Breed-specific Single Nucleotide Polymorphisms Research Articles

IDog: a multi-omics resource for canids study.

iDog (https://ngdc.cncb.ac.cn/idog/) is a comprehensive public resource for domestic dogs (Canis lupus familiaris) and wild canids, designed to integrate multi-omics data and provide data services for the worldwide canine research community. Notably, iDog 2.0 features a 15-fold increase in genomic samples, including 29.55 million single nucleotide polymorphisms (SNPs) and 16.54 million insertions/deletions (InDels) from 1929 modern samples and 29.09 million SNPs from 111 ancient Canis samples. Additionally, 43487 breed-specific SNPs and 530 disease/trait-associated variants have been identified and integrated. The platform also includes data from 141 BioProjects involving gene expression analyses and a single-cell transcriptome module containing data from 105057 Beagle hippocampus cells. iDog 2.0 also includes an epignome module that evaluates DNA methylation patterns across 547 samples and chromatin accessibility across 87 samples for the analysis of gene expression regulation. Additionally, it provies phenotypic data for 897 dog diseases, 3207 genotype-to-phenotype (G2P) pairs, and 349 dog disease-associated genes, along with two newly constructed ontologies for breed and disease standardization. Finally, 13 new analytical tools have been added. Given these enhancements, the updated iDog 2.0 is an invaluable resource for the global cannie research community.

Elucidating breed-specific variants of native pigs in Korea: insights into pig breeds’ genomic characteristics

ABSTRACT Although conserving native pig breeds is important in Korea, research on the genomic aspects to identify breed-specific variations in native pig breeds is uncommon. Single nucleotide polymorphisms (SNPs) can be a powerful source for identifying breed-specific variants. We used whole genome sequencing data, including Jeju Native Pig (JNP), Korean Native Pig (KNP), Korean Wild Boar (KWB), and other western commercial pig breeds to determine native pig breed-specific SNPs. Furthermore, the goal was not only to determine the genomic specificity of native pig breeds but also to identify SNPs that carry breed-specific information (breed-informative SNPs) that can be related to breed characteristics. The representative characteristics of native pigs are their unique meat quality and disease resistance. We surveyed the gene ontology (GO) of native pigs with breed-specific SNPs. Examining the genes associated with GO may contribute to revealing the reasons for the unique characteristics of native pig breeds. The enriched GOs terms were neuron projection development, cell surface receptor signaling pathway, ion homeostasis in JNP, cell adhesion and wound healing in KNP, and DNA repair and reproduction in KWB. We expect that this study of breed-specific SNPs will enable us to gain a deeper understanding of native pigs in Korea.

Bioinformatic analysis of genomes of commercial breeds of domestic pigs for identification of breed-specific SNPs

Determining the purebredity of farm animals in a breeding system is of key importance for the entire livestock industry. Purebred breeding of plant breeds is designed to ensure the production of high-value improving breeding material for commercial livestock breeding. Determination of purebredity of pigs can be carried out using single nucleotide polymorphisms (SNP). The multiplexing technology today has reached a level that makes it possible to characterize tens and hundreds of thousands of polymorphic variants simultaneously for hundreds of animals in one run of the device. For the first time, using bioinformatics methods, an analysis of genome-wide projects was carried out for 264 individuals of the species Sus scrofa located in the Sequence Read Archive (NCBI-SRA). The in silico genotype was determined for 692 SNPs, of which 59 SNPs showed a significant potential for differentiation of four commercial breeds: large white (the most significant SNPs are Chr. 6: g.85845403T> G and Chr.16: g.74053569T> C), duroc (Chr. 4: g.55661608A> G, Chr. 14: g.107689091T> C and Chr. 14: g.107939105T> C), landrace (Chr. 5: g.99925204A> G, Chr. 18: g .40100481A> G and Chr. 18: g.7664624A> G) and pietrain (Chr. 13: g.136017764T> C and Chr.17: g.47595840A> G). For breeds of duroc and pietrain pigs, the accuracy of differentiation was at least 99%, for breeds of large white and landrace pigs - over 80%, however, the sensitivity indicator characterizing the percentage of false positive results of classification was slightly over 65%. Creation of models for molecularand-genetic studies of these breeds will allow for a genetic examination of their purebredity, which will contribute to an increase in their breeding value and preservation of the national gene pool.

Comparative analysis of five different methods to design a breed-specific SNP panel for cattle

Single nucleotide polymorphisms (SNPs) have now replaced microsatellite markers in several species for various genetic investigations like parentage assignment, genetic breed composition, assessment for individuality and, most popularly, as a useful tool in genomic selection. However, such a resource, which can offer to assist breed identification in a cost-effective manner is still not explored in cattle breeding programs. In our study, we have tried to describe methods for reducing the number of SNPs to develop a breed-specific panel. We have used SNP data from Dryad open public access repository. Starting from a global dataset of 178 animals belonging to 10 different breeds, we selected five panels each comprising of similar number of SNPs using different methods i.e., Delta, Pairwise Wright’s FST, informativeness for assignment, frequent item feature selection (FIFS) and minor allele frequency–linkage disequilibrium (MAF-LD) based method. MAF-LD based method has been recently developed by us for construction of breed-specific SNP panels. The STRUCTURE software analysis of MAF-LD based method showed appropriate clustering in comparison to other panels. Later, the panel of 591 breed-specific SNPs was called to their respective breeds using Venny 2.1.0 and UGent web tools software. Breed-specific SNPs were later annotated by using various Bioinformatics softwares.

Genomic evaluation for a three-way crossbreeding system considering breed-of-origin of alleles

BackgroundGenomic prediction of purebred animals for crossbred performance can be based on a model that estimates effects of single nucleotide polymorphisms (SNPs) in purebreds on crossbred performance. For crossbred performance, SNP effects might be breed-specific due to differences between breeds in allele frequencies and linkage disequilibrium patterns between SNPs and quantitative trait loci. Accurately tracing the breed-of-origin of alleles (BOA) in three-way crosses is possible with a recently developed procedure called BOA. A model that accounts for breed-specific SNP effects (BOA model), has never been tested empirically on a three-way crossbreeding scheme. Therefore, the objectives of this study were to evaluate the estimates of variance components and the predictive accuracy of the BOA model compared to models in which SNP effects for crossbred performance were assumed to be the same across breeds, using either breed-specific allele frequencies ({text{G}}_{text{A}} model) or allele frequencies averaged across breeds ({text{G}}_{text{B}} model). In this study, we used data from purebred and three-way crossbred pigs on average daily gain (ADG), back fat thickness (BF), and loin depth (LD).ResultsEstimates of variance components for crossbred performance from the BOA model were mostly similar to estimates from models {text{G}}_{text{A}} and {text{G}}_{text{B}}. Heritabilities for crossbred performance ranged from 0.24 to 0.46 between traits. Genetic correlations between purebred and crossbred performance ({text{r}}_{text{pc}}) across breeds ranged from 0.30 to 0.62 for ADG and from 0.53 to 0.74 for BF and LD. For ADG, prediction accuracies of the BOA model were higher than those of the {text{G}}_{text{A}} and {text{G}}_{text{B}} models, with significantly higher accuracies only for one maternal breed. For BF and LD, prediction accuracies of models {text{G}}_{text{A}} and {text{G}}_{text{B}} were higher than those of the BOA model, with no significant differences. Across all traits, models {text{G}}_{text{A}} and {text{G}}_{text{B}} yielded similar predictions.ConclusionsThe BOA model yielded a higher prediction accuracy for ADG in one maternal breed, which had the lowest {text{r}}_{text{pc}} (0.30). Using the BOA model was especially relevant for traits with a low {text{r}}_{text{pc}}. In all other cases, the use of crossbred information in models {text{G}}_{text{A}} and {text{G}}_{text{B}}, does not jeopardize predictions and these models are more easily implemented than the BOA model.

Single nucleotide polymorphism discovery in bovine liver using RNA-seq technology.

BackgroundRNA-seq is a useful next-generation sequencing (NGS) technology that has been widely used to understand mammalian transcriptome architecture and function. In this study, a breed-specific RNA-seq experiment was utilized to detect putative single nucleotide polymorphisms (SNPs) in liver tissue of young bulls of the Polish Red, Polish Holstein-Friesian (HF) and Hereford breeds, and to understand the genomic variation in the three cattle breeds that may reflect differences in production traits.ResultsThe RNA-seq experiment on bovine liver produced 107,114,4072 raw paired-end reads, with an average of approximately 60 million paired-end reads per library. Breed-wise, a total of 345.06, 290.04 and 436.03 million paired-end reads were obtained from the Polish Red, Polish HF, and Hereford breeds, respectively. Burrows-Wheeler Aligner (BWA) read alignments showed that 81.35%, 82.81% and 84.21% of the mapped sequencing reads were properly paired to the Polish Red, Polish HF, and Hereford breeds, respectively. This study identified 5,641,401 SNPs and insertion and deletion (indel) positions expressed in the bovine liver with an average of 313,411 SNPs and indel per young bull. Following the removal of the indel mutations, a total of 195,3804, 152,7120 and 205,3184 raw SNPs expressed in bovine liver were identified for the Polish Red, Polish HF, and Hereford breeds, respectively. Breed-wise, three highly reliable breed-specific SNP-databases (SNP-dbs) with 31,562, 24,945 and 28,194 SNP records were constructed for the Polish Red, Polish HF, and Hereford breeds, respectively. Using a combination of stringent parameters of a minimum depth of ≥10 mapping reads that support the polymorphic nucleotide base and 100% SNP ratio, 4,368, 3,780 and 3,800 SNP records were detected in the Polish Red, Polish HF, and Hereford breeds, respectively. The SNP detections using RNA-seq data were successfully validated by kompetitive allele-specific PCR (KASPTM) SNP genotyping assay. The comprehensive QTL/CG analysis of 110 QTL/CG with RNA-seq data identified 20 monomorphic SNP hit loci (CARTPT, GAD1, GDF5, GHRH, GHRL, GRB10, IGFBPL1, IGFL1, LEP, LHX4, MC4R, MSTN, NKAIN1, PLAG1, POU1F1, SDR16C5, SH2B2, TOX, UCP3 and WNT10B) in all three cattle breeds. However, six SNP loci (CCSER1, GHR, KCNIP4, MTSS1, EGFR and NSMCE2) were identified as highly polymorphic among the cattle breeds.ConclusionsThis study identified breed-specific SNPs with greater SNP ratio and excellent mapping coverage, as well as monomorphic and highly polymorphic putative SNP loci within QTL/CGs of bovine liver tissue. A breed-specific SNP-db constructed for bovine liver yielded nearly six million SNPs. In addition, a KASPTM SNP genotyping assay, as a reliable cost-effective method, successfully validated the breed-specific putative SNPs originating from the RNA-seq experiments.

Single Nucleotide Polymorphism Discovery in Bovine Pituitary Gland Using RNA-Seq Technology.

Examination of bovine pituitary gland transcriptome by strand-specific RNA-seq allows detection of putative single nucleotide polymorphisms (SNPs) within potential candidate genes (CGs) or QTLs regions as well as to understand the genomics variations that contribute to economic trait. Here we report a breed-specific model to successfully perform the detection of SNPs in the pituitary gland of young growing bulls representing Polish Holstein-Friesian (HF), Polish Red, and Hereford breeds at three developmental ages viz., six months, nine months, and twelve months. A total of 18 bovine pituitary gland polyA transcriptome libraries were prepared and sequenced using the Illumina NextSeq 500 platform. Sequenced FastQ databases of all 18 young bulls were submitted to NCBI-SRA database with NCBI-SRA accession numbers SRS1296732. For the investigated young bulls, a total of 113,882,3098 raw paired-end reads with a length of 156 bases were obtained, resulting in an approximately 63 million paired-end reads per library. Breed-wise, a total of 515.38, 215.39, and 408.04 million paired-end reads were obtained for Polish HF, Polish Red, and Hereford breeds, respectively. Burrows-Wheeler Aligner (BWA) read alignments showed 93.04%, 94.39%, and 83.46% of the mapped sequencing reads were properly paired to the Polish HF, Polish Red, and Hereford breeds, respectively. Constructed breed-specific SNP-db of three cattle breeds yielded at 13,775,885 SNPs. On an average 765,326 breed-specific SNPs per young bull were identified. Using two stringent filtering parameters, i.e., a minimum 10 SNP reads per base with an accuracy ≥ 90% and a minimum 10 SNP reads per base with an accuracy = 100%, SNP-db records were trimmed to construct a highly reliable SNP-db. This resulted in a reduction of 95,7% and 96,4% cut-off mark of constructed raw SNP-db. Finally, SNP discoveries using RNA-Seq data were validated by KASP™ SNP genotyping assay. The comprehensive QTLs/CGs analysis of 76 QTLs/CGs with RNA-seq data identified KCNIP4, CCSER1, DPP6, MAP3K5 and GHR CGs with highest SNPs hit loci in all three breeds and developmental ages. However, CAST CG with more than 100 SNPs hits were observed only in Polish HF and Hereford breeds.These findings are important for identification and construction of novel tissue specific SNP-db and breed specific SNP-db dataset by screening of putative SNPs according to QTL db and candidate genes for bovine growth and reproduction traits, one can develop genomic selection strategies for growth and reproductive traits.

Multibreed genomic evaluations using purebred Holsteins, Jerseys, and Brown Swiss

Multibreed models are currently used in traditional US Department of Agriculture (USDA) dairy cattle genetic evaluations of yield and health traits, but within-breed models are used in genomic evaluations. Multibreed genomic models were developed and tested using the 19,686 genotyped bulls and cows included in the official August 2009 USDA genomic evaluation. The data were divided into training and validation sets. The training data set comprised bulls that were daughter proven and cows that had records as of November 2004, totaling 5,331Holstein, 1,361 Jersey, and 506 Brown Swiss. The validation data set had 2,508Holstein, 413 Jersey, and 185 Brown Swiss bulls that were unproven (no daughter information) in November 2004 and proven by August 2009. A common set of 43,385 single nucleotide polymorphisms (SNP) was used for all breeds. Three methods of multibreed evaluation were investigated. Method 1 estimated SNP effects separately within breed and then applied those breed-specific SNP estimates to the other breeds. Method 2 estimated a common set of SNP effects from combined genotypes and phenotypes of all breeds. Method 3 solved for correlated SNP effects within each breed estimated jointly using a multitrait model where breeds were treated as different traits. Across-breed genomic predicted transmitting ability (GPTA) and within-breed GPTA were compared using regressions to predict the deregressed validation data. Method 1 worked poorly, and coefficients of determination (R2) were much lower using training data from a different breed to estimate SNP effects. Correlations between direct genomic values computed using training data from different breeds were less than 30% and sometimes negative. Across-breed GPTA from method 2had higher R2 values than parent average alone but typically produced lower R2 values than the within-breed GPTA. The across-breed R2 exceeded the within-breed R2 for a few traits in the Brown Swiss breed, probably because information from the other breeds compensated for the small numbers of Brown Swiss training animals. Correlations between within-breed GPTA and across-breed GPTA ranged from 0.91 to 0.93. The multibreed GPTA from method 3 were significantly better than the current within-breed GPTA, and adjusted R2 for protein yield (the only trait tested for method 3) were highest of all methods for all breeds. However, method 3 increased the adjusted R2 by only 0.01 for Holsteins, ≤0.01 for Jerseys, and 0.01 for Brown Swiss compared with within-breed predictions.

Use of Breed-Specific Single Nucleotide Polymorphisms to Discriminate Between Holstein and Jersey Dairy Cattle Breeds

Emphasis on livestock genetic improvement in the past decades has led to commercialization of different breeds of livestock species. Breed validation has become increasingly important to assess the safety and authenticity of livestock products in global and domestic markets. The objective of this study was to evaluate the use of breed-specific single nucleotide polymorphisms (SNPs) in discriminating between Holstein and Jersey dairy cattle breeds. Two separate resource populations were used, including a reference population consisting of 498 Holstein and 83 Jersey bull DNA samples, and a validation population consisting of 260 Holstein and 34 Jersey cow DNA samples. Five Jersey-specific and four Holstein-specific SNPs were identified and genotyped on the reference and validation resource populations. The reference population was used to validate the breed-specific SNPs used in this study and to predict the allocation efficiencies and misclassification probabilities of different combinations of SNPs. Individual animals in the validation population were allocated to either breed based on the presence of breed-specific alleles. It was found that any combination of three breed-specific SNPs had, on average, high breed allocation efficiency of >95% and low misclassification probability of <5%. In conclusion, this study demonstrates a simple, yet effective, method of using breed-specific SNPs to discriminate between Jersey and Holstein cattle breeds.

Identification of high utility SNPs for population assignment and traceability purposes in the pig using high-throughput sequencing

The objectives of this study were to develop breed-specific single nucleotide polymorphisms (SNPs) in five pig breeds sequenced with Illumina's Genome Analyzer and to investigate their usefulness for breed assignment purposes. DNA pools were prepared for Duroc, Landrace, Large White, Pietrain and Wild Boar. The total number of animals used for sequencing was 153. SNP discovery was performed by aligning the filtered reads against Build 7 of the pig genome. A total of 313,964 high confidence SNPs were identified and analysed for the presence of breed-specific SNPs (defined in this context as SNPs for which one of the alleles was detected in only one breed). There were 29,146 putative breed-specific SNPs identified, of which 4441 were included in the PorcineSNP60 beadchip. Upon re-examining the genotypes obtained using the beadchip, 193 SNPs were confirmed as being breed specific. These 193 SNPs were subsequently used to assign an additional 490 individuals from the same breeds, using the sequenced individuals as reference populations. In total, four breed assignment tests were performed. Results showed that for all methods tested 99% of the animals were correctly assigned, with an average probability of assignment of at least 99.2%, indicating the high utility of breed-specific markers for breed assignment and traceability. This study provides a blueprint for the way next-generation sequencing technologies can be used for the identification of breed-specific SNPs, as well as evidence that these SNPs may be a powerful tool for breed assignment and traceability of animal products to their breeds of origin.

A Simple Polymerase Chain Reaction-based Method for the Discrimination of Three Chicken Breeds

A large number of branded chicken products exist in Japan, and in some cases, the breed of chicken is an important factor used to attract consumer interest in the retail product. In order to establish a simple method for verifying such breed claims we applied the amplified fragment length polymorphism (AFLP) technique to nine chicken breeds (White Cornish, Red Cornish, White Plymouth Rock, New Hampshire, Rhode Island Red, Barred Plymouth Rock, Hinaidori, Tosajidori, Tsushimajidori) to search for molecular markers able to discriminate chicken breeds. Three breed-specific single nucleotide polymorphisms (SNP) were identified, one for each of Hinaidori, Tosajidori, or New Hampshire. A total of 219 individuals from the nine breeds were analyzed using a specific PCR test for each of these SNP. The PCR tests made it possible to discriminate between the breeds of chickens to identify products from these three breeds. This PCR method provides an efficient method for the routine analysis and verification of certified chicken products.

Selection of single-nucleotide polymorphisms and quality of genotypes used in genomic evaluation of dairy cattle in the United States and Canada

Nearly 57,000 single-nucleotide polymorphisms (SNP) genotyped with the Illumina BovineSNP50 BeadChip (Illumina Inc., San Diego, CA) were investigated to determine usefulness of the associated SNP for genomic prediction. Genotypes were obtained for 12,591 bulls and cows, and SNP were selected based on 5,503 bulls with genotypes from a larger set of SNP. The following SNP were deleted: 6,572 that were monomorphic, 3,213 with scoring problems (primarily because of poor definition of clusters and excess number of clusters), and 3,649 with a minor allele frequency of <2%. Number of SNP for each minor allele frequency class (≥2%) was fairly uniform (777 to 1,004). For 5 contiguous SNP assigned to chromosome 7, no bulls were heterozygous, which indicated that those SNP are actually on the nonpseudoautosomal portion of the X chromosome. Another 178 SNP that were not assigned to a chromosome but that had many fewer heterozygotes than expected were also assigned to the X chromosome. Existence of Hardy-Weinberg equilibrium was investigated by comparing observed with expected heterozygosity. For 11 SNP, the observed percentage of heterozygous individuals differed from the expected by >15%; therefore, those SNP were deleted. For 2,628 SNP, the genotype at another SNP was highly correlated (i.e., genotypes were identical for >99.5% of bulls), and those were deleted. After edits, 40,874 SNP remained. A parent–progeny conflict was declared when the genotypes were alternate homozygotes. Mean number of conflicts was 2.3 when pedigree was correct and 2,411 when it was incorrect. The sire was genotyped for >93% of animals. Maternal grandsire genotype was similarly checked; however, because alternate homozygotes could be valid, a conflict threshold of 16% was used to indicate a need for further investigation. Genotyping consistency was investigated for 21 bulls genotyped twice with differences primarily from SNP that were not scored in one of the genotypes. Concordance for readable SNP was extremely high (99.96–100%). Thousands of SNP that were polymorphic in Holsteins were monomorphic in Jerseys or Brown Swiss, which indicated that breed-specific SNP sets are required or that all breeds need to be considered in the SNP selection process. Genotypes from the Illumina BovineSNP50 BeadChip are of high accuracy and provide the basis for genomic evaluations in the United States and Canada.

Genome-wide identification of breed-informative single-nucleotide polymorphisms in three South African indigenous cattle breeds

Access to genotyping assays enables the identification of informative markers that discriminate between cattle breeds. Identification of these markers can assist in breed assignment, improvement and conservation. The objective of this study was to identify breed informative markers to discriminate between three South African indigenous cattle breeds. Data from BovineSNP50 and GeneSeek Genomic Profiler (GGP-80K) assays were generated for Afrikaner, Drakensberger and Nguni, and were analysed for their genetic differentiation. Hereford and Angus were included as outgroups. Breeds were differentiated using principal component analysis (PCA). Single-nucleotide polymorphisms (SNPs) within the breeds were determined when minor allele frequency (MAF) was ≥ 0.05. Breed-specific SNPs were identified using Reynolds Fst and extended Lewontin and Krakauer's (FLK) statistics. These SNPs were validated using three African breeds, namely N’Dama, Kuri and Zebu from Madagascar. PCA discriminated among the breeds. A larger number of polymorphic SNPs was detected in Drakensberger (73%) than in Afrikaner (56%) and Nguni (65%). No substantial numbers of informative SNPs (Fst ≥ 0.6) were identified among indigenous breeds. Eleven SNPs were validated as discriminating the indigenous breeds from other African breeds. This is because the SNPs on BovineSNP50 and GGP-80K assays were ascertained as being common in European taurine breeds. Lower MAF and SNP informativeness observed in this study limits the application of these assays in breed assignment, and could have other implications for genome-wide studies in South African indigenous breeds. Sequencing should therefore be considered to discover new SNPs that are common among indigenous South African breeds and also SNPs that discriminate among these indigenous breeds.