scholarly journals Genome-wide association study and Genomic Prediction of spot blotch disease in wheat (Triticum aestivum L.) using genotyping by sequencing

2020 ◽  
Author(s):  
Vipin Tomar ◽  
Ravi P Singh ◽  
Jesse Poland ◽  
Daljit Singh ◽  
Arun K Joshi ◽  
...  
Keyword(s):  
Disease Resistance ◽  
Genomic Prediction ◽  
Prediction Accuracy ◽  
Genome Wide Association Study ◽  
Genotyping By Sequencing ◽  
Spot Blotch ◽  
Genomic Region ◽  
Genome Wide Association ◽  
Genome Wide ◽  
Genomic Regions

Abstract Background Spot blotch caused by Bipolaris sorokiniana is a major constraint in wheat production in tropics and subtropics. There is limited information available on GWAS and study on genomic prediction is completely lacking. To reveal the genetic markers associated with disease resistance, we performed a genome-wide association study (GWAS) for spot blotch disease in 141 spring wheat lines. Results Based on the testing under natural infection in three years at hot spots location in Pusa, India and Jamalpur, Bangladesh, the genotypes showed significant genetic variation for disease severity. Using Genotyping-by-Sequencing (GBS) based 18637 polymorphic SNP markers and phenotyping from diverse environments, we identified 23 genomic regions across the genome ( p < 0.001) on 14 chromosomes associated with disease scores. Consistent with the previous reports, a most stable genomic region on chromosome 2B, 5B and 7D were detected across the environments. The new genomic region on chromosome 3D was also identified. We performed functional annotation with wheat genome assembly annotation (IWGSC Ref Seq v1.0) and identified NBS-LRR and 35 other plant defense-related protein families across multiple chromosome regions. Using a five-fold cross-validation scheme, we observed moderate prediction accuracy for 3 of 4 environments indicated that our model was able to successfully capture the quantitative variation underlying the SB variation in our population. Conclusions The GWAS based on the phenotypic data from PUSA India and BARI Bangladesh resulted in a total of 23 genomic regions on 14 chromosomes. The new genomic region appeared on chromosome 3D associated with Zinc finger protein that play important role in plant disease resistance. The genomic prediction model for spot blotch disease resistance in wheat was tested and obtained moderate prediction accuracy.

scholarly journals Genome‑wide association study and genomic prediction for growth traits in yellow-plumage chicken using genotyping-by-sequencing

2021 ◽  
Vol 53 (1) ◽  
Author(s):  
Ruifei Yang ◽  
Zhenqiang Xu ◽  
Qi Wang ◽  
Di Zhu ◽  
Cheng Bian ◽  
...  
Keyword(s):  
Association Study ◽  
Genomic Prediction ◽  
Genetic Background ◽  
Prediction Accuracy ◽  
Genome Wide Association Study ◽  
Growth Traits ◽  
Genome Wide Association ◽  
Genomic Feature ◽  
Genomic Information ◽  
Genome Wide

Abstract Background Growth traits are of great importance for poultry breeding and production and have been the topic of extensive investigation, with many quantitative trait loci (QTL) detected. However, due to their complex genetic background, few causative genes have been confirmed and the underlying molecular mechanisms remain unclear, thus limiting our understanding of QTL and their potential use for the genetic improvement of poultry. Therefore, deciphering the genetic architecture is a promising avenue for optimising genomic prediction strategies and exploiting genomic information for commercial breeding. The objectives of this study were to: (1) conduct a genome-wide association study to identify key genetic factors and explore the polygenicity of chicken growth traits; (2) investigate the efficiency of genomic prediction in broilers; and (3) evaluate genomic predictions that harness genomic features. Results We identified five significant QTL, including one on chromosome 4 with major effects and four on chromosomes 1, 2, 17, and 27 with minor effects, accounting for 14.5 to 34.1% and 0.2 to 2.6% of the genomic additive genetic variance, respectively, and 23.3 to 46.7% and 0.6 to 4.5% of the observed predictive accuracy of breeding values, respectively. Further analysis showed that the QTL with minor effects collectively had a considerable influence, reflecting the polygenicity of the genetic background. The accuracy of genomic best linear unbiased predictions (BLUP) was improved by 22.0 to 70.3% compared to that of the conventional pedigree-based BLUP model. The genomic feature BLUP model further improved the observed prediction accuracy by 13.8 to 15.2% compared to the genomic BLUP model. Conclusions A major QTL and four minor QTL were identified for growth traits; the remaining variance was due to QTL effects that were too small to be detected. The genomic BLUP and genomic feature BLUP models yielded considerably higher prediction accuracy compared to the pedigree-based BLUP model. This study revealed the polygenicity of growth traits in yellow-plumage chickens and demonstrated that the predictive ability can be greatly improved by using genomic information and related features.

scholarly journals Genome-wide association study and genomic predictions for exterior traits in Yorkshire pigs1

2019 ◽  
Vol 97 (7) ◽  
pp. 2793-2802 ◽  
Author(s):  
Jungjae Lee ◽  
SeokHyun Lee ◽  
Jong-Eun Park ◽  
Sung-Ho Moon ◽  
Sung-Woon Choi ◽  
...  
Keyword(s):  
Association Study ◽  
Genomic Prediction ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Breeding Value ◽  
Response Variable ◽  
Genome Wide ◽  
Yorkshire Pigs ◽  
Genomic Regions ◽  
Response Variables

Abstract The objectives of this study were to identify informative genomic regions that affect the exterior traits of purebred Korean Yorkshire pigs and to investigate and compare the accuracy of genomic prediction for response variables. Phenotypic data on body height (BH), body length (BL), and total teat number (TTN) from 2,432 Yorkshire pigs were used to obtain breeding values including as response variable the estimated breeding value (EBV) and 2 types of deregressed EBVs—one including the parent average (DEBVincPA) and the other excluding it (DEBVexcPA). A final genotype panel comprising 46,199 SNP markers was retained for analysis after quality control for common SNPs. The BayesB and BayesC methods—with various π and weighted response variables (EBV, DEBVincPA, or DEBVexcPA)—were used to estimate SNP effects, through the genome-wide association study. The significance of genomic windows (1 Mb) was obtained at 1.0% additive genetic variance and was subsequently used to identify informative genomic regions. Furthermore, SNPs with a high model frequency (≥0.90) were considered informative. The accuracy of genomic prediction was estimated using a 5-fold cross-validation with the K-means clustering method. Genomic accuracy was measured as the genomic correlation between the molecular breeding value and the individual weighted response variables (EBV, DEBVincPA, or DEBVexcPA). The number of identified informative windows (1 Mb) for BH, BL, and TTN was 4, 3, and 4, respectively. The number of significant SNPs for BH, BL, and TTN was 6, 4, and 5, respectively. Diversity π did not influence the accuracy of genomic prediction. The BayesB method showed slightly higher genomic accuracy for exterior traits than BayesC method in this study. In addition, the genomic accuracy using DEBVincPA as response variable was higher than that using other response variables. Therefore, the genomic accuracy using BayesB (π = 0.90) with DEBVinPA as a response variable was the most effective in this study. The genomic accuracy values for BH, BL, and TTN were calculated to be 0.52, 0.60, and 0.51, respectively.

scholarly journals Population demographic history and population structure for Pakistani Nili-Ravi breeding bulls based on SNP genotyping to identify genomic regions associated with male effects for milk yield and body weight

PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0242500
Author(s):  
Saher Islam ◽  
Umesh K. Reddy ◽  
Purushothaman Natarajan ◽  
Venkata Lakshmi Abburi ◽  
Amna Arshad Bajwa ◽  
...  
Keyword(s):  
Body Weight ◽  
Population Structure ◽  
Association Study ◽  
Milk Yield ◽  
Genome Wide Association Study ◽  
Water Buffalo ◽  
Genotyping By Sequencing ◽  
Genome Wide Association ◽  
Genome Wide ◽  
Genomic Regions

The domestic Nili-Ravi water buffalo (Bubalus bubalis) is the best dairy animal contributing 68% to total milk production in Pakistan. In this study, we identified genome-wide single nucleotide polymorphisms (SNPs) to estimate various population genetic parameters such as diversity, pairwise population differentiation, linkage disequilibrium (LD) distribution and for genome-wide association study for milk yield and body weight traits in the Nili-Ravi dairy bulls that they may pass on to their daughters who are retained for milking purposes. The genotyping by sequencing approach revealed 13,039 reference genome-anchored SNPs with minor allele frequency of 0.05 among 167 buffalos. Population structure analysis revealed that the bulls were grouped into two clusters (K = 2), which indicates the presence of two different lineages in the Pakistani Nili-Ravi water buffalo population, and we showed the extent of admixture of these two lineages in our bull collection. LD analysis revealed 4169 significant SNP associations, with an average LD decay of 90 kb for these buffalo genome. Genome-wide association study involved a multi-locus mixed linear model for milk yield and body weight to identify genome-wide male effects. Our study further illustrates the utility of the genotyping by sequencing approach for identifying genomic regions to uncover additional demographic complexity and to improve the complex dairy traits of the Pakistani Nili-Ravi water buffalo population that would provide the lot of economic benefits to dairy industry.

scholarly journals Genome-wide association study in almost 195,000 individuals identifies 50 previously unidentified genetic loci for eye color

2021 ◽  
Vol 7 (11) ◽  
pp. eabd1239
Author(s):  
Mark Simcoe ◽  
Ana Valdes ◽  
Fan Liu ◽  
Nicholas A. Furlotte ◽  
David M. Evans ◽  
...  
Keyword(s):  
Association Study ◽  
Genome Wide Association Study ◽  
Color Variation ◽  
Genome Wide Association ◽  
Nucleotide Polymorphisms ◽  
Melanin Pigmentation ◽  
Eye Color ◽  
Human Eye ◽  
Genome Wide ◽  
Genomic Regions

Human eye color is highly heritable, but its genetic architecture is not yet fully understood. We report the results of the largest genome-wide association study for eye color to date, involving up to 192,986 European participants from 10 populations. We identify 124 independent associations arising from 61 discrete genomic regions, including 50 previously unidentified. We find evidence for genes involved in melanin pigmentation, but we also find associations with genes involved in iris morphology and structure. Further analyses in 1636 Asian participants from two populations suggest that iris pigmentation variation in Asians is genetically similar to Europeans, albeit with smaller effect sizes. Our findings collectively explain 53.2% (95% confidence interval, 45.4 to 61.0%) of eye color variation using common single-nucleotide polymorphisms. Overall, our study outcomes demonstrate that the genetic complexity of human eye color considerably exceeds previous knowledge and expectations, highlighting eye color as a genetically highly complex human trait.

scholarly journals Genome-Wide Association Study (GWAS) for Examining the Genomics Controlling Prickle Production in Red Raspberry (Rubus idaeus L.)

Agronomy ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 27
Author(s):  
Archana Khadgi ◽  
Courtney A. Weber
Keyword(s):  
Association Study ◽  
Genome Wide Association Study ◽  
Genomic Region ◽  
Rubus Idaeus ◽  
Genome Wide Association ◽  
Nucleotide Polymorphisms ◽  
Red Raspberry ◽  
Genome Wide ◽  
A Genome ◽  
Genotype By Sequencing

Red raspberry (Rubus idaeus L.) is an expanding high-value berry crop worldwide. The presence of prickles, outgrowths of epidermal tissues lacking vasculature, on the canes, petioles, and undersides of leaves complicates both field management and harvest. The utilization of cultivars with fewer prickles or prickle-free canes simplifies production. A previously generated population segregating for prickles utilizing the s locus between the prickle-free cultivar Joan J (ss) and the prickled cultivar Caroline (Ss) was analyzed to identify the genomic region associated with prickle development in red raspberry. Genotype by sequencing (GBS) was combined with a genome-wide association study (GWAS) using fixed and random model circulating probability unification (FarmCPU) to analyze 8474 single nucleotide polymorphisms (SNPs) and identify significant markers associated with the prickle-free trait. A total of four SNPs were identified on chromosome 4 that were associated with the phenotype and were located near or in annotated genes. This study demonstrates how association genetics can be used to decipher the genetic control of important horticultural traits in Rubus, and provides valuable information about the genomic region and potential genes underlying the prickle-free trait.

scholarly journals Genome-Wide Association Study (GWAS) to Identify Salt-Tolerance QTLs Carrying Novel Candidate Genes in Rice During Early Vegetative Stage

Rice ◽  
2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Leila Nayyeripasand ◽  
Ghasem Ali Garoosi ◽  
Asadollah Ahmadikhah
Keyword(s):  
Association Study ◽  
Candidate Gene ◽  
Candidate Genes ◽  
Salinity Tolerance ◽  
Genome Wide Association Study ◽  
Dry Weight ◽  
Genome Wide Association ◽  
Vegetative Stage ◽  
Genome Wide ◽  
Genomic Regions

Abstract Background Rice is considered as a salt-sensitive plant, particularly at early vegetative stage, and its production is suffered from salinity due to expansion of salt affected land in areas under cultivation. Hence, significant increase of rice productivity on salinized lands is really necessary. Today genome-wide association study (GWAS) is a method of choice for fine mapping of QTLs involved in plant responses to abiotic stresses including salinity stress at early vegetative stage. In this study using > 33,000 SNP markers we identified rice genomic regions associated to early stage salinity tolerance. Eight salinity-related traits including shoot length (SL), root length (RL), root dry weight (RDW), root fresh weight (RFW), shoot fresh weight (SFW), shoot dry weight (SDW), relative water content (RWC) and TW, and 4 derived traits including SL-R, RL-R, RDW-R and RFW-R in a diverse panel of rice were evaluated under salinity (100 mM NaCl) and normal conditions in growth chamber. Genome-wide association study (GWAS) was applied based on MLM(+Q + K) model. Results Under stress conditions 151 trait-marker associations were identified that were scattered on 10 chromosomes of rice that arranged in 29 genomic regions. A genomic region on chromosome 1 (11.26 Mbp) was identified which co-located with a known QTL region SalTol1 for salinity tolerance at vegetative stage. A candidate gene (Os01g0304100) was identified in this region which encodes a cation chloride cotransporter. Furthermore, on this chromosome two other candidate genes, Os01g0624700 (24.95 Mbp) and Os01g0812000 (34.51 Mbp), were identified that encode a WRKY transcription factor (WRKY 12) and a transcriptional activator of gibberellin-dependent alpha-amylase expression (GAMyb), respectively. Also, a narrow interval on the same chromosome (40.79–42.98 Mbp) carries 12 candidate genes, some of them were not so far reported for salinity tolerance at seedling stage. Two of more interesting genes are Os01g0966000 and Os01g0963000, encoding a plasma membrane (PM) H+-ATPase and a peroxidase BP1 protein. A candidate gene was identified on chromosome 2 (Os02g0730300 at 30.4 Mbp) encoding a high affinity K+ transporter (HAK). On chromosome 6 a DnaJ-encoding gene and pseudouridine synthase gene were identified. Two novel genes on chromosome 8 including the ABI/VP1 transcription factor and retinoblastoma-related protein (RBR), and 3 novel genes on chromosome 11 including a Lox, F-box and Na+/H+ antiporter, were also identified. Conclusion Known or novel candidate genes in this research were identified that can be used for improvement of salinity tolerance in molecular breeding programmes of rice. Further study and identification of effective genes on salinity tolerance by the use of candidate gene-association analysis can help to precisely uncover the mechanisms of salinity tolerance at molecular level. A time dependent relationship between salt tolerance and expression level of candidate genes could be recognized.

Sign in / Sign up

Export Citation Format

Share Document