Whole-Genome Sequencing on 220 Alfalfa (Medicago sativa L.) Accessions Identified Association of DREB1C Gene with Fall Dormancy Height

Fall dormancy (FD) is one of the most important traits of alfalfa (Medicago sativa) for cultivar selection to overcome winter stress. Although transcriptomics, proteomics analysis, and QTL mapping have revealed some important genes correlated with FD, the genetic architecture of this trait is still unclear. There are no applicable genes or markers for selection, which hinders progress in the genetic research and molecular breeding for the trait. We conducted whole-genome sequencing (WGS) on 220 alfalfa accessions at 10x depth. Among the 875,023 SNPs, four of them were associated with FD height using GWAS. One SNP located on chromosome 6 is in linkage disequilibrium with dehydration-responsive element-binding protein 1C (DREB1C). Furthermore, seven DREB genes are clustered in this region, one of which has previously been shown to enhance freezing tolerance in the model plant Medicago truncatula. The candidate genes uncovered by our research will benefit the transgenic and CRISPR-Cas9 research of FD in alfalfa. This gene will also be useful for molecular marker development and marker-associated breeding of FD for alfalfa.

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Whole-Genome Sequencing on 220 Alfalfa (Medicago sativa L.) Accessions Identified Loci Associated with Fall Dormancy

10.21203/rs.3.rs-1006624/v1 ◽

2021 ◽

Author(s):

Fan Zhang ◽

Junmei Kang ◽

Ruicai Long ◽

Mingna Li ◽

Yan Sun ◽

...

Keyword(s):

Medicago Sativa ◽

Whole Genome Sequencing ◽

Genome Sequencing ◽

Genome Wide Association Study ◽

Genetic Research ◽

Whole Genome ◽

Cultivar Selection ◽

Fall Dormancy ◽

Element Binding Protein ◽

Responsive Element

Abstract Fall dormancy (FD) is one of the most important traits of alfalfa (Medicago sativa) for cultivar selection to overcome winter damage. Regrowth plant height following autumn clipping is an indirect way to evaluate FD. Although transcriptomics, proteomics analysis, and QTL mapping have revealed some important genes correlated with FD, the genetic architecture of this trait is still unclear. There are no applicable genes or markers for selection, which hinders progress in the genetic research and molecular breeding for the trait. We conducted whole-genome sequencing (WGS) on 220 alfalfa accessions at 10x depth. Among the 875,023 SNPs, seven of them were associated with FD using genome-wide association study (GWAS). One SNP located on chromosome 6 is in linkage disequilibrium with dehydration-responsive element-binding protein 1C (DREB1C). Furthermore, seven DREB genes are clustered in this region, one of which has previously been shown to enhance freezing tolerance in the model plant Medicago truncatula. The candidate genes uncovered by our research will benefit the transgenic and CRISPR-Cas9 research of FD in alfalfa. This gene will also be useful for marker development and assisted selection of FD for alfalfa.

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Genetic tools to improve reproduction traits in dairy cattle

Reproduction Fertility and Development ◽

10.1071/rd14379 ◽

2015 ◽

Vol 27 (1) ◽

pp. 14 ◽

Cited By ~ 6

Author(s):

A. Capitan ◽

P. Michot ◽

A. Baur ◽

R. Saintilan ◽

C. Hozé ◽

...

Keyword(s):

Dairy Cattle ◽

Whole Genome Sequencing ◽

Genome Sequencing ◽

Genetic Research ◽

Detection Methods ◽

Whole Genome ◽

Sequencing Data ◽

Lethal Mutations ◽

Embryonic Lethal ◽

Embryonic Lethal Mutations

Fertility is a major concern in the dairy cattle industry and has been the subject of numerous studies over the past 20 years. Surprisingly, most of these studies focused on rough female phenotypes and, despite their important role in reproductive success, male- and embryo-related traits have been poorly investigated. In recent years, the rapid and important evolution of technologies in genetic research has led to the development of genomic selection. The generalisation of this method in combination with the achievements of the AI industry have led to the constitution of large databases of genotyping and sequencing data, as well as refined phenotypes and pedigree records. These resources offer unprecedented opportunities in terms of fundamental and applied research. Here we present five such examples with a focus on reproduction-related traits: (1) detection of quantitative trait loci (QTL) for male fertility and semen quality traits; (2) detection of QTL for refined phenotypes associated with female fertility; (3) identification of recessive embryonic lethal mutations by depletion of homozygous haplotypes; (4) identification of recessive embryonic lethal mutations by mining whole-genome sequencing data; and (5) the contribution of high-density single nucleotide polymorphism chips, whole-genome sequencing and imputation to increasing the power of QTL detection methods and to the identification of causal variants.

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