scholarly journals Genome-wide mediation analysis: bridging the divide between genotype and phenotype via transcriptomic data in maize

2021 ◽  
Author(s):  
Zhikai Yang ◽  
Gen Xu ◽  
Qi Zhang ◽  
TOSHIHIRO OBATA ◽  
Jinliang Yang

Mapping genotype to phenotype is an essential topic in genetics and genomics research. As the Omics data become increasingly available, genome-wide association study (GWAS) has been widely applied to establish the relationship between genotype and phenotype. However, signals detected by GWAS usually span broad genomic regions with many underneath candidate genes, making it challenging to interpret and validate the molecular functions of the candidate genes. Under the context of genetics research, we hypothesized a causal chain from genotype to phenotype partially mediated by intermediate molecular processes, i.e., gene expression. To test this hypothesis, we applied the high dimensional mediation analysis, a class of causal inference method with an assumed causal chain from the exposure to the mediator to the outcome, and implemented it to the maize diversity panel (N=280 lines). Using 40 publicly available agronomic traits, 66 newly generated metabolic traits, and published RNA-seq data from seven different tissues, we detected N=736 unique mediating genes, explaining an average of 12.7\% phenotypic variance due to mediation. Noticeably, 83/736 (11\%) genes were identified in mediating more than one trait, suggesting the prevalence of pleiotropic mediating effects. Among those pleiotropic mediators, benzoxazinone synthesis 13 (Bx13), a well-characterized gene encoding a 2-oxoglutarate-dependent dioxygenase, was identified mediating 37 different agronomic and metabolic traits. Further genetic and genomic analyses of the bx13 and adjacent mediating genes suggested a 3D co-regulation modulation likely affect their expression levels and eventually lead to phenotypic consequences. Our results suggested the genome-wide mediation analysis is a powerful tool to integrate Omics data in providing causal inference to connect genotype to phenotype.

2019 ◽  
Author(s):  
Waltram Ravelombola ◽  
Jun Qin ◽  
Ainong Shi ◽  
Fengmin Wang ◽  
Yan Feng ◽  
...  

Abstract Background Soybean [ Glycine max (L.) Merr.] is a legume of great interest worldwide. Enhancing genetic gain for agronomic traits via molecular approaches has been long considered as the main task for soybean breeders and geneticists. The objectives of this study were to evaluate maturity, plant height, seed weight, and yield in a diverse soybean accession panel, to conduct a genome-wide association study (GWAS) for these traits and identify SNP markers associated with the four traits, and to assess genomic selection (GS) accuracy. Results A total of 250 soybean accessions were evaluated for maturity, plant height, seed weight, and yield over three years. This panel was genotyped with a total of 10,259 high quality SNPs postulated from genotyping by sequencing (GBS). GWAS was performed using a Bayesian Information and Linkage Disequilibrium Iteratively Nested Keyway (BLINK) model, and GS was evaluated using a ridge regression best linear unbiased predictor (rrBLUP) model. The results revealed that a total of 20, 31, 37, 31, and 23 SNPs were significantly associated with the average 3-year data for maturity, plant height, seed weight, and yield, respectively; some significant SNPs were mapped into previously described loci ( E2 , E4 , and Dt1 ) affecting maturity and plant height in soybean and a new locus mapped on chromosome 20 was significantly associated with plant height; Glyma.10g228900 , Glyma.19g200800 , Glyma.09g196700 , and Glyma.09g038300 were candidate genes found in the vicinity of the top or the second best SNP for maturity, plant height, seed weight, and yield, respectively; a 11.5-Mb region of chromosome 10 was associated with both seed weight and yield; and GS accuracy was trait-, year-, and population structure-dependent. Conclusions The SNP markers identified from this study for plant height, maturity, seed weight and yield can be used to improve the four agronomic traits through marker-assisted selection (MAS) and GS in soybean breeding programs. After validation, the candidate genes can be transferred to new cultivars using SNP markers through MAS. The high GS accuracy has confirmed that the four agronomic traits can be selected in molecular breeding through GS.


2020 ◽  
Author(s):  
Aditi Bhandari ◽  
Nitika Sandhu ◽  
Jérôme Bartholome ◽  
Tuong-Vi Cao-Hamadoun ◽  
Nourollah Ahmadi ◽  
...  

Abstract Background Reproductive-stage drought stress is a major impediment to rice production in rainfed areas. Conventional and marker-assisted breeding strategies for developing drought-tolerant rice varieties are being optimized by mining and exploiting adaptive traits, genetic diversity; identifying the alleles, and understanding their interactions with genetic backgrounds for their increased contribution to drought tolerance. Field experiments were conducted in this study to identify marker-trait associations (MTAs) involved in response to yield under reproductive-stage (RS) drought. A diverse set of 280 indica-aus accessions was phenotyped for ten agronomic traits including yield and yield-related traits under normal irrigated condition and under two managed reproductive-stage drought environments. The accessions were genotyped with 215,250 single nucleotide polymorphism markers. Results The study identified a total of 219 significant MTAs for 10 traits and candidate gene analysis within a 200kb window centred from GWAS identified SNP peaks detected these MTAs within/ in close proximity to 38 genes, 4 earlier reported major grain yield QTLs and 6 novel QTLs for 7 traits out of the 10. The significant MTAs were mainly located on chromosomes 1, 2, 5, 6, 9, 11 and 12 and the percent phenotypic variance captured for these traits ranged from 5 to 88%. The significant positive correlation of grain yield with yield-related and other agronomic traits except for flowering time, observed under different environments point towards their contribution in improving rice yield under drought. Seven promising accessions were identified for use in future genomics-assisted breeding programs targeting grain yield improvement under drought. Conclusion These results provide a promising insight into the complex genetic architecture of grain yield under reproductive-stage drought in different environments. Validation of major genomic regions reported in the study will enable their effectiveness to develop drought-tolerant varieties following marker-assisted selection as well as to identify genes and understanding the associated physiological mechanisms.


2019 ◽  
Author(s):  
Deissy Katherine Juyo Rojas ◽  
Johana Carolina Soto Sedano ◽  
Agim Ballvora ◽  
Jens Léon ◽  
Teresa Mosquera Vásquez

AbstractPotato, Solanum tuberosum, is one of the highest consumed food in the world, being the basis of the diet of millions of people. The main limiting and destructive disease of potato is late blight, caused by Phytophtora infestans. Here, we present a multi-environmental analysis of the response to P. infestans using an association panel of 150 accessions of S. tuberosum Group Phureja, evaluated in two localities in Colombia. Disease resistance data were merged with a genotyping matrix of 83,862 SNPs obtained by 2b-restriction site–associated DNA and Genotyping by sequencing approaches into a Genome-wide association study. We are reporting 16 organ-specific QTL conferring resistance to late blight. These QTL explain from 13.7% to 50.9% of the phenotypic variance. Six and ten QTL were detected for resistance response in leaves and stem, respectively. In silico analysis revealed 15 candidate genes for resistance to late blight. Four of them have no functional genome annotation, while eleven candidate genes code for diverse proteins, including one leucine-rich repeat kinase.


2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Hilal Betul Kaya ◽  
Deniz Akdemir ◽  
Roberto Lozano ◽  
Oznur Cetin ◽  
Hulya Sozer Kaya ◽  
...  

AbstractOlive (Olea europaea L.) is one of the most economically and historically important fruit crops worldwide. Genetic progress for valuable agronomic traits has been slow in olive despite its importance and benefits. Advances in next generation sequencing technologies provide inexpensive and highly reproducible genotyping approaches such as Genotyping by Sequencing, enabling genome wide association study (GWAS). Here we present the first comprehensive GWAS study on olive using GBS. A total of 183 accessions (FULL panel) were genotyped using GBS, 94 from the Turkish Olive GenBank Resource (TOGR panel) and 89 from the USDA-ARS National Clonal Germplasm Repository (NCGR panel) in the USA. After filtering low quality and redundant markers, GWAS was conducted using 24,977 SNPs in FULL, TOGR and NCGR panels. In total, 52 significant associations were detected for leaf length, fruit weight, stone weight and fruit flesh to pit ratio using the MLM_K. Significant GWAS hits were mapped to their positions and 19 candidate genes were identified within a 10-kb distance of the most significant SNP. Our findings provide a framework for the development of markers and identification of candidate genes that could be used in olive breeding programs.


2019 ◽  
Vol 20 (22) ◽  
pp. 5675 ◽  
Author(s):  
Lang Wu ◽  
Peng Wang ◽  
Yihao Wang ◽  
Qing Cheng ◽  
Qiaohua Lu ◽  
...  

There are many agronomic traits of pepper (Capsicum L.) with abundant phenotypes that can benefit pepper growth. Using specific-locus amplified fragment sequencing (SLAF-seq), a genome-wide association study (GWAS) of 36 agronomic traits was carried out for 287 representative pepper accessions. To ensure the accuracy and reliability of the GWAS results, we analyzed the genetic diversity, distribution of labels (SLAF tags and single nucleotide polymorphisms (SNPs)) and population differentiation and determined the optimal statistical model. In our study, 1487 SNPs were highly significantly associated with 26 agronomic traits, and 2126 candidate genes were detected in the 100-kb region up- and down-stream near these SNPs. Furthermore, 13 major association peaks were identified for 11 key agronomic traits. Then we examined the correlations among the 36 agronomic traits and analyzed SNP distribution and found 37 SNP polymerization regions (total size: 264.69 Mbp) that could be selected areas in pepper breeding. We found that the stronger the correlation between the two traits, the greater the possibility of them being in more than one polymerization region, suggesting that they may be linked or that one pleiotropic gene controls them. These results provide a theoretical foundation for future multi-trait pyramid breeding of pepper. Finally, we found that the GWAS signals were highly consistent with those from the nuclear restorer-of-fertility (Rf) gene for cytoplasmic male sterility (CMS), verifying their reliability. We further identified Capana06g002967 and Capana06g002969 as Rf candidate genes by functional annotation and expression analysis, which provided a reference for the study of cytoplasmic male sterility in Capsicum.


2017 ◽  
Vol 7 (7) ◽  
pp. 2391-2403 ◽  
Author(s):  
Amanda S Lobell ◽  
Rachel R Kaspari ◽  
Yazmin L Serrano Negron ◽  
Susan T Harbison

Abstract Ovariole number has a direct role in the number of eggs produced by an insect, suggesting that it is a key morphological fitness trait. Many studies have documented the variability of ovariole number and its relationship to other fitness and life-history traits in natural populations of Drosophila. However, the genes contributing to this variability are largely unknown. Here, we conducted a genome-wide association study of ovariole number in a natural population of flies. Using mutations and RNAi-mediated knockdown, we confirmed the effects of 24 candidate genes on ovariole number, including a novel gene, anneboleyn (formerly CG32000), that impacts both ovariole morphology and numbers of offspring produced. We also identified pleiotropic genes between ovariole number traits and sleep and activity behavior. While few polymorphisms overlapped between sleep parameters and ovariole number, 39 candidate genes were nevertheless in common. We verified the effects of seven genes on both ovariole number and sleep: bin3, blot, CG42389, kirre, slim, VAChT, and zfh1. Linkage disequilibrium among the polymorphisms in these common genes was low, suggesting that these polymorphisms may evolve independently.


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