Genotyping by Sequencing Reads of 20 Vicia faba Lines with High and Low Vicine and Convicine Content

Heinrich, Felix; Gültaş, Mehmet; Link, Wolfgang; Schmitt, Armin O.

doi:10.3390/data5030063

Cited by 2 publications

(2 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Afterwards, I describe the framework that I developed to identify regulatory SNPs based on genotyping-by-sequencing data and, finally, I present the MIDESP algorithm for the detection of epistatic SNP pairs using mutual information. The content in this chapter is mostly taken from my published papers [52,165,187] (see Appendices A.1, A.2 and A.3).…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Identification of regulatory SNPs and epistatic SNP pairs using deep learning and information theory

Heinrich¹

Self Cite

View full text Add to dashboard Cite

In the last two decades, new technologies have made DNA genotyping and sequencing far more time and cost efficient. The resulting tremendous increase in the amount of available genomic data allows for a deeper understanding of the relationship between the genotype and the phenotype. In this thesis, I present two novel frameworks which analyze specific aspects of the relationship between the genotype and the phenotype, namely the identification of regulatory SNPs (rSNPs) as well as the detection of epistatic SNP pairs. Additional thanks go to the group of Prof. Wolfgang Link whose collaboration helped to facilitate my Master's thesis and first publication.Finally, I would like to thank my parents. They supported me during my studies and in my daily life and they have made it possible for me to concentrate fully on my studies. I dedicate this thesis to them.Last but not least, I thank my sister Jasmin who, despite her own work and studies, found the time to proofread my publications and this thesis. Contents x Material and methods

show abstract

Section: Methodsmentioning

confidence: 99%

“…A more detailed description of the sequencing process is given in my publication [187] (see Appendix A.2). For each sample, approximately 3 million 150 bp long paired end reads could be obtained, which results in a total sequence length of about 18 Gbp.…”

Section: Genotyping-by-sequencing Data Of Vicia Fabamentioning

confidence: 99%

Identification of regulatory SNPs and epistatic SNP pairs using deep learning and information theory

Heinrich¹

Self Cite

View full text Add to dashboard Cite

show abstract

Optimization of Genotyping‐by‐Sequencing (GBS) for Germplasm Fingerprinting and Trait Mapping in Faba Bean

Zhang,

Fechete,

Himmelbach

et al. 2024

Legume Science

View full text Add to dashboard Cite

Faba bean (Vicia faba L.) is an important pulse crop with a wide range of agroecological adaptations. The development of genomic tools and a comprehensive catalog of extant genetic diversity are crucial for developing improved faba bean cultivars. The lack of a cost‐effective genotyping platform limits the characterization of large germplasm collections, understanding of genetic diversity across populations, and implementing breeder's tools like genomic selection. Genotyping‐by‐sequencing (GBS) offers high‐resolution genotyping for both model and crop plant species, even without a reference genome sequence. The genome fragments targeted by GBS depend substantially on the restriction enzyme (RE) used for the complexity reduction step. Species with complex genomic architecture require optimization of GBS with proper RE to realize the full potential of GBS. Here, we evaluated various REs in the GBS method and identified that the combination of ApeKI/MseI proved to be the most appropriate for faba bean based on the best library quality, a high number of genomic loci spread across chromosomes, and high enrichment loci associated with the gene space. With the new optimized protocol, we constructed a genetic map using a recombinant inbred line (RIL) population and identified a QTL for seed hilum color on Chromosome 1. In addition, we also genotyped a diversity panel and performed a genome‐wide association studies (GWAS) for important agronomic traits, including plant height (PH), flowering time (FT), and number of pods per plant (PPP). We identified six SNP markers significantly associated with these traits and listed potential candidate genes. The optimized faba bean‐specific GBS procedure will facilitate access to the untapped genetic diversity for genetic research and breeding and may facilitate functional genomics.

show abstract

Genotyping by Sequencing Reads of 20 Vicia faba Lines with High and Low Vicine and Convicine Content

Cited by 2 publications

References 7 publications

Identification of regulatory SNPs and epistatic SNP pairs using deep learning and information theory

Identification of regulatory SNPs and epistatic SNP pairs using deep learning and information theory

Optimization of Genotyping‐by‐Sequencing (GBS) for Germplasm Fingerprinting and Trait Mapping in Faba Bean

Contact Info

Product

Resources

About