scholarly journals Genome-wide association studies on heat stress tolerance during grain development in wheat (Triticum aestivum L.)

2020 ◽  
Author(s):  
Jie Guo ◽  
Weiping Shi ◽  
Jiahui Guo ◽  
Linqi Yue ◽  
Lei Zhuang ◽  
...  
Keyword(s):  
Heat Stress ◽  
Heat Tolerance ◽  
Association Studies ◽  
Starch Content ◽  
Kernel Weight ◽  
Genome Wide Association ◽  
Phenotypic Traits ◽  
Genome Wide Association Studies ◽  
Wheat Cultivars ◽  
Genome Wide

Abstract BackgroundHeat stress at the late reproductive stages is a common problem encountered in autumn-sown wheat production regions in China with the affected area covering as much as two-thirds of the crop. In order to develop wheat cultivars with heat-tolerance, it is crucial to explore favorable alleles for use in breeding programs.ResultsIn this study, we performed a 90K iSelect SNP genotyping assay on a collection of 207 wheat cultivars subjected to heat stress during grain-fill growth stage in three years (2015-2017). Genotypic analyses of 19 phenotypic traits revealed that heat stress had major impacts on grain weight, size, and quality. Correlation analyses indicated that thousand kernel weight (TKW) was significantly correlated with grain width (GW) and grain perimeter (GP), whereas grain protein content (GPC) was negatively correlated with total starch content (TSC) (P <0.01). We applied heat susceptibility indices (HSI) for different traits to assess heat tolerance. Genome-wide association studies (GWAS) revealed a total of 125 marker-trait associations (MTAs) at 63 SNP loci on 16 chromosomes each accounting for phenotypic variation (R2) of 3.0-21.4%. 17 loci showed significant associations in three environments. The analysis of selective sweeps indicated that RAC875_c19042_2102 (2B), wsnp_Ex_c257_491667 (3B), wsnp_Ex_rep_c101323_86702413 (5A) and BS00061911_51 (7A) were selected between two subpopulations (top 5%).ConclusionsThese four key MTAs detected in the present study are candidates for further genetic dissection and development of molecular markers.

scholarly journals Genome-wide association studies for heat stress response in Bos taurus × Bos indicus crossbred cattle

2019 ◽  
Vol 102 (9) ◽  
pp. 8148-8158 ◽  
Author(s):  
Pamela I. Otto ◽  
Simone E.F. Guimarães ◽  
Lucas L. Verardo ◽  
Ana Luísa S. Azevedo ◽  
Jeremie Vandenplas ◽  
...  
Keyword(s):  
Heat Stress ◽  
Stress Response ◽  
Bos Taurus ◽  
Association Studies ◽  
Bos Indicus ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Crossbred Cattle ◽  
Heat Stress Response ◽  
Genome Wide

scholarly journals Genome-Wide Association Study of Maize Aboveground Dry Matter Accumulation at Seedling Stage

2021 ◽  
Vol 11 ◽  
Author(s):  
Xianju Lu ◽  
Jinglu Wang ◽  
Yongjian Wang ◽  
Weiliang Wen ◽  
Ying Zhang ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Dry Matter ◽  
Association Studies ◽  
Genome Wide Association ◽  
Phenotypic Traits ◽  
Pathway Enrichment Analysis ◽  
Dry Matter Accumulation ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Maize Varieties

Dry matter accumulation and partitioning during the early phases of development could significantly affect crop growth and productivity. In this study, the aboveground dry matter (DM), the DM of different organs, and partition coefficients of a maize association mapping panel of 412 inbred lines were evaluated at the third and sixth leaf stages (V3 and V6). Further, the properties of these phenotypic traits were analyzed. Genome-wide association studies (GWAS) were conducted on the total aboveground biomass and the DM of different organs. Analysis of GWAS results identified a total of 1,103 unique candidate genes annotated by 678 significant SNPs (P value &lt; 1.28e–6). A total of 224 genes annotated by SNPs at the top five of each GWAS method and detected by multiple GWAS methods were regarded as having high reliability. Pathway enrichment analysis was also performed to explore the biological significance and functions of these candidate genes. Several biological pathways related to the regulation of seed growth, gibberellin-mediated signaling pathway, and long-day photoperiodism were enriched. The results of our study could provide new perspectives on breeding high-yielding maize varieties.

scholarly journals Genome-wide association studies for yield component traits in a macadamia breeding population

2019 ◽  
Author(s):  
Katie O'Connor ◽  
Ben Hayes ◽  
Craig Hardner ◽  
Catherine Nock ◽  
Abdul Baten ◽  
...  
Keyword(s):  
Multiple Regression ◽  
Complex Traits ◽  
Association Studies ◽  
Kernel Weight ◽  
Genome Wide Association ◽  
Genomic Relationship Matrix ◽  
Relationship Matrix ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
A Genome

Abstract Background: Breeding for new macadamia cultivars with high nut yield is expensive in terms of time, labour and cost. Most trees set nuts after four to five years, and candidate varieties for breeding are evaluated for at least eight years for various traits. Genome-wide association studies (GWAS) are promising methods to reduce evaluation and selection cycles by identifying genetic markers linked with key traits, potentially enabling early selection through marker-assisted selection. This study used 295 progeny from 32 full-sib families and 29 parents (18 phenotyped) which were planted across four sites, with each tree genotyped for 4,113 SNPs. ASReml-R was used to perform association analyses with linear mixed models including a genomic relationship matrix to account for population structure. Traits investigated were: nut weight (NW), kernel weight (KW), kernel recovery (KR), percentage of whole kernels (WK), tree trunk circumference (TC), percentage of racemes that survived from flowering through to nut set, and number of nuts per raceme. Results: Seven SNPs were significantly associated with NW (at a genome-wide false discovery rate of <0.05), and four with WK. Multiple regression, as well as mapping of markers to genome assembly scaffolds suggested that some SNPs were detecting the same QTL. There were 44 significant SNPs identified for TC although multiple regression suggested detection of 16 separate QTLs. Conclusions: These findings have important implications for macadamia breeding, and highlight the difficulties of heterozygous populations with rapid LD decay. By coupling validated marker-trait associations detected through GWAS with MAS, genetic gain could be increased by reducing the selection time for economically important nut characteristics. Genomic selection may be a more appropriate method to predict complex traits like tree size and yield.

scholarly journals In Search of Complex Disease Risk through Genome Wide Association Studies

Mathematics ◽  
2021 ◽  
Vol 9 (23) ◽  
pp. 3083
Author(s):  
Lorena Alonso ◽  
Ignasi Morán ◽  
Cecilia Salvoro ◽  
David Torrents
Keyword(s):  
Genetic Variants ◽  
Complex Disease ◽  
Disease Risk ◽  
Association Studies ◽  
Personalised Medicine ◽  
Genome Wide Association ◽  
Phenotypic Traits ◽  
Genome Wide Association Studies ◽  
Treatment Protocols ◽  
Genome Wide

The identification and characterisation of genomic changes (variants) that can lead to human diseases is one of the central aims of biomedical research. The generation of catalogues of genetic variants that have an impact on specific diseases is the basis of Personalised Medicine, where diagnoses and treatment protocols are selected according to each patient’s profile. In this context, the study of complex diseases, such as Type 2 diabetes or cardiovascular alterations, is fundamental. However, these diseases result from the combination of multiple genetic and environmental factors, which makes the discovery of causal variants particularly challenging at a statistical and computational level. Genome-Wide Association Studies (GWAS), which are based on the statistical analysis of genetic variant frequencies across non-diseased and diseased individuals, have been successful in finding genetic variants that are associated to specific diseases or phenotypic traits. But GWAS methodology is limited when considering important genetic aspects of the disease and has not yet resulted in meaningful translation to clinical practice. This review presents an outlook on the study of the link between genetics and complex phenotypes. We first present an overview of the past and current statistical methods used in the field. Next, we discuss current practices and their main limitations. Finally, we describe the open challenges that remain and that might benefit greatly from further mathematical developments.

scholarly journals Potential of Genome-Wide Association Studies and Genomic Selection to Improve Productivity and Quality of Commercial Timber Species in Tropical Rainforest, a Case Study of Shorea platyclados

Forests ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 239 ◽  
Author(s):  
Sawitri ◽  
Naoki Tani ◽  
Mohammad Na’iem ◽  
Widiyatno ◽  
Sapto Indrioko ◽  
...  
Keyword(s):  
Genomic Selection ◽  
Association Studies ◽  
Genome Wide Association ◽  
Phenotypic Traits ◽  
Timber Species ◽  
Genome Wide Association Studies ◽  
Plant Materials ◽  
Genome Wide ◽  
Shorea Platyclados

Shorea platyclados (Dark Red Meranti) is a commercially important timber tree species in Southeast Asia. However, its stocks have dramatically declined due, inter alia, to excessive logging, insufficient natural regeneration and a slow recovery rate. Thus, there is a need to promote enrichment planting and develop effective technique to support its rehabilitation and improve timber production through implementation of Genome-Wide Association Studies (GWAS) and Genomic Selection (GS). To assist such efforts, plant materials were collected from a half-sib progeny population in Sari Bumi Kusuma forest concession, Kalimantan, Indonesia. Using 5900 markers in sequences obtained from 356 individuals, we detected high linkage disequilibrium (LD) extending up to >145 kb, suggesting that associations between phenotypic traits and markers in LD can be more easily and feasibly detected with GWAS than with analysis of quantitative trait loci (QTLs). However, the detection power of GWAS seems low, since few single nucleotide polymorphisms linked to any focal traits were detected with a stringent false discovery rate, indicating that the species’ phenotypic traits are mostly under polygenic quantitative control. Furthermore, Machine Learning provided higher prediction accuracies than Bayesian methods. We also found that stem diameter, branch diameter ratio and wood density were more predictable than height, clear bole, branch angle and wood stiffness traits. Our study suggests that GS has potential for improving the productivity and quality of S. platyclados, and our genomic heritability estimates may improve the selection of traits to target in future breeding of this species.

scholarly journals Candidate genes for productivity identified by genome-wide association study with indicators of class in the Russian meat merino sheep breed

2020 ◽  
Vol 24 (8) ◽  
pp. 836-843
Author(s):  
A. Y. Krivoruchko ◽  
O. A. Yatsyk ◽  
E. Y. Safaryan
Keyword(s):  
Candidate Genes ◽  
Genome Wide Association Study ◽  
Association Studies ◽  
Genome Wide Association ◽  
Phenotypic Traits ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
High Association ◽  
Genome Wide ◽  
Individual Snps

Genome-wide association studies allow identification of loci and polymorphisms associated with the formation of relevant phenotypes. When conducting a full genome analysis of sheep, particularly promising is the study of individuals with outstanding productivity indicators – exhibition animals, representatives of the super-elite class. The aim of this study was to identify new candidate genes for economically valuable traits based on the search for single nucleotide polymorphisms (SNPs) associated with belonging to different evaluation classes in rams of the Russian meat merino breed. Animal genotyping was performed using Ovine Infinium HD BeadChip 600K DNA, association search was performed using PLINK v. 1.07 software. Highly reliable associations were found between animals belonging to different evaluation classes and the frequency of occurrence of individual SNPs on chromosomes 2, 6, 10, 13, and 20. Most of the substitutions with high association reliability are concentrated on chromosome 10 in the region 10: 30859297–31873769. To search for candidate genes, 15 polymorphisms with the highest association reliability were selected (–log10(р) > 9). Determining the location of the analyzed SNPs relative to the latest annotation Oar_rambouillet_v1.0 allowed to identify 11 candidate genes presumably associated with the formation of a complex of phenotypic traits of animals in the exhibition group: RXFP2, ALOX5AP, MEDAG, OPN5, PRDM5, PTPRT, TRNAS-GGA, EEF1A1, FRY, ZBTB21-like, and B3GLCT-like. The listed genes encode proteins involved in the control of the cell cycle and DNA replication, regulation of cell proliferation and apoptosis, lipid and carbohydrate metabolism, the development of the inflammatory process and the work of circadian rhythms. Thus, the candidate genes under consideration can influence the formation of exterior features and productive qualities of sheep. However, further research is needed to confirm the influence of genes and determine the exact mechanisms for implementing this influence on the phenotype.

scholarly journals Revealing New Candidate Genes for Teat Number Relevant Traits in Duroc Pigs Using Genome-Wide Association Studies

Animals ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 806
Author(s):  
Yang Li ◽  
Lei Pu ◽  
Liangyu Shi ◽  
Hongding Gao ◽  
Pengfei Zhang ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Association Studies ◽  
Significant Snps ◽  
Genomic Region ◽  
Genome Wide Association ◽  
Phenotypic Traits ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Teat Number ◽  
The Right

The number of teats is related to the nursing ability of sows. In the present study, we conducted genome-wide association studies (GWAS) for traits related to teat number in Duroc pig population. Two mixed models, one for counted and another for binary phenotypic traits, were employed to analyze seven traits: the right (RTN), left (LTN), and total (TTN) teat numbers; maximum teat number on a side (MAX); left minus right side teat number (LR); the absolute value of LR (ALR); and the presence of symmetry between left and right teat numbers (SLR). We identified 11, 1, 4, 13, and 9 significant SNPs associated with traits RTN, LTN, MAX, TTN, and SLR, respectively. One significant SNP (MARC0038565) was found to be simultaneous associated with RTN, LTN, MAX and TTN. Two annotated genes (VRTN and SYNDIG1L) were located in genomic region around this SNP. Three significant SNPs were shown to be associated with TTN, RTN and MAX traits. Seven significant SNPs were simultaneously detected in two traits of TTN and RTN. Other two SNPs were only identified in TTN. These 13 SNPs were clustered in the genomic region between 96.10—98.09 Mb on chromosome 7. Moreover, nine significant SNPs were shown to be significantly associated with SLR. In total, four and 22 SNPs surpassed genome-wide significance and suggestive significance levels, respectively. Among candidate genes annotated, eight genes have documented association with the teat number relevant traits. Out of them, DPF3 genes on Sus scrofa chromosome (SSC) 7 and the NRP1 gene on SSC 10 were new candidate genes identified in this study. Our findings demonstrate the genetic mechanism of teat number relevant traits and provide a reference to further improve reproductive performances in practical pig breeding programs.

scholarly journals Multi-Locus Genome-Wide Association Study of Four Yield-Related Traits in Chinese Wheat Landraces

2021 ◽  
Vol 12 ◽  
Author(s):  
Yu Lin ◽  
Kunyu Zhou ◽  
Haiyan Hu ◽  
Xiaojun Jiang ◽  
Shifan Yu ◽  
...  
Keyword(s):  
Genome Wide Association Study ◽  
Association Studies ◽  
Kernel Weight ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Genome Wide ◽  
Wheat Landraces ◽  
Variation Explained ◽  
Chinese Wheat

Wheat (Triticum aestivum L.) is one of the most important crops in the world. Here, four yield-related traits, namely, spike length, spikelets number, tillers number, and thousand-kernel weight, were evaluated in 272 Chinese wheat landraces in multiple environments. Five multi-locus genome-wide association studies (FASTmrEMMA, ISIS EN-BLASSO, mrMLM, pKWmEB, and pLARmEB) were performed using 172,711 single-nucleotide polymorphisms (SNPs) to identify yield-related quantitative trait loci (QTL). A total of 27 robust QTL were identified by more than three models. Nine of these QTL were consistent with those in previous studies. The remaining 18 QTL may be novel. We identified a major QTL, QTkw.sicau-4B, with up to 18.78% of phenotypic variation explained. The developed kompetitive allele-specific polymerase chain reaction marker for QTkw.sicau-4B was validated in two recombinant inbred line populations with an average phenotypic difference of 16.07%. After combined homologous function annotation and expression analysis, TraesCS4B01G272300 was the most likely candidate gene for QTkw.sicau-4B. Our findings provide new insights into the genetic basis of yield-related traits and offer valuable QTL to breed wheat cultivars via marker-assisted selection.

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