Author

Nicolas Heslot

Limagrain (France)

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

Click to filter author papers

Genetics· 3

Signature Assays, Organisms & Methods

Click to filter · or open tag

Research Focus:benchmarking· 2 Approach:statistical model· 2 Research Focus:variant calling· 2 Assay:whole-genome sequencing· 2 Research Focus:genome assembly· 1 Approach:optimal transport· 1 Organism:plant (other)· 1 Organism:zebrafish· 1

Frequent Co-Authors

Alain CharcossetiD· 1 shared Alain Murigneux· 1 shared Fabienne Henriot· 1 shared Gregor GorjanciD· 1 shared Ivan PocrnićiD· 1 shared Jana ObšteteriD· 1 shared Laurence MoreauiD· 1 shared Mathilde Berton· 1 shared

Activity by Year

2020-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

1 shared paperGenetics

Alain CharcossetORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Identification of heterotic group-specific haplotypes and impact of residual inbreeding on grain yield of maize elite hybrids

Romain Kadoumi, Nicolas Heslot, Fabienne Henriot, Alain Murigneux, Mathilde Berton, Laurence Moreau, Alain Charcosset

This study identifies heterotic group-specific haplotypes and shows that residual inbreeding from commercial hybrids negatively impacts maize grain yield.

bioRxiv · Jun 21, 2026 · PreprintGenetics

A method for partitioning trends in genetic mean and variance to understand breeding practices

Thiago de Paula Oliveira, Jana Obšteter, Ivan Pocrnić, Nicolas Heslot, Gregor Gorjanc

The paper introduces a method to partition genetic mean and variance contributions in breeding programs to better understand selection paths and optimize breeding strategies.

bioRxiv · Jan 10, 2022 · PreprintGenetics

Optimization of selective phenotyping and population design for genomic prediction

Nicolas Heslot, Vitaliy Feoktistov

The paper optimizes population design for genomic prediction by selecting preexisting individuals to phenotype and extending this to connected population designs for maize hybrids.

Journal of Agricultural Biological and Environmental Statistics · Sep 26, 2020Peer-reviewedGenetics