Single Nucleotide Polymorphism Panel Research Articles

Identification of novel SNP markers for kinship analysis in the Korean population

Kinship testing using genetic markers such as short tandem repeats (STRs) and single nucleotide polymorphisms (SNPs) is crucial for forensic analysis. Although STR markers have superior discriminatory power due to their highly polymorphic properties, they have several weak points in determining extended distant or complex relationships because of high mutation rates and low success rates in degraded samples. Therefore, SNPs are regarded as promising tools in forensic science because they have low mutation rates and small amplicon sizes. Herein, we propose an SNP panel consisting of 1400 autosomal SNPs obtained from the Korean National Standard Reference Variome (KoVariome) database. To evaluate its performance, in-silico analysis was performed using whole-genome sequencing (WGS) data from 21 Korean families. Subsequently, to estimate pairwise relatedness, kinship coefficients were calculated using PLINK, and Welch’s one-way ANOVA test with Games–Howell’s pairwise comparison test was performed. As a result, the average kinship coefficients of first- (parent–offspring and full siblings), second- (grandparent–grandchildren and aunt/uncle–niece/nephew), and third- (first cousin and grandniece/grandnephew) degree relatives, and unrelated were 0.24, 0.11, − 0.054, and − 0.0082, respectively. Consequently, relatives (first and second degree) were distinguished from non-relatives; however, further studies are required to investigate more effective SNP markers for discriminating extended kinship. Nevertheless, the results of this study go beyond the scope of screening using the discovered 1400 SNPs in Korean families and suggest the applicability of kinship analysis in the Korean population.

Classification of cattle breeds based on the random forest approach

The determination of breed composition or the population of origin has several practical applications, including the authentication of brand mono-breed products that have recently been developed in several livestock species, including cattle. Therefore, the aim of the present study was to verify the applicability of a random forest (RF) approach to distinguish between different dairy and beef cattle breeds based on a reduced panel of single nucleotide polymorphisms (SNPs). A total of 1,370 animals from 17 cattle breeds were genotyped with a 50 K SNP microarray. After SNP pruning, 5,296 SNPs were retained for further analysis. Six methods were used for determining panels of the most informative SNPs: Wright's fixation index (FST), principal component analysis (PCA), random forest (RF) based on the Gini index (GI; two variants) and RF based on the mean decrease in accuracy (MDA; two variants). There was a similar distribution of selected SNPs per BTA, especially for the FST and PCA methods. Two panels of 96 SNPs obtained with two variants of RF-GI and RF-MDA contained the same SNPs but with a different ranking. The percentage of correct classification on the test set (10% of cases randomly selected from the whole dataset) was 100% for the Angus, Hereford, Holstein, Brown Swiss, and Jersey breeds. For the Simmental, Piedmontese, Romagnola, Shorthorn, Norwegian Red, Charolais, Cika, Tyrol Grey, Limousin, Austrian Pinzgau, Slovak Pinzgau, and Slovak Spotted breeds, it was 75.00 – 87.50%, 0.00 – 66.67%, 66.67 – 100.00%, 80.00 – 100.00%, 0.00 – 50.00%, 75.00 – 100.00%, 0.00 – 66.67%, 90.91 - 100.00%, 91.67%, 81.82 - 100.00%, 93.33 - 100.00%, 55.56 - 100.00%, respectively. The overall correct classification rate (for all breeds together) was 87.14%, 94.29%, 90.00% and 88.57% for RF-GI, RF-MDA, FST and PCA, respectively. Consequently, the most accurate method for distinguishing between cattle breeds was RF based on the MDA, although the differences amongst models were not large.

An unbiased kinship estimation method for genetic data analysis

Accurate estimate of relatedness is important for genetic data analyses, such as heritability estimation and association mapping based on data collected from genome-wide association studies. Inaccurate relatedness estimates may lead to biased heritability estimations and spurious associations. Individual-level genotype data are often used to estimate kinship coefficient between individuals. The commonly used sample correlation-based genomic relationship matrix (scGRM) method estimates kinship coefficient by calculating the average sample correlation coefficient among all single nucleotide polymorphisms (SNPs), where the observed allele frequencies are used to calculate both the expectations and variances of genotypes. Although this method is widely used, a substantial proportion of estimated kinship coefficients are negative, which are difficult to interpret. In this paper, through mathematical derivation, we show that there indeed exists bias in the estimated kinship coefficient using the scGRM method when the observed allele frequencies are regarded as true frequencies. This leads to negative bias for the average estimate of kinship among all individuals, which explains the estimated negative kinship coefficients. Based on this observation, we propose an unbiased estimation method, UKin, which can reduce kinship estimation bias. We justify our improved method with rigorous mathematical proof. We have conducted simulations as well as two real data analyses to compare UKin with scGRM and three other kinship estimating methods: rGRM, tsGRM, and KING. Our results demonstrate that both bias and root mean square error in kinship coefficient estimation could be reduced by using UKin. We further investigated the performance of UKin, KING, and three GRM-based methods in calculating the SNP-based heritability, and show that UKin can improve estimation accuracy for heritability regardless of the scale of SNP panel.

Screening Discriminating SNPs for Chinese Indigenous Pig Breeds Identification Using a Random Forests Algorithm.

Chinese indigenous pig breeds have unique genetic characteristics and a rich diversity; however, effective breed identification methods have not yet been well established. In this study, a genotype file of 62,822 single-nucleotide polymorphisms (SNPs), which were obtained from 1059 individuals of 18 Chinese indigenous pig breeds and 5 cosmopolitan breeds, were used to screen the discriminating SNPs for pig breed identification. After linkage disequilibrium (LD) pruning filtering, this study excluded 396 SNPs on non-constant chromosomes and retained 20.92~-27.84% of SNPs for each of the 18 autosomes, leaving a total of 14,823 SNPs. The principal component analysis (PCA) showed the largest differences between cosmopolitan and Chinese pig breeds (PC1 = 10.452%), while relatively small differences were found among the 18 indigenous pig breeds from the Yangtze River Delta region of China. Next, a random forest (RF) algorithm was used to filter these SNPs and obtain the optimal number of decision trees (ntree = 1000) using corresponding out-of-bag (OOB) error rates. By comparing two different SNP ranking methods in the RF analysis, the mean decreasing accuracy (MDA) and mean decreasing Gini index (MDG), the effects of panels with different numbers of SNPs on the assignment accuracy, and the statistics of SNP distribution on each chromosome in the panels, a panel of 1000 of the most breed-discriminative tagged SNPs were finally selected based on the MDA screening method. A high accuracy (>99.3%) was obtained by the breed prediction of 318 samples in the RF test set; thus, a machine learning classification method was established for the multi-breed identification of Chinese indigenous pigs based on a low-density panel of SNPs.

A low-density single nucleotide polymorphism panel for brown trout (Salmo trutta L.) suitable for exploring genetic diversity at a range of spatial scales.

The rivers of southern England and northern France which drain into the English Channel contain several genetically unique groups of trout (Salmo trutta L.) that have suffered dramatic declines in numbers over the past 40 years. Knowledge of levels and patterns of genetic diversity is essential for effective management of these vulnerable populations. Using restriction site-associated DNA sequencing (RADseq) data, we describe the development and characterisation of a panel of 95 single nucleotide polymorphism (SNP) loci for trout from this region and investigate their applicability and variability in both target (i.e., southern English) and non-target trout populations from northern Britain and Ireland. In addition, we present three case studies which demonstrate the utility and resolution of these genetic markers at three levels of spatial separation:(a) between closely related populations in nearby rivers, (b) within a catchment and (c) when determining parentage and familial relationships between fish sampled from a single site, using both empirical and simulated data. The SNP loci will be useful for population genetic and assignment studies on brown trout within the UK and beyond.

A novel SNP assay reveals increased genetic variability and abundance following translocations to a remnant Allegheny woodrat population

BackgroundAllegheny woodrats (Neotoma magister) are found in metapopulations distributed throughout the Interior Highlands and Appalachia. Historically these metapopulations persisted as relatively fluid networks, enabling gene flow between subpopulations and recolonization of formerly extirpated regions. However, over the past 45 years, the abundance of Allegheny woodrats has declined throughout the species’ range due to a combination of habitat destruction, declining hard mast availability, and roundworm parasitism. In an effort to initiate genetic rescue of a small, genetically depauperate subpopulation in New Jersey, woodrats were translocated from a genetically robust population in Pennsylvania (PA) in 2015, 2016 and 2017. Herein, we assess the efficacy of these translocations to restore genetic diversity within the recipient population.ResultsWe designed a novel 134 single nucleotide polymorphism panel, which was used to genotype the six woodrats translocated from PA and 82 individuals from the NJ population captured before and after the translocation events. These data indicated that a minimum of two translocated individuals successfully produced at least 13 offspring, who reproduced as well. Further, population-wide observed heterozygosity rose substantially following the first set of translocations, reached levels comparable to that of populations in Indiana and Ohio, and remained elevated over the subsequent years. Abundance also increased during the monitoring period, suggesting Pennsylvania translocations initiated genetic rescue of the New Jersey population.ConclusionsOur results indicate, encouragingly, that very small numbers of translocated individuals can successfully restore the genetic diversity of a threatened population. Our work also highlights the challenges of managing very small populations, such as when translocated individuals have greater reproductive success relative to residents. Finally, we note that ongoing work with Allegheny woodrats may broadly shape our understanding of genetic rescue within metapopulations and across heterogeneous landscapes.

SNP- and haplotype-based single-step genomic predictions for body weight, wool, and reproductive traits in North American Rambouillet sheep.

Rambouillet sheep are commonly raised in extensive grazing systems in the US, mainly for wool and meat production. Genomic evaluations in US sheep breeds, including Rambouillet, are still incipient. Therefore, we aimed to evaluate the feasibility of performing genomic prediction of breeding values for various traits in Rambouillet sheep based on single nucleotide polymorphisms (SNP) or haplotypes (fitted as pseudo-SNP) under a single-step GBLUP approach. A total of 28,834 records for birth weight (BWT), 23,306 for postweaning weight (PWT), 5,832 for yearling weight (YWT), 9,880 for yearling fibre diameter (YFD), 11,872 for yearling greasy fleece weight (YGFW), and 15,984 for number of lambs born (NLB) were used in this study. Seven hundred forty-one individuals were genotyped using a moderate (50 K; n=677) or high (600 K; n=64) density SNP panel, in which 32 K SNP in common between the two SNP panels (after genotypic quality control) were used for further analyses. Single-step genomic predictions using SNP (H-BLUP) or haplotypes (HAP-BLUP) from blocks with different linkage disequilibrium (LD) thresholds (0.15, 0.35, 0.50, 0.65, and 0.80) were evaluated. We also considered different blending parameters when constructing the genomic relationship matrix used to predict the genomic-enhanced estimated breeding values (GEBV), with alpha equal to 0.95 or 0.50. The GEBV were compared to the estimated breeding values (EBV) obtained from traditional pedigree-based evaluations (A-BLUP). The mean theoretical accuracy ranged from 0.499 (A-BLUP for PWT) to 0.795 (HAP-BLUP using haplotypes from blocks with LD threshold of 0.35 and alpha equal to 0.95 for YFD). The prediction accuracies ranged from 0.143 (A-BLUP for PWT) to 0.330 (A-BLUP for YGFW) while the prediction bias ranged from -0.104 (H-BLUP for PWT) to 0.087 (HAP-BLUP using haplotypes from blocks with LD threshold of 0.15 and alpha equal to 0.95 for YGFW). The GEBV dispersion ranged from 0.428 (A-BLUP for PWT) to 1.035 (A-BLUP for YGFW). Similar results were observed for H-BLUP or HAP-BLUP, independently of the LD threshold to create the haplotypes, alpha value, or trait analysed. Using genomic information (fitting individual SNP or haplotypes) provided similar or higher prediction and theoretical accuracies and reduced the dispersion of the GEBV for body weight, wool, and reproductive traits in Rambouillet sheep. However, there were no clear improvements in the prediction bias when compared to pedigree-based predictions. The next step will be to enlarge the training populations for this breed to increase the benefits of genomic predictions.

Bibliometric Analysis of Research on the Main Genes Involved in Meat Tenderness.

Tenderness is one of the main characteristics of meat because it determines its price and acceptability. This is the first bibliometric study on the trend of research on the role of genes in meat tenderness. A total of 175 original and English-language articles published up to 2021 were retrieved from Scopus. The bibliometric analysis was carried out with VOSviewer (version 1.6.18, Eck and Waltman, Leiden, Netherlands) and complemented with the Analyze search results service from Scopus. Erroneous and duplicate data were eliminated, and incomplete information was added to standardize the results. Scientific production was evaluated by means of quantity, quality and structure indicators. As a first glance, 8.816% of authors have published more than 50% of papers mainly related to genes encoding the calpain (CAPN)-calpastatin (CAST) system and single nucleotide polymorphisms (SNPs). Among other findings, a strong link was found between the contribution of the main countries (led by the United States with) and their institutions (led by the USDA Agricultural Research Service with) to their gross domestic product. Most studies on the topic are published in the Journal of Animal Science, and other journals with high impact according to the number of citations and different metrics. Finally, when evaluating the most cited articles, the occurrence and association of the main keywords, it was confirmed that research is focused on the role of CAPN and CAST genes and of SNPs in beef tenderness. The change in science was emphasized; although marker-assisted selection is still used, genes have an infinitesimal effect on complex traits. Therefore, since about 2010, new research groups adopted genomic selection to evaluate dense panels of SNPs and better explain genetic variation in meat tenderness.

PSIII-4 Late-Breaking: Genetic Marker Association Study of Heifer Pregnancy in Red Angus Cattle

Abstract Heifer pregnancy (HPG) is lowly heritable, yet economically relevant in beef cattle production systems. Hence, identifying single nucleotide polymorphisms (SNP) associated with phenotype could increase the amount of information used in the genetic evaluation of the trait. Using RNA-sequence data from lactating Holstein cows, a set of SNP (n = 69) were discovered among embryo mortality conceptuses (Conceptus-SNP) associated with maternal recognition of pregnancy on day 16 after artificial insemination (AI). To further study these SNP, our objective was to conduct analyses to identify markers associated with HPG in Red Angus. Phenotypic records and genotypes were provided by the Red Angus Association of America (RAAA). For phenotypes, a total of 59,387 cattle records, from the June 2022 RAAA genetic evaluation, were used in the analysis. For genotype data, a 47,860 SNP panel (excluding SNP on the X-chromosome) were formed by combining the historical RAAA genotype data (96,162 animals with genotypes) and genotypes from whole genome sequence of 30 prominent Red Angus AI sires. Markers were mapped to the ARS-UCD1.2 bovine reference genome and then imputed to 47,860 SNP panel using findhap software. A subset of SNP (n = 2,169 SNP; Conceptus-SNP and the multi-breed selected reduced panel [MSRP]) were extracted from the imputed genotypes file. Using PLINK software, genotype quality control procedure was performed so that animals with call rate < 0.9 were removed. A marker was removed if: it had minor allele frequency < 0.01, not in Hardy–Weinberg equilibrium (P < 0.00001), or in high linkage disequilibrium (r2 > 0.95). The final genotype file contained 96,667 animals with 2,137 SNP. A Bayes Cπ single-step super hybrid model (π = 0.99), using the BOLT software package, was used to estimate marker’s posterior probability of inclusion (PPI), the marker significance criterion in predicting HPG. A marker’s PPI was calculated as the average probability from four different Gibbs sampling chains of 75,000 iterations that included 5,000 iterations as burn-in. Markers rs42576394 (18:60583784) and rs42942055 (14:34249373) had PPI of 25.5 and 7.1%, respectively; suggesting association with HPG. None of the Conceptus-SNP had a detectable association with HPG; however, these Conceptus-SNP may be much more informative for genotype to phenotype association analyses for the trait of stayability. Such a trait would be measured with lactating mature beef cows and potentially more similar to the lactating Holstein cows from which the markers were discovered.

PSIII-2 Late-Breaking: Collaboration to Demonstrate the Potential Use and Value of Electronic Identification and DNA Testing in the Sheep Industry

Abstract The dearth of individual performance records derived from an extensively driven production system coupled with the impracticality of utilizing reproductive technologies makes commercial genetic improvement challenging in small ruminants. We collaborated with five producers throughout California to assess how electronic ID (EID) and genetic testing could inform ram selection. Our objective was to determine how the data collected from these technologies could augment genetic improvement on commercial ranches. Familiarity and use of EID tags on ranches at the start of the research varied; thus, allowing for a qualitative reflection on the participant's perceptions of the usefulness of this technology. Ear notch samples were collected and EID ear tags were placed in 2,963 sheep; 305 rams, and 2,658 of their potential progeny. We partnered with Superior Farms (Dixon, CA) to genotype the animals using their Flock54 single nucleotide polymorphism panel which contains 956 markers for assigning parentage, and includes markers linked to quantitative trait loci and/or known single gene causative markers to aid in disease management. SNP data was used to assign paternity and determine sire prolificacy. A total of 524 carcass samples from ram lambs from two of the ranches were processed at Superior Farms' plant and assessed with a USDA-approved camera grading system (e+v, Oranienburg, Germany) that matches EID’s to carcass data. Progeny contemporary group deviations were calculated for hot carcass weight, yield grade, and ovine cutability calculation (OCC) which predicts the yield of edible product on the carcass. The average number of lambs per sire born at each ranch and the mean OCC of the progeny for each sire were compared using a one-way analysis of variance. There was a significant ranch effect on the average progeny number per ram (P < 0.05). The ranch with the lowest ram to ewe ratio (1:10) also has the lowest average progeny per ram and the ranch with the greatest ratio (1:50) has the most progeny per ram. There was a large range in the number of lambs per sire (0-135) within each ranch. There was a significant sire effect (P < 0.05) on average OCC within each progeny contemporary group, meaning some sires were producing offspring with significantly more marketable meat. The use of EIDs in combination with genetic testing, allowed for the collection of individual progeny performance data. This provided insight into sire performance and identified prolific sires that were also producing lambs with superior carcass merit. Producers could use this information to select for high-performing rams; however, there is an unavoidable delay between ram turnout and the collection of progeny carcass data. This limits the practical utility of these data and reinforces the value of having estimated breeding values available at ram purchase to select genetically superior rams.

Species-informative SNP markers for characterising freshwater prawns of genus Macrobrachium in Cameroon.

Single Nucleotide Polymorphisms (SNPs) are now popular for a myriad of applications in animal and plant species including, ancestry assignment, conservation genetics, breeding, and traceability of animal products. The objective of this study was to develop a customized cost-effective SNP panel for genetic characterisation of Macrobrachium species in Cameroon. The SNPs identified in a previous characterization study were screened as viable candidates for the reduced panel. Starting from a full set of 1,814 SNPs, a total of 72 core SNPs were chosen using conventional approaches: allele frequency differentials, minor allele frequency profiles, and Wright’s Fst statistics. The discriminatory power of reduced set of informative SNPs were then tested using the admixture analysis, principal component analysis, and discriminant analysis of principal components. The panel of prioritised SNP markers (i.e., N = 72 SNPs) distinguished Macrobrachium species with 100% accuracy. However, large sample size is needed to identify more informative SNPs for discriminating genetically closely related species, including M. macrobrachion versus M. vollenhovenii and M. sollaudii versus M. dux. Overall, the findings in this study show that we can accurately characterise Macrobrachium using a small set of core SNPs which could be useful for this economically important species in Cameroon. Given the results obtained in this study, a larger independent validation sample set will be needed to confirm the discriminative capacity of this SNP panel for wider commercial and research applications.

Replacement of microsatellite markers by imputed medium-density SNP arrays for parentage control in German warmblood horses

In horses, parentage control is currently performed based on an internationally standardized panel of 17 microsatellite (MS) markers comprising 12 mandatory and five optional markers. Unlike MS, single nucleotide polymorphism (SNP) profiles support a wider portfolio of genomic applications, including parentage control. A transition to SNP-based parentage control is favorable, but requires additional efforts for ensuring generation-overlapping availability of marker genotypes of the same type. To avoid double genotyping of either parents or offspring for changing to SNP technology and enable efficient transition, we tested whether MS genotypes used for parentage control could be reliably imputed from a medium-density SNP panel in German warmblood horses. Imputation accuracy was tested in a tenfold cross-validation with two approaches: within breed (option A) and across breeds (option B). Average imputation accuracies of 97.98% (A) and 96.17% (B) were achieved, respectively. Due to interbreed differences in genotyping rates, five MS markers of low genotyping rate (GTR; < 90%) could be imputed with higher accuracy within breed (98.18%) than across breeds (90.73%). MS markers with high GTR performed homogeneously well in option B (98.44%) and showed slightly lower accuracy in option A (97.90%). Among these markers, AHT5 proved to be problematic for imputation regardless of the approach, revealing accuracies of 86.40% (A) and 88.70% (B). Better results for MS markers with high GTR and savings in computational processing justified the choice of option B for routine implementation. To date, more than 9500 horses have undergone the new parentage control based on imputed MS genotypes.

31 Genotype Concordance between SNP Chip and Imputed Low-Pass Whole-Genome Sequence in Beef Cattle

Abstract Genotypes generated from common single nucleotide polymorphisms (SNP) chips have been the sole source of genomic information for current beef cattle genetic evaluations. More recently, the development of low-pass whole-genome sequencing (LPS) followed by imputation to full sequence and variant calls has provided an alternative option to generate genotypes for inclusion into genetic evaluations. The objective of this study was to estimate the genotype concordance between SNP chip and LPS genotypes. Ear samples, via tissue sampling units, were obtained from 226 individuals. A subset of 109 individuals also had blood samples collected. Samples were sent to GeneSeek (Neogen company, Lincoln, NE) for genotyping (100K or 50K) and LPS and imputation was performed by Gencove. A total of 33,451 and 78,032 SNP overlapping between SNP panel and LPS for ear and blood samples, respectively, were used for further analyses. Genotype concordance was performed by counting the number of matching genotypes per SNP between (1) SNP chip vs. LPS in ear and blood samples, and (2) LPS in blood vs. LPS in ear samples. The average concordances between SNP chip vs. LPS in ear and blood samples were 0.97±0.04 and 0.98±0.06, respectively. The average concordance between LPS in blood vs. ear samples was 0.97±0.03. In conclusion, the concordance was high regardless of the tissue type, and, at least in these data, differences in resulting genetic predictions would not be expected between the use of genotypes derived from SNP chips or LPS. Additional work is warranted to determine sensitivity to relationships between target animals and the reference set used for imputation. The USDA is an equal opportunity provider and employer.

PSIV-B-21 Genome-Wide Association Studies for Ketosis in Dairy Cattle

Abstract Lactating dairy cows often experience a negative energy balance (NEB) and must mobilize adipose reserves to adapt to this metabolic stress. Dairy cows that are unable to adapt to this NEB often suffer from metabolic disorders such as ketosis causing significant financial losses due to a reduction in milk production, poor reproductive performance, and an increased risk of developing other disorders. Therefore, the aim of this study was to identify genes and their associated biological pathways to better understand the molecular genetic basis for the development of ketosis. Genome wide association studies analysis was performed using a mixed linear model on 436 Jersey and Holstein cows ranging in ketosis history and genotyped for high density single nucleotide polymorphisms (SNPs) panel. After quality control, 409 with 617,527 SNPs were included in further analyses. The association analysis was performed using a mixed linear model implemented in GCTA software and fitting SNP, breed, and pen as fixed effects with animal as random effect. The top 100 significant SNPs (P &amp;lt; 0.0003) were mapped to 29 genes. Gene enrichment analyses were conducted using DAVID software to determine biological pathways enriched for the identified list of genes. The genomic heritability estimated in this study was 0.17 indicating existence of genetic influence on ketosis in animals in this herd. The analyses revealed candidate genes to be involved in biological pathways involving coronary vascular development, platelet activation and aggregation and osteoclast differentiation. The results indicated a relationship between ketosis development and the immune system or development of other diseases. Further research is needed to validate the identified biological mechanisms underlying the variation between cows for ketosis incidence and progression in dairy cows.

Genetic diversity and population structure of locally adapted Brazilian horse breeds assessed using genome-wide single nucleotide polymorphisms

Animals first introduced in Brazil with the discovery were submitted to various selective pressures over five centuries, developing adaptive traits specific to the hostile environments found in the country. A high quantity of genotypic information can be generated quickly and with high repeatability and reliability using genome-wide Single Nucleotide Polymorphism (SNP) panels. Blood samples from 285 horses belonging to eight Brazilian breeds (Baixadeiro, Lavradeiro, Marajoara, Puruca, Campeiro, Crioulo, Mangalarga Marchador and Pantaneiro) and two commercial breeds sampled in Brazil (Arabian and English Thoroughbred) were genotyped focusing on elucidating the genetic structure and composition within and among Brazilian horse breeds and some of their possible founders. Data from the GGP Equine BeadChip (GeneSeek® Genomic Profiler™ Equine, 65.157 SNPs) was used to assess basic diversity parameters, genetic distance (pairwise FST and Nei), Principal Component Analysis (PCA), Analysis of Molecular Variance (AMOVA) and population structure (ADMIXTURE). Results showed that Crioulo (few animals), Pantaneiro, Mangalarga Marchador, and Campeiro breeds possess distinct genetic bases from the others and each other. The Lavradeiro, Baixadeiro, Puruca, and Marajoara breeds have a shared genetic basis, hindering their differentiation. The results also reflected a geographic division of the Brazilian equine breeds, with those originally from the North and Northeast regions (Lavradeiro, Marajora, Puruca and Baixadeiro) grouped. On the other hand, animals from the South and Southeast regions (Crioulo, Campeiro and Mangalarga Marchador) were genetically closer although distinguished. The Pantaneiro breed originating from Pantanal Matogrossense in the Midwest region of Brazil, separated from all the others. Overall, high values of genetic variability and low values of FIS were observed for the Brazilian naturalized breeds. Both Arabian and English Thoroughbred sampled in Brazil presented a similar genetic variability to the Brazilian breeds but were genetically differentiated. This study aims to understand better the genetic variability and relation among Brazilian naturalized horse breeds and their possible origins. This information helps establish and maintain conservation nuclei and programs for each horse breed. Results found here can be used as a base for backup decisions regarding management to optimize conservation programs and other support sampling strategies for the National Animal Germplasm Program.

Identification of Microsatellite-Based Markers and Breed-Specific Single Nucleotide Polymorphism Panels for Parentage Assignment in Bovines

Identification of Microsatellite-Based Markers and Breed-Specific Single Nucleotide Polymorphism Panels for Parentage Assignment in Bovines

From STRs to SNPs via ddRAD-seq: Geographic assignment of confiscated tortoises at reduced costs.

Assigning individuals to their source populations is crucial for conservation research, especially for endangered species threatened by illegal trade and translocations. Genetic assignment can be achieved with different types of molecular markers, but technical advantages and cost saving are recently promoting the shift from short tandem repeats (STRs) to single nucleotide polymorphisms (SNPs). Here, we designed, developed, and tested a small panel of SNPs for cost‐effective geographic assignment of individuals with unknown origin of the endangered Mediterranean tortoise Testudo hermanni. We started by performing a ddRAD‐seq experiment on 70 wild individuals of T. hermanni from 38 locations. Results obtained using 3182 SNPs are comparable to those previously obtained using STR markers in terms of genetic structure and power to identify the macro‐area of origin. However, our SNPs revealed further insights into the substructure in Western populations, especially in Southern Italy. A small panel of highly informative SNPs was then selected and tested by genotyping 190 individuals using the KASP genotyping chemistry. All the samples from wild populations of known geographic origin were genetically re‐assigned with high accuracy to the original population. This reduced SNPs panel represents an efficient molecular tool that enables individuals to be genotyped at low cost (less than €15 per sample) for geographical assignment and identification of hybrids. This information is crucial for the management in‐situ of confiscated animals and their possible re‐allocation in the wild. Our methodological pipeline can easily be extended to other species.

A New Genotyping‐in‐Thousands‐by‐Sequencing Single Nucleotide Polymorphism Panel for Mixed‐Stock Analysis of Chum Salmon from Coastal Western Alaska

AbstractGenetic stock identification is becoming increasingly important in the management of Chum Salmon Oncorhynchus keta from western Alaska due to frequent run failures in recent times. It has been notoriously difficult to distinguish populations of summer‐run Chum Salmon among four major regions in coastal western Alaska: Norton Sound, lower Yukon River, Kuskokwim River, and Nushagak River. Here we developed and evaluated a panel of single nucleotide polymorphism (SNP) markers designed to coamplify using the genotyping‐in‐thousands by sequencing (GT‐seq) method, which would greatly enhance the efficiency of genotyping samples from baseline populations and from mixed‐stock fisheries or incidental catches. We selected 479 SNPs in 355 amplicons from ~30,000 candidate SNPs for the GT‐seq panel. Evaluations using single‐stock and realistic fishery mixture simulations indicated that the panel was able to satisfactorily distinguish Norton Sound from the other regions to the south but was unable to distinguish among lower Yukon, Kuskokwim, and Nushagak rivers with accuracy &gt;90%. The low degree of population structure among Chum Salmon in this region, described in previous studies and confirmed with tens of thousands of SNPs here, means that genetic stock identification will be inadequate to guide management decisions at the spatial scale desired by stakeholders and fishery managers in the region.

Potato Cultivar Identification in South Africa Using a Custom SNP Panel.

DNA fingerprinting is a molecular technique applied to identify genetic differences between plant cultivars or lines and is used for genetic purity testing. The suitability of single nucleotide polymorphism (SNP) panels for the fingerprinting of tetraploid potato were investigated as a new high throughput, objective, and cost-effective method instead of simple sequence repeats (SSRs) and polyacrylamide gel electrophoresis (PAGE). One-hundred and ninety (190) potato cultivars, including various cultivars currently important in South Africa, were genotyped at 500 SNP positions utilising SeqSNP by LGC Biosearch Technologies. An optimal panel of 25 SNP markers was identified that could discriminate between South African potato cultivars on genetic allele dosage. The genotypes of these SNPs were validated on selected potato genotypes using KASP (Kompetitive Allele Specific PCR) SNP assays. A database of SNP genotype profiles was compiled for all the entries of the germplasm database. The panel of 21 successful SNPs accurately identified the unique potato cultivars in the database. The KASP SNP assays of the successful SNP panel are therefore available for potato DNA fingerprinting as new germplasm, or purity test requests are submitted to ARC-VIMP. This panel provides an objective method for assigning putative cultivar identity to unknown samples submitted for fingerprinting.

Clinical effects of Cariprazine and their relationship with polymorphisms of dopamine and serotonin receptors: preliminary results from a prospective study on schizophrenia and bipolar disorder

IntroductionCariprazine (CAR) is a D2, D3, 5HT1A receptor partial agonist and a 5HT2A, 5HT2B antagonist, used to treat Schizophrenia and Bipolar disorder. Interindividual variability in therapeutic and side effects of antipsychotics is difficult to predict, due to non-genetic and genetic factors. Single nucleotide polymorphisms (SNPs) are the main source of genetic variability, the ones in dopamine and serotonin receptors to which CAR binds are indeed likely to determine response to treatment.ObjectivesThe aim of the study is to define a relationship between CAR clinical efficacy and SNPs in dopamine and serotonin receptors genes of patients affected by schizophrenia and bipolar disorder.MethodsWe recruited 16 patients starting a monotherapy with CAR, evaluated at baseline and after 2, 4 and 8 weeks through BPRS rating scale. We selected a panel of SNPs in DR2, DR3, 5HT1A and 5HT2A receptors, with a frequency higher that 10% in Caucasians and functionally characterized. Cut-off for response to treatment was a 50% reduction of BPRS score. Statistical analysis was performed with one-way ANOVA followed by the test for linear trend between columns.ResultsAll subjects achieved response after 8 weeks of treatment, but 6 patients after 4 weeks. Early responders have a genetic profile associated with increased dopamine and serotonin receptor expression and/or binding affinity for their specific ligands. The association don’t reach statistical significance, probably due to low number of patients.ConclusionsPreliminary results suggest that an array of dopamine and serotonin receptors SNPs could predict time to respond to CAR in schizophrenia and bipolar disorder.DisclosureThe study is founded by Recordati AG, that commercialize the drug under study (Cariprazine) in Switzerland. Funding covers the costs for genetic analysis and other procedures of the study, no financial compensation is planned for investigators/authors.