minimal-variation, majority-rule consensus sequence was constructed from the most common mitotypes and termed the “Sylvester” reference sequence (SRS) (Supplemental Figure S1) [26]. All mtDNA mitotypes were then defined by their variant sites relative to this sequence so that the minimal number of variants would need to be recorded to describe all identified mitotypes.

The random match probability (RMP) was calculated according to Stoneking et al [28]. The exclusion probability of the feline mtDNA CR mitotype was calculated as 1 – RMP. The individual populations were combined into six major population groups based on geography. Population data was calculated for the breeds with greatest representation. For the six population groups and seven major breeds, the mean number of uncorrected pair-wise differences and nucleotide diversities within and between populations was calculated in ARLEQUIN version 3.1 [29] following standard procedures [30–31]. The analysis of molecular variance (AMOVA) program in ARLEQUIN was used to estimate the degree of variation within each population and the degree of differentiation between all six populations. The program NETWORK 4.5 (Fluxus Technology Ltd., Clare, Suffolk, UK) was used to create a phylogenetic network of the universal mitotypes and associated mitogroup subtypes, which incorporates all possible shortest, least complex maximum parsimony phylogenetic trees from the data set [32].

3. Results

3.1 Mitotype generation

A 492 bp product was trimmed to 402 bp (ref seq positions 16814 – 206) for sequence analysis to maintain full-length, double-stranded, high-quality sequence data across all samples. The assembled data set includes 1,394 samples representing 25 populations (Table 1), 26 breeds (Table 2), one PCR positive control sample and cell line CCL-94. The mitotype distributions are found in Table 1 and Table 2. Heteroplasmies (samples that appeared to have one or more polymorphic nucleotide sites in the sequence) were observed in 10 of 1394 samples (0.76%) and are denoted using standard IUPAC nomenclature in the tables. Sequence variants of the mitotypes were compared to the SRS and are presented in Table 3. The mitotypes established by Tarditi and colleagues [26] have been correlated and are consistent with this data. Twelve distinct, major mitotypes, with representative samples > 0.7% of the total 1394 samples are designated A – L and are considered “universal types” (UT). These sequences have been submitted to GenBank (Accession Nos.: EU864495 - EU864506). An additional 30 subtypes were also identified; none represented greater than 0.75% of the total sample set. These rare mitotypes were placed into a mitogroup based upon shared derived characters according to phylogenetic placement protocols [33]. A median joining network tree depicts the relationship of each mitotype (Figure 1). Three additional mitotypes were identified that could neither be placed into a mitogroup nor occurred at significant frequency to warrant major mitotype designation. These sample groups are considered outliers (OL) and are identified by columns OL1 – 3 in Table 1 and Table 2 and Figure 2. Unique mitotypes (N = 104, 7.5%), which are found in only 1 individual in this data set, are identified in column U. Considering all breeds and populations, 149 mitotypes were identified (Supplemental Figure S2).

Table 3.

Table of Universal Mitotype Defining Nucleotides

Mitotype defining sites are provided based upon the first published mt sequence [10] and the Sylvester Reference Sequence [26]. For the SRS, both the sequence position and occupying nucleotide are indicated. OL indicates outlier groups 1,2 and 3.

Lopez SRS Universal Mitotype OL
U20753 Pos. NTP A A1 A1a A2 A3 A4 A5 A6 A6a A6b A7 A8 A9 B B1 B2 B3 B4 B5 B6 C C1 C2 C3 C4 C5 D D1 D2 D3 D4 D5 E E1 F G G1 H I J K L 1 2 3
16815 2 A . G - . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
16820 7 T . . . . . . . C C C . . . . . . . . . . . C . . . . . . . . . C C . . . . C . . . . C C
16824 11 A . . . . . . . . . . . . . G G G G G G G G G G G G G G G G G G G . . . . . . . G . . . . .
16825 12 A . . . . . . . . G . G . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
16834 21 T . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C .
16859 46 C . . . . . . . T T T . . . . . . . . . T T T T T T . . . . . . T T . . . T T . . . T T T
16867 54 C . . . . . . . . . T . . . . . . . . . . . . . . . . . . . . . . . . . . . . . T . . T T
16899 86 T . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C .
16957 144 C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . T T . . . . T . . . . . .
16961 148 A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . G G G .
16962 149 A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . G G .
16973 160 T . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A . . . . . . .
16985 172 A . . . . . . . . . . . . . . . . . . . G G G G . G . . . . . . . . . . . G . . . . G G .
16986 173 T C C C C C C C C C C C C C . . . . . . C . . . . . . . C . . . . . . . . . . C . C C . . C
16988 175 C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . T T . . . . . . . . . . .
16989 176 T . . . . . . . . . . . . . . C . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
16997 184 G . . . . . . . . . . . . . . . . . A . . A . . . . . . . . A . A A . . A . . . . . . A .
7 203 A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . G . . . . . .
59 255 C . . . . . . . . . . . . . . . . . . . T T T T T T . . . . . . . . . . . T . T . . . . .
62.1 259 - . . . . . . . . . . . . T . . . . . . . . . . . . . . . . . . . T . . . . T . . . . T .
63 260 T . . . . . . . . . . . . A A A A A A A A A A A A A A A A A A A A A A A A A . A A . A .
128 325 T . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C
130 327 T C C C C C C C C C C C C C . . . . . . . . . . . . . . . . . . . . . . . . C . C C . . .
131 328 T . . . . . . . . . . . . . . . . . . . . . . C . . . . . . . . . . . . . . . . . . . . .
159 356 T . . . . . . . . . . . . . C C C C C C C C C C C C C C C C C C . . . . C C . . C . . C C C
160 357 C . . . T . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . T . .
161 358 T . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C . .
168 365 G . . . . . . . . . . . . . . . . . . . . . . . . . . . . A . . . . . . . . . . . . . A .
169 366 T . . . . . . . . . . . . . . . . . . . . . . . . . C C C C C C C C C . . C . C . . C C .
173 370 G A A A A A A A A A A A A A . . . . . . . . . . . A . . . . . . . A . . . . A . A A . A .
180 377 A . . . . . . . . . . . . . . . . . . . . . . . . T . . . . . . . . . . . . . . . . . . .
182 379 G . . . . . . . . . . . . . . . . . . T . . . . . T . . . . . . . . . . . . . . . . . . .
185 382 G . . . . T . . . . . . . . . . . . . T . . . . . T . . . . . . . . . . . . . . . . . . .
192 389 A . . . . . . T . . . . . . . . T . . . . . . . . . . . . . . . . . . . . . . . . . . . .
193 390 G . . . . . . . . . . . . . . . . T . . . . . . . . . . . . . . . . . . . . . . . . . . .
196 393 A . . . . . T T . . . . . . . . T . . . . . . . . . . . . . . . . . . . . . . . . . . . .
200 397 G . . . . . T . . . . . T . . . . . . . . . . . . . . . T . . . . . . . . . . . . . . . .
203 400 A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . G .
Open in a new tab

Figure 1. Network diagram of universal mitotypes and subtypes for domestic cat CR.

Figure 1

Open in a new tab

Circled letters indicate the universal mitotypes. Circles encompassing mitotypes are not to scale, although A is the most common. Subtypes are indicated at nodes. Stars indicate theoretical intermediary mitotypes predicted by network analysis. Numbers on branches indicate nucleotide position changes in the sequence alignment with the Sylvester reference sequence (SRS). Three unattributed groups (OL1–3) are indicated as well.

Figure 2. Frequency of feline universal mitotypes in random bred populations.

Figure 2

Open in a new tab

Frequencies of all 12 universal mitochondrial haplotypes for each random bred group are present. Outlier group 1 (OL1) is not represented as it is restricted to Fancy breed cats. Unique types (U) are presented as well.

3.2 World Wide Feline Population Genetics

The mtDNA CR mitotypes, including unique mitotypes, averaged 98.4% similarity among the cats, ranging from 93.0% to 99.8%. The most distinctive mitotype had 16 nucleotide differences. These were derived from the Texas sample set designated mitotype OL2 (Table 2). The genetic diversity measure for the entire population was 0.8813 ± 0.0046 with a random match probability of 11.9%. The frequency of each mitotype in the random bred populations is presented in Figure 2. Approximately 83.6% of the cats were represented by the 12 universal mitotypes. An additional 8.0% (N = 112) of cats are represented by 30 subtypes of the universal mitotypes A – E and G. Unique types accounted for 7.5% of mitotypes identified. The remaining 0.9% were not attributed universal mitotype status and are designated types OL1 – 3. Four major mitotypes, A – D, represented 60 – 70% of individuals in all populations. Compared to the SRS, mitotype A is defined by: 16986C, 130C and 173C, mitotype B by: 16824G, 63A and 159C, mitotype C by: 16824G, 16859T, 16985G, 59T, 63A and 159C, and mitotype D by: 16824G, 63A, 159C and 169C (Table 3). Universal types B and D differ by a single position (Table 3). DNA and cell lines from the four most common mitotypes are available for distribution from the authors. Each random bred population (19 of 25) representing > 1% (N = 13) of the total population had at least three of the common mitotypes. These populations all had mitotype A, 16 of 19 had B, 17 of 19 had C, and 15 of 19 had D. No population contained all 12 universal mitotypes and 14 of 19 had at least one unique mitotype. The fewest unique mitotypes, < 1% frequency, were found within the Indian Ocean Trade route countries. Both Iran/Iraq and the Eastern Mediterranean had roughly 4% unique mitotypes, the USA had ∼5% unique mitotypes. East Asia had ∼14% and Europe had 43% unique.

When evaluated according to taxonomic units based upon origin and breed [27], mitotype frequency distribution shows regional associations (Table 1, Table 2 and Figure 2). For example, mitotype B is the major mitotype for random bred cats in the USA, representing 28.4% of the population, but is minor in the Eastern Mediterranean, representing only 2.8% of the population, and absent in the Iraqi and Iranian sample sets. Similarly, mitotype J is absent in the USA, Europe, along the Indian Ocean trade route and East Asian samples, but found at a low frequency in the Eastern Mediterranean and the Middle East. Almost 46% of the cats representing the population from Iran/Iraq are mitotype D, which is nearly 20% greater than any other population for this mitotype. Interestingly, the proportion of the European and East Asian samples with unique mitotypes is 3 – 8-fold greater than in the USA, Eastern Mediterranean, along the Indian Ocean trade route and Iran/Iraq populations.

Nucleotide diversity (π) ranged from 4.39 ± 2.2 in the Indian Ocean trade route population to 8.56 ± 4.0 in the European population (Supplemental Table S1). The greatest number of observed pairwise differences was found in the USA population with 32. The total observed nucleotide diversity for all six random bred populations was 5.55 ± 2.7.

3.3. United States Feline Population Genetics

Mitotypes A – C accounted for approximately 60 – 78% of all cats in each USA population. All USA sample sets contained the four most common mitotypes, except Missouri where mitotype D is absent. Together, mitotypes A – D comprised 73.0% of the US population. The major mitotype for each US population was type B. Subtype A1a is exclusively found in the Hawaiian island population. Non-assigned group OL2 is restricted to the Texas population. Approximately 4.9% of the cat population in the USA had unique mitotypes, ranging from 7.5% in the largest population to 0% in the Southern California and Texas sample sets (Table 1).

3.4. Fancy Cat Breed Population Genetics

With respect to breeds, 22 of 26 breeds had mitotype A. Mitotypes A – C accounted for 59.7% of all types. Two breeds had only one of the 12 universal mitotypes, Siberians with mitotype A and Turkish Vans with mitotype D. Unique mitotypes comprised 9.7% of the breed mitotypes and were found in all but five breeds. The greatest number of universal mitotypes identified in any one breed was the six mitotypes, A - D, G, and I in Persians. The greatest number of types, nine, was found in Birmans despite 60.9% of the samples for this breed having mitotype A. For breeds, 64% (16 of 25 breeds with the Havana Brown breed excluded) had a single type in excess of 40%. For the random bred cats, only 33.3% of the sites (eight sites out of 24 with Lebanon excluded) had a single mitotype comprising at least 40% of the types. The non-assigned group OL1 is comprised solely of fancy breed cats. Mitotype C2 is restricted to four Maine Coon cats, the only example of a mitotype being restricted to a single breed.

Nucleotide diversity of seven breeds representing different hypothetical geographic origins ranged from 2.52 ± 1.4 in the Turkish Vans to 5.76 ± 2.9 in the Siamese (Supplemental Table S1). Maximum observed pairwise differences ranged from 11 – 34 respectively. Nucleotide diversity for all breeds averaged 5.62 ± 2.7.

4. Discussion

The forensic community often debates which data sets are valid for genetic comparisons and for determining the significance of a DNA match. Human populations and races and breeds of domesticated animals can be clearly genetically defined with molecular and DNA markers, suggesting substructure. However, genetic markers that have common frequencies in all populations can alleviate this concern for finding the appropriate data set to determine match probabilities. Mitochondrial DNA is expected to have less discriminatory power than nuclear markers due to its maternal inheritance and lack of recombination [34]. Although mtDNA has a high mutation rate, regions with too much genetic variation can lead to heteroplasmy that complicates forensic interpretations [35–36], especially in tissue types, such as hair, which have a high mitotic index [37–38]. Thus, a mtDNA region with a balance of variation, high for discrimination of an individual, but low to minimize heteroplasmy, needs to be defined in each species. The region analyzed in this study excludes the two highly repetitive regions in the mtDNA that show extensive heteroplasmy [2, 12, 24] and this study and our own recent work suggests that the region has low heteroplasmy [26] (unpublished data Huang et al., submitted)

Assessment of human mtDNA mitotypes has focused on hyper-variable regions I and II. These regions demonstrate a high degree of genetic variability coupled with low match probabilities. Likewise in cats, a 402 bp segment of the cat mtDNA CR has shown to have strong discriminatory power and low heteroplasmy [2, 26]. To date, statistical support for the cat mtDNA CR as a forensic tool has been limited to the work of Halverson and Basten [2]. This study has extended the initial investigations of the same mtDNA region with additional USA populations, 25 worldwide populations, and 364 cats representing 26 USA breeds.

The 402 bp sequenced region from worldwide sampling of nearly 1,400 domestic cats reveals 12 universal mitotypes that have a frequency of >1% of the combined population set. However, most of the 12 mitotypes can be collapsed into two major mitotypes, mitotypes A and D, as B, C, F, G, J, K and L have only three or fewer mutations in difference. Mitotypes E, H, and I remain distinct, as do the rare outlier mitotypes OL1 – 3, resulting in 8 distinct cat mitotypes throughout the world. Mitotype K appears to have derived in the USA from mitotype A, while mitotype J is limited to the Eastern Mediterranean, derived from mitotype D. An interesting comparison would be evaluating the CR of the five major mtDNA types identified in the domestication study of the cat to the five major types identified in this study [23].

To effectively define the universal mitotypes within a geographic location, excessive sequencing efforts may not be required. For example, the Egyptian and the Northern California, data sets were able to identify eleven or more of the twelve universal types with sample sizes of 130 and 133, respectively. The 100 samples of the New York data set failed to identify mitotype F, a mitotype found in all other reasonably sampled United States populations, however, ten major mitotypes were found. Similarly, the Southern California population had 99 representative samples and identified nine major mitotypes. Estimates of the required sample sizes for human populations are similar. Interestingly, the most common western (USA and Europe) mitotype B, is not found in several Middle Eastern countries but is present in India, China and Southeast Asian. Thus, when evaluating population structure in both forensic and evolution studies, the extent of historical and recent migration patterns needs to be considered. In addition, some missing mitotypes may be due to a sampling bias if broad areas for a given region are not considered.

The proportion of unique mitotypes within a population was generally less than 10%, except for the two European populations of Germany and Italy, where over 50% of cats had unique mitotypes. The two regions also had less than 25 sampled individuals. Thus, the “unique” mitotypes may actually represent universal mitotypes or subtypes that have not yet had sufficient sampling to identify additional samples with the same type. The within European pairwise differences was significantly higher (8.56 ± 4.0) than any other within or between group comparison except the Europe – East Asia comparison. This data supports previous STR studies that suggest European and Southeast Asia cats are fairly distinct [27]. Hence, a more extensive survey of European mtDNA domestic cat structuring seems warranted.

Purebred cats were undifferentiated with respect to mitotypes. None formed monophyletic groups nor were they restricted to a single mitotype although a subset of Maine Coon cats do possess a distinguishing mitotype (16820C in the C mitogroup). Some were representative of their hypothetical country of origin Korat (Thailand), Birman (Burma) and Siamese (Thailand), Turkish Van (Turkey), while others were not, such as the Turkish Angora (Turkey). Overall, the mtDNA correlates breeds to their geographical origins, but the mitotypes are not sufficiently distinct to define a breed or population.

The presented data set includes mtDNA CR data from 1,394 individual cats. The mtDNA region examined by Japanese researchers [25] was avoided due to concerns regarding inclusion of a repetitive sequence at the 3’ area that is polymorphic but difficult to sequence in forensic samples [2]. However, comparisons between the current study and the Japanese study yielded similar results. The 1,394 samples in this study have a genetic diversity value of 0.8813 ± 0.0046 compared to 0.8767 ± 0.0277 for the Japanese feline sample set. The random match probability was 12.0% compared to 14.1% for the Japanese samples. The similarity of both the genetic diversity values and the random match probabilities suggests that the regions are comparable in forensic applications and both regions could be useful if sufficient DNA is available for analysis.

The cat mtDNA CR examined in this study also has comparable power to a similar study in the dog[39]. Persians, which represent >50% of fancy breed cats in the USA, have a diversity value of 0.8456 with an RMP of 20.4%. Increasing sample size may reduce the random match probabilities. In the small sample set from a human Japanese population (N = 50), genetic diversity of 0.973 and random match probability of 4.6% [40] was determined. Diversity values increased minimally, ranging from 0.996 to 0.998 with increasing sample sizes. Correspondingly, random match probabilities decreased from 2.2 to 0.6% [41]. Across the cat breeds, heterozygosity approaches 0.880 with a random match probability of 13%. Since unique alleles are in low frequency in any given cat population, increasing sample numbers will not necessarily result in increased diversity values or decreased RMPs. More likely, heterozygosity values will decrease as common allele numbers increase with efforts to identify unique mitotypes within a single population. Caution should be noted with cat populations however, as they may not disperse as readily as other species, and parent offspring relationships may be common in a given area, thus, we reinforce that mtDNA data be used primarily as an exclusionary tool.

Differences between human, canine, and feline genetic diversities and random match probabilities are a reflection of the historical age of each group. Human mtDNA mitotypes have been diverging for greater than 150,000 years [42] with Eurasians diverging from a single population 60,000 – 80,000 years ago [43]. Although domestic dog progenitors may have diverged from their wolf ancestors as long as 100,000 years ago [44], dog domestication and subsequent mitochondrial mitotype proliferation has been more recent. Mitochondrial data suggest all dogs originated from 3 females in China roughly 15,000 years before present [45], and the accumulation of mutations has accelerated with a relaxation of selective constraints has been suggested as well [46]. Also, extensive selection for breeds has occurred within the last 200 years and currently there are an estimated 400+ breeds recognized by various worldwide kennel clubs [47].

Cat domestication is more recent than for most animal breeds. Archeological evidence suggests cats were in direct contact with humans as early as 9,500 years ago [48]. From a pragmatic perspective, this is the logical consequence of the domestication of grains occurring in the same time interval [49–50]. The archeological evidence is supported by mtDNA studies that suggest five mitochondrial lineages were present roughly 9,000 years before present and from these five lineages all contemporary mitotypes have been derived [23]. However, as domestication is subjective, especially with respect to cats, the intentional breeding of cats may not have occurred until as late as the 19th century B.C., during the 12th Egyptian dynasty [51]. Breed proliferation has occurred within the last 100 years with most breeds originating within the last 50 years. Moreover, several cat “breeds” are merely coat color or length variants of the different breeds, fostering the exchange of mitochondrial mitotypes across breeds. The relatively short time-span of domestic cat expansion and corresponding mitochondrial mitotype divergence addresses the issue of decreased genetic diversity values compared to humans and dogs. However, it also may prove advantageous as the extensive sampling required to resolve sub-structuring in human populations may prove unnecessary in the domestic cat. The robust sampling of cats from USA indicate little sub-structuring between the populations, all populations having the most common mitotypes and similar frequencies of unique mitotypes. The mean pairwise differences within random bred cat (5.55 ± 2.7) groups were similar to the level found between groups (5.6 ± 2.7). However, the European and Southeast Asian populations appear distinct and the high level of unique mitotypes in the European sampling suggests that more extensive non-USA data sets for cat mtDNA may be warranted.

5. Conclusions

The data set for the 402 bp region of the cat mtDNA CR includes 493 random bred cats from the USA, 534 random-bred cats from non-US populations, and 364 representing 26 cat breeds. Thus, this study represents a 6-fold increase in the available samples for comparison in forensic applications. Additionally, this data set has comparable diversity values and random match probabilities to previous studies while extending the use of this region in forensic applications [2]. The analyzed mtDNA region has sufficiently high discriminatory power and low heteroplasmy to warrant global use in forensic applications. The random bred and fancy breed cats from the USA do not appear to have intense sub-structuring. However, they are different from areas abroad, suggesting more robust analyses may need to be considered for non-USA populations.

Supplementary Material

01

Table 4.

Random Match and Exclusion Probabilities for Random Bred and Breed Populations

No. Heterozygosity Random Match
Probability		 Probability of
Exclusion
Random Bred Population 1027 0.8813±0.0046 12.0 88.0
East Asia 56 0.7787±0.0416 23.5 76.5
Eastern Mediterranean 233 0.8556±0.0147 14.8 85.2
Europe 58 0.9619 ± 0.0136 5.5 94.5
Indian Ocean Trade Route 115 0.858 ± 0.012 14.9 85.1
Iran/Iraq 72 0.7559 ± 0.0452 25.5 74.5
United States 493 0.8321±0.0095 17.0 83.0
Breeds 364 0.8719 ± 0.0101 13.0 87.0
Abyssinian 12 0.6381 ± 0.0973 41.5 59.5
Birman 23 0.6917 ± 0.1095 33.8 66.2
British Shorthair 23 0.6601 ± 0.0973 36.7 63.3
Burmese 18 0.7974 ± 0.0739 24.7 75.3
Persian 17 0.8456 ± 0.0439 20.4 79.6
Siamese 25 0.72 ± 0.0655 30.9 69.1
Turkish Van 16 0.6083 ± 0.1302 43.0 57.0
Open in a new tab

Acknowledgements

We appreciate the contribution of samples from Margaret Slater (formerly of Texas A&M University), Betsy Arnold (Caring for Cats Veterinary Practice), Amanda Payne-Del Vega (University of California - Davis), Erasmus Dzila Kalu (Lamu Veterinary Clinic), KyoWoan Cho (Gyeongsang National University), Ki Jin Ko, Gloria Lauris (Egyption Mau Rescue Organization) and the many cat breeders, including members of The Cat Fanciers’ Association, the Rome Sanctuary, the Singapore Cat Club and The International Cat Association. Funding was provided in part by NIH-NCRR R24 RR016094, the UC Davis School of Veterinary Medicine STAR program, the UC Davis Veterinary Genetics Laboratory, and the UC Davis Forensic Sciences graduate program.

Footnotes

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

6. References

  • 1.D’Andrea F, Fridez F, Coquoz R. Preliminary experiments on animal hair transfer during simulated criminal behavior. J Forensic Sci. 1998;43:1257–1258. [Google Scholar]
  • 2.Halverson JL, Basten C. Forensic DNA identification of animal-derived trace evidence: tools for linking victims and suspects. Croat Med J. 2005;46:598–605. [PubMed] [Google Scholar]
  • 3.Menotti-Raymond MA, David VA, O’Brien SJ. Pet cat hair implicates murder suspect. Nature. 1997;386:774. doi: 10.1038/386774a0. [DOI] [PubMed] [Google Scholar]
  • 4.Muller K, Brugger C, Klein R, Miltner E, Reuther F, Wiegand P. STR typing of hairs from domestic cats. Forentic Science International Genetics. 2008;3 [Google Scholar]
  • 5.Halverson JL, Lyons LA. Forensic DNA Identification of Feline Hairs: Casework and a Mitochondrial Database. Proceedings of the American Academy of Forensic Sciences. 2004 [Google Scholar]
  • 6.Budowle B, Allard MW, Wilson MR, Chakraborty R. Forensics and mitochondrial DNA: applications, debates, and foundations. Annu Rev Genomics Hum Genet. 2003;4:119–141. doi: 10.1146/annurev.genom.4.070802.110352. [DOI] [PubMed] [Google Scholar]
  • 7.Coomber N, David VA, O’Brien SJ, Menotti-Raymond M. Validation of a short tandem repeat multiplex typing system for genetic individualization of domestic cat samples. Croat Med J. 2007;48:547–555. [PMC free article] [PubMed] [Google Scholar]
  • 8.Lipinski MJ, Amigues Y, Blasi M, Broad TE, Cherbonnel C, Cho GJ, Corley S, Daftari P, Delattre DR, Dileanis S, Flynn JM, Grattapaglia D, Guthrie A, Harper C, Karttunen PL, Kimura H, Lewis GM, Longeri M, Meriaux JC, Morita M, Morrin-O’donnell R C, Niini T, Pedersen NC, Perrotta G, Polli M, Rittler S, Schubbert R, Strillacci MG, Van Haeringen H, Van Haeringen W, Lyons LA. An international parentage and identification panel for the domestic cat (Felis catus) Anim Genet. 2007;38:371–377. doi: 10.1111/j.1365-2052.2007.01632.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Menotti-Raymond MA, David VA, Wachter LL, Butler JM, O’Brien SJ. An STR forensic typing system for genetic individualization of domestic cat (Felis catus) samples. J Forensic Sci. 2005;50:1061–1070. [PubMed] [Google Scholar]
  • 10.Lopez JV, Cevario S, O’Brien SJ. Complete nucleotide sequences of the domestic cat (Felis catus) mitochondrial genome and a transposed mtDNA tandem repeat (Numt) in the nuclear genome. Genomics. 1996;33:229–246. doi: 10.1006/geno.1996.0188. [DOI] [PubMed] [Google Scholar]
  • 11.Buckley-Beason VA, Johnson WE, Nash WG, Stanyon R, Menninger JC, Driscoll CA, Howard J, Bush M, Page JE, Roelke ME, Stone G, Martelli PP, Wen C, Ling L, Duraisingam RK, Lam PV, O’Brien SJ. Molecular evidence for species-level distinctions in clouded leopards. Curr Biol. 2006;16:2371–2376. doi: 10.1016/j.cub.2006.08.066. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Eizirik E, Bonatto SL, Johnson WE, Crawshaw PG, Jr, Vie JC, Brousset DM, O’Brien SJ, Salzano FM. Phylogeographic patterns and evolution of the mitochondrial DNA control region in two neotropical cats (Mammalia, felidae) J Mol Evol. 1998;47:613–624. doi: 10.1007/pl00006418. [DOI] [PubMed] [Google Scholar]
  • 13.Eizirik E, Kim JH, Menotti-Raymond M, Crawshaw PG, Jr, O’Brien SJ, Johnson WE. Phylogeography, population history and conservation genetics of jaguars (Panthera onca, Mammalia, Felidae) Mol Ecol. 2001;10:65–79. doi: 10.1046/j.1365-294x.2001.01144.x. [DOI] [PubMed] [Google Scholar]
  • 14.Johnson WE, Culver M, Iriarte JA, Eizirik E, Seymour KL, O’Brien SJ. Tracking the evolution of the elusive Andean mountain cat (Oreailurus jacobita) from mitochondrial DNA. J Hered. 1998;89:227–232. doi: 10.1093/jhered/89.3.227. [DOI] [PubMed] [Google Scholar]
  • 15.Johnson WE, Godoy JA, Palomares F, Delibes M, Fernandes M, Revilla E, O’Brien SJ. Phylogenetic and phylogeographic analysis of Iberian lynx populations. J Hered. 2004;95:19–28. doi: 10.1093/jhered/esh006. [DOI] [PubMed] [Google Scholar]
  • 16.Johnson WE, O’Brien SJ. Phylogenetic reconstruction of the Felidae using 16S rRNA and NADH-5 mitochondrial genes. J Mol Evol. 1997;44 Suppl 1:S98–S116. doi: 10.1007/pl00000060. [DOI] [PubMed] [Google Scholar]
  • 17.Johnson WE, Slattery JP, Eizirik E, Kim JH, Raymond MM, Bonacic C, Cambre R, Crawshaw P, Nunes A, Seuanez HN, Moreira MA, Seymour KL, Simon F, Swanson W, O’Brien SJ. Disparate phylogeographic patterns of molecular genetic variation in four closely related South American small cat species. Mol Ecol. 1999;8:S79–S94. doi: 10.1046/j.1365-294x.1999.00796.x. [DOI] [PubMed] [Google Scholar]
  • 18.Masuda R, Lopez JV, Slattery JP, Yuhki N, O’Brien SJ. Molecular phylogeny of mitochondrial cytochrome b and 12S rRNA sequences in the Felidae: ocelot and domestic cat lineages. Mol Phylogenet Evol. 1996;6:351–365. doi: 10.1006/mpev.1996.0085. [DOI] [PubMed] [Google Scholar]
  • 19.Napolitano C, Bennett M, Johnson WE, O’Brien SJ, Marquet PA, Barria I, Poulin E, Iriarte A. Ecological and biogeographical inferences on two sympatric and enigmatic Andean cat species using genetic identification of faecal samples. Mol Ecol. 2008;17:678–690. doi: 10.1111/j.1365-294X.2007.03606.x. [DOI] [PubMed] [Google Scholar]
  • 20.Tamada T, Siriaroonrat B, Subramaniam V, Hamachi M, Lin LK, Oshida T, Rerkamnuaychoke W, Masuda R. Molecular diversity and phylogeography of the Asian leopard cat, Felis bengalensis, inferred from mitochondrial and Y-chromosomal DNA sequences. Zoolog Sci. 2008;25:154–163. doi: 10.2108/zsj.25.154. [DOI] [PubMed] [Google Scholar]
  • 21.Uphyrkina O, Johnson WE, Quigley H, Miquelle D, Marker L, Bush M, O’Brien SJ. Phylogenetics, genome diversity and origin of modern leopard, Panthera pardus. Mol Ecol. 2001;10:2617–2633. doi: 10.1046/j.0962-1083.2001.01350.x. [DOI] [PubMed] [Google Scholar]
  • 22.Wilting A, Buckley-Beason VA, Feldhaar H, Gadau J, O’Brien S J, Linsenmair KE. Clouded leopard phylogeny revisited: support for species recognition and population division between Borneo and Sumatra. Front Zool. 2007;4:15. doi: 10.1186/1742-9994-4-15. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Driscoll CA, Menotti-Raymond M, Roca AL, Hupe K, Johnson WE, Geffen E, Harley EH, Delibes M, Pontier D, Kitchener AC, Yamaguchi N, O’Brien S J, Macdonald DW. The Near Eastern origin of cat domestication. Science. 2007;317:519–523. doi: 10.1126/science.1139518. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Hertwig ST, Schweizer M, Stepanow S, Jungnickel A, Boehle UR, Fischer MS. Regionally high rates of hybridization and introgression in German wildcat populations (Felis silvestris, Carnivora, Felidae) Journal of Zoological Systematics and Evolutionary Research. 2009;3:15. [Google Scholar]
  • 25.Tamada T, Kurose N, Masuda R. Genetic diversity in domestic cats Felis catus of the Tsushima Islands, based on mitochondrial DNA cytochrome b and control region nucleotide sequences. Zoolog Sci. 2005;22:627–633. doi: 10.2108/zsj.22.627. [DOI] [PubMed] [Google Scholar]
  • 26.Tarditi CR, Grahn RA, Evans JJ, Kurushima JD, Lyons LA. Mitochondrial DNA Sequencing of Cat Hair: An Informative Forensic Tool. J Forensic Sci. doi: 10.1111/j.1556-4029.2010.01592.x. (in press) [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Lipinski MJ, Froenicke L, Baysac KC, Billings NC, Leutenegger CM, Levy AM, Longeri M, Niini T, Ozpinar H, Slater MR, Pedersen NC, Lyons LA. The ascent of cat breeds: genetic evaluations of breeds and worldwide random-bred populations. Genomics. 2008;91:12–21. doi: 10.1016/j.ygeno.2007.10.009. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Stoneking M, Hedgecock D, Higuchi RG, Vigilant L, Erlich HA. Population variation of human mtDNA control region sequences detected by enzymatic amplification and sequence-specific oligonucleotide probes. Am J Hum Genet. 1991;48:370–382. [PMC free article] [PubMed] [Google Scholar]
  • 29.Excoffier L, Laval G, Schneider S. Arlequin (version 3.0): An integrated software package for population genetics data analysis. Evol Bioinform Online. 2005;1:47–50. [PMC free article] [PubMed] [Google Scholar]
  • 30.Tajima F. Evolutionary relationship of DNA sequences in finite populations, Genetics. 1983;105:437–460. doi: 10.1093/genetics/105.2.437. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Tajima F. Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics. 1989;123:585–595. doi: 10.1093/genetics/123.3.585. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Bandelt HJ, Forster P, Rohl A. Median-joining networks for inferring intraspecific phylogenies. Mol Biol Evol. 1999;16:37–48. doi: 10.1093/oxfordjournals.molbev.a026036. [DOI] [PubMed] [Google Scholar]
  • 33.Richards MB, Macaulay VA, Bandelt HJ, Sykes BC. Phylogeography of mitochondrial DNA in western Europe. Ann Hum Genet. 1998;62:241–260. doi: 10.1046/j.1469-1809.1998.6230241.x. [DOI] [PubMed] [Google Scholar]
  • 34.Giles RE, Blanc H, Cann HM, Wallace DC. Maternal inheritance of human mitochondrial DNA. Proc Natl Acad Sci U S A. 1980;77:6715–6719. doi: 10.1073/pnas.77.11.6715. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Budowle B, Allard MW, Wilson MR. Critique of interpretation of high levels of heteroplasmy in the human mitochondrial DNA hypervariable region I from hair. Forensic Sci Int. 2002;126:30–33. doi: 10.1016/s0379-0738(02)00019-1. [DOI] [PubMed] [Google Scholar]
  • 36.Grzybowski T. Extremelyhigh levels of human mitochondrial DNA heteroplasmy in single hair roots. Electrophoresis. 2000;21:548–553. doi: 10.1002/(SICI)1522-2683(20000201)21:3<548::AID-ELPS548>3.0.CO;2-U. [DOI] [PubMed] [Google Scholar]
  • 37.Linch CA, Whiting DA, Holland MM. Human hair histogenesis for the mitochondrial DNA forensic scientist. J Forensic Sci. 2001;46:844–853. [PubMed] [Google Scholar]
  • 38.Tully G, Barritt SM, Bender K, Brignon E, Capelli C, Dimo-Simonin N, Eichmann C, Ernst CM, Lambert C, Lareu MV, Ludes B, Mevag B, Parson W, Pfeiffer H, Salas A, Schneider PM, Staalstrom E. Results of a collaborative study of the EDNAP group regarding mitochondrial DNA heteroplasmy and segregation in hair shafts. Forensic Sci Int. 2004;140:1–11. doi: 10.1016/S0379-0738(03)00181-6. [DOI] [PubMed] [Google Scholar]
  • 39.Gundry RL, Allard MW, Moretti TR, Honeycutt RL, Wilson MR, Monson KL, Foran DR. Mitochondrial DNA analysis of the domestic dog: control region variation within and among breeds. J Forensic Sci. 2007;52:562–572. doi: 10.1111/j.1556-4029.2007.00425.x. [DOI] [PubMed] [Google Scholar]
  • 40.Koyama H, Iwasa M, Maeno Y, Tsuchimochi T, Isobe I, Seko-Nakamura Y, Monma-Ohtaki J, Matsumoto T, Ogawa S, Sato B, Nagao M. Mitochondrial sequence haplotype in the Japanese population. Forensic Sci Int. 2002;125:93–96. doi: 10.1016/s0379-0738(01)00611-9. [DOI] [PubMed] [Google Scholar]
  • 41.Seo Y, Stradmann-Bellinghausen B, Rittner C, Takahama K, Schneider PM. Sequence polymorphism of mitochondrial DNA control region in Japanese. Forensic Sci Int. 1998;97:155–164. doi: 10.1016/s0379-0738(98)00153-4. [DOI] [PubMed] [Google Scholar]
  • 42.Vigilant L, Stoneking M, Harpending H, Hawkes K, Wilson AC. African populations and the evolution of human mitochondrial DNA. Science. 1991;253:1503–1507. doi: 10.1126/science.1840702. [DOI] [PubMed] [Google Scholar]
  • 43.Watson E, Forster P, Richards M, Bandelt HJ. Mitochondrial footprints of human expansions in Africa. Am J Hum Genet. 1997;61:691–704. doi: 10.1086/515503. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Vila C, Savolainen P, Maldonado JE, Amorim IR, Rice JE, Honeycutt RL, Crandall KA, Lundeberg J, Wayne RK. Multiple and ancient origins of the domestic dog. Science. 1997;276:1687–1689. doi: 10.1126/science.276.5319.1687. [DOI] [PubMed] [Google Scholar]
  • 45.Savolainen P, Zhang YP, Luo J, Lundeberg J, Leitner T. Genetic evidence for an East Asian origin of domestic dogs. Science. 2002;298:1610–1613. doi: 10.1126/science.1073906. [DOI] [PubMed] [Google Scholar]
  • 46.Bjornerfeldt S, Webster MT, Vila C. Relaxation of selective constraint on dog mitochondrial DNA following domestication. Genome Res. 2006;16:990–994. doi: 10.1101/gr.5117706. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.Moody J, Clark L, Murphy K. The Dog and Its Genome. Cold Spring Harbor: Cold Spring Harbor Laboratory Press; 2006. ed. [Google Scholar]
  • 48.Vigne JD, Guilaine J, Debue K, Haye L, Gerard P. Early taming of the cat in Cyprus. Science. 2004;304:259. doi: 10.1126/science.1095335. [DOI] [PubMed] [Google Scholar]
  • 49.Morrell PL, Clegg MT. Genetic evidence for a second domestication of barley (Hordeum vulgare) east of the Fertile Crescent. Proc Natl Acad Sci U S A. 2007;104:3289–3294. doi: 10.1073/pnas.0611377104. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50.Tanno K, Willcox G. How fast was wild wheat domesticated? Science. 2006;311:1886. doi: 10.1126/science.1124635. [DOI] [PubMed] [Google Scholar]
  • 51.Malek J. The Cat in Ancient Egypt. London: British Museum Press; 1993. ed. [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

01
NIHMS184595-supplement-01.doc (168KB, doc)

RESOURCES