Stefan Marklund

Parentage testing and linkage analysis in the horse using a set of highly polymorphic microsatellites

Ten (TG)n positive clones, isolated from an equine genomic library and sequenced, contained 12-19 uninterrupted TG repeats. Primers for polymerase chain reaction (PCR) were synthesized and nine of these (TG)n loci (HTG7-15) were successfully amplified and utilized in this study together with five previously reported equine microsatellite loci (HTG2-6). The PCR products were analysed by polyacrylamide gel electrophoresis followed by automated laser fluorescence detection or autoradiography. All microsatellites showed polymorphism and stable Mendelian inheritance. Differences in microsatellite variability between horse breeds were detected. A linkage analysis comprising HTG2-15, one coat colour gene and 16 genetic blood markers enabled addition of HTG2 to linkage group U2 and a new linkage group (U6) was established comprising the loci HTG7 and HTG12. Close linkage was excluded within a set of eight microsatellites. The estimated probability of exclusion in four breeds for a parentage test based on these eight loci varied between 0.96 and 0.99.

A large duplication associated with dominant white color in pigs originated by homologous recombination between LINE elements flanking KIT.

The Dominant White (I/KIT) locus is one of the major coat color loci in the pig. Previous studies showed that the Dominant White (I) and Patch (IP) alleles are both associated with a duplication including the entire KIT coding sequence. We have now constructed a BAC contig spanning the three closely linked tyrosine kinase receptor genes PDGFRA–KIT–KDR. The size of the duplication was estimated at about 450 kb and includes KIT, but not PDGFRA and KDR. Sequence analysis revealed that the duplication arose by unequal homologous recombination between two LINE elements flanking KIT. The same unique duplication breakpoint was identified in animals carrying the I and IP alleles across breeds, implying that Dominant White and Patch alleles are descendants of a single duplication event. An unexpected finding was that Piétrain pigs carry the KIT duplication, since this breed was previously assumed to be wild type at this locus. Comparative sequence analysis indicated that the distinct phenotypic effect of the duplication occurs because the duplicated copy lacks some regulatory elements located more than 150 kb upstream of KIT exon 1 and necessary for normal KIT expression.

Close association between sequence polymorphism in the KIT gene and the roan coat color in horses

Abstract. The roan coat color in horses is controlled by a dominant allele that is lethal in the homozygous condition. Phenotypic similarities to some pigmentation disorders in human and mouse, combined with comparative mapping data, identified KIT, encoding the mast cell growth factor receptor, as a major candidate gene for the roan locus (Rn). Rn has previously been mapped to equine linkage group (LG) II. In this study, LGII was expanded with KIT and PDGFRA (platelet-derived growth factor receptor α) by use of RFLP and linkage analysis. Moreover, highly significant linkage disequilibrium between Rn and a KIT TaqI RFLP, representing a synonymous substitution in exon 19, was revealed. There was a strong KIT-Rn association in most breeds. Almost the complete KIT-encoding sequence was determined by sequence analysis of RT-PCR products. Comparison of horse KIT cDNA sequences, representing three different alleles (two different rn and one Rn), revealed five sequence polymorphisms and several mRNA splice variants, but none of these proved to be specifically associated with Rn. An insertion of a partial (79 bp) LINE1-element between exons 1 and 2, leading to a frameshift, represented about 30% of KIT transcripts in the Belgian roan horse used for the sequence analysis. However, an association between this L1 splice insertion and the roan phenotype was not verified when testing additional unrelated roan and non-roan horses from different breeds. The study strengthens the hypothesis that the roan coat color is controlled by KIT, but further analyses are needed to reveal the causative mutation(s).

A frameshift mutation in golden retriever dogs with progressive retinal atrophy endorses SLC4A3 as a candidate gene for human retinal degenerations.

Progressive retinal atrophy (PRA) in dogs, the canine equivalent of retinitis pigmentosa (RP) in humans, is characterised by vision loss due to degeneration of the photoreceptor cells in the retina, eventually leading to complete blindness. It affects more than 100 dog breeds, and is caused by numerous mutations. RP affects 1 in 4000 people in the Western world and 70% of causal mutations remain unknown. Canine diseases are natural models for the study of human diseases and are becoming increasingly useful for the development of therapies in humans. One variant, prcd-PRA, only accounts for a small proportion of PRA cases in the Golden Retriever (GR) breed. Using genome-wide association with 27 cases and 19 controls we identified a novel PRA locus on CFA37 (praw = 1.94×10−10, pgenome = 1.0×10−5), where a 644 kb region was homozygous within cases. A frameshift mutation was identified in a solute carrier anion exchanger gene (SLC4A3) located within this region. This variant was present in 56% of PRA cases and 87% of obligate carriers, and displayed a recessive mode of inheritance with full penetrance within those lineages in which it segregated. Allele frequencies are approximately 4% in the UK, 6% in Sweden and 2% in France, but the variant has not been found in GRs from the US. A large proportion of cases (approximately 44%) remain unexplained, indicating that PRA in this breed is genetically heterogeneous and caused by at least three mutations. SLC4A3 is important for retinal function and has not previously been associated with spontaneously occurring retinal degenerations in any other species, including humans.

Identification of candidate genes and mutations in QTL regions for chicken growth using bioinformatic analysis of NGS and SNP-chip data

Mapping of chromosomal regions harboring genetic polymorphisms that regulate complex traits is usually followed by a search for the causative mutations underlying the observed effects. This is often a challenging task even after fine mapping, as millions of base pairs including many genes will typically need to be investigated. Thus to trace the causative mutation(s) there is a great need for efficient bioinformatic strategies. Here, we searched for genes and mutations regulating growth in the Virginia chicken lines – an experimental population comprising two lines that have been divergently selected for body weight at 56 days for more than 50 generations. Several quantitative trait loci (QTL) have been mapped in an F2 intercross between the lines, and the regions have subsequently been replicated and fine mapped using an Advanced Intercross Line. We have further analyzed the QTL regions where the largest genetic divergence between the High-Weight selected (HWS) and Low-Weight selected (LWS) lines was observed. Such regions, covering about 37% of the actual QTL regions, were identified by comparing the allele frequencies of the HWS and LWS lines using both individual 60K SNP chip genotyping of birds and analysis of read proportions from genome resequencing of DNA pools. Based on a combination of criteria including significance of the QTL, allele frequency difference of identified mutations between the selected lines, gene information on relevance for growth, and the predicted functional effects of identified mutations we propose here a subset of candidate mutations of highest priority for further evaluation in functional studies. The candidate mutations were identified within the GCG, IGFBP2, GRB14, CRIM1, FGF16, VEGFR-2, ALG11, EDN1, SNX6, and BIRC7 genes. We believe that the proposed method of combining different types of genomic information increases the probability that the genes underlying the observed QTL effects are represented among the candidate mutations identified.

Molecular characterization and mutational screening of the PRKAG3 gene in the horse

The PRKAG3 gene encodes a muscle-specific isoform of the regulatory γ subunit of AMP-activated protein kinase (AMPK). A major part of the coding PRKAG3 sequence was isolated from horse muscle cDNA using reverse-transcriptase (RT)-PCR analysis. Horse-specific primers were used to amplify genomic fragments containing 12 exons. Comparative sequence analysis of horse, pig, mouse, human, Fugu, and zebrafish was performed to establish the exon/intron organization of horse PRKAG3 and to study the homology among different isoforms of AMPK γ genes in vertebrates. The results showed conclusively that the three different isoforms (γ1, γ2, and γ3) were established already in bony fishes. Seven single nucleotide polymorphisms (SNPs), five causing amino acid substitutions, were identified in a screening across horse breeds with widely different phenotypes as regards muscle development and intended performance. The screening of a major part of the PRKAG3 coding sequence in a small case/control material of horses affected with polysaccharide storage myopathy did not reveal any mutation that was exclusively associated with this muscle storage disease. The breed comparison revealed several potentially interesting SNPs. One of these (Pro258Leu) occurs at a residue that is highly conserved among AMPK γ genes. In an SNP screening, the variant allele was only found in horse breeds that can be classified as heavy (Belgian) or moderately heavy (North Swedish Trotter, Fjord, and Swedish Warmblood) but not in light horse breeds selected for speed or racing performance (Standardbred, Thoroughbred, and Quarter horse) or in ponies (Icelandic horses and Shetland pony). The results will facilitate future studies of the possible functional significance of PRKAG3 polymorphisms in horses.

SNP detection and prediction of variability between chicken lines using genome resequencing of DNA pools

BackgroundNext-generation sequencing technologies are widely used for detection of millions of Single Nucleotide Polymorphisms (SNPs) and also provide a means of assessing their variation. This information is useful for composing subsets of highly informative SNPs for region-specific or genome-wide analysis and to identify mutations regulating phenotypic differences within or between populations. In this study, we investigated the sensitivity of SNP detection and introduced the flanking SNPs value (FSV) as a novel measure for predicting SNP-variability using ~5X genome resequencing with ABI SOLID and DNA pools from two chicken lines divergently selected for juvenile bodyweight.ResultsGenotyping with a 60 K SNP chip revealed polymorphisms within or between two divergently selected chicken lines for 31 363 SNPs, 48% of which were also detected using resequencing of DNA pools. SNP detection using resequencing was more powerful for positions with larger differences in allele frequency between the lines. About 50% of the SNPs with non-reference allele frequencies in the range 0.5-0.6 and 67% of those with frequencies > 0.9 could be detected. On average, ~3.7 SNPs/kb were detected by resequencing, with about 5% lower density on microchromosomes than on macrochromosomes. There was a positive correlation between the observed between-line SNP variation from the 60 K chip analysis and our proposed FSV score computed from the genome resequencing data. The strongest correlations on macrochromosomes and microchromosomes were observed when the FSV was calculated with total flanking regions of 62 kb (correlation 0.55) and 38 kb (correlation 0.45), respectively.ConclusionsGenome resequencing with limited coverage (~5X) using pooled DNA samples and three non-reference reads as a threshold for SNP detection, identified 50 - 67% of the 60 K SNPs with a non-reference allele frequency larger than 0.5. The SNP density was around 5% lower on the microchromosomes, most likely because of their higher gene content. Our proposed method to estimate the SNP variation (FSV) uses additional sequence information to better predict SNP informativity. The FSV scores showed higher correlations for SNPs with a larger difference in allele frequency between the populations. The correlation was strongest on macrochromosomes, probably due to a lower recombination rate.

PASE: a novel method for functional prediction of amino acid substitutions based on physicochemical properties.

Background: Non-synonymous single-nucleotide polymorphisms (nsSNPs) within the coding regions of genes causing amino acid substitutions (AASs) may have a large impact on protein function. The possibilities to identify nsSNPs across genomes have increased notably with the advent of next-generation sequencing technologies. Thus, there is a strong need for efficient bioinformatics tools to predict the functional effect of AASs. Such tools can be used to identify the most promising candidate mutations for further experimental validation. Results: Here we present prediction of AAS effects (PASE), a novel method that predicts the effect of an AASs based on physicochemical property changes. Evaluation of PASE, using a few AASs of known phenotypic effects and 3338 human AASs, for which functional effects have previously been scored with the widely used SIFT and PolyPhen tools, show that PASE is a useful method for functional prediction of AASs. We also show that the predictions can be further improved by combining PASE with information about evolutionary conservation. Conclusion: PASE is a novel algorithm for predicting functional effects of AASs, which can be used for pinpointing the most interesting candidate mutations. PASE predictions are based on changes in seven physicochemical properties and can improve predictions from many other available tools, which are based on evolutionary conservation. Using available experimental data and predictions from the already existing tools, we demonstrate that PASE is a useful method for predicting functional effects of AASs, even when a limited number of query sequence homologs/orthologs are available.

Forensic tracing of horse identities using urine samples and DNA markers

Abstract The possibility to carry out DNA testing using horse urine samples collected for doping control was tested using nine microsatellite markers and one mitochondrial D‐loop single strand conformation polymorphism (SSCP). Genomic DNA for polymerase chain reaction (PCR) analysis was prepared from different volumes of urine (5, 40 and 80 μ1 urine per reaction) using a simple protocol. Consistent genetic data were obtained from urine and blood samples except in a few cases where PCR analysis of the smallest urine volume per preparation only revealed one allele in heterozygotes. In these cases serial reactions showed that the two alleles were randomly amplified, probably because of a very low number of initial target molecules. In most cases the amount of PCR product increased with increasing volume per preparation but three samples showed a drastic reduction of PCR product. For these samples ultrafiltration of the most concentrated preparation dramatically improved the results and enabled genotyping wit...

Identification of Null Alleles and Deletions from SNP Genotypes for an Intercross Between Domestic and Wild Chickens

We analyzed genotypes from ~10K single-nucleotide polymorphisms (SNPs) in two families of an F2 intercross between Red Junglefowl and White Leghorn chickens. Possible null alleles were found by patterns of incompatible and missing genotypes. We estimated that 2.6% of SNPs had null alleles compared with 2.3% with genotyping errors and that 40% of SNPs in which a parent and offspring were genotyped as different homozygotes had null alleles. Putative deletions were identified by null alleles at adjacent markers. We found two candidate deletions that were supported by fluorescence intensity data from a 60K SNP chip. One of the candidate deletions was from the Red Junglefowl, and one was present in both the Red Junglefowl and White Leghorn. Both candidate deletions spanned protein-coding regions and were close to a previously detected quantitative trait locus affecting body weight in this population. This study demonstrates that the ~50K SNP genotyping arrays now available for several agricultural species can be used to identify null alleles and deletions in data from large families. We suggest that our approach could be a useful complement to linkage analysis in experimental crosses.