Genotyping Strategy Research Articles

Evaluation of simple sequence repeats (SSR) and single nucleotide polymorphism (SNP)-based methods in olive varieties from the Northwest of Spain and potential for miniaturization

Miniaturization of DNA-based techniques can bring interesting advantages for food analysis, such as portability of complex analytical procedures. In the olive oil industry, miniaturization can be particularly interesting for authenticity and traceability applications, through in situ control of raw materials before production and/or the final products. However, variety identification is challenging, and implementation on miniaturized settings must be carefully evaluated, starting from the selected analytical approach. In this work, SSR- and SNP-based genotyping strategies were investigated for the identification and differentiation of two olive varieties from the Northwest of Spain. For the selected SNPs two genotyping methods were tested: real-time allele-specific PCR and high resolution melting analysis. These methods were compared and evaluated regarding their potential for integration in a microfluidic device. Both SNP-based methods proved to be successful for identification of the selected varieties, however real-time allele-specific PCR was the one that achieved the best results when analyzing mixtures, allowing the identification of both monovarietal samples and mixtures of the varieties tested with up to 25%.

Whole-Genome-Based Helicobacter pylori Geographic Surveillance: A Visualized and Expandable Webtool.

Helicobacter pylori exhibit specific geographic distributions that are related to clinical outcomes. Despite the high infection rate of H. pylori throughout the world, the genetic epidemiology surveillance of H. pylori still needs to be improved. This study used the single nucleotide polymorphisms (SNPs) profiling approach based on whole genome sequencing (WGS) to facilitate genomic population analyses of H. pylori and encourage the dissemination of microbial genotyping strategies worldwide. A total number of 1,211 public H. pylori genomes were downloaded and used to construct the typing tool, named HpTT (H. pylori Typing Tool). Combined with the metadata, we developed two levels of genomic typing, including a continent-scale and a country scale that nested in the continent scale. Results showed that Asia was the largest isolate source in our dataset, while isolates from Europe and Oceania were comparatively more widespread. More specifically, Switzerland and Australia are the main sources of widespread isolates in their corresponding continents. To integrate all the typing information and enable researchers to compare their dataset against the existing global database easily and rapidly, a user-friendly website (https://db.cngb.org/HPTT/) was developed with both genomic typing tools and visualization tools. To further confirm the validity of the website, ten newly assembled genomes were downloaded and tested precisely located on the branch as we expected. In summary, the H. pylori typing tool (HpTT) is a novel genomic epidemiological tool that can achieve high-resolution analysis of genomic typing and visualizing simultaneously, providing insights into the genetic population structure, evolution analysis, and epidemiological surveillance of H. pylori.

Cost-effectiveness analysis of genotype screening and therapeutic drug monitoring in patients with inflammatory bowel disease treated with azathioprine therapy: a Chinese healthcare perspective using real-world data.

BackgroundThis study aimed to analyze the cost-effectiveness of combining screening for thiopurine methyl transferase (TPMT) and nucleotide triphosphate diphosphatase (NUDT15) defective alleles with therapeutic drug monitoring (TDM) in Chinese patients with inflammatory bowel disease (IBD) treated with azathioprine (AZA).MethodsWe evaluated the cost-effectiveness of combining screening for NUDT15 and TPMT deficiency with TDM in patients receiving AZA treatment over a 1-year horizon by developing a decision tree model. Real-world data and published literature were used to derive model inputs. The model’s primary outcomes included quality-adjusted life-years (QALYs) and incremental cost-effectiveness ratios (ICERs). One-way and probabilistic sensitivity analyses were used to address uncertainty.ResultsCompared to NUDT15 genotyping, the combined TPMT/NUDT15 genotyping strategy cost an additional $13.83, yielding an ICER of $3,929.54/QALY, which was under the willingness-to-pay level of $30,425 per QALY in China. Compared to strategies with singular TPMT genotyping or no genotyping, the combined TPMT/NUDT15 genotyping strategy gained 0.00406 and 0.00782 QALYs and reduced the cost by $25.15 and $99.06, respectively. Additionally, incorporating TDM of AZA was more effective and less expensive than strategies without TDM. One-way sensitivity analysis revealed the expense attached to severe myelotoxicity to be the factor with the greatest influence in the present research. The application of the combined genotype screening strategy with TDM of AZA treatment was found to have a 91.7% chance of being cost-effective.ConclusionsFor Chinese patients with IBD who receive an AZA regimen, a strategy involving combined NUDT15/TPMT genotype screening prior to treatment initiation and incorporating TDM for treatment management is cost-effective compared to strategies involving genotyping of NUDT15 or TPMT alone or genotyping without TDM.

Leaf gas exchange of lowland rice in response to nitrogen source and vapor pressure deficit

AbstractBackgroundIn anaerobic lowland fields, ammonium (NH4+) is the dominant form of nitrogen (N) taken up by rice plants, however, with the large expansion of water‐saving irrigation practices, nitrification is favored during drained periods, leading to an increased availability of nitrate (NO3−).AimSince the uptake and assimilation of the two N‐sources differ in their demand of photosynthates, leaf gas exchange may be subject to adjustments in response to N‐sources, particularly at high evaporative demand, when stomatal conductance (gs) is very sensitive.MethodsThree experiments were carried out to study leaf gas exchange of various lowland rice varieties in response to N‐source at low and high vapor pressure deficit (VPD). In the first experiment, seedlings of 12 rice varieties were grown at high VPD for 3 weeks. From this, four rice varieties differing in gs and CO2 assimilation rate (A) were selected and grown for 2 weeks at low VPD, and after that, they were shifted to high VPD for 1 week, whereas in the third experiment, the same varieties were grown separately at low and high VPD conditions for 2 weeks. In all three experiments, plants were grown hydroponically in nutrient solution with N‐sources as sole NH4+ or NO3−.ResultsAt high VPD, NO3− nutrition led to a higher gs and A in four out of 12 varieties (IR64, BT7, NU838, and Nipponbare) relative to NH4+ nutrition, while no effect was observed at low VPD or after a short‐term exposure to high VPD. Further, varieties with a high intrinsic water‐use efficiency (WUEi; IR64 and BT7) showed the strongest response to N‐source. Higher gs was partially supported by increased root/shoot ratio, but could not be fully explained by the measured parameters. However, higher A in NO3−‐fed plants did not always result in increased plant dry matter, which is probably related to the higher energy demand for NO3− assimilation. Our results suggest that at high VPD, NO3− nutrition can improve leaf gas exchange in varieties having a high WUEi, provided a sufficient water supply.ConclusionTherefore, intensified nitrification under water‐saving irrigation measures may improve leaf gas exchange and the growth of rice plants under high transpirational demand. However, choice of variety seems crucial since large varietal differences were observed in response to N‐source. Further, breeding strategies for genotypes adapted to aerobic soil conditions should consider responses to NO3−, potentially using gas exchange measurements as a screening tool.

Impact of Pan-Ethnic Expanded Carrier Screening in Improving Population Health Outcomes: Proceedings from a Multi-Stakeholder Virtual Roundtable Summit, June 25, 2020.

Impact of Pan-Ethnic Expanded Carrier Screening in Improving Population Health Outcomes: Proceedings from a Multi-Stakeholder Virtual Roundtable Summit, June 25, 2020.

Comprehensive strategy improves the genetic diagnosis of different polycystic kidney diseases.

Polycystic kidney disease (PKD) is known to occur in three main forms, namely autosomal dominant PKD (ADPKD), autosomal recessive PKD (ARPKD) and syndromic PKD (SPKD), based on the clinical manifestations and genetic causes, which are diagnosable from the embryo stage to the later stages of life. Selection of the genetic test for the individuals with diagnostic imaging reports of cystic kidneys without a family history of the disease continues to be a challenge in clinical practice. With the objective of maintaining a limit on the time and medical cost of the procedure, a practical strategy for genotyping and targeted validation to resolve cystogene variations was developed in our clinical laboratory, which combined the techniques of whole‐exome sequencing (WES), Long‐range PCR (LR‐PCR), Sanger sequencing and multiplex ligation–dependent probe amplification (MLPA) to work in a stepwise approach. In this context, twenty‐six families with renal polycystic disorders were enrolled in the present study. Thirty‐two variants involving four ciliary genes (PKD1, PKHD1, TMEM67 and TMEM107) were identified and verified in 23 families (88.5%, 23/26), which expanded the variant spectrum by 16 novel variants. Pathogenic variations in five foetuses of six families diagnosed with PKD were identified using prenatal ultrasound imaging. Constitutional biallelic and digenic variations constituted the pathogenic patterns in these foetuses. The preliminary clinical data highlighted that the WES + LR PCR‐based workflow followed in the present study is efficient in detecting divergent variations in PKD. The biallelic and digenic mutations were revealed as the main pathogenic patterns in the foetuses with PKD.

Global population structure and genotyping framework for genomic surveillance of the major dysentery pathogen, Shigella sonnei

Shigella sonnei is the most common agent of shigellosis in high-income countries, and causes a significant disease burden in low- and middle-income countries. Antimicrobial resistance is increasingly common in all settings. Whole genome sequencing (WGS) is increasingly utilised for S. sonnei outbreak investigation and surveillance, but comparison of data between studies and labs is challenging. Here, we present a genomic framework and genotyping scheme for S. sonnei to efficiently identify genotype and resistance determinants from WGS data. The scheme is implemented in the software package Mykrobe and tested on thousands of genomes. Applying this approach to analyse >4,000 S. sonnei isolates sequenced in public health labs in three countries identified several common genotypes associated with increased rates of ciprofloxacin resistance and azithromycin resistance, confirming intercontinental spread of highly-resistant S. sonnei clones and demonstrating the genomic framework can facilitate monitoring the spread of resistant clones, including those that have recently emerged, at local and global scales.

Improving the Detection of Homologous Blood Transfusion in Sport Doping: A Full DNA‐based Genotyping Strategy on Dried Blood Spots

Homologous blood transfusions (hBT) are prohibited in sport by the World Anti-Doping Agency (WADA) as they represent one of the illicit strategies that athletes can pursue to improve the oxygen supply to the tissues, with a consequent enhancement of the athletic performance. The current method of detection of hBT is based on the phenotypic mismatch analysis of red blood cells (RBC) surface antigens by flow cytofluorimetry. Despite the excellent sensitivity and specificity of the method, some critical issues have progressively emerged, mostly related ti the relatively high risk of false-negative results. At the same time, the method is not applicable to blood samples collected as “dried blood spots”. To overcome these difficulties, we designed and developed a detection strategy based on DNA analysis. The wide inter-individual variability of DNA genotypes allows to completely eliminate the problem represented by the “false negative” results, improving also the overall sensitivity of the anti-doping tests. Our method is based on a combination of the forensic typing of DNA with the genotyping of SNP genetic polymorphisms. The effectiveness of the proposed approach has been confirmed by the analysis of positive samples obtained by mixing whole blood from two different compatible donors, who shared the same panel of RBC surface antigens, collected on DBS cards. DNA was isolated by a DNA forensic extraction kit based on magnetic beads. Our results suggest that the proposed approach, once validated on samples from real transfused subjects, can complement the current testing strategy based on the mismatch of the RBC surface antigens.

Comparative genomics of Edwardsiellaictaluri revealed four distinct host-specific genotypes and thirteen potential vaccine candidates

Edwardsiella ictaluri has been considered an important threat for catfish aquaculture industry for more than 4 decades and an emerging pathogen of farmed tilapia but only 9 sequenced genomes were publicly available. We hereby report two new complete genomes of E. ictaluri originated from diseased hybrid red tilapia (Oreochromis sp.) and striped catfish (Pangasianodon hypophthalmus) in Southeast Asia. E. ictaluri species has an open pan-genome consisting of 2615 core genes and 5592 pan genes. Phylogenetic analysis using core genome MLST (cgMLST) and ANI values consistently placed E. ictaluri isolates into 4 host-specific genotypes. Presence of unique genes and absence of certain genes from each genotype provided potential biomarkers for further development of genotyping scheme. Vaccine candidates with high antigenic, solubility and secretion probabilities were identified in silico from the core genes. Microevolution within the species is brought about by bacteriophages and insertion elements and possibly drive host adaptation.

Genotyping atypical porcine pestivirus using NS5a

Atypical porcine pestivirus (APPV) is an emerging virus discovered in 2014 and it can cause congenital tremors in pigs. Molecular epidemiology serves as an essential tool in monitoring and controlling the disease. Virus epidemiology mainly relies on genome sequencing and phylogenetic characterization. Previous molecular epidemiology studies have been using different genes/regions for phylogeny, namely whole genome, Npro, and E2 coding sequences. However, with increasing number of APPV sequences available in GenBank, no systemic studies have been performed for detailed classification of APPV strains around the globe. The goal of this study is to propose a classification strategy or taxonomy of APPV strains at genotype, subgenotype, and isolate levels. A total of 76 whole genomes and 16 partial polyprotein coding sequences were analyzed for genetic variability and suitability of all individual genes for viral phylogenies. Our results revealed that, among all the viral genes, NS5a coding sequences were proved to be the most suitable alternative for tracing APPV strains supported by its capability of reproducing the same phylogenetic and evolutionary information as the whole viral genome did. Also, a reliable cutoff to accurately classify APPV at different levels is established. We propose a genotyping scheme with three well-defined genotypes (1-3) and 7 subgenotypes for genotype 1 (1.1-1.7). For whole genome analysis, a threshold value of 84%-91% pairwise identity allows separation of all APPV subgenotypes, whereas 80% identity clearly segregate the three major APPV genotypes. For NS5a gene analysis, 82%-91% identity allows subgenotype separation and 76% identity segregate APPV genotypes. Additionally, genetic distance of whole genome exhibits ≤8% in isolate level, 9%-14% in subgenotype level, and 17%-22% in genotype level, while for NS5a encoding sequences the genetic distance displays ≤9% in isolate level, 9.9%-19.1% in subgenotype level, and 21.6%-29.7% in genotype level. These allow a clear segregation among APPV genotypes, subgenotypes, and isolates. Therefore, the proposed strategy in this study provides a solid and improved basis for molecular phylogenetics to understand APPV genetic diversity, trace the origins and control the spread of new disease outbreaks.

Frequency and characterization of RHD variant alleles in a population of blood donors from southeastern Brazil: Comparison with other populations

BackgroundThe correct determination of D antigen could help to avoid alloimmunization in pregnant women and patients receiving blood transfusions. However, there are limitations in the identification of D variants as the partial and weak D phenotypes make the determination of D antigen a great challenge in the transfusion routine.’ Study design and methodsThe molecular characterization of D variants was performed on blood donors from southeastern Brazil with atypical D typing. Furthermore, the serological profile of all RHD variant alleles identified was analyzed using different Anti-D clones. The prevalence of RHD alleles and genotypes found was compared with those described in other countries and in other regions from Brazil. ResultsAtypical serologic D typing occurred in 0.79 % of blood donors. The majority of RHD variant alleles (88 %) were first characterized by multiplex PCR and PCR-SSP as RHD*weak partial 4 (47 %), followed by RHD*weak D type 3 (29.9 %), RHD*weak D type 2 (3.9 %) and RHD*weak D type 1 (3.1 %). Genomic DNA sequencing characterized the RHD*weak partial 4 variants found in RHD*DAR1.2 (weak 4.2.2) (22 %), RHD*DAR3 (weak 4.0.1) (2.4 %), RHD*DAR3.1 (weak 4.0) (22 %) and RHD*DAR4 (weak 4.1) (0.8 %). RHD variant alleles associated with partial D, such as, RHD*DAU-4 (1.6 %), RHD*DAU-5 (2.4 %), RHD*DAU-6 (1.6 %), RHD* DIII type 8 (1.6 %), RHD*DVII (3.9 %) and RHD* DMH (0.8 %) were also observed. ConclusionThe prevalence of RHD variant alleles observed in this cohort differ from those found in other populations, including Brazilians from other regions. RHD allele distribution in specific regions should be considered for implementation of algorithms and genotyping strategies aiming at a more effective and safe transfusion.

Genomic diversity and molecular epidemiology of Pasteurella multocida.

Pasteurella multocida is a bacterial pathogen with the ability to infect a multitude of hosts including humans, companion animals, livestock, and wildlife. This study used bioinformatic approaches to explore the genomic diversity of 656 P. multocida isolates and epidemiological associations between host factors and specific genotypes. Isolates included in this study originated from a variety of hosts, including poultry, cattle, swine, rabbits, rodents, and humans, from five different continents. Multi-locus sequence typing identified 69 different sequence types. In-silico methodology for determining capsular serogroup was developed, validated, and applied to all genome sequences, whereby capsular serogroups A, B, D, and F were found. Whole genome phylogeny was constructed from 237,670 core single nucleotide variants (SNVs) and demonstrated an overall lack of host or capsular serogroup specificity, with the exception of isolates from bovine sources. Specific SNVs within the srlB gene were identified in P. multocida subsp. septica genomes, representing specific mutations that may be useful for differentiating one of the three known subspecies. Significant associations were identified between capsular serogroup and virulence factors, including capsular serogroup A and OmpH1, OmpH3, PlpE, and PfhB1; capsular serogroup B and HgbA and PtfA; and capsular serogroup F and PtfA and PlpP. Various mobile genetic elements were identified including those similar to ICEPmu1, ICEhin1056, and IncQ1 plasmids, all of which harbored multiple antimicrobial resistance-encoding genes. Additional analyses were performed on a subset of 99 isolates obtained from turkeys during fowl cholera outbreaks from a single company which revealed that multiple strains of P. multocida were circulating during the outbreak, instead of a single, highly virulent clone. This study further demonstrates the extensive genomic diversity of P. multocida, provides epidemiological context to the various genotyping schemes that have traditionally been used for differentiating isolates, and introduces additional tools for P. multocida molecular typing.

Fluorescent quenching probes based SAA 1 genotyping with a fully automated system

ObjectiveThe aim of the present study is to develop and validate a reliable and simple application for genotyping serum amyloid A1 (SAA1). MethodsThe specific nested PCR was performed to amplify a product of SAA1 gene. Two quenching probes (QPs) were designed for detecting two single nucleotide polymorphism (SNP) sites, rs1136743(C/T) and rs1136747(C/T) respectively for SAA1 genotypes. The specific nested PCR and QPs of SAA1 genotying was introduced into a fully automated genotyping system (I-densy, ARKRAY, Inc.), which enables the genotyping of SAA1 from whole blood. ResultsSix genotypes of SAA1 (α+/+, β+/+, γ+/+, αβ, αγ and βγ) could be determined by monitoring the fluorescence intensity of two QPs with melting temperature (TM) analysis. Total 121 clinical samples were SAA1 genotyped in the fluorescent quenching probes based method with a fully automated I-densy system and were further sequence confirmed with a PCR direct sequencing approach. ConclusionThis fully automated system is a rapid and reliable strategy for the SAA1 genotyping and for its future clinical application.

Genotyping strategies for maximizing genomic information in evaluations of the Latxa dairy sheep breed

Genomic selection has been implemented over the years in several livestock species, due to the achievable higher genetic progress. The use of genomic information in evaluations provides better prediction accuracy than do pedigree-based evaluations, and the makeup of the genotyped population is a decisive point. The aim of this work is to compare the effect of different genotyping strategies (number and type of animals) on the prediction accuracy for dairy sheep Latxa breeds. A simulation study was designed based on the real data structure of each population, and the phenotypic and genotypic data obtained were used in genetic (BLUP) and genomic (single-step genomic BLUP) evaluations of different genotyping strategies. The genotyping of males was beneficial when they were genetically connected individuals and if they had daughters with phenotypic records. Genotyping females with their own lactation records increased prediction accuracy, and the connection level has less relevance. The differences in genotyping females were independent of their estimated breeding value. The combined genotyping of males and females provided intermediate accuracy results regardless of the female selection strategy. Therefore, assuming that genotyping rams is interesting, the incorporation of genotyped females would be beneficial and worthwhile. The benefits of genotyping individuals from various generations were highlighted, although it was also possible to gain prediction accuracy when historic individuals were not considered. Greater genotyped population sizes resulted in more accuracy, even if the increase seems to reach a plateau.

Genotyping Strategies Using ddRAD Sequencing in Farmed Arctic Charr (Salvelinus alpinus).

Simple SummaryAnimal breeding in recent years has benefited greatly from the availability of large-scale genetic information. The most widely applied genomic tools in selective breeding are specialized arrays that use DNA hybridization. However, the high financial investments accompanying this practice impair the profitability of emerging aquaculture species, including Arctic charr. The aim of the current study was to assess and compare the potential of two cost-efficient genotyping strategies applicable in a variety of breeding-related tasks, such as pedigree verification, genetic diversity screening and detection of genomic regions that are associated with phenotypes of economic importance. Both strategies are based on reduced representation sequencing but differ in sequencing coverage (low and high). The low coverage strategy offers a higher density of DNA markers, but also presents a greater proportion of missing data in the marker set and is characterized by more uncertainty in determining heterozygosity compared to high coverage. Our results show that while high coverage genotyping performs better in genetic diversity and kinship analyses, a low coverage strategy is more successful in identifying genomic regions associated with phenotypic traits, leading to the conclusion that both strategies could be of value into selection schemes.Incorporation of genomic technologies into fish breeding programs is a modern reality, promising substantial advances regarding the accuracy of selection, monitoring the genetic diversity and pedigree record verification. Single nucleotide polymorphism (SNP) arrays are the most commonly used genomic tool, but the investments required make them unsustainable for emerging species, such as Arctic charr (Salvelinus alpinus), where production volume is low. The requirement to genotype a large number of animals for breeding practices necessitates cost effective genotyping approaches. In the current study, we used double digest restriction site-associated DNA (ddRAD) sequencing of either high or low coverage to genotype Arctic charr from the Swedish national breeding program and performed analytical procedures to assess their utility in a range of tasks. SNPs were identified and used for deciphering the genetic structure of the studied population, estimating genomic relationships and implementing an association study for growth-related traits. Missing information and underestimation of heterozygosity in the low coverage set were limiting factors in genetic diversity and genomic relationship analyses, where high coverage performed notably better. On the other hand, the high coverage dataset proved to be valuable when it comes to identifying loci that are associated with phenotypic traits of interest. In general, both genotyping strategies offer sustainable alternatives to hybridization-based genotyping platforms and show potential for applications in aquaculture selective breeding.

Genotype Imputation to Improve the Cost-Efficiency of Genomic Selection in Rabbits.

Simple SummaryGenotyping costs are still the major limitation for the uptake of genomic selection by the rabbit meat industry, as a large number of genetic markers are needed for improving the prediction of breeding values by genomic data. In this study, several genotyping strategies were examined through simulation scenarios to disentangle the best feasible options of implementing genomic selection in rabbit breeding programs. Most scenarios emphasized the genotyping of candidate animals with a low Single Nucleotide Polymorphism (SNP) density platform. Imputation accuracies were high for the scenarios with ancestors genotyped at high or medium SNP-densities. However, the scenario with male ancestors genotyped at high SNP-density and only dams genotyped at medium SNP-density showed the best economically feasible strategy, taking into account the trade-off among genotyping costs, the accuracy of breeding values and response to selection. The results confirmed that by combining the imputation technique with a mindful selection of the animals to be genotyped, it is possible to achieve better performance than Best Linear Unbiased Prediction (BLUP), reducing genotyping cost at the same time.Genomic selection uses genetic marker information to predict genomic breeding values (gEBVs), and can be a suitable tool for selecting low-hereditability traits such as litter size in rabbits. However, genotyping costs in rabbits are still too high to enable genomic prediction in selective breeding programs. One method for decreasing genotyping costs is the genotype imputation, where parents are genotyped at high SNP-density (HD) and the progeny are genotyped at lower SNP-density, followed by imputation to HD. The aim of this study was to disentangle the best imputation strategies with a trade-off between genotyping costs and the accuracy of breeding values for litter size. A selection process, mimicking a commercial breeding rabbit selection program for litter size, was simulated. Two different Quantitative Trait Nucleotide (QTN) models (QTN_5 and QTN_44) were generated 36 times each. From these simulations, seven different scenarios (S1–S7) and a further replicate of the third scenario (S3_A) were created. Scenarios consist of a different combination of genotyping strategies. In these scenarios, ancestors and progeny were genotyped with a mix of three different platforms, containing 200,000, 60,000, and 600 SNPs under a cost of EUR 100, 50 and 11 per animal, respectively. Imputation accuracy (IA) was measured as a Pearson’s correlation between true genotype and imputed genotype, whilst the accuracy of gEBVs was the correlation between true breeding value and the estimated one. The relationships between IA, the accuracy of gEBVs, genotyping costs, and response to selection were examined under each QTN model. QTN_44 presented better performance, according to the results of genomic prediction, but the same ranks between scenarios remained in both QTN models. The highest IA (0.99) and the accuracy of gEBVs (0.26; QTN_44, and 0.228; QTN_5) were observed in S1 where all ancestors were genotyped at HD and progeny at medium SNP-density (MD). Nevertheless, this was the most expensive scenario compared to the others in which the progenies were genotyped at low SNP-density (LD). Scenarios with low average costs presented low IA, particularly when female ancestors were genotyped at LD (S5) or non-genotyped (S7). The S3_A, imputing whole-genomes, had the lowest accuracy of gEBVs (0.09), even worse than Best Linear Unbiased Prediction (BLUP). The best trade-off between genotyping costs and the accuracy of gEBVs (0.234; QTN_44 and 0.199) was in S6, in which dams were genotyped with MD whilst grand-dams were non-genotyped. However, this relationship would depend mainly on the distribution of QTN and SNP across the genome, suggesting further studies on the characterization of the rabbit genome in the Spanish lines. In summary, genomic selection with genotype imputation is feasible in the rabbit industry, considering only genotyping strategies with suitable IA, accuracy of gEBVs, genotyping costs, and response to selection.

SLCO1B1 Phenotype and CYP3A5 Polymorphism Significantly Affect Atorvastatin Bioavailability.

Atorvastatin, prescribed for the treatment of hypercholesterolemia, demonstrated overwhelming benefits in reducing cardiovascular morbidity and mortality. However, many patients discontinue therapy due to adverse reactions, especially myopathy. The Dutch Pharmacogenetics Working Group (DPWG) recommends an alternative agent to atorvastatin and simvastatin or a dose adjustment depending on other risk factors for statin-induced myopathy in SLCO1B1 rs4149056 CC or TC carriers. In contrast, the Clinical Pharmacogenetics Implementation Consortium (CPIC) published their guideline on simvastatin, but not on atorvastatin. In this work, we aimed to demonstrate the effect of SLCO1B1 phenotype and other variants (e.g., in CYP3A4/5, UGT enzymes or SLC transporters) on atorvastatin pharmacokinetics. For this purpose, a candidate-gene pharmacogenetic study was proposed. The study population comprised 156 healthy volunteers enrolled in atorvastatin bioequivalence clinical trials. The genotyping strategy comprised a total of 60 variants in 15 genes. Women showed higher exposure to atorvastatin compared to men (p = 0.001), however this difference disappeared after dose/weight (DW) correction. The most relevant pharmacogenetic differences were the following: AUC/DW and Cmax /DW based on (a) SLCO1B1 phenotype (p < 0.001 for both) and (b) CYP3A5*3 (p = 0.004 and 0.018, respectively). As secondary findings: SLC22A1 *2/*2 genotype was related to higher Cmax/DW (ANOVA p = 0.030) and SLC22A1 *1/*5 genotype was associated with higher Vd/F (ANOVA p = 0.032) compared to SLC22A1 *1/*1, respectively. Finally, UGT2B7 rs7439366 *1/*1 genotype was associated with higher tmax as compared with the *1/*3 genotype (ANOVA p = 0.024). Based on our results, we suggest that SLCO1B1 is the best predictor for atorvastatin pharmacokinetic variability and that prescription should be adjusted based on it. We suggest that the CPIC should include atorvastatin in their statin-SLCO1B1 guidelines. Interesting and novel results were observed based on CYP3A5 genotype, which should be confirmed with further studies.Atorvastatin, prescribed for the treatment of hypercholesterolemia, demonstrated overwhelming benefits in reducing cardiovascular morbidity and mortality. However, many patients discontinue therapy due to adverse reactions, especially myopathy. The Dutch Pharmacogenetics Working Group (DPWG) recommends an alternative agent to atorvastatin and simvastatin or a dose adjustment depending on other risk factors for statin-induced myopathy in SLCO1B1 rs4149056 CC or TC carriers. In contrast, the Clinical Pharmacogenetics Implementation Consortium (CPIC) published their guideline on simvastatin, but not on atorvastatin. In this work, we aimed to demonstrate the effect of SLCO1B1 phenotype and other variants (e.g., in CYP3A4/5, UGT enzymes or SLC transporters) on atorvastatin pharmacokinetics. For this purpose, a candidate-gene pharmacogenetic study was proposed. The study population comprised 156 healthy volunteers enrolled in atorvastatin bioequivalence clinical trials. The genotyping strategy comprised a total of 60 variants in 15 genes. Women showed higher exposure to atorvastatin compared to men (p = 0.001), however this difference disappeared after dose/weight (DW) correction. The most relevant pharmacogenetic differences were the following: AUC/DW and Cmax /DW based on (a) SLCO1B1 phenotype (p < 0.001 for both) and (b) CYP3A5*3 (p = 0.004 and 0.018, respectively). As secondary findings: SLC22A1 *2/*2 genotype was related to higher Cmax/DW (ANOVA p = 0.030) and SLC22A1 *1/*5 genotype was associated with higher Vd/F (ANOVA p = 0.032) compared to SLC22A1 *1/*1, respectively. Finally, UGT2B7 rs7439366 *1/*1 genotype was associated with higher tmax as compared with the *1/*3 genotype (ANOVA p = 0.024). Based on our results, we suggest that SLCO1B1 is the best predictor for atorvastatin pharmacokinetic variability and that prescription should be adjusted based on it. We suggest that the CPIC should include atorvastatin in their statin-SLCO1B1 guidelines. Interesting and novel results were observed based on CYP3A5 genotype, which should be confirmed with further studies.

Genotypic diversity of Mycobacterium tuberculosis isolates and its association with drug-resistance status in Xinjiang, China

Xinjiang is a unique region of Central Asian part of China. It is widely noted for high tuberculosis burden and particularly for growing prevalence of drug resistance. Understanding genotypic distribution of Mycobacterium tuberculosis could help clarify unknown causes for the spread of drug-resistant strains. We analyzed 986 M. tuberculosis isolates collected from Xinjiang. Two genotyping schemes, i.e., spoligotyping and multiple-locus variable number tandem repeats (VNTR), were used to determine the phylogenetic lineages and their association with drug-resistances. The M. tuberculosis isolates studied displayed wide distribution of spoligotypic lineages, including Beijing, T, CAS, Ural, LAM, MANU, H, X, EAI, S, Microti, and BOV. The dominant Beijing lineage showed statistical difference from non-Beijing lineages in patients ages (P < 0.001), ethnic groups (P < 0.001) and resistance of three or more drugs (P = 0.008). Further analysis of the year of 2017 subset (n = 257) using VNTR scheme revealed an extremely high discrimination power (Hunter-Gaston discriminatory index = 0.9994). Cluster analysis showed a much lower recent transmission index (7.93%), indicating that the high drug-resistant tuberculosis in this region was mainly caused by reactivation or inappropriate therapy rather than by recent transmission. These data would be valuable for making and implementing policies for improving tuberculosis treatment and care in Xinjiang.

Selective genotyping and phenotypic data inclusion strategies of crossbred progeny for combined crossbred and purebred selection in swine breeding.

Inclusion of crossbred (CB) data into traditionally purebred (PB) genetic evaluations has been shown to increase the response in CB performance. Currently, it is unrealistic to collect data on all CB animals in swine production systems, thus, a subset of CB animals must be selected to contribute genomic/phenotypic information. The aim of this study was to evaluate selective genotyping strategies in a simulated 3-way swine crossbreeding scheme. The swine crossbreeding scheme was simulated and produced 3-way CB animals for 6 generations with 3 distinct PB breeds each with 25 and 175 mating males and females, respectively. F1 crosses (400 mating females) produced 4,000 terminal CB progeny which were subjected to selective genotyping. The genome consisted of 18 chromosomes with 1,800 QTL and 72k SNP markers. Selection was performed using estimated breeding values (EBV) for CB performance. It was assumed that both PB and CB performance was moderately heritable (h2=0.4). Several scenarios altering the genetic correlation between PB and CB performance (rpc=0.1,0.3,0.5,0.7,or0.9) were considered. CB animals were chosen based on phenotypes to select 200, 400, or 800 CB animals to genotype per generation. Selection strategies included: (1) Random: random selection, (2) Top: highest phenotype, (3) Bottom: lowest phenotype, (4) Extreme: half highest and half lowest phenotypes, and (5) Middle: average phenotype. Each selective genotyping strategy, except for Random, was considered by selecting animals in half-sib (HS) or full-sib (FS) families. The number of PB animals with genotypes and phenotypes each generation was fixed at 1,680. Each unique genotyping strategy and rpc scenario was replicated 10 times. Selection of CB animals based on the Extreme strategy resulted in the highest (P < 0.05) rates of genetic gain in CB performance (ΔG) when rpc<0.9. For highly correlated traits (rpc=0.9) selective genotyping did not impact (P > 0.05) ΔG. No differences (P > 0.05) were observed in ΔG between top, bottom, or middle when rpc>0.1. Higher correlations between true breeding values (TBV) and EBV were observed using Extreme when rpc<0.9. In general, family sampling method did not impact ΔG or the correlation between TBV and EBV. Overall, the Extreme genotyping strategy produced the greatest genetic gain and the highest correlations between TBV and EBV, suggesting that 2-tailed sampling of CB animals is the most informative when CB performance is the selection goal.

ТЕХНОЛОГИЯ ГЕНОДИАГНОСТИКИ BOVINE LEUKEMIA VIRUS У КРУПНОГО РОГАТОГО СКОТА, В ВЫРАБАТЫВАЕМОМ СЫРЬЕ И ПРОИЗВОДИМОЙ ПРОДУКЦИИ

The most important task of the dairy cattle industry is to obtain high quality raw milk. To achieve it, a set of measures is required, including aimed at increasing the biological safety of produced raw materials. The aim of the study was to create a scientific and methodological basis for the Bovine leukemia virus (BLV) gene diagnostics in a combined format of pathogen indication and identification. This required updating the strategy of BLV PCR-RFLP genotyping, consistent with its phylogenetic classification, taking into account the growing knowledge about the genetic diversity of 11 genotypes of the studied viral pathogen. When staging nested PCR, oligonucleotide primers were used, which initiate at the final stage of the reaction the production of a 444 bp env-gene fragment of the pathogen. Five restriction endonucleases were used in PCR-RFLP BLV genotyping of: PvuII, SspI, AsuHPI, HaeIII, and BstX2I. As a result of verification of the developed Bovine leukemia virus method for gene identification with an updated genotyping strategy, a technical result was obtained, expressed in the ability to identify all 11 BLV genotypes discovered to date by interpreting the generated 58 genotype-associated combinations of PCR-RFLP profiles.