Single Nucleotide Polymorphism Panel Research Articles

Genomic inbreeding coefficients using imputed genotypes: assessing differences among SNP panels in Holstein-Friesian dairy cows.

The objective of this study was to evaluate the effect of imputation of single nucleotide polymorphisms (SNP) on the estimation of genomic inbreeding coefficients. Imputed genotypes of 68,127 Italian Holstein dairy cows were analyzed. Cows were initially genotyped with two high density (HD) SNP panels, namely the Illumina Infinium BovineHD BeadChip (678 cows; 777,962 SNP) and the Genomic Profiler HD-150K (641 cows; 139,914 SNP), and four medium density (MD): GeneSeek Genomic Profiler 3 (10,679 cows; 26,151 SNP), GeneSeek Genomic Profiler 4 (33,394 cows; 30,113 SNP), GeneSeek MD (12,030 cows; 47,850 SNP) and the Labogena MD (10,705 cows; 41,911 SNP). After imputation, all cows had genomic information on 84,445 SNP. Seven genomic inbreeding estimators were tested: (i) four PLINK v1.9 estimators (F, Fhat1,2,3), (ii) two genomic relationship matrix (grm) estimators [VanRaden's 1st method, but with observed allele frequencies (Fgrm) and VanRaden's 3rd method that is allelic free and pedigree dependent (Fgrm2)], and (iii) a runs of homozygosity (roh) - based estimator (Froh). Genomic inbreeding coefficients of each SNP panel were compared with genomic inbreeding coefficients derived from the 84,445 imputation SNP. Coefficients of the HD SNP panels were consistent between genotyped-imputed SNP (Pearson correlations ~99%), while variability across SNP panels and estimators was observed in the MD SNP panels, with Labogena MD providing, on average, more consistent estimates. The robustness of Labogena MD, can be partly explained by the fact that 97.85% of the SNP of this panel is included in the 84,445 SNP selected by ANAFIBJ for routine genomic imputations, while this percentage for the other MD SNP panels varied between 55 and 60%. Runs of homozygosity was the most robust estimator. Genomic inbreeding estimates using imputation SNP are influenced by the SNP number of the SNP panel that are included in the imputed SNP, and performance of genomic inbreeding estimators depends on the imputation.

Computational investigation of the impact of potential AT2R polymorphism on small molecule binding

For more than a century, the renin-angiotensin system (RAS) has been acknowledged for playing a crucial part in the physiological control of arterial pressure, as well as sodium and fluid balance. It is now generally acknowledged that one of the receptor of RAS system i.e. angiotensin type 2 receptor (AT2R) functions as a repair system during pathophysiologic circumstances and performs a significant protective role. Efforts have been made previously to design suitable agonist and antagonist molecules to potentially modulate AT2R. One of the agonists and antagonists, named C21 and EMA401, has been studied in a number of pathological conditions. Additionally, a wide panel of single nucleotide polymorphisms (SNPs) has been reported for AT2R, which might potentially affect the efficacy of these molecules. Therefore, computational investigations have been carried out to analyze all the SNPs (1151) reported in NCBI to find potential SNPs affecting the active site of AT2R, as this domain is still unexplored. Structures of these polymorphic forms were modeled, and in silico drug interaction studies with C21 and EMA401 were carried out. The two mutants (rs868939201 and rs1042852794) that significantly affect the binding affinity as that of the wild type were subjected to molecular dynamics simulations. Our analysis of native and mutant AT2R and their complexes with C21 and EMA401 indicated that the occurrence of these mutations affects the conformation of the protein and has affected the binding of these ligand molecules. The study’s findings will aid in the development of better, more versatile medications in the near future, and also in vitro and in vivo studies might be planned in accordance with recent findings. Communicated by Ramaswamy H. Sarma

Development of a new SNP panel for bowhead whales (Balaena mysticetus)

Population genetic research is a critical tool for the conservation and management of marine mammals and other species. The bowhead whale (Balaena mysticetus) is subject to aboriginal subsistence hunting in Alaska, Canada, Chukotka, and Greenland and managed by the International Whaling Commission for all those countries except Canada. Genetic studies support conservation management plans and the determination of safe hunting quotas by providing information on levels of genetic diversity, estimates of abundance and effective population size, and stock separation. Because bowhead populations are monitored in several countries, including genetic monitoring, there is a need for methods that can be consistently used in multiple labs that provide comparable data that can be publicly shared and built upon by successive studies. Here we present a new panel of single nucleotide polymorphisms (SNPs), derived from multiple bowhead populations, that meet those criteria. We describe the use of the Fluidigm SNPtype assay for analyzing 69 autosomal, 6 X-chromosome, and 1 Y-chromosome SNPs. Results indicate that the methods herein are reliable and have low error rates. Because SNPs are discrete sequence-based genetic markers, the panel of loci described here can be replicated, used in different labs, and are directly comparable, making SNPs more useful than existing microsatellite markers.

Genetic investigation of 124 SNPs in a Myanmar population using the Precision ID Identity Panel and the Illumina MiSeq

Single nucleotide polymorphisms (SNPs) have become popular in forensic genetics as an alternative to short tandem repeats (STRs). The Precision ID Identity Panel (Thermo Fisher Scientific), consisting of 90 autosomal SNPs and 34 Y-chromosomal SNPs, enabled human identification studies on global populations through next-generation sequencing (NGS). However, most previous studies on the panel have used the Ion Torrent platform, and there are few reports on the Southeast Asian population. Here, a total of 96 unrelated males from Myanmar (Yangon) were analyzed with the Precision ID Identity Panel on a MiSeq (Illumina) using an in-house TruSeq compatible universal adapter and a custom variant caller, Visual SNP. The sequencing performance evaluated by locus balance and heterozygote balance was comparable to that of the Ion Torrent platform. For 90 autosomal SNPs, the combined match probability (CMP) was 6.994 × 10−34, lower than that of 22 PowerPlex Fusion autosomal STRs (3.130 × 10−26). For 34 Y-SNPs, 14 Y-haplogroups (mostly O2 and O1b) were observed. We found 51 cryptic variations (42 haplotypes) around target SNPs, of which haplotypes corresponding to 33 autosomal SNPs decreased CMP. Interpopulation analysis revealed that the Myanmar population is genetically closer to the East and Southeast Asian populations. In conclusion, the Precision ID Identity Panel can be successfully analyzed on the Illumina MiSeq and provides high discrimination power for human identification in the Myanmar population. This study broadened the accessibility of the NGS-based SNP panel by expanding the available NGS platforms and adopting a robust NGS data analysis tool.

Transcriptome-Assisted SNP Marker Discovery for Phytophthora infestans Resistance in Solanum lycopersicum L.

Late blight, caused by oomycetes Phytophthora infestans is one of the most challenging fungal diseases to manage in tomato plants (Solanum lycopersicum L.). Toward managing the disease, conventional breeding has successfully introgressed genetic loci conferring disease resistance from various wild relatives of tomato into commercial varieties. The cataloging of disease-associated SNP markers and a deeper understanding of disease-resistance mechanisms are needed to keep up with the demand for commercial varieties resistant against emerging pathogen strains. To this end, we performed transcriptome sequencing to evaluate the gene expression dynamics of tomato varieties, resistant and susceptible to Phytophthora infection. Further integrating the transcriptome dataset with large-scale public genomic data of varieties with known disease phenotypes, a panel of single nucleotide polymorphism (SNP) markers correlated with disease resistance was identified. These SNPs were then validated on 31 lines with contrasting phenotypes for late blight. The identified SNPs are located on genes coding for a putative cysteine-rich transmembrane module (CYSTM), Solyc09g098310, and a nucleotide-binding site-leucine-rich repeat protein, Solyc09g098100, close to the well-studied Ph-3 resistance locus known to have a role in plant immunity against fungal infections. The panel of SNPs generated by this study using transcriptome sequencing showing correlation with disease resistance across a broad set of plant material can be used as markers for molecular screening in tomato breeding.

Genomic prediction of survival against Vibrio harveyi in leopard coral grouper (Plectropomus leopardus) using GBLUP, weighted GBLUP, and BayesCπ

Leopard coral grouper (Plectropomus leopardus) is a marine economic fish that widely inhabits the western Pacific. In recent years, the quantity of wild-captured leopard coral grouper has had difficulty meeting commercial and recreational needs. Therefore, it is necessary to develop the artificial culture of leopard coral grouper. However, disease outbreaks caused by Vibrio harveyi have hindered the sustainable development of the leopard coral grouper farming industry. The primary purposes of this study are to 1) estimate the genomic heritability of survival against V. harveyi in P. leopardus; 2) perform a genome-wide association study (GWAS) to determine the genetic architecture; and 3) compare the predictive accuracy variation of genomic methods using different density single nucleotide polymorphism (SNP) panels and cross-validation grouping strategies. We collected 800 leopard coral groupers from two commercial aquatic companies and challenged them using V. harveyi by abdominal injection to obtain the survival phenotypes. After resequencing and quality control, a total of 798 fish and 1,211,259 high-quality SNPs were retained for downstream analysis. The genomic heritability (underlying scale) of survival against V. harveyi in leopard coral grouper ranged from 0.16 to 0.24. Eight trait-related regions with genetic variance explained >1% were identified from the GWAS results, and thirty genes were annotated from these regions. The accuracies of three genomic methods, genomic BLUP (GBLUP), weighted GBLUP (wGBLUP), and BayesCπ, showed ascending trends with the number of SNPs varied from 2 k to 100 k and reach a plateau when 30 k or more SNPs were used for prediction. In addition, there was no obvious difference in predictive accuracy between the three methods when 30 k SNPs were used for prediction. In conclusion, survival against V. harveyi in leopard coral grouper belongs to a low-to-moderate-heritability trait and has a polygenic genetic architecture. Although it is feasible to apply genomic methods using the reference group constructed from nonfamily materials, a full investigation of the relationship between candidates and the reference group is necessary in leopard coral grouper commercial breeding programs, which would help maximize the predictive accuracy.

Differentiation of the domestic pig and wild boar using genotyping-by-sequencing

Domestic pigs and wild boars have undergone frequent interspecies crossbreeding; therefore, the presence of hybrids makes it challenging to find genetic markers that distinguish both subspecies. The aim of this research is to identify the DNA regions that underwent strong selection during the domestication of the pig and to give an insight into the genetic diversity of the Polish wild boar and domestic pigs by implementing the genotyping-by-sequencing (GBS) technique. We studied two groups of animals: one consisted of domestic pigs (Landrace, Large White, Duroc, Puławska and Pietrain), while the second group included wild boars from Poland. The filtered single nucleotide polymorphisms (SNP) panel used in this study included 7,298 markers that were spread across 18 porcine autosomes and unmapped contigs. The maximum-likelihood phylogenetic trees and multidimensional scaling (MDS) clearly separated the populations of pigs from the wild boars. We also detected genome regions that demonstrated the most significant genetic differences between the domestic pigs and wild boars. These regions were distributed on eight different autosomes and overlapped with 48 different pig RefSeq genes. The KEGG pathway, Reactome and GO terms were further used to assign a functional significance to the identified genes that were associated with inter alia muscle development (MYOG, MEOX2), pre-weaning mortality stress (MYO7A) and sensory perception (TAS1R3).

Multiple founding paternal lineages inferred from the newly-developed 639-plex Y-SNP panel suggested the complex admixture and migration history of Chinese people

BackgroundNon-recombining regions of the Y-chromosome recorded the evolutionary traces of male human populations and are inherited haplotype-dependently and male-specifically. Recent whole Y-chromosome sequencing studies have identified previously unrecognized population divergence, expansion and admixture processes, which promotes a better understanding and application of the observed patterns of Y-chromosome genetic diversity.ResultsHere, we developed one highest-resolution Y-chromosome single nucleotide polymorphism (Y-SNP) panel targeted for uniparental genealogy reconstruction and paternal biogeographical ancestry inference, which included 639 phylogenetically informative SNPs. We genotyped these loci in 1033 Chinese male individuals from 33 ethnolinguistically diverse populations and identified 256 terminal Y-chromosomal lineages with frequency ranging from 0.0010 (singleton) to 0.0687. We identified six dominant common founding lineages associated with different ethnolinguistic backgrounds, which included O2a2b1a1a1a1a1a1a1-M6539, O2a1b1a1a1a1a1a1-F17, O2a2b1a1a1a1a1b1a1b-MF15397, O2a2b2a1b1-A16609, O1b1a1a1a1b2a1a1-F2517, and O2a2b1a1a1a1a1a1-F155. The AMOVA and nucleotide diversity estimates revealed considerable differences and high genetic diversity among ethnolinguistically different populations. We constructed one representative phylogenetic tree among 33 studied populations based on the haplogroup frequency spectrum and sequence variations. Clustering patterns in principal component analysis and multidimensional scaling results showed a genetic differentiation between Tai-Kadai-speaking Li, Mongolic-speaking Mongolian, and other Sinitic-speaking Han Chinese populations. Phylogenetic topology inferred from the BEAST and Network relationships reconstructed from the popART further showed the founding lineages from culturally/linguistically diverse populations, such as C2a/C2b was dominant in Mongolian people and O1a/O1b was dominant in island Li people. We also identified many lineages shared by more than two ethnolinguistically different populations with a high proportion, suggesting their extensive admixture and migration history.ConclusionsOur findings indicated that our developed high-resolution Y-SNP panel included major dominant Y-lineages of Chinese populations from different ethnic groups and geographical regions, which can be used as the primary and powerful tool for forensic practice. We should emphasize the necessity and importance of whole sequencing of more ethnolinguistically different populations, which can help identify more unrecognized population-specific variations for the promotion of Y-chromosome-based forensic applications.

Design and validation of a high-density single nucleotide polymorphism array for the Eastern oyster (Crassostrea virginica).

Dense single nucleotide polymorphism (SNP) arrays are essential tools for rapid high-throughput genotyping for many genetic analyses, including genomic selection and high-resolution population genomic assessments. We present a high-density (200 K) SNP array developed for the Eastern oyster (Crassostrea virginica), which is a species of significant aquaculture production and restoration efforts throughout its native range. SNP discovery was performed using low-coverage whole-genome sequencing of 435 F1 oysters from families from 11 founder populations in New Brunswick, Canada. An Affymetrix Axiom Custom array was created with 219,447 SNPs meeting stringent selection criteria and validated by genotyping more than 4,000 oysters across 2 generations. In total, 144,570 SNPs had a call rate >90%, most of which (96%) were polymorphic and were distributed across the Eastern oyster reference genome, with similar levels of genetic diversity observed in both generations. Linkage disequilibrium was low (maximum r2 ∼0.32) and decayed moderately with increasing distance between SNP pairs. Taking advantage of our intergenerational data set, we quantified Mendelian inheritance errors to validate SNP selection. Although most of SNPs exhibited low Mendelian inheritance error rates overall, with 72% of called SNPs having an error rate of <1%, many loci had elevated Mendelian inheritance error rates, potentially indicating the presence of null alleles. This SNP panel provides a necessary tool to enable routine application of genomic approaches, including genomic selection, in C. virginica selective breeding programs. As demand for production increases, this resource will be essential for accelerating production and sustaining the Canadian oyster aquaculture industry.

SNP panel for evaluation of genetic variability and relationship in roe deer (Capreolus capreolus).

Blood samples from forty-six roe deer ( Capreolus capreolus) acquired during officially approved hunting in six hunting divisions throughout Poland were used to isolate the genomic DNA. All individuals were genotyped by MD_Bovine BeadChip (Illumina) for 46.750 Single Nucleotide Polymorphism (SNP) markers. SNPs of inappropriate clusters, with a marker call rate lower than 90% and with a minor allele frequency (MAF) lower than 0.01, located on sex chromosomes and mitochondrial DNA, were removed. Altogether, 21.033 SNP markers were included for further analysis. Observed and expected heterozygosity amounted to 0.098 and 0.119, respectively. Among 21.033 markers, a panel of 148 SNPs were selected for relationship analysis. They were unlinked and had a MAF higher than 0.2. This set of SNPs showed a probability of parentage exclusion of 1.29x10 -6 and 2.37x10 -19 for one, and two known parents, respectively. The probability of identity was estimated at 1.8x10 -40. The probabilities obtained in this study are sufficient for the monitoring and effective management of the genetic diversity of roe deer in Poland and is a cost-effective complementary tool for forensic applications.

Development and evaluations of the ancestry informative markers of the VISAGE Enhanced Tool for Appearance and Ancestry

The VISAGE Enhanced Tool for Appearance and Ancestry (ET) has been designed to combine markers for the prediction of bio-geographical ancestry plus a range of externally visible characteristics into a single massively parallel sequencing (MPS) assay. We describe the development of the ancestry panel markers used in ET, and the enhanced analyses they provide compared to previous MPS-based forensic ancestry assays. As well as established autosomal single nucleotide polymorphisms (SNPs) that differentiate sub-Saharan African, European, East Asian, South Asian, Native American, and Oceanian populations, ET includes autosomal SNPs able to efficiently differentiate populations from Middle East regions. The ability of the ET autosomal ancestry SNPs to distinguish Middle East populations from other continentally defined population groups is such that characteristic patterns for this region can be discerned in genetic cluster analysis using STRUCTURE. Joint cluster membership estimates showing individual co-ancestry that signals North African or East African origins were detected, or cluster patterns were seen that indicate origins from central and Eastern regions of the Middle East. In addition to an augmented panel of autosomal SNPs, ET includes panels of 85 Y-SNPs, 16 X-SNPs and 21 autosomal Microhaplotypes. The Y- and X-SNPs provide a distinct method for obtaining extra detail about co-ancestry patterns identified in males with admixed backgrounds. This study used the 1000 Genomes admixed African and admixed American sample sets to fully explore these enhancements to the analysis of individual co-ancestry. Samples from urban and rural Brazil with contrasting distributions of African, European, and Native American co-ancestry were also studied to gauge the efficiency of combining Y- and X-SNP data for this purpose. The small panel of Microhaplotypes incorporated in ET were selected because they showed the highest levels of haplotype diversity amongst the seven population groups we sought to differentiate. Microhaplotype data was not formally combined with single-site SNP genotypes to analyse ancestry. However, the haplotype sequence reads obtained with ET from these loci creates an effective system for de-convoluting two-contributor mixed DNA. We made simple mixture experiments to demonstrate that when the contributors have different ancestries and the mixture ratios are imbalanced (i.e., not 1:1 mixtures) the ET Microhaplotype panel is an informative system to infer ancestry when this differs between the contributors.

Genome wide association study of thyroid hormone levels following challenge with porcine reproductive and respiratory syndrome virus.

Introduction: Porcine reproductive and respiratory syndrome virus (PRRSV) causes respiratory disease in piglets and reproductive disease in sows. Piglet and fetal serum thyroid hormone (i.e., T3 and T4) levels decrease rapidly in response to Porcine reproductive and respiratory syndrome virus infection. However, the genetic control of T3 and T4 levels during infection is not completely understood. Our objective was to estimate genetic parameters and identify quantitative trait loci (QTL) for absolute T3 and/or T4 levels of piglets and fetuses challenged with Porcine reproductive and respiratory syndrome virus. Methods: Sera from 5-week-old pigs (N = 1792) at 11 days post inoculation (DPI) with Porcine reproductive and respiratory syndrome virus were assayed for T3 levels (piglet_T3). Sera from fetuses (N = 1,267) at 12 or 21days post maternal inoculation (DPMI) with Porcine reproductive and respiratory syndrome virus of sows (N = 145) in late gestation were assayed for T3 (fetal_T3) and T4 (fetal_T4) levels. Animals were genotyped using 60K Illumina or 650K Affymetrix single nucleotide polymorphism (SNP) panels. Heritabilities, phenotypic correlations, and genetic correlations were estimated using ASREML; genome wide association studies were performed for each trait separately using Julia for Whole-genome Analysis Software (JWAS). Results: All three traits were low to moderately heritable (10%-16%). Phenotypic and genetic correlations of piglet_T3 levels with weight gain (0-42 DPI) were 0.26 ± 0.03 and 0.67 ± 0.14, respectively. Nine significant quantitative trait loci were identified for piglet_T3, on Sus scrofa chromosomes (SSC) 3, 4, 5, 6, 7, 14, 15, and 17, and collectively explaining 30% of the genetic variation (GV), with the largest quantitative trait loci identified on SSC5, explaining 15% of the genetic variation. Three significant quantitative trait loci were identified for fetal_T3 on SSC1 and SSC4, which collectively explained 10% of the genetic variation. Five significant quantitative trait loci were identified for fetal_T4 on SSC1, 6, 10, 13, and 15, which collectively explained 14% of the genetic variation. Several putative immune-related candidate genes were identified, including CD247, IRF8, and MAPK8. Discussion: Thyroid hormone levels following Porcine reproductive and respiratory syndrome virus infection were heritable and had positive genetic correlations with growth rate. Multiple quantitative trait loci with moderate effects were identified for T3 and T4 levels during challenge with Porcine reproductive and respiratory syndrome virus and candidate genes were identified, including several immune-related genes. These results advance our understanding of growth effects of both piglet and fetal response to Porcine reproductive and respiratory syndrome virus infection, revealing factors associated with genomic control of host resilience.

Haplotype analysis of genomic prediction by incorporating genomic pathway information based on high-density SNP marker in Chinese yellow-feathered chicken

Genomic selection using single nucleotide polymorphism (SNP) markers is now intensively investigated in breeding and has been widely utilized for genetic improvement. Currently, several studies have used haplotype (consisting of multiallelic SNPs) for genomic prediction and revealed its performance advantage. In this study, we comprehensively evaluated the performance of haplotype models for genomic prediction in 15 traits, including 6 growth, 5 carcass, and 4 feeding traits in a Chinese yellow-feathered chicken population. We adopted 3 methods to define haplotypes from high-density SNP panels, and our strategy included combining Kyoto Encyclopedia of Genes and Genomes pathway information and considering linkage disequilibrium (LD) information. Our results showed an increase in prediction accuracy due to haplotypes ranging from -0.04∼27.16% in all traits, where the significant improvements were found in 12 traits. The estimates of haplotype epistasis heritability were strongly correlated with the accuracy increase by haplotype models. In addition, incorporating genomic annotation information could further increase the accuracy of the haplotype model, where the further increase in accuracy is significantly relative to the increase of relative haplotype epistasis heritability. The genomic prediction using LD information for constructing haplotypes has the best prediction performance among the 4 traits. These results uncovered that haplotype methods were beneficial for genomic prediction, and the accuracy could be further increased by incorporating genomic annotation information. Moreover, using LD information would potentially improve the performance of genomic prediction.

Development of a diagnostic single nucleotide polymorphism (SNP) panel for identifying geographic origins of Cochliomyia hominivorax, the New World screwworm

The New World screwworm, Cochliomyia hominivorax, causes myiasis in livestock, humans, and other warm-blooded animals in much of South America and the Caribbean. It has been eradicated from North and Central America using the sterile insect technique and a biological barrier is currently maintained at the Panama - Colombian border. However, C. hominivorax is still a threat to eradicated areas as outbreaks can and do occur. In order to identify the origin of a fly involved in an outbreak scenario, diagnostic tools would be beneficial. Recently, the geographic population structure of this species was identified using single nucleotide polymorphisms (SNPs). Here we characterize the three major regional clusters: South America, the Inner Caribbean, and the Outer Caribbean. The objective of this study was to develop a SNP (single nucleotide polymorphism) panel to distinguish between these three clusters. A panel was developed using two unique SNPs per region for a total of six SNPs. This diagnostic SNP assay will allow for rapid source determination of flies from future incursions in order to intercept introductory pathways and aid in the control of New World screwworm.

From Wisent to the Lab and Back Again—A Complex SNP Set for Population Management as an Effective Tool in European Bison Conservation

Proper management and genetic monitoring of the modern European bison (Bison bonasus) population is one of the most important responsibilities for this species’ conservation. Up-to-date, complex genetic analysis performed using a consistent molecular method is needed for population management as a tool to further validate and maintain the genetic diversity of the species. The identification of the genetic line when pedigree data are missing, as well as the identification of parentage and individuals, are crucial for this purpose. The aim of our research was to create a small but informative panel of SNP (single-nucleotide polymorphism) markers that can be used for routine genotyping of the European bison at low cost. In our study, we used a custom-designed microarray to genotype a large number of European bison, totaling 455 samples from two genetic lines. The results of this analysis allowed us to select highly informative markers. In this paper, we present an effective single nucleotide polymorphism set, divided into separate panels to perform genetic analyses of European bison, which is needed for population monitoring and management. We proposed a total of 20 SNPs to detect hybridization with Bos taurus and Bison bison, a panel of 50 SNPs for individuals and parentage identification, as well as a panel of 30 SNPs for assessing membership of the genetic line. These panels can be used together or independently depending on the research goal and can be applied using various methods.

Design of a low-density SNP panel for intramuscular fat content and fatty acid composition of backfat in free-range Iberian pigs.

Intramuscular fat (IMF) content and fatty acids (FA) profile determine important sensory and technological characteristics of the meat, being interesting traits to be included in breeding programs for Iberian pig. In a previous study, we analyzed the longissimus dorsi transcriptome of Iberian pigs with divergent breeding values for IMF identifying 63 and 12 functional candidate genes and long non-coding RNA being differentially expressed. The first objective of this work was to use the RNA-seq data generated in that study in order to design a low-density panel with 50 single-nucleotide polymorphisms (SNP). The second aim was to evaluate the effects of this SNP panel on IMF content and backfat FA profile in a closed commercial population of Iberian pigs. The IMF content and backfat FA composition were determined in 940 Iberian pigs. A total of 837 SNPs were identified in the selection of genes and lncRNA. Out of the 50 selected SNP, 11 were monomorphic in the population and 2 failed in their genotyping. Association analyses were carried out for the 37 SNP segregating in the population (minor allele frequency, MAF > 0.05). Regarding IMF content, a significant additive effect (q-value < 0.05) was observed for ADIPOQ:g.124646194T > G SNP, in which the G allele was linked to an increase of 7.59% (additive effect expressed as a percentage of the mean of the trait). For the backfat FA composition, we observed 24 SNP with significant associations. The strongest effects were detected for the ELOVL6:g.112186423A > G and FASN_rs331694510G > A SNP. The A allele of both SNPs were associated to a lower percentage of palmitic (C16:0) and palmitoleic (C16:1) acids and an increase in oleic acid (C18:1). In addition, the AMPD3:g.49043886C > G SNP had significant effects on C16:0, stearic (C18:0), C18:1 and on the sum of saturated and monounsaturated fatty acids. Finally, significant effects of the EGR2:66286345G > T SNP on C18:0 and C18:1 and other minor FA were observed. Our findings reveal ADIPOQ:g.124646194T > G, ELOVL6:g.112186423A > G, and FASN_rs331694510G > A may be useful in breeding programs for Iberian pigs including FA profile and IMF content as selection goals, provided that their potential effects on other traits of interest are controlled.

The use of a genomic relationship matrix for breed assignment of cattle breeds: comparison and combination with a machine learning method.

To develop a breed assignment model, three main steps are generally followed: 1) The selection of breed informative single nucleotide polymorphism (SNP); 2) The training of a model, based on a reference population, that allows to classify animals to their breed of origin; and 3) The validation of the developed model on external animals i.e., that were not used in previous steps. However, there is no consensus in the literature about which methodology to follow for the first step, nor about the number of SNP to be selected. This can raise many questions when developing the model and lead to the use of sophisticated methodologies for selecting SNP (e.g., with iterative algorithms, partitions of SNP, or combination of several methods). Therefore, it may be of interest to avoid the first step by the use of all the available SNP. For this purpose, we propose the use of a genomic relationship matrix (GRM), combined or not with a machine learning method, for breed assignment. We compared it with a previously developed model based on selected informative SNP. Four methodologies were investigated: 1) The PLS_NSC methodology: selection of SNP based on a partial least square-discriminant analysis (PLS-DA) and breed assignment by classification based on the nearest shrunken centroids (NSC) method; 2) Breed assignment based on the highest mean relatedness of an animal to the reference populations of each breed (referred to mean_GRM); 3) Breed assignment based on the highest SD of the relatedness of an animal to the reference populations of each breed (referred to SD_GRM) and 4) The GRM_SVM methodology: the use of means and SD of the relatedness defined in mean_GRM and SD_GRM methodologies combined with the linear support vector machine (SVM), a machine learning method used for classification. Regarding mean global accuracies, results showed that the use of mean_GRM or GRM_SVM was not significantly different (Bonferroni corrected P > 0.0083) than the model based on a reduced SNP panel (PLS_NSC). Moreover, the mean_GRM and GRM_SVM methodology were more efficient than PLS_NSC as it was faster to compute. Therefore, it is possible to bypass the selection of SNP and, by the use of a GRM, to develop an efficient breed assignment model. In routine, we recommend the use of GRM_SVM over mean_GRM as it gave a slightly increased global accuracy, which can help endangered breeds to be maintained. The script to execute the different methodologies can be accessed on: https://github.com/hwilmot675/Breed_assignment.

Genomic selection for survival under naturally occurring Saprolegnia oomycete infection in farmed European whitefish Coregonus lavaretus.

Saprolegnia oomycete infection causes serious economic losses and reduces fish health in aquaculture. Genomic selection based on thousands of DNA markers is a powerful tool to improve fish traits in selective breeding programs. Our goal was to develop a single nucleotide polymorphism (SNP) marker panel and to test its use in genomic selection for improved survival against Saprolegnia infection in European whitefish Coregonus lavaretus, the second most important farmed fish species in Finland. We used a double digest restriction site associated DNA (ddRAD) genotyping by sequencing method to produce a SNP panel, and we tested it analyzing data from a cohort of 1,335 fish, which were measured at different times for mortality to Saprolegnia oomycete infection and weight traits. We calculated the genetic relationship matrix (GRM) from the genome-wide genetic data, integrating it in multivariate mixed models used for the estimation of variance components and genomic breeding values (GEBVs), and to carry out Genome-Wide Association Studies for the presence of quantitative trait loci (QTL) affecting the phenotypes in analysis. We identified one major QTL on chromosome 6 affecting mortality to Saprolegnia infection, explaining 7.7% to 51.3% of genetic variance, and a QTL for weight on chromosome 4, explaining 1.8% to 5.4% of genetic variance. Heritability for mortality was 0.20 to 0.43 on the liability scale, and heritability for weight was 0.44 to 0.53. The QTL for mortality showed an additive allelic effect. We tested whether integrating the QTL for mortality as a fixed factor, together with a new GRM calculated excluding the QTL from the genetic data, would improve the accuracy estimation of GEBVs. This test was done through a cross-validation approach, which indicated that the inclusion of the QTL increased the mean accuracy of the GEBVs by 0.28 points, from 0.33 to 0.61, relative to the use of full GRM only. The area under the curve of the receiver-operator curve for mortality increased from 0.58 to 0.67 when the QTL was included in the model. The inclusion of the QTL as a fixed effect in the model increased the correlation between the GEBVs of early mortality with the late mortality, compared to a model that did not include the QTL. These results validate the usability of the produced SNP panel for genomic selection in European whitefish and highlight the opportunity for modeling QTLs in genomic evaluation of mortality due to Saprolegnia infection.

Evaluation of parentage testing using single nucleotide polymorphism markers for draft horses in Japan.

We evaluated the utility of single nucleotide polymorphism (SNP) markers for parentage testing in Breton (BR) and Percheron (PR) horses in Japan using the proposed International Society for Animal Genetics (P-ISAG) 147 SNP panel and 414 autosomal SNPs. Genomic DNA was extracted from 98 horses of two breeds, BR (n = 47) and PR (n = 51), and sequenced using next-generation sequencing. The average minor allele frequencies for the P-ISAG panel for BR and PR were 0.306 and 0.301, respectively. The combined probabilities of exclusion (PEs) given two parents and one offspring: exclude a relationship (PE01) and given one parent and one offspring: exclude their relationship (PE02) were over 0.9999 for both breeds. Using the P-ISAG panel, no exclusion or doubtful cases were identified in 35 valid parent-offspring pairs, suggesting that the P-ISAG panel is helpful for parentage verification in both breeds. In contrast, as 0.18% of falsely accepted parentages were observed in the parentage discovery cases, additional markers such as the combination of the P-ISAG panel and 414 autosomal SNPs (561-SNP set) presented here should be used to identify valid parent-offspring pairs of horses with unknown parentage relationships.

GWAS on Imputed Whole-Genome Sequence Variants Reveal Genes Associated with Resistance to Piscirickettsia salmonis in Rainbow Trout (Oncorhynchus mykiss).

Genome-wide association studies (GWAS) allow the identification of associations between genetic variants and important phenotypes in domestic animals, including disease-resistance traits. Whole Genome Sequencing (WGS) data can help increase the resolution and statistical power of association mapping. Here, we conduced GWAS to asses he facultative intracellular bacterium Piscirickettsia salmonis, which affects farmed rainbow trout, Oncorhynchus mykiss, in Chile using imputed genotypes at the sequence level and searched for candidate genes located in genomic regions associated with the trait. A total of 2130 rainbow trout were intraperitoneally challenged with P. salmonis under controlled conditions and genotyped using a 57K single nucleotide polymorphism (SNP) panel. Genotype imputation was performed in all the genotyped animals using WGS data from 102 individuals. A total of 488,979 imputed WGS variants were available in the 2130 individuals after quality control. GWAS revealed genome-wide significant quantitative trait loci (QTL) in Omy02, Omy03, Omy25, Omy26 and Omy27 for time to death and in Omy26 for binary survival. Twenty-four (24) candidate genes associated with P. salmonis resistance were identified, which were mainly related to phagocytosis, innate immune response, inflammation, oxidative response, lipid metabolism and apoptotic process. Our results provide further knowledge on the genetic variants and genes associated with resistance to intracellular bacterial infection in rainbow trout.