Sarah Hearne focuses on identifying and “upcycling” breeder-relevant native genetic variation for broader crop improvement applications. Working with multidisciplinary teams she explores, harnesses, re-combines and co-develops applications and approaches in the areas of genomics, informatics, biometrics and breeding methodology, driving data synergies towards more efficient and effective upstream discovery and breeding. She currently leads projects on Mining Useful Alleles for Climate Change Adaptation from CGIAR Gene Banks, the Seeds of Discovery initiative and the Trait Discovery and Deployment and Toolbox areas of the Excellence in Breeding Platform. These activities focus on the large-scale genotypic and targeted phenotypic characterization of germplasm bank collections resulting in the identification of accessions and genomic regions of value, and translation of this knowledge into new breeder demanded donor germplasm. This data-driven science is complemented by emphasis on outcome-oriented project and people management, data management and equitable, IP-sensitive knowledge sharing. Hearne is responsible for online resources that facilitate access to data, tools, services, germplasm, advice and training for other researchers and breeders.

1. Application of DSI
Sarah Hearne, November 2022

2. ?
Uninformed selection
Data driven selection of
alleles and accessions of
breeding relevance

3. Annual Average Temperature
50
0 100 150
Mb
Heatshock transcription factor
hsftf9
00
Chromosome9
‐log10
p
0
20
40
60
80
Drought, temperature stress, acid soils, salinity, fertility, agronomic practice adaptation…
Alberto Romero

4. Ross-Ibarra, Gates, Runcie, Hearne, Li, Crossa, Perez, Sonder. Unpublished.
Training
panel
Training
panel
DSI and Genome-based Predictions

5. Data Stewardship under Allele Mining
• Ensure data remains in the
public domain as an IPG
• Ensure that data is as
accessible as possible to as
broad a range of stakeholders
as possible
• Data licensing in CIMMYT instances
of Dataverse and Germinate
platforms
– Licensing
• Use of data for research, educational,
scientific publishing purposes
• The user shall not seek any form of
intellectual property rights or other
legal rights over data accessed
• Data may not be redistributed in any
form without written consent of the
provider
• Data and derived knowledge available in
processed and raw forms
Proactive Data Management