Hans D. Daetwyler

DeepBioGS: a hybrid framework for integrating crop growth modelling with genomic prediction through neural networks

DeepBioGS integrates genomic selection with crop growth models using deep learning to improve prediction of genotype performance across environments.

Novel design of imputation-enabled SNP arrays for breeding and research applications supporting multi-species hybridisation

The paper introduces a novel SNP array design for multi-species hybridisation in breeding and research, demonstrating its utility in wheat and barley with high-resolution data and imputation capabilities.

Demographic history, cold adaptation, and recent NRAP recurrent convergent evolution at amino acid residue 100 in the world northernmost cattle from Russia

The paper investigates the evolutionary history and adaptation of two northern Russian cattle breeds, identifying a convergent mutation in NRAP associated with cold adaptation.

Quantifying the contribution of sequence variants with regulatory and evolutionary significance to 34 bovine complex traits

The paper identifies sequence variants with regulatory and evolutionary significance in cattle and ranks them using a Functional-And-Evolutionary Trait Heritability score to improve genomic prediction.

Genome variants associated with RNA splicing variation in bovine are extensively shared between tissues

The paper identifies bovine sQTLs associated with RNA splicing variation and shows they are shared across tissues and linked to complex traits.

Meta-Analysis Of Sequence-Based Association Studies Across Three Cattle Breeds Reveals 25 QTL For Fat And Protein Percentages In Milk At Nucleotide Resolution

Evaluation of the accuracy of imputed sequence variants and their utility for causal variant detection in cattle

This study evaluates imputation accuracy in cattle and identifies QTL for milk fat percentage using imputed variants.