scholarly journals Accurate Diagnosis of Small Ruminant Lentivirus Infection Is Needed for Selection of Resistant Sheep through TMEM154 E35K Genotyping

Pathogens ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 83
Author(s):  
Hugo Ramírez ◽  
Irache Echeverría ◽  
Alfredo A. Benito ◽  
Idoia Glaria ◽  
Julio Benavides ◽  
...  
Keyword(s):  
Small Ruminant ◽  
Association Studies ◽  
Positive Association ◽  
Control Measures ◽  
Genome Wide Association Studies ◽  
Infection Status ◽  
Single Strain ◽  
Strain Design ◽  
Breed Selection ◽  
Selection Of

Small ruminant lentiviruses (SRLV) cause an incurable multiorganic disease widely spread in sheep and goats that disturbs animal welfare and production. In the absence of a vaccine, control measures have been traditionally based on early diagnosis and breeding with virus-inactivated colostrum with segregation of seropositive animals. However, antigenic heterogeneity, poor antibody production due to low viral load, and single strain design of most available ELISA, pose a threat to SRLV diagnosis. Genome-wide association studies have described TMEM154 E35K polymorphism as a good genetic marker for selection of resistant animals in some American and European breeds. In this study, a multitargeted serological and virological screening of more than 500 animals from four different breeds (latxa, raza Navarra, assaf, and churra) attending to SRLV infection status was performed. Then, animals were genotyped to characterize TMEM154 E35K polymorphism. ELISA procedures, individually considered, only identified a proportion of the seropositive animals, and PCR detected a fraction of seronegative animals, globally offering different animal classifications according to SRLV infection status. TMEM154 allele frequency differed substantially among breeds and a positive association between seroprevalence and TMEM154 genotype was found only in one breed. Selection based on TMEM154 may be suitable for specific ovine breeds or SRLV strains, however generalization to the whole SRLV genetic spectrum, ovine breeds, or epidemiological situation may need further validation.

scholarly journals Genomic Analysis, Progress and Future Perspectives in Dairy Cattle Selection: A Review

Animals ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 599
Author(s):  
Miguel A. Gutierrez-Reinoso ◽  
Pedro M. Aponte ◽  
Manuel Garcia-Herreros
Keyword(s):  
Dairy Cattle ◽  
Production Efficiency ◽  
Association Studies ◽  
Phenotypic Traits ◽  
Progeny Testing ◽  
Genome Wide Association Studies ◽  
Genetic Progress ◽  
Breeding Programs ◽  
Increased Risk ◽  
Selection Of

Genomics comprises a set of current and valuable technologies implemented as selection tools in dairy cattle commercial breeding programs. The intensive progeny testing for production and reproductive traits based on genomic breeding values (GEBVs) has been crucial to increasing dairy cattle productivity. The knowledge of key genes and haplotypes, including their regulation mechanisms, as markers for productivity traits, may improve the strategies on the present and future for dairy cattle selection. Genome-wide association studies (GWAS) such as quantitative trait loci (QTL), single nucleotide polymorphisms (SNPs), or single-step genomic best linear unbiased prediction (ssGBLUP) methods have already been included in global dairy programs for the estimation of marker-assisted selection-derived effects. The increase in genetic progress based on genomic predicting accuracy has also contributed to the understanding of genetic effects in dairy cattle offspring. However, the crossing within inbred-lines critically increased homozygosis with accumulated negative effects of inbreeding like a decline in reproductive performance. Thus, inaccurate-biased estimations based on empirical-conventional models of dairy production systems face an increased risk of providing suboptimal results derived from errors in the selection of candidates of high genetic merit-based just on low-heritability phenotypic traits. This extends the generation intervals and increases costs due to the significant reduction of genetic gains. The remarkable progress of genomic prediction increases the accurate selection of superior candidates. The scope of the present review is to summarize and discuss the advances and challenges of genomic tools for dairy cattle selection for optimizing breeding programs and controlling negative inbreeding depression effects on productivity and consequently, achieving economic-effective advances in food production efficiency. Particular attention is given to the potential genomic selection-derived results to facilitate precision management on modern dairy farms, including an overview of novel genome editing methodologies as perspectives toward the future.

scholarly journals Genome-wide association mapping reveals race-specific SNP markers associated with anthracnose resistance in carioca common beans

PLoS ONE ◽  
2021 ◽  
Vol 16 (5) ◽  
pp. e0251745
Author(s):  
Caléo Panhoca de Almeida ◽  
Jean Fausto de Carvalho Paulino ◽  
Caio Cesar Ferrari Barbosa ◽  
Gabriel de Moraes Cunha Gonçalves ◽  
Roberto Fritsche-Neto ◽  
...  
Keyword(s):  
Quantitative Resistance ◽  
Association Studies ◽  
Colletotrichum Lindemuthianum ◽  
Genome Wide Association ◽  
High Yield ◽  
Genome Wide Association Studies ◽  
Anthracnose Resistance ◽  
Resistant Cultivars ◽  
Genome Wide ◽  
Selection Of

Brazil is the largest consumer of dry edible beans (Phaseolus vulgaris L.) in the world, 70% of consumption is of the carioca variety. Although the variety has high yield, it is susceptible to several diseases, among them, anthracnose (ANT) can lead to losses of up to 100% of production. The most effective strategy to overcome ANT, a disease caused by the fungus Colletotrichum lindemuthianum, is the development of resistant cultivars. For that reason, the selection of carioca genotypes resistant to multiple ANT races and the identification of loci/markers associated with genetic resistance are extremely important for the genetic breeding process. Using a carioca diversity panel (CDP) with 125 genotypes and genotyped by BeadChip BARCBean6K_3 and a carioca segregating population AM (AND-277 × IAC-Milênio) genotyped by sequencing (GBS). Multiple interval mapping (MIM) and genome-wide association studies (GWAS) were used as mapping tools for the resistance genes to the major ANT physiological races present in the country. In general, 14 single nucleotide polymorphisms (SNPs) showed high significance for resistance by GWAS, and loci associated with multiple races were also identified, as the Co-3 locus. The SNPs ss715642306 and ss715649427 in linkage disequilibrium (LD) at the beginning of chromosome Pv04 were associated with all the races used, and 16 genes known to be related to plant immunity were identified in this region. Using the resistant cultivars and the markers associated with significant quantitative resistance loci (QRL), discriminant analysis of principal components (DAPC) was performed considering the allelic contribution to resistance. Through the DAPC clustering, cultivar sources with high potential for durable anthracnose resistance were recommended. The MIM confirmed the presence of the Co-14 locus in the AND-277 cultivar which revealed that it was the only one associated with resistance to ANT race 81. Three other loci were associated with race 81 on chromosomes Pv03, Pv10, and Pv11. This is the first study to identify new resistance loci in the AND-277 cultivar. Finally, the same Co-14 locus was also significant for the CDP at the end of Pv01. The new SNPs identified, especially those associated with more than one race, present great potential for use in marker-assisted and early selection of inbred lines.

scholarly journals Genome-wide association studies of Shigella spp. and Enteroinvasive Escherichia coli isolates demonstrate an absence of genetic markers for prediction of disease severity

2019 ◽  
Author(s):  
Amber C. A. Hendriks ◽  
Frans A.G. Reubsaet ◽  
A.M.D. (Mirjam) Kooistra ◽  
John W. A. Rossen ◽  
Bas E. Dutilh ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Disease Severity ◽  
Genetic Variants ◽  
Association Studies ◽  
Control Measures ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Severity Scores ◽  
Shigella Spp

Abstract Background We investigated the association of symptoms and disease severity of shigellosis patients with genetic determinants of infecting Shigella and entero-invasive Escherichia coli (EIEC), because determinants that predict disease outcome per individual patient could be used to prioritize control measures. For this purpose, genome wide association studies (GWAS) were performed using presence or absence of single genes, combinations of genes, and k-mers. All genetic variants were derived from draft genome sequences of isolates from a multicenter cross-sectional study conducted in the Netherlands during 2016 and 2017. Clinical data of patients consisting of binary/dichotomous representation of symptoms and their calculated severity scores were also available from this study. To verify the suitability of the used methods, the genetic differences between the genera Shigella and Escherichia were used as control. Results The obtained isolates were representative for a population structure as encountered in a Western European country. No association was found between single genes or combinations of genes and separate symptoms or disease severity scores. One potentially associated intergenic region was found using a k-mer approach, however, this turned out to be a false positive. Our benchmark characteristic, genus, resulted in eight associated genes and >3,000,000 k-mers, indicating adequate performance of the used algorithms. Conclusions To conclude, using several microbial GWAS methods, genetic variants in Shigella spp. and EIEC that can predict specific symptoms or a more severe course of disease were not identified, suggesting that disease severity of shigellosis is dependent on other factors than the genetic variation of the infecting bacteria. Specific genes or gene fragments of isolates from patients are unsuitable to predict outcomes and cannot be used for development, prioritization and optimization of guidelines for control measures of shigellosis or infections with EIEC.

scholarly journals Analysis of whole exome sequencing in severe mental illness hints at selection of brain development and immune related genes

2021 ◽  
Author(s):  
Jayant Mahadevan ◽  
Ajai Kumar Pathak ◽  
Alekhya Vemula ◽  
Ravi Kumar Nadella ◽  
Biju Viswanath ◽  
...  
Keyword(s):  
Mental Illness ◽  
Severe Mental Illness ◽  
Positive Selection ◽  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Association Studies ◽  
Psychiatric Disease ◽  
Genome Wide Association Studies ◽  
Whole Exome ◽  
Selection Of

Evolutionary trends may underlie some aspects of the risk for common, non-communicable disorders, including psychiatric disease. We analyzed whole exome sequencing data from 80 unique individuals from India coming from families with two or more individuals with severe mental illness. We used Population Branch Statistics (PBS) to identify variants and genes under positive selection and identified 75 genes as candidates for positive selection. Of these, 20 were previously associated with Schizophrenia, Alzheimers disease and cognitive abilities in genome wide association studies. We then checked whether any of these 75 genes were involved in common biological pathways or related to specific cellular or molecular functions. We found that immune related pathways and functions related to innate immunity such as antigen binding were over-represented. We also evaluated for the presence of Neanderthal introgressed segments in these genes and found Neanderthal introgression in a single gene out of the 75 candidate genes. However, the introgression pattern indicates the region is unlikely to be the source for selection. Our findings hint at how selection pressures in individuals from families with a history of severe mental illness may diverge from the general population. Further, it also provides insights into the genetic architecture of severe mental illness, such as schizophrenia and its link to immune factors.

Selection of representative SNP sets for genome-wide association studies: a metaheuristic approach

2011 ◽  
Vol 6 (6) ◽  
pp. 1207-1218 ◽  
Author(s):  
Gürkan Üstünkar ◽  
Süreyya Özöğür-Akyüz ◽  
Gerhard W. Weber ◽  
Christoph M. Friedrich ◽  
Yeşim Aydın Son
Keyword(s):  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Selection Of

scholarly journals Genome-wide association studies of Shigella spp. and Enteroinvasive Escherichia coli isolates demonstrate an absence of genetic markers for prediction of disease severity

2019 ◽  
Author(s):  
Amber C. A. Hendriks ◽  
Frans A.G. Reubsaet ◽  
A.M.D. (Mirjam) Kooistra ◽  
John W. A. Rossen ◽  
Bas E. Dutilh ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Disease Severity ◽  
Genetic Variants ◽  
Association Studies ◽  
Control Measures ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Severity Scores ◽  
Shigella Spp

Abstract Background We investigated the association of symptoms and disease severity of shigellosis patients with genetic determinants of infecting Shigella and entero-invasive Escherichia coli (EIEC), because determinants that predict disease outcome per individual patient could be used to prioritize control measures. For this purpose, genome wide association studies (GWAS) were performed using presence or absence of single genes, combinations of genes, and k-mers. All genetic variants were derived from draft genome sequences of isolates from a multicenter cross-sectional study conducted in the Netherlands during 2016 and 2017. Clinical data of patients consisting of binary/dichotomous representation of symptoms and their calculated severity scores were also available from this study. To verify the suitability of the used methods, the genetic differences between the genera Shigella and Escherichia were used as control. Results The obtained isolates were representative for a population structure as encountered in a Western European country. No association was found between single genes or combinations of genes and separate symptoms or disease severity scores. One potentially associated intergenic region was found using a k-mer approach, however, this turned out to be a false positive. Our benchmark characteristic, genus, resulted in eight associated genes and >3,000,000 k-mers, indicating adequate performance of the used algorithms. Conclusions To conclude, using several microbial GWAS methods, genetic variants in Shigella spp. and EIEC that can predict specific symptoms or a more severe course of disease were not identified, suggesting that disease severity of shigellosis is dependent on other factors than the genetic variation of the infecting bacteria. Specific genes or gene fragments of isolates from patients are unsuitable to predict outcomes and cannot be used for development, prioritization and optimization of guidelines for control measures of shigellosis or infections with EIEC.

scholarly journals Snp Characteristics and Validation Success in Genome Wide Association Studies

2021 ◽  
Author(s):  
Olga Gorlova ◽  
Xiangjun Xiao ◽  
Spiridon Tsavachidis ◽  
Christopher I. Amos ◽  
Ivan P. Gorlov
Keyword(s):  
Success Rate ◽  
Association Studies ◽  
Statistical Significance ◽  
Positive Association ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Multivariable Logistic Regression Model ◽  
Functional Studies ◽  
Genome Wide

Abstract Genome wide association studies (GWASs) have identified tens of thousands of single nucleotide polymorphisms (SNPs) associated with human diseases and characteristics. A significant fraction of GWAS findings can be false positives. The gold standard for true positives is an independent validation. The goal of this study was to identify SNP features associated with validation success. Summary statistics from the Catalog of Published GWASs were used in the analysis. Since our goal was an analysis of reproducibility, we focused on the diseases/phenotypes targeted by at least 10 GWASs. GWASs were arranged in discovery-validation pairs based on the time of publication, with the discovery GWAS published before validation. We used four definitions of the validation success that differ by stringency. Associations of SNP features with validation success were consistent across the definitions. The strongest predictor of SNP validation was the level of statistical significance in the discovery GWAS. The magnitude of the effect size was associated with validation success in a non-linear manner. SNPs with risk allele frequencies in the range 30-70% showed a higher validation success rate compared to rarer or more common SNPs. Missense, 5’UTR, stop gained, and SNPs located in transcription factor binding sites had a higher validation success rate compared to intergeneic, intronic, or synonymous SNPs. There was a positive association between validation success and the level of evolutionary conservation of the sites. In addition, validation success was higher when discovery and validation GWASs targeted the same ethnicity. All predictors of validation success remained significant in a multivariable logistic regression model indicating their independent contribution. To conclude, we identified SNP features predicting validation success of GWAS hits. These features can be used to select SNPs for validation and downstream functional studies.

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