Genome-Wide Association Studies Identifying Multiple Loci Associated With Alfalfa Forage Quality

Autotetraploid alfalfa is a major hay crop planted all over the world due to its adaptation in different environments and high quality for animal feed. However, the genetic basis of alfalfa quality is not fully understood. In this study, a diverse panel of 200 alfalfa accessions were planted in field trials using augmented experimental design at three locations in 2018 and 2019. Thirty-four quality traits were evaluated by Near Infrared Reflectance Spectroscopy (NIRS). The plants were genotyped using a genotyping by sequencing (GBS) approach and over 46,000 single nucleotide polymorphisms (SNPs) were obtained after variant calling and filtering. Genome-wide association studies (GWAS) identified 28 SNP markers associated with 16 quality traits. Among them, most of the markers were associated with fiber digestibility and protein content. Phenotypic variations were analyzed from three locations and different sets of markers were identified by GWAS when using phenotypic data from different locations, indicating that alfalfa quality traits were also affected by environmental factors. Among different sets of markers identified by location, two markers were associated with nine traits of fiber digestibility. One marker associated with lignin content was identified consistently in multiple environments. Putative candidate genes underlying fiber-related loci were identified and they are involved in the lignin and cell wall biosynthesis. The DNA markers and associated genes identified in this study will be useful for the genetic improvement of forage quality in alfalfa after the validation of the markers.

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Genome-wide association studies provide insights into the genetic determination of fruit traits of pear

Nature Communications ◽

10.1038/s41467-021-21378-y ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Ming-Yue Zhang ◽

Cheng Xue ◽

Hongju Hu ◽

Jiaming Li ◽

Yongsong Xue ◽

...

Keyword(s):

Fruit Quality ◽

Molecular Breeding ◽

Association Studies ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Quality Traits ◽

Fruit Traits ◽

Stone Cell ◽

Genome Wide ◽

Fruit Quality Traits

AbstractPear is a major fruit tree crop distributed worldwide, yet its breeding is a very time-consuming process. To facilitate molecular breeding and gene identification, here we have performed genome-wide association studies (GWAS) on eleven fruit traits. We identify 37 loci associated with eight fruit quality traits and five loci associated with three fruit phenological traits. Scans for selective sweeps indicate that traits including fruit stone cell content, organic acid and sugar contents might have been under continuous selection during breeding improvement. One candidate gene, PbrSTONE, identified in GWAS, has been functionally verified to be involved in the regulation of stone cell formation, one of the most important fruit quality traits in pear. Our study provides insights into the complex fruit related biology and identifies genes controlling important traits in pear through GWAS, which extends the genetic resources and basis for facilitating molecular breeding in perennial trees.

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Genomic Prediction and Genome-Wide Association Studies of Flour Yield and Alveograph Quality Traits Using Advanced Winter Wheat Breeding Material

Genes ◽

10.3390/genes10090669 ◽

2019 ◽

Vol 10 (9) ◽

pp. 669 ◽

Cited By ~ 2

Author(s):

Peter S. Kristensen ◽

Just Jensen ◽

Jeppe R. Andersen ◽

Carlos Guzmán ◽

Jihad Orabi ◽

...

Keyword(s):

Winter Wheat ◽

Genomic Prediction ◽

Association Studies ◽

Wheat Breeding ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Quality Traits ◽

Breeding Programs ◽

Genome Wide ◽

Flour Yield

Use of genetic markers and genomic prediction might improve genetic gain for quality traits in wheat breeding programs. Here, flour yield and Alveograph quality traits were inspected in 635 F6 winter wheat breeding lines from two breeding cycles. Genome-wide association studies revealed single nucleotide polymorphisms (SNPs) on chromosome 5D significantly associated with flour yield, Alveograph P (dough tenacity), and Alveograph W (dough strength). Additionally, SNPs on chromosome 1D were associated with Alveograph P and W, SNPs on chromosome 1B were associated with Alveograph P, and SNPs on chromosome 4A were associated with Alveograph L (dough extensibility). Predictive abilities based on genomic best linear unbiased prediction (GBLUP) models ranged from 0.50 for flour yield to 0.79 for Alveograph W based on a leave-one-out cross-validation strategy. Predictive abilities were negatively affected by smaller training set sizes, lower genetic relationship between lines in training and validation sets, and by genotype–environment (G×E) interactions. Bayesian Power Lasso models and genomic feature models resulted in similar or slightly improved predictions compared to GBLUP models. SNPs with the largest effects can be used for screening large numbers of lines in early generations in breeding programs to select lines that potentially have good quality traits. In later generations, genomic predictions might be used for a more accurate selection of high quality wheat lines.

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Single-Locus and Multi-Locus Genome-Wide Association Studies in the Genetic Dissection of Fiber Quality Traits in Upland Cotton (Gossypium hirsutum L.)

Frontiers in Plant Science ◽

10.3389/fpls.2018.01083 ◽

2018 ◽

Vol 9 ◽

Cited By ~ 17

Author(s):

Chengqi Li ◽

Yuanzhi Fu ◽

Runrun Sun ◽

Yuanyuan Wang ◽

Qinglian Wang

Keyword(s):

Upland Cotton ◽

Association Studies ◽

Fiber Quality ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Genetic Dissection ◽

Quality Traits ◽

Gossypium Hirsutum L ◽

Fiber Quality Traits ◽

Genome Wide

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Candidate gene-based association genetics analysis of herbage quality traits in perennial ryegrass (Lolium perenne L.)

Crop and Pasture Science ◽

10.1071/cp12392 ◽

2013 ◽

Vol 64 (3) ◽

pp. 244 ◽

Cited By ~ 8

Author(s):

L. W. Pembleton ◽

J. Wang ◽

N. O. I. Cogan ◽

J. E. Pryce ◽

G. Ye ◽

...

Keyword(s):

Association Mapping ◽

Candidate Gene ◽

Perennial Ryegrass ◽

Association Studies ◽

Phenotypic Variance ◽

Genome Wide Association Studies ◽

Quality Traits ◽

Near Infrared Reflectance ◽

Genome Wide ◽

Herbage Quality

Due to the complex genetic architecture of perennial ryegrass, based on an obligate outbreeding reproductive habit, association-mapping approaches to genetic dissection offer the potential for effective identification of genetic marker–trait linkages. Associations with genes for agronomic characters, such as components of herbage nutritive quality, may then be utilised for accelerated cultivar improvement using advanced molecular breeding practices. The objective of the present study was to evaluate the presence of such associations for a broad range of candidate genes involved in pathways of cell wall biosynthesis and carbohydrate metabolism. An association-mapping panel composed from a broad range of non-domesticated and varietal sources was assembled and assessed for genome-wide sequence polymorphism. Removal of significant population structure obtained a diverse meta-population (220 genotypes) suitable for association studies. The meta-population was established with replication as a spaced-plant field trial. All plants were genotyped with a cohort of candidate gene-derived single nucleotide polymorphism (SNP) markers. Herbage samples were harvested at both vegetative and reproductive stages and were measured for a range of herbage quality traits using near infrared reflectance spectroscopy. Significant associations were identified for ~50% of the genes, accounting for small but significant components of phenotypic variance. The identities of genes with associated SNPs were largely consistent with detailed knowledge of ryegrass biology, and they are interpreted in terms of known biochemical and physiological processes. Magnitudes of effect of observed marker–trait gene association were small, indicating that future activities should focus on genome-wide association studies in order to identify the majority of causal mutations for complex traits such as forage quality.

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