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Genetics

D-Index
74
Citations
25058
World Ranking
1950
National Ranking
895

Overview

Jean-Luc Jannink is affiliated with the Agricultural Research Service in the United States. Their research primarily focuses on agricultural and biological sciences, with significant contributions in biochemistry, genetics, and molecular biology. The subfields of their work prominently include plant science, genetics, oceanography, molecular biology, and ecology.

The main topics covered by their research encompass:

  • Genetics and Plant Breeding
  • Genetic Mapping and Diversity in Plants and Animals
  • Cassava Research and Cyanide
  • Genetic and Phenotypic Traits in Livestock
  • Wheat and Barley Genetics and Pathology
  • Genetic and Environmental Crop Studies
  • Marine and Coastal Plant Biology

Jannink has been involved in publishing research papers in various scientific venues. Frequent publication venues include:

  • Harvard Dataverse
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Frontiers in Plant Science
  • G3 Genes Genomes Genetics
  • Crop Science

Recent notable papers authored or co-authored by Jannink include:

  • "GrainGenes: a data-rich repository for small grains genetics and genomics", 2022, Database
  • "Genome-wide association analysis reveals new insights into the genetic architecture of defensive, agro-morphological and quality-related traits in cassava", 2020, Plant Molecular Biology
  • "Breedbase: a digital ecosystem for modern plant breeding", 2022, G3 Genes Genomes Genetics
  • "Genomic mating in outbred species: predicting cross usefulness with additive and total genetic covariance matrices", 2021, Genetics
  • "Multi-omics prediction of oat agronomic and seed nutritional traits across environments and in distantly related populations", 2021, Theoretical and Applied Genetics

Frequent collaborators in Jannink's research include:

  • Jesse Poland
  • Kauê de Sousa
  • Jacob van Etten
  • Carlo Fadda
  • Basazen Fantahun Lakew

Best Publications

  • Development of High-Density Genetic Maps for Barley and Wheat Using a Novel Two-Enzyme Genotyping-by-Sequencing Approach

    Jesse A. Poland;Jesse A. Poland;Patrick J. Brown;Mark E. Sorrells;Jean Luc Jannink;Jean Luc Jannink

  • Genomic Selection for Crop Improvement

    Elliot L. Heffner;Mark E. Sorrells;Jean-Luc Jannink

  • Genomic selection in plant breeding: from theory to practice.

    Jean Luc Jannink;Aaron J. Lorenz;Hiroyoshi Iwata

  • Genomic Selection in Wheat Breeding using Genotyping-by-Sequencing

    Jesse A. Poland;Jeffrey Endelman;Julie Dawson;Jessica Rutkoski

  • Genomic Selection in Plant Breeding: A Comparison of Models

    Nicolas Heslot;Nicolas Heslot;Hsiao-Pei Yang;Mark E. Sorrells;Jean-Luc Jannink

  • Plant Breeding with Genomic Selection: Gain per Unit Time and Cost

    Elliot L. Heffner;Aaron J. Lorenz;Jean Luc Jannink;Mark E. Sorrells

  • Genomic selection and association mapping in rice (Oryza sativa): effect of trait genetic architecture, training population composition, marker number and statistical model on accuracy of rice genomic selection in elite, tropical rice breeding lines.

    Jennifer Spindel;Hasina Begum;Deniz Akdemir;Parminder Virk

  • Genomic Selection in Plant Breeding. Knowledge and Prospects.

    Aaron J. Lorenz;Shiaoman Chao;Franco G. Asoro;Elliot L. Heffner

  • Factors Affecting Accuracy From Genomic Selection in Populations Derived From Multiple Inbred Lines: A Barley Case Study

    Shengqiang Zhong;Jack C.M. Dekkers;Rohan Luigi Fernando;Jean-Luc Jannink

  • Multiple Trait Genomic Selection Methods Increase Genetic Value Prediction Accuracy

    Yi Jia;Jean-Luc Jannink;Jean-Luc Jannink

  • Shrinkage estimation of the realized relationship matrix.

    Jeffrey B Endelman;Jean-Luc Jannink

  • Genomic Selection Accuracy using Multifamily Prediction Models in a Wheat Breeding Program

    Elliot L. Heffner;Jean-Luc Jannink;Mark E. Sorrells

  • Training set optimization under population structure in genomic selection.

    Julio Isidro;Jean‑Luc Jannink;Deniz Akdemir;Jesse Poland

  • Integrating environmental covariates and crop modeling into the genomic selection framework to predict genotype by environment interactions

    Nicolas Heslot;Nicolas Heslot;Deniz Akdemir;Mark E. Sorrells;Jean-Luc Jannink

  • Perspectives for Genomic Selection Applications and Research in Plants

    Nicolas Heslot;Jean-Luc Jannink;Mark E. Sorrells

  • Increased prediction accuracy in wheat breeding trials using a marker × environment interaction genomic selection model.

    Marco Lopez-Cruz;Jose Crossa;David Bonnett;Susanne Dreisigacker

  • Genomic Selection Accuracy for Grain Quality Traits in Biparental Wheat Populations

    Elliot L. Heffner;Jean-Luc Jannink;Hiroyoshi Iwata;Edward Souza

  • Genome-wide prediction models that incorporate de novo GWAS are a powerful new tool for tropical rice improvement.

    Spindel Je;Begum H;Akdemir D;Collard B

  • Effectiveness of Genomic Prediction of Maize Hybrid Performance in Different Breeding Populations and Environments

    Vanessa S. Windhausen;Gary N. Atlin;John M. Hickey;Jose Crossa

  • Genomic Prediction in Maize Breeding Populations with Genotyping-by-Sequencing

    Jose Crossa;Yoseph Beyene;Semagn Kassa;Paulino Pérez

Frequent Co-Authors

Mark E. Sorrells
Mark E. Sorrells Cornell University
Peter Kulakow
Peter Kulakow International Institute of Tropical Agriculture
Chiedozie Egesi
Chiedozie Egesi Cornell University
Jesse Poland
Jesse Poland King Abdullah University of Science and Technology
Hiroyoshi Iwata
Hiroyoshi Iwata University of Tokyo
José Crossa
José Crossa International Maize and Wheat Improvement Center
Michael A. Gore
Michael A. Gore Cornell University
Kevin P. Smith
Kevin P. Smith University of Minnesota
Shiaoman Chao
Shiaoman Chao Agricultural Research Service
Edward S. Buckler
Edward S. Buckler Cornell University

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