Whole-Genome sequencing and genetic variant analysis of a quarter Horse mare
© Doan et al; licensee BioMed Central Ltd. 2012
Received: 22 October 2011
Accepted: 17 February 2012
Published: 17 February 2012
The catalog of genetic variants in the horse genome originates from a few select animals, the majority originating from the Thoroughbred mare used for the equine genome sequencing project. The purpose of this study was to identify genetic variants, including single nucleotide polymorphisms (SNPs), insertion/deletion polymorphisms (INDELs), and copy number variants (CNVs) in the genome of an individual Quarter Horse mare sequenced by next-generation sequencing.
Using massively parallel paired-end sequencing, we generated 59.6 Gb of DNA sequence from a Quarter Horse mare resulting in an average of 24.7X sequence coverage. Reads were mapped to approximately 97% of the reference Thoroughbred genome. Unmapped reads were de novo assembled resulting in 19.1 Mb of new genomic sequence in the horse. Using a stringent filtering method, we identified 3.1 million SNPs, 193 thousand INDELs, and 282 CNVs. Genetic variants were annotated to determine their impact on gene structure and function. Additionally, we genotyped this Quarter Horse for mutations of known diseases and for variants associated with particular traits. Functional clustering analysis of genetic variants revealed that most of the genetic variation in the horse's genome was enriched in sensory perception, signal transduction, and immunity and defense pathways.
This is the first sequencing of a horse genome by next-generation sequencing and the first genomic sequence of an individual Quarter Horse mare. We have increased the catalog of genetic variants for use in equine genomics by the addition of novel SNPs, INDELs, and CNVs. The genetic variants described here will be a useful resource for future studies of genetic variation regulating performance traits and diseases in equids.
The sequencing and assembly of a horse genome was a great achievement in equine genomics and veterinary medicine because of the broad range of potential applications of this information for improving health and performance and for understanding differences among species . To date, however, only a single genome of a Thoroughbred mare has been sequenced and made publicly available . The current catalog of genetic variants in the equine genome consists of 1,163,580 single nucleotide polymorphisms (SNPs; dbSNP: http://www.ncbi.nlm.nih.gov/projects/SNP/ [build 135]), with no insertion/deletion polymorphisms (INDELs) or copy number variants (CNVs) having been deposited into a publicly available database (dbSNP or dbVar, http://www.ncbi.nlm.nih.gov/dbvar). Of the known SNPs in horses, most (~64%) originate from the Thoroughbred mare used for the genome assembly .
Sequencing the genome of a Quarter Horse was considered important for several reasons. Almost 3 million Quarter Horses were registered in the United States in 2010 according to the American Quarter Horse Association, making it the single largest breed registry in the country [2, 3]. When one includes non-registered Quarter Horses and other Quarter Horse-influenced breed registries (e.g., American Paint Horse Association), the Quarter Horse is by far the largest contributor to the population of horses in the United States. Although Quarter Horse breeding was, and continues to be, strongly influenced by Thoroughbred bloodlines, the 2 breeds were selectively bred to enhance different traits. Thoroughbred breeding has selected for speed over distances of 3/4 to 2 miles, whereas selection in the Quarter Horse has emphasized speed over shorter distances and compliant disposition suited to working cattle and other ranch-related duties . Thus, there are important phenotypic differences between the breeds that have been achieved by selective breeding with a clear underlying genetic component [5, 6]. Moreover, there are single-gene disorders in Quarter Horses, such as polysaccharide storage myopathy (PSSM) [7, 8], hyperkalemic periodic paralysis (HYPP) , glycogen branching enzyme deficiency (GBED) , and hereditary equine regional dermal asthenia (HERDA) [11, 12]. Most diseases and traits (such as predisposition to osteoarthritis or body-type) are complex, involving multiple genes, which may be modulated by environmental factors [5, 13, 14]. Thus, identifying genetic variants in the genome of a single Quarter Horse would provide a wealth of information for future genomic studies in equids.
Here we describe the whole-genome sequencing of an individual Quarter Horse mare using massively parallel paired-end sequencing. Sequence reads were mapped to the reference Thoroughbred nuclear and mitochondrial genomes. We developed a comprehensive list of genetic variants, including SNPs, INDELs, and CNVs. We annotated genetic variants and examined their impact on gene structure and function. The genomic sequence was also examined for mutations and polymorphisms associated with diseases and traits in horses. Furthermore, we examined biological processes enriched for genetic variants and compared these biological processes between this Quarter Horse mare and the reference Thoroughbred mare.
Whole-genome sequencing, alignment, and identification of new genomic sequence
Sequence generation and mapping to equCab2 reference genome
Bases Mapped (Gb)
Average Depth of Coverage
% of Reference Mapped
Bases Mapped to ChrUn (Mb)
De Novo Assembly of Unmapped (Mb)
Identification of genetic variants
Annotation of SNPs in the Quarter Horse genome
Intergenic (Upstream w/in 1 kb)
Intergenic (Downstream w/in 1 kb)
Intergenic (Up/Down w/in 1 kb)
Intron Splice Site
Exon Splice Site
10,485 (305 imprinted)
Comparison of putative SNPs in the mapped sequences to the horse SNP database (dbSNP, http://www.ncbi.nlm.nih.gov/projects/SNP/) revealed that 342,726 were known and 2,814,367 were novel, including 18,140 non-synonymous SNPs (11,434 radical and 6,706 conservative) and 2,629 complex (i.e., tri-allelic) SNPs. Comparison of the putative SNPs to those identified in the sequencing and assembly of the reference Thoroughbred genome revealed that 244,669 SNPs were overlapping between the 2 horses, including 174,682 intergenic and 69,987 genic SNPs. By removing overlapping known SNPs, we found that the Quarter Horse and Thoroughbred genomes had 2,912,424 and 522,610 unique SNPs, respectively.
Annotation of INDELs in the Quarter Horse genome
INDELs (1 bp - 8 bp)
Intergenic (Upstream w/in 1 kb)
Intergenic (Downstream w/in 1 kb)
Intergenic (Up/Down w/in 1 kb)
Intron Splice Site
Exon Splice Site
Stop - Gain
Copy number variants (CNVs) were identified using a read-depth algorithm that corrects for GC bias. CNVs were then filtered to remove those within telomeric regions, as investigation of these regions is associated with high false discovery rates . The filtered analysis revealed 282 CNVs, including 274 gains, 6 losses, and 2 homozygous deletions (Additional file 28, Table S24, Additional file 29, Figure S5 and Additional file 30, Figure S6). The sizes ranged from 3.74 kb to 4.84 Mb, with an average length of 296.1 kb. Annotation of the CNVs indicated that 192 and 90 were genic and intergenic, respectively.
Pathway, trait, and disease analysis of identified genetic variants
Comparison of biological pathways containing heterozygous non-synonymous SNPs between the Quarter Horse and reference Thoroughbred (Additional file 33, Table S26) revealed that the Quarter Horse had SNPs enriched in pathways for sensory perception (36%; P = 1.3 × 10-36), cellular processes (18%; P = 4.8 × 10-5), and signal transduction (16%; P = 1.2 × 10-3; Additional file 34, Figure S8A), whereas the Thoroughbred had SNPs enriched in pathways for immunity and defense (36%; P = 5.2 × 10-8), sensory perception (23%; P = 6.4 × 10-14), and cellular processes (13%; P = 2.7 × 10-1; Additional file 34, Figure S8B). As the enrichment analysis reflected percentages of genes within pathways, and because the Quarter Horse contained nearly three times as many heterozygous SNPs as the Thoroughbred, we determined the total number of genes for each BP term that contained a non-synonymous heterozygous SNP. As expected, the Quarter Horse had more genes containing SNPs for each BP class, except for the immune and defense (P = 2.4 × 10-27) and nucleic acid metabolism (P = 1.1 × 10-11) pathways (Additional file 34, Figure S8C, Additional file 35, Tables S27 and Additional file 36, Table S28).
Analysis of genetic variants for known traits and diseases
transient receptor potential cation channel
Leopard complex spotting and congenital stationary night blindness
peptidyl-prolyl cis-trans isomerase B
Hereditary equine regional dermal asthenia
myosin-Va isoform 1
Lavender foal syndrome
Del 1 bp
melanocyte-stimulating hormone receptor
Chestnut coat color
melanocyte-stimulating hormone receptor
Chestnut coat color
mast/stem cell growth factor receptor
mast/stem cell growth factor receptor
Tobiano spotting pattern
pyruvate dehydrogenase kinase isozyme 4
pyruvate dehydrogenase kinase isozyme 4
laminin subunit gamma-2 precursor
Junctional epidermolysis bullosa
melanocyte protein 17 precursor
Silver coat color
Junctional epidermolysis bullosa
DNA-dependent protein kinase catalytic subunit
Severe combined immunodeficiency
Del 5 bp
ryanodine receptor 1 isoform 2
creatine kinase M-type
glycogen [starch] synthase muscle
Polysaccharide storage myopathy
sodium channel protein type 4 subunit alpha
Equine hyperkalemic periodic paralysis
proton-coupled amino acid transporter 1
endothelin B receptor precursor
Lethal white foal syndrome
growth/differentiation factor 8 precursor
Optimum racing distance
membrane-associated transporter protein isoform
Cream coat color
cytochrome c oxidase subunit 4 isoform 2
agouti-signaling protein precursor
Black and bay color
Del 11 bp
Gray coat color
The current catalog of equine genetic variants is limited and primarily consists of those detected from the sequencing and assembly of a single Thoroughbred horse . In the present study, we describe the whole-genome sequencing and identification of genetic variants in the genome of a Quarter Horse mare. To our knowledge, this is the first published report of a whole-genome sequence of a Quarter Horse and the only horse genome sequenced by next-generation sequencing. At 25X sequence coverage, we estimated that approximately 85-88% of the horse's genome could be genotyped . Our analysis yielded 3.1 million SNPs, 193 thousand INDELs, and 282 CNVs. Despite the fact that approximately 10% of the novel homozygous SNPs likely reflect errors in the reference genome (given that the accuracy of the reference genome is 99.99%) and that our false discovery rate (FDR) for SNP detection is approximately 1.5% (Doan et al. unpublished studies), the genetic variants identified here represent a significant addition to what is currently available for studies in horses. It should be noted that the breeding structure of Quarter Horses and Thoroughbreds, as well as the differences in sequencing technology (i.e., next-generation sequencing of DNA fragments vs. Sanger sequencing of bacterial artificial clones) most likely contributed to the increased amount of genetic variation identified in this study. We suspect that many genetic variants were missed due to the parameters applied during our variant detection (e.g., requiring a minimum of 10X sequence coverage). To minimize this false negative rate (FNR) we provide a list of SNPs and INDELs using a less stringent calling criterion (5X minimum sequence coverage; Additional file 5, Table S3). However, caution should be used with these variants as the FDR is expected to increase with a reduced minimum coverage, although not directly proportional to the decrease of the FNR.
De novo assembly of reads not mapping to the assembled or un-assembled chromosomes led to the generation of 19.1 Mb of new horse genomic sequence. Our analysis of CNVs in horses and cattle using array comparative genomic hybridization (Doan et al., unpublished studies), as well as studies in the human and mouse show that large (Mb) deletions are common variants in the genome [21–24]. This presence/absence variation  is common, and thus we suspect that some percentage of the de novo assembled sequence represents sequence missing from the reference Thoroughbred genome due to homozygous deletions.
Functional annotation clustering analysis of genetic variants revealed that pathways for sensory perception, signal transduction, protein processing, cellular process, and immunity and defense were differentially affected by each type of genetic variant (i.e., SNPs, INDELs, and CNVs), suggesting varying degrees of tolerance and selection for genetic variants underlying these biological processes. Genes involved in sensory perception pathways contained most of the genetic variation, primarily SNPs (27%) and CNVs (60%). The observed enrichment in sensory perception genes may be related to selection of the Quarter Horse for a relatively calm disposition [26, 27], although this is highly speculative at this point, and will only be determined by future population based-studies. Conversely, these variants could reflect misassemblies in the reference genome or misalignments in the Quarter Horse reads to the reference sequence, as these genes exist as large families with numerous pseudogenes.
This is the first sequencing of a horse genome by next-generation sequencing and the first genomic sequence of an individual Quarter Horse. The genetic variants identified in this study will be a useful resource for future studies to understand the genetic basis of phenotypic variation and disease in equids.
DNA was isolated from whole blood of a Quarter Horse mare using a standard phenol-chloroform extraction including 2 phenol-chloroform-isoamyl (PCI) steps, followed by rinses with chloroform, isopropanol, and 70% ethanol. The sample was suspended in Qiagen EB buffer (Qiagen Sciences, Germantown, MD). The Texas A&M University Institutional Animal Care and Use Committee approved this study.
For the construction of sequencing libraries, we first sonicated high-quality genomic DNA by pulsing 3X for 15 sec/pulse at 14% using a Sonic Dismembrator 500 (Fisher Scientific, Pittsburg, PA) and purified with an Invitrogen PureLink PCR Kit (Invitrogen, Carlsbad, CA). The DNA was blunt end-repaired, adenylated, and ligated with paired-end adaptors, according to the manufacturer's protocol (Illumina, San Diego CA). The prepared library was resolved on a 2% low range agarose gel and a 2-mm section of DNA was isolated at 271 bp (Qiagen Sciences, Germantown, MD). The library was then enriched according to the manufacturer's protocol (Illumina, San Diego CA). The size and concentration of the sequencing library was determined by PCR, visualization of polyacrylamide gel electrophoresis (PAGE) gels, and through the use of the Agilent 2100 Bioanalyzer DNA kit (Agilent Technologies, San Diego CA). Cluster generation and paired-end sequencing was performed according to the manufacturer's protocols (Illumina) at the AgriLife Genomics and Bioinformatics Center (College Station, TX)
We used the trim function in the CLC Genomics Workbench (CLC Bio, Aarhus, Denmark) using the following parameters: ambiguous limit, 2; ambiguous trim, yes; quality limit, 0.1; quality trim, yes; and, remove 3' nucleotide, no; remove 5' nucleotide, no. The CLC Genomics Workbench Reference Mapping function was used to assemble the trimmed reads to the equCab2 reference assembly using the following parameters: similarity score = 0.8; and, length fraction = 0.5. Paired-end reads were mapped using an insert range of 180-bp to 500-bp and reads mapping to multiple places in the reference were mapped using the random setting. In order to determine the percent of the genome that was mapped by uniquely mapped read, we used the previously stated settings with nonspecific reads being ignored.
We used the SNP detection function in CLC Genomics Workbench, based on the neighborhood quality standard (NQS) algorithm, using the following parameters: minimum coverage = 5; minimum central base quality = 30; average base quality over a window length of 11 nucleotides = 15; and, minimum allele frequency = 35%. SNPs were filtered by removing those within 10 bp of another variant (both INDELs and SNPs). Also, SNPs located within the pseudo-autosomal region (PAR) were removed . The remaining SNPs were filtered by read-depth to create SNP analyses with minimum depths of 5, 6, 7, 8, 9, and 10.
We used the deletion and insertion polymorphism (DIP) function in CLC Genomics Workbench using the following parameters: minimum coverage = 5; minimum allele frequency = 35%; and, maximum expected variations = 2. INDELs were filtered in a similar manner as SNPs, with those near other variants and within the PAR being removed. Analyses were conducted at both 5X and 10X read-depths.
We used the Control-FREE copy number algorithm (FREEC) program to identify CNVs in the mapped sequence data . We optimized the program for our data using a break-point threshold of -0.0013 and a coefficient of variation of 0.045. Additionally, we removed any CNVs located within 1 Mb of the beginning and end of all chromosomes in order to reduce the potential for erroneous calling.
Genetic variant annotation and analysis
We re-annotated the variant calls from CLC Genomics using both Galaxy http://galaxy.psu.edu/ and ANNOVAR software programs [29, 30]. The join and merge functions in Galaxy were used to annotate the SNPs and INDELs. We used these functions to compare the SNPs to all known SNPs in dbSNP as well as those identified in the reference horse. The ANNOVAR program used the Ensembl annotation database to create an mRNA library, allowing for the determination of amino acid changes. The program was used to determine the locations of all variants within the genome. We also annotated the known SNPs from the reference Thoroughbred genome to determine amino acid changes as well as gene locations for a comparison to the Quarter Horse. The SNPs were divided into groups based on radical and conservative amino acid changes, where radical SNPs result in a difference in polarity or charge when the amino acid was changed while conservative SNPs cause no change in polarity or charge.
The gene lists for each group were converted to human Ensembl gene IDs using Ensembl Biomart. Biological function analysis was performed through the DAVID Functional Annotation Tool, using the default settings . The resulting biological process terms were further grouped by similarities in function to determine enrichment for specific biological processes (Additional file 37, Table S29). Statistical significance (p-value) for each enriched group was determined using Fisher's combined probability test with the p-value created from the DAVID Functional Annotation Tool. The enriched genes for each biological process group were compared between the Quarter Horse and reference Thoroughbred using the Fisher's exact test for a 2 × 2 contingency table.
Analysis of de novo assembly of unmapped reads
We created a de novo assembly of all reads that did not align to the reference genome (including ChrMt and ChrUn) using de Bruijn Graphs (CLC Genomics). We were able to assemble 8,186,040 of the 12,657,236 unmapped reads into contigs with minimum and average contig lengths of 200 bp and 537 bp, respectively. We performed de novo assembly of reads not mapping to either assembled or unassembled chromosomes using the following parameters: similarity = 0.8; length fraction = 0.5; insertion cost = 3; deletion cost = 3; mismatch cost = 3; minimum paired distance = 180 bp; and, maximum paired distance = 500 bp. The resulting 35,540 contigs were further analyzed by BLAST, mapping all complete genomes and chromosomes from RefSeq.
Sequence data and genetic variants
The Illumina FASTQ data generated from this study has been submitted to the NCBI Sequence Read Archive http://www.ncbi.nlm.nih.gov/sra under accession number SRX110702. The mapped sequences and genetic variants have been submitted to Intrepid Bioinformatics and are available for public viewing http://server1.intrepidbio.com/FeatureBrowser/ngsdatasetrecord/record?ngsrecord=6197673305. A complete list of SNPs, INDELs, and CNVs are listed in Additional files 5, 6, and 24, Tables S3, S4 and S24.
We thank Sam Wigington at Texas A&M University, College of Veterinary Medicine and Biomedical Sciences for identification of the mare whose genome we sequenced. Funding for this study was provided by Texas AgriLife Research; the GW & G Pool Large Animal Hospital Endowment at the Department of Large Animal Clinical Sciences, College of Veterinary Medicine and Biomedical Sciences; the Department of Animal Science; and the Link Equine Research Endowment, Texas A&M University. This publication is based in part on work supported by Award No. KUS-C1-016-04, made by King Abdullah University of Science and Technology (KAUST).
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